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Rekant J, Ortmeyer H, Giffuni J, Friedman B, Addison O. Physical Functioning, Physical Activity, and Variability in Gait Performance during the Six-Minute Walk Test. SENSORS (BASEL, SWITZERLAND) 2024; 24:4656. [PMID: 39066052 PMCID: PMC11280787 DOI: 10.3390/s24144656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 07/09/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024]
Abstract
Instrumenting the six-minute walk test (6MWT) adds information about gait quality and insight into fall risk. Being physically active and preserving multi-directional stepping abilities are also important for fall risk reduction. This analysis investigated the relationship of gait quality during the 6MWT with physical functioning and physical activity. Twenty-one veterans (62.2 ± 6.4 years) completed the four square step test (FSST) multi-directional stepping assessment, a gait speed assessment, health questionnaires, and the accelerometer-instrumented 6MWT. An activity monitor worn at home captured free-living physical activity. Gait measures were not significantly different between minutes of the 6MWT. However, participants with greater increases in stride time (ρ = -0.594, p < 0.01) and stance time (ρ = -0.679, p < 0.01) during the 6MWT reported lower physical functioning. Neither physical activity nor sedentary time were related to 6MWT gait quality. Participants exploring a larger range in stride time variability (ρ = 0.614, p < 0.01) and stance time variability (ρ = 0.498, p < 0.05) during the 6MWT required more time to complete the FSST. Participants needing at least 15 s to complete the FSST meaningfully differed from those completing the FSST more quickly on all gait measures studied. Instrumenting the 6MWT helps detect ranges of gait performance and provides insight into functional limitations missed with uninstrumented administration. Established FSST cut points identify aging adults with poorer gait quality.
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Affiliation(s)
- Julie Rekant
- Baltimore VA Medical Center, Baltimore Department of Physical Therapy and Rehabilitation Sciences, University of Maryland, Baltimore, MD 21201, USA; (H.O.); (J.G.); (B.F.); (O.A.)
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2
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Kim YK, Gwerder M, Taylor WR, Baur H, Singh NB. Adaptive gait responses to varying weight-bearing conditions: Inferences from gait dynamics and H-reflex magnitude. Exp Physiol 2024; 109:754-765. [PMID: 38488681 PMCID: PMC11061628 DOI: 10.1113/ep091492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 02/28/2024] [Indexed: 05/02/2024]
Abstract
This study investigates the effects of varying loading conditions on excitability in neural pathways and gait dynamics. We focussed on evaluating the magnitude of the Hoffman reflex (H-reflex), a neurophysiological measure representing the capability to activate motor neurons and the timing and placement of the foot during walking. We hypothesized that weight manipulation would alter H-reflex magnitude, footfall and lower body kinematics. Twenty healthy participants were recruited and subjected to various weight-loading conditions. The H-reflex, evoked by stimulating the tibial nerve, was assessed from the dominant leg during walking. Gait was evaluated under five conditions: body weight, 20% and 40% additional body weight, and 20% and 40% reduced body weight (via a harness). Participants walked barefoot on a treadmill under each condition, and the timing of electrical stimulation was set during the stance phase shortly after the heel strike. Results show that different weight-loading conditions significantly impact the timing and placement of the foot and gait stability. Weight reduction led to a 25% decrease in double limb support time and an 11% narrowing of step width, while weight addition resulted in an increase of 9% in step width compared to body weight condition. Furthermore, swing time variability was higher for both the extreme weight conditions, while the H-reflex reduced to about 45% between the extreme conditions. Finally, the H-reflex showed significant main effects on variability of both stance and swing phases, indicating that muscle-motor excitability might serve as feedback for enhanced regulation of gait dynamics under challenging conditions.
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Affiliation(s)
- Yong Kuk Kim
- Laboratory for Movement Biomechanics, Institute for Biomechanics, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Michelle Gwerder
- Laboratory for Movement Biomechanics, Institute for Biomechanics, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - William R. Taylor
- Laboratory for Movement Biomechanics, Institute for Biomechanics, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Heiner Baur
- School of Health Professions, PhysiotherapyUniversity of Applied SciencesBernSwitzerland
| | - Navrag B. Singh
- Laboratory for Movement Biomechanics, Institute for Biomechanics, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
- Singapore‐ETH Centre, Future Health Technologies ProgramSingaporeSingapore
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Baudendistel ST, Haussler AM, Rawson KS, Earhart GM. Minimal clinically important differences of spatiotemporal gait variables in Parkinson disease. Gait Posture 2024; 108:257-263. [PMID: 38150946 PMCID: PMC10878409 DOI: 10.1016/j.gaitpost.2023.11.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/18/2023] [Accepted: 11/21/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND Assessment of gait function in People with Parkinson Disease (PwPD) is an important tool for monitoring disease progression in PD. While comprehensive gait analysis has become increasingly popular, only one study, Hass et al. (2014), has established minimal clinically important differences (MCID) for one spatiotemporal variable (velocity) in PwPD. RESEARCH QUESTION What are the MCIDs for velocity and additional spatiotemporal variables, including mean, variability, and asymmetry of step length, time, and width? METHODS As part of a larger clinic-based initiative, 382 medicated, ambulatory PwPD walked on an instrumented walkway during routine clinical visits. Distribution and anchor-based methods (Unified Parkinson's Disease Rating Scale-III, Modified Hoehn and Yahr, and the mobility subsection of the Parkinson Disease Questionnaire) were used to calculate MCIDs for variables of interest in a cross-sectional approach. RESULTS Distribution measures for all variables are presented. Of nine gait variables, four were significantly associated with every anchor and pooled to the following values: velocity (8.2 cm/s), step length mean (3.6 cm), step length variability (0.7%), and step time variability (0.67%). SIGNIFICANCE The finalized MCID for velocity (8.2 cm/s) was nearly half of the MCID of 15 cm/s reported by Hass et al., potentially due to differences in calculations. These results allow for evaluations of effectiveness of interventions by providing values that are specific to changes in gait for PwPD. Alterations of methodology including different versions of clinical or walking assessments, and/or different calculation and selection of gait variables necessitate careful reasoning when using presented MCIDs.
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Affiliation(s)
- Sidney T Baudendistel
- Program in Physical Therapy, Washington University School of Medicine in St. Louis, United States
| | - Allison M Haussler
- Program in Physical Therapy, Washington University School of Medicine in St. Louis, United States
| | - Kerri S Rawson
- Program in Physical Therapy, Washington University School of Medicine in St. Louis, United States; Department of Neurology, Washington University School of Medicine in St. Louis, United States
| | - Gammon M Earhart
- Program in Physical Therapy, Washington University School of Medicine in St. Louis, United States; Department of Neurology, Washington University School of Medicine in St. Louis, United States; Department of Neuroscience, Washington University School of Medicine in St. Louis, United States.
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Delgado-Ortiz L, Polhemus A, Keogh A, Sutton N, Remmele W, Hansen C, Kluge F, Sharrack B, Becker C, Troosters T, Maetzler W, Rochester L, Frei A, Puhan MA, Garcia-Aymerich J. Listening to the patients' voice: a conceptual framework of the walking experience. Age Ageing 2023; 52:7008636. [PMID: 36729471 PMCID: PMC9894103 DOI: 10.1093/ageing/afac233] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 06/27/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND walking is crucial for an active and healthy ageing, but the perspectives of individuals living with walking impairment are still poorly understood. OBJECTIVES to identify and synthesise evidence describing walking as experienced by adults living with mobility-impairing health conditions and to propose an empirical conceptual framework of walking experience. METHODS we performed a systematic review and meta-ethnography of qualitative evidence, searching seven electronic databases for records that explored personal experiences of walking in individuals living with conditions of diverse aetiology. Conditions included Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture, heart failure, frailty and sarcopenia. Data were extracted, critically appraised using the NICE quality checklist and synthesised using standardised best practices. RESULTS from 2,552 unique records, 117 were eligible. Walking experience was similar across conditions and described by seven themes: (i) becoming aware of the personal walking experience, (ii) the walking experience as a link between individuals' activities and sense of self, (iii) the physical walking experience, (iv) the mental and emotional walking experience, (v) the social walking experience, (vi) the context of the walking experience and (vii) behavioural and attitudinal adaptations resulting from the walking experience. We propose a novel conceptual framework that visually represents the walking experience, informed by the interplay between these themes. CONCLUSION a multi-faceted and dynamic experience of walking was common across health conditions. Our conceptual framework of the walking experience provides a novel theoretical structure for patient-centred clinical practice, research and public health.
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Affiliation(s)
| | | | - Alison Keogh
- Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland
| | | | | | - Clint Hansen
- Department of Neurology, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Felix Kluge
- Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Basil Sharrack
- Department of Neuroscience and Sheffield NIHR Translational Neuroscience BRC, Sheffield Teaching Hospitals NHS Foundation Trust & University of Sheffield, Sheffield, UK
| | - Clemens Becker
- Department of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Thierry Troosters
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium,Department of Respiratory Diseases, University Hospitals Leuven, Leuven, Belgium
| | - Walter Maetzler
- Department of Neurology, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Lynn Rochester
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Anja Frei
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Milo A Puhan
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Judith Garcia-Aymerich
- Address correspondence to: J. Garcia-Aymerich, ISGlobal, Dr. Aiguader 88, PRBB. Barcelona, Spain. Tel: (+34) 93 214 73 80;
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Liu R, Wang Z, Qiu S, Zhao H, Wang C, Shi X, Lin F. A Wearable Gait Analysis and Recognition Method for Parkinson's Disease Based on Error State Kalman Filter. IEEE J Biomed Health Inform 2022; 26:4165-4175. [PMID: 35544509 DOI: 10.1109/jbhi.2022.3174249] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
INTRODUCTION For the purpose of quantitative analysis, this paper proposes a wearable gait analysis method for Parkinson's disease (PD) to evaluates the motor ability. METHODS The error state Kalman filter (ESKF) is used for attitude update, and the gait parameters are modified by phase segmentation and zero velocity update (ZUPT) algorithm. In addition, this study uses gait parameters as classifier features to recognize abnormal gait, and compares the recognition effect with statistical features. RESULTS The effect of our gait system is verified by comparison with the OptiTrack system, and the mean absolute error (MAE) of step length and foot clearance are 2.523.61cm and 0.961.24cm respectively. Forty Parkinson's patients and forty age-matched healthy people are recruited for gait comparison, the analysis results showed significant differences between the two groups. The abnormal gait recognition results show that gait features have stronger generalization ability than statistical features in leave-one-subject-out (LOSO) validation. CONCLUSION The method proposed in this study can be applied to the gait analysis and objective evaluation of PD.
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Moura da Silva PM, Oliveira Bezerra AB, Araújo Farias LB, Ribeiro TS, Morya E, Cavalcanti FADC. Existing predictive methods applied to gait analysis of patients with diabetes: study protocol for a systematic review. BMJ Open 2022; 12:e051981. [PMID: 35190422 PMCID: PMC8862448 DOI: 10.1136/bmjopen-2021-051981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
INTRODUCTION Type 2 diabetes can lead to gait abnormalities, including a longer stance phase, shorter steps and improper foot pressure distribution. Quantitative data from objective methods for evaluating gait patterns are accurate and cost-effective. In addition, it can also help predictive methods to forecast complications and develop early strategies to guide treatments. To date, no research has systematically summarised the predictive methods used to assess type 2 diabetic gait. Therefore, this protocol aims to identify which predictive methods have been employed to assess the diabetic gait. METHODS AND ANALYSIS This protocol will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA-P) statement. Electronic searches of articles from inception to January 2022 will be performed, from May 2021 to 31 January 2022, in the Web of Science, MEDLINE, Embase, IEEE Xplore Digital Library, Scopus, CINAHL, Google Scholar, APA PsycInfo, the Cochrane Library and in references of key articles and grey literature without language restrictions. We will include studies that examined the development and/or validation of predictive methods to assess type 2 diabetic gait in adults aged >18 years without amputations, use of assistive devices, ulcers or neuropathic pain. Two independent reviewers will screen the included studies and extract the data using a customised charting form. A third reviewer will resolve any disagreements. A narrative synthesis will be performed for the included studies. Risk of bias and quality of evidence will be assessed using the Prediction Model Risk of Bias Assessment Tool and the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis. ETHICS AND DISSEMINATION Ethical approval is not required because only available secondary published data will be analysed. The findings will be disseminated through peer-reviewed journals and/or presentations at relevant conferences and other media platforms. PROSPERO REGISTRATION NUMBER CDR42020199495.
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Affiliation(s)
- Patrícia Mayara Moura da Silva
- Physical Therapy Department, Federal University of Rio Grande do Norte, Natal, Brazil
- Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, Macaíba, Brazil
| | | | | | - Tatiana Souza Ribeiro
- Physical Therapy Department, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Edgard Morya
- Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, Macaíba, Brazil
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Rohafza M, Soangra R, Smith JA, Ignasiak NK. Self-paced treadmills do not allow for valid observation of linear and nonlinear gait variability outcomes in patients with Parkinson's disease. Gait Posture 2022; 91:35-41. [PMID: 34634614 DOI: 10.1016/j.gaitpost.2021.10.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 10/04/2021] [Accepted: 10/06/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND Due to the imposed constant belt speed, motorized treadmills are known to affect linear and nonlinear gait variability outcomes. This is particularly true of patients with Parkinson's Disease where the treadmill can act as an external pacemaker. Self-paced treadmills update the belt speed in response to the subject's walking speed and might, therefore, be a useful tool for measurement of gait variability in this patient population. This study aimed to compare gait variability during walking at self-paced and constant treadmill speeds with overground walking in individuals with PD and individuals with unimpaired gait. METHODS Thirteen patients with Parkinson's Disease and thirteen healthy controls walked under three conditions: overground, on a treadmill at a constant speed, and using three self-paced treadmill modes. Gait variability was assessed with coefficient of variation (CV), sample entropy (SampEn), and detrended fluctuation analysis (DFA) of stride time and length. Systematic and random error between the conditions was quantified. RESULTS For individuals with PD, error in variability measurement was less during self-paced modes compared with constant treadmill speed for stride time but not for stride length. However, there was substantial error for stride time and length variability for all treadmill conditions. For healthy controls the error in measurement associated with treadmill walking was substantially less. SIGNIFICANCE The large systematic and random errors between overground and treadmill walking prohibit meaningful gait variability observations in patients with Parkinson's Disease using self-paced or constant-speed treadmills.
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Affiliation(s)
- Maryam Rohafza
- Department of Physical Therapy, Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA, 92866, USA
| | - Rahul Soangra
- Department of Physical Therapy, Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA, 92866, USA; Department of Electrical and Computer Science Engineering, Fowler School of Engineering, Chapman University, Orange, CA, 92866, USA.
| | - Jo Armour Smith
- Department of Physical Therapy, Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA, 92866, USA
| | - Niklas König Ignasiak
- Department of Electrical and Computer Science Engineering, Fowler School of Engineering, Chapman University, Orange, CA, 92866, USA
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Godi M, Arcolin I, Giardini M, Corna S, Schieppati M. A pathophysiological model of gait captures the details of the impairment of pace/rhythm, variability and asymmetry in Parkinsonian patients at distinct stages of the disease. Sci Rep 2021; 11:21143. [PMID: 34707168 PMCID: PMC8551236 DOI: 10.1038/s41598-021-00543-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/05/2021] [Indexed: 01/15/2023] Open
Abstract
Locomotion in people with Parkinson' disease (pwPD) worsens with the progression of disease, affecting independence and quality of life. At present, clinical practice guidelines recommend a basic evaluation of gait, even though the variables (gait speed, cadence, step length) may not be satisfactory for assessing the evolution of locomotion over the course of the disease. Collecting variables into factors of a conceptual model enhances the clinical assessment of disease severity. Our aim is to evaluate if factors highlight gait differences between pwPD and healthy subjects (HS) and do it at earlier stages of disease compared to single variables. Gait characteristics of 298 pwPD and 84 HS able to walk without assistance were assessed using a baropodometric walkway (GAITRite®). According to the structure of a model previously validated in pwPD, eight spatiotemporal variables were grouped in three factors: pace/rhythm, variability and asymmetry. The model, created from the combination of three factor scores, proved to outperform the single variables or the factors in discriminating pwPD from HS. When considering the pwPD split into the different Hoehn and Yahr (H&Y) stages, the spatiotemporal variables, factor scores and the model showed that multiple impairments of gait appear at H&Y stage 2.5, with the greatest difference from HS at stage 4. A contrasting behavior was found for the asymmetry variables and factor, which showed differences from the HS already in the early stages of PD. Our findings support the use of factor scores and of the model with respect to the single variables in gait staging in PD.
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Affiliation(s)
- Marco Godi
- Division of Physical Medicine and Rehabilitation, Scientific Institute of Veruno, Istituti Clinici Scientifici Maugeri IRCCS, 28010, Gattico-Veruno, NO, Italy
| | - Ilaria Arcolin
- Division of Physical Medicine and Rehabilitation, Scientific Institute of Veruno, Istituti Clinici Scientifici Maugeri IRCCS, 28010, Gattico-Veruno, NO, Italy.
| | - Marica Giardini
- Division of Physical Medicine and Rehabilitation, Scientific Institute of Veruno, Istituti Clinici Scientifici Maugeri IRCCS, 28010, Gattico-Veruno, NO, Italy
| | - Stefano Corna
- Division of Physical Medicine and Rehabilitation, Scientific Institute of Veruno, Istituti Clinici Scientifici Maugeri IRCCS, 28010, Gattico-Veruno, NO, Italy
| | - Marco Schieppati
- Scientific Institute of Pavia, Istituti Clinici Scientifici Maugeri IRCCS, 27100, Pavia, Italy
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Polhemus A, Delgado-Ortiz L, Brittain G, Chynkiamis N, Salis F, Gaßner H, Gross M, Kirk C, Rossanigo R, Taraldsen K, Balta D, Breuls S, Buttery S, Cardenas G, Endress C, Gugenhan J, Keogh A, Kluge F, Koch S, Micó-Amigo ME, Nerz C, Sieber C, Williams P, Bergquist R, Bosch de Basea M, Buckley E, Hansen C, Mikolaizak AS, Schwickert L, Scott K, Stallforth S, van Uem J, Vereijken B, Cereatti A, Demeyer H, Hopkinson N, Maetzler W, Troosters T, Vogiatzis I, Yarnall A, Becker C, Garcia-Aymerich J, Leocani L, Mazzà C, Rochester L, Sharrack B, Frei A, Puhan M. Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes. NPJ Digit Med 2021; 4:149. [PMID: 34650191 PMCID: PMC8516969 DOI: 10.1038/s41746-021-00513-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 08/09/2021] [Indexed: 02/08/2023] Open
Abstract
Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice.
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Affiliation(s)
- Ashley Polhemus
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
| | - Laura Delgado-Ortiz
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Barcelona, Spain
| | - Gavin Brittain
- Department of Neuroscience and Sheffield NIHR Translational Neuroscience BRC, Sheffield Teaching Hospitals NHS Foundation Trust & University of Sheffield, Sheffield, England
| | - Nikolaos Chynkiamis
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University Newcastle, Newcastle, UK
| | - Francesca Salis
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Heiko Gaßner
- Department of Molecular Neurology, University Hospital Erlangen, Erlangen, Germany
| | - Michaela Gross
- Department of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Cameron Kirk
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Rachele Rossanigo
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Kristin Taraldsen
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Diletta Balta
- Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy
| | - Sofie Breuls
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
- Department of Respiratory Diseases, University hospitals Leuven, Leuven, Belgium
| | - Sara Buttery
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Gabriela Cardenas
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Barcelona, Spain
| | - Christoph Endress
- Department of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Julia Gugenhan
- Department of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Alison Keogh
- Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland
| | - Felix Kluge
- Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Sarah Koch
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Barcelona, Spain
| | - M Encarna Micó-Amigo
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Corinna Nerz
- Department of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Chloé Sieber
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Parris Williams
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Ronny Bergquist
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Magda Bosch de Basea
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Barcelona, Spain
| | - Ellen Buckley
- Insigneo Institute, Department of Mechanical Engineering, University of Sheffield, Sheffield, UK
| | - Clint Hansen
- Department of Neurology, University Medical Center Schleswig-Holstein, Kiel, Germany
| | | | - Lars Schwickert
- Department of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Kirsty Scott
- Insigneo Institute, Department of Mechanical Engineering, University of Sheffield, Sheffield, UK
| | - Sabine Stallforth
- Department of Molecular Neurology, University Hospital Erlangen, Erlangen, Germany
| | - Janet van Uem
- Department of Neurology, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Beatrix Vereijken
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Andrea Cereatti
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy
| | - Heleen Demeyer
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
- Department of Respiratory Diseases, University hospitals Leuven, Leuven, Belgium
- Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium
| | | | - Walter Maetzler
- Department of Neurology, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Thierry Troosters
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
- Department of Respiratory Diseases, University hospitals Leuven, Leuven, Belgium
| | - Ioannis Vogiatzis
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University Newcastle, Newcastle, UK
| | - Alison Yarnall
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Clemens Becker
- Department of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Judith Garcia-Aymerich
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Barcelona, Spain
| | - Letizia Leocani
- Department of Neurology, San Raffaele University, Milan, Italy
| | - Claudia Mazzà
- Insigneo Institute, Department of Mechanical Engineering, University of Sheffield, Sheffield, UK
| | - Lynn Rochester
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Basil Sharrack
- Department of Neuroscience and Sheffield NIHR Translational Neuroscience BRC, Sheffield Teaching Hospitals NHS Foundation Trust & University of Sheffield, Sheffield, England
| | - Anja Frei
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Milo Puhan
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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10
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Kuruvithadam K, Menner M, Taylor WR, Zeilinger MN, Stieglitz L, Schmid Daners M. Data-Driven Investigation of Gait Patterns in Individuals Affected by Normal Pressure Hydrocephalus. SENSORS 2021; 21:s21196451. [PMID: 34640771 PMCID: PMC8512819 DOI: 10.3390/s21196451] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/14/2021] [Accepted: 09/15/2021] [Indexed: 11/16/2022]
Abstract
Normal pressure hydrocephalus (NPH) is a chronic and progressive disease that affects predominantly elderly subjects. The most prevalent symptoms are gait disorders, generally determined by visual observation or measurements taken in complex laboratory environments. However, controlled testing environments can have a significant influence on the way subjects walk and hinder the identification of natural walking characteristics. The study aimed to investigate the differences in walking patterns between a controlled environment (10 m walking test) and real-world environment (72 h recording) based on measurements taken via a wearable gait assessment device. We tested whether real-world environment measurements can be beneficial for the identification of gait disorders by performing a comparison of patients’ gait parameters with an aged-matched control group in both environments. Subsequently, we implemented four machine learning classifiers to inspect the individual strides’ profiles. Our results on twenty young subjects, twenty elderly subjects and twelve NPH patients indicate that patients exhibited a considerable difference between the two environments, in particular gait speed (p-value p=0.0073), stride length (p-value p=0.0073), foot clearance (p-value p=0.0117) and swing/stance ratio (p-value p=0.0098). Importantly, measurements taken in real-world environments yield a better discrimination of NPH patients compared to the controlled setting. Finally, the use of stride classifiers provides promise in the identification of strides affected by motion disorders.
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Affiliation(s)
- Kiran Kuruvithadam
- Product Development Group Zurich, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland;
| | - Marcel Menner
- Institute for Dynamic Systems and Control, ETH Zurich, 8092 Zurich, Switzerland; (M.M.); (M.N.Z.)
| | - William R. Taylor
- Laboratory for Movement Biomechanics, Institute for Biomechanics, ETH Zurich, 8093 Zurich, Switzerland;
| | - Melanie N. Zeilinger
- Institute for Dynamic Systems and Control, ETH Zurich, 8092 Zurich, Switzerland; (M.M.); (M.N.Z.)
| | - Lennart Stieglitz
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland;
| | - Marianne Schmid Daners
- Product Development Group Zurich, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland;
- Correspondence:
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11
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Bouça-Machado R, Jalles C, Guerreiro D, Pona-Ferreira F, Branco D, Guerreiro T, Matias R, Ferreira JJ. Gait Kinematic Parameters in Parkinson's Disease: A Systematic Review. JOURNAL OF PARKINSONS DISEASE 2021; 10:843-853. [PMID: 32417796 PMCID: PMC7458503 DOI: 10.3233/jpd-201969] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Gait impairments are common and highly disabling for Parkinson's disease (PD) patients. With the development of technology-based tools, it is now possible to measure the spatiotemporal parameters of gait with a reduced margin of error, thereby enabling a more accurate characterization of impairment. OBJECTIVE To summarize and critically appraise the characteristics of technology-based gait analysis in PD and to provide mean and standard deviation values for spatiotemporal gait parameters. METHODS A systematic review was conducted using the databases CENTRAL, MEDLINE, Embase, and PEDro from their inception to September 2019 to identify all observational and experimental studies conducted in PD or atypical parkinsonism that included a technology-based gait assessment. Two reviewers independently screened citations and extracted data. RESULTS We included 95 studies, 82.1% (n = 78) reporting a laboratory gait assessment and 61.1% (n = 58 studies) using a wearable sensor. The most frequently reported parameters were gait velocity, stride and step length, and cadence. A statistically significant difference was found when comparing the mean values of each of these parameters in PD patients versus healthy controls. No statistically significant differences were found in the mean value of the parameters when comparing wearable versus non-wearable sensors, different types of wearable sensors, and different sensor locations. CONCLUSION Our results provide useful information for performing objective technology-based gait assessment in PD, as well as mean values to better interpret the results. Further studies should explore the clinical meaningfulness of each parameter and how they behave in a free-living context and throughout disease progression.
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Affiliation(s)
- Raquel Bouça-Machado
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Avenida Professor Egas Moniz, Lisboa, Portugal.,CNS - Campus Neurológico Sénior, Torres Vedras, Portugal
| | - Constança Jalles
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Avenida Professor Egas Moniz, Lisboa, Portugal
| | | | | | - Diogo Branco
- LASIGE, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Tiago Guerreiro
- LASIGE, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
| | - Ricardo Matias
- Champalimaud Research and Clinical Centre, Champalimaud Centre for the Unknown, Lisbon, Portugal.,Human Movement Analysis Lab, Escola Superior Saúde - Instituto Politécnico de Setúbal, Setúbal, Portugal
| | - Joaquim J Ferreira
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Avenida Professor Egas Moniz, Lisboa, Portugal.,CNS - Campus Neurológico Sénior, Torres Vedras, Portugal.,Laboratory of Clinical Pharmacology and Therapeutics, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
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12
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Kenig A, Kolben Y, Asleh R, Amir O, Ilan Y. Improving Diuretic Response in Heart Failure by Implementing a Patient-Tailored Variability and Chronotherapy-Guided Algorithm. Front Cardiovasc Med 2021; 8:695547. [PMID: 34458334 PMCID: PMC8385752 DOI: 10.3389/fcvm.2021.695547] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/21/2021] [Indexed: 01/12/2023] Open
Abstract
Heart failure is a major public health problem, which is associated with significant mortality, morbidity, and healthcare expenditures. A substantial amount of the morbidity is attributed to volume overload, for which loop diuretics are a mandatory treatment. However, the variability in response to diuretics and development of diuretic resistance adversely affect the clinical outcomes. Morevoer, there exists a marked intra- and inter-patient variability in response to diuretics that affects the clinical course and related adverse outcomes. In the present article, we review the mechanisms underlying the development of diuretic resistance. The role of the autonomic nervous system and chronobiology in the pathogenesis of congestive heart failure and response to therapy are also discussed. Establishing a novel model for overcoming diuretic resistance is presented based on a patient-tailored variability and chronotherapy-guided machine learning algorithm that comprises clinical, laboratory, and sensor-derived inputs, including inputs from pulmonary artery measurements. Inter- and intra-patient signatures of variabilities, alterations of biological clock, and autonomic nervous system responses are embedded into the algorithm; thus, it may enable a tailored dose regimen in a continuous manner that accommodates the highly dynamic complex system.
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Affiliation(s)
- Ariel Kenig
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Yotam Kolben
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Rabea Asleh
- Department of Cardiology, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Offer Amir
- Department of Cardiology, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
- The Azrieli Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel
| | - Yaron Ilan
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
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13
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Gupta P, Man REK, Fenwick EK, Aravindhan A, Gan ATL, Thakur S, Soh BLP, Wood JM, Black AA, Chan A, Ng D, Hean TK, Goh E, Mary CFF, Loo J, Forde CG, Sabanayagam C, Cheng CY, Wong TY, Lamoureux EL. Rationale and Methodology of The PopulatION HEalth and Eye Disease PRofile in Elderly Singaporeans Study [PIONEER]. Aging Dis 2020; 11:1444-1458. [PMID: 33269099 PMCID: PMC7673841 DOI: 10.14336/ad.2020.0206] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Accepted: 02/06/2020] [Indexed: 12/23/2022] Open
Abstract
To describe the rationale, design and methodology of a geographically-representative and population-based study investigating the epidemiology, impact, personal and economic burden of age-related eye diseases, declining visual and other sensory systems in Asians aged >60 years in Singapore.PIONEER (The PopulatION HEalth and Eye Disease PRofilE in Elderly Singaporeans Study) is currently a cross-sectional study targeting 3152 Chinese, Malay and Indian adults who are Singapore citizens or permanent residents aged 60 years and older living across Singapore. The study is intended to be longitudinal, with several waves of data planned to be collected in the future. The sampling frame consisted of 7000 names derived from age, gender and ethnicity-stratified random sampling of individuals >60 years. Selected individuals were invited via letters, home visits, and telephone calls for a clinical assessment at the Singapore Eye Research Institute. Individuals with limited mobility were examined in a custom-designed mobile eye clinic. Questionnaires were subsequently administered at participants' homes by trained interviewers in their preferred language. A total of 3,299 participants (from East, West, North and South Singapore) were approached from December 2017 to November 2019. Of these, 953 (28.5%) were deemed ineligible. Out of 2,346 eligible participants, 904 (38.5%) refused, and 1,442 (61.5%) attended our clinical testing protocol, giving an initial response rate of 61.5%. Of these, 1,170 (81%) were cognitively able to complete the questionnaire assessment. The mean age±SD of our participants was 73.8±8.6 years; n=798 (55.3%) were female; and 828 (57.4%) were of Chinese ethnicity. The findings from this study will allow a deeper understanding of the risk factors and impact of aging in Asian populations, particularly in relation to the visual function and other functional system.
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Affiliation(s)
- Preeti Gupta
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
| | - Ryan Eyn Kidd Man
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
| | - Eva K Fenwick
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
- Duke-NUS Medical School, Singapore.
| | - Amudha Aravindhan
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
| | - Alfred TL Gan
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
| | - Sahil Thakur
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
| | | | - Joanne M Wood
- Queensland University of Technology, Brisbane, Australia.
| | - Alex A Black
- Queensland University of Technology, Brisbane, Australia.
| | | | - David Ng
- Duke-NUS Medical School, Singapore.
| | | | | | | | - Jenny Loo
- National University Hospital, Singapore.
| | - Ciaran Gerard Forde
- Singapore Institute for Clinical Sciences, National University of Singapore, Singapore.
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
- Duke-NUS Medical School, Singapore.
| | - Ching-Yu Cheng
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
- Duke-NUS Medical School, Singapore.
- Department of Ophthalmology, National University of Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
- Duke-NUS Medical School, Singapore.
- Department of Ophthalmology, National University of Singapore, Singapore
| | - Ecosse L Lamoureux
- Singapore Eye Research Institute and Singapore National Eye Centre, Singapore.
- Duke-NUS Medical School, Singapore.
- Department of Ophthalmology, National University of Singapore, Singapore
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14
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Ilan Y, Spigelman Z. Establishing patient-tailored variability-based paradigms for anti-cancer therapy: Using the inherent trajectories which underlie cancer for overcoming drug resistance. Cancer Treat Res Commun 2020; 25:100240. [PMID: 33246316 DOI: 10.1016/j.ctarc.2020.100240] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 10/30/2020] [Accepted: 11/16/2020] [Indexed: 06/11/2023]
Abstract
Drug resistance is a major obstacle for successful therapy of many malignancies and is affecting the loss of response to chemotherapy and immunotherapy. Tumor-related compensatory adaptation mechanisms contribute to the development of drug resistance. Variability is inherent to biological systems and altered patterns of variability are associated with disease conditions. The marked intra and inter patient tumor heterogeneity, and the diverse mechanism contributing to drug resistance in different subjects, which may change over time even in the same patient, necessitate the development of personalized dynamic approaches for overcoming drug resistance. Altered dosing regimens, the potential role of chronotherapy, and drug holidays are effective in cancer therapy and immunotherapy. In the present review we describe the difficulty of overcoming drug resistance in a dynamic system and present the use of the inherent trajectories which underlie cancer development for building therapeutic regimens which can overcome resistance. The establishment of a platform wherein patient-tailored variability signatures are used for overcoming resistance for ensuing long term sustainable improved responses is presented.
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Affiliation(s)
- Yaron Ilan
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel.
| | - Zachary Spigelman
- Department of Hematology and Oncology, Lahey Hospital and Beth Israel Medical Center, MA, USA
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15
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Bäcklund T, Öhberg F, Johansson G, Grip H, Sundström N. Novel, clinically applicable method to measure step-width during the swing phase of gait. Physiol Meas 2020; 41:065005. [PMID: 32442989 DOI: 10.1088/1361-6579/ab95ed] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Step-width during walking is an indicator of stability and balance in patients with neurological disorders, and development of objective tools to measure this clinically would be a great advantage. The aim of this study was to validate an in-house-developed gait analysis system (Striton), based on optical and inertial sensors and a novel method for stride detection, for measuring step-width during the swing phase of gait and temporal parameters. APPROACH The step-width and stride-time measurements were validated in an experimental setup, against a 3D motion capture system and on an instrumented walkway. Further, test-retest and day-to-day variability were evaluated, and gait parameters were collected from 87 elderly persons (EP) and four individuals with idiopathic normal pressure hydrocephalus (iNPH) before/after surgery. MAIN RESULTS Accuracy of the step-width measurement was high: in the experimental setup mean error was 0.08 ± 0.25 cm (R = 1.00) and against the 3D motion capture system 0.04 ± 1.12 cm (R = 0.98). Test-retest and day-to-day measurements were equal within ±0.5 cm. Mean difference in stride time was -0.003 ± 0.008 s between Striton and the instrumented walkway. The Striton system was successfully applied in the clinical setting on individuals with iNPH, which had larger step-width (6.88 cm, n = 4) compared to EP (5.22 cm, n = 87). SIGNIFICANCE We conclude that Striton is a valid, reliable and wearable system for quantitative assessment of step-width and temporal parameters during gait. Initial measurements indicate that the newly defined step-width parameter differs between EP and patients with iNPH and before/after surgery. Thus, there is potential for clinical applicability in patients with reduced gait stability.
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Affiliation(s)
- Tomas Bäcklund
- Department of Radiation Sciences, Biomedical Engineering, Umeå University, Umeå, Sweden
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16
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Marmelat V, Duncan A, Meltz S, Meidinger RL, Hellman AM. Fractal auditory stimulation has greater benefit for people with Parkinson's disease showing more random gait pattern. Gait Posture 2020; 80:234-239. [PMID: 32554147 PMCID: PMC7375405 DOI: 10.1016/j.gaitpost.2020.05.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 04/20/2020] [Accepted: 05/17/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Healthy gait dynamics are characterized by the presence of fractal, persistent stride-to-stride variations, which become more random with Parkinson's disease (PD). Rhythmic auditory stimulation with fractal beat-to-beat variations can change gait dynamics in people with PD toward more persistence. RESEARCH QUESTION How does gait in people with PD change when synchronizing steps with fractal melodic metronomes with different step-to-beat ratios, and which stimulus do they prefer? METHODS In this cross-sectional study, 15 people with PD and 15 healthy older adults walked over-ground in three conditions: self-paced, paced by a fractal auditory stimulus with a 1:1 step-to-beat ratio ('metronome'), and fractal auditory stimulus with a 1:2 step-to-beat ratio ('music'). Gait dynamics were recorded with instrumented insoles, and detrended fluctuation analysis (DFA) was applied to the series of stride time intervals. Stimuli preference was assessed using Likert-like scales and open-ended questions. ANOVAs were used to compare mean, coefficient of variation, α-DFA, and the responses from the continuous Likert scales. Pearson correlations were used to assess the relationship between 'music' and 'metronome' enjoyment or difficulty with gait outcomes, and to determine the association between baseline α-DFA and changes due to the stimuli. RESULTS Our major findings are that (i) stride-to-stride variations were more persistent with the 'metronome' compared to baseline for both groups, (ii) the effect was greater for people with lower α-DFA at baseline (i.e., more random stride-to-stride variations), and (iii) both groups found the 'metronome' less difficult to synchronize with. SIGNIFICANCE This study showed that people with PD and healthy older adults walk with higher statistical persistence in their stride-to-stride variations when instructed to synchronize their steps with a fractal stimulus. Participants with lower persistence at baseline benefited the most from the fractal 'metronome', highlighting the importance to develop patient-centered tests and interventions.
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Affiliation(s)
- Vivien Marmelat
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, Nebraska, 68184, United States of America,Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, 68198, United States of America
| | - Austin Duncan
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, Nebraska, 68184, United States of America
| | - Shane Meltz
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, Nebraska, 68184, United States of America
| | - Ryan L. Meidinger
- Department of Biomechanics, University of Nebraska at Omaha, Omaha, Nebraska, 68184, United States of America
| | - Amy M. Hellman
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, 68198, United States of America
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17
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Ravi DK, Marmelat V, Taylor WR, Newell KM, Stergiou N, Singh NB. Assessing the Temporal Organization of Walking Variability: A Systematic Review and Consensus Guidelines on Detrended Fluctuation Analysis. Front Physiol 2020; 11:562. [PMID: 32655400 PMCID: PMC7324754 DOI: 10.3389/fphys.2020.00562] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 05/05/2020] [Indexed: 12/18/2022] Open
Abstract
Human physiological signals are inherently rhythmic and have a hallmark feature in that even distant intrasignal measurements are related to each other. This relationship is termed long-range correlation and has been recognized as an indicator of the optimal state of the observed physiological systems, among which the locomotor system. Loss of long-range correlations has been found as a result of aging as well as disease, which can be evaluated with detrended fluctuation analysis (DFA). Recently, DFA and the scaling exponent α have been employed for understanding the degeneration of temporal regulation of human walking biorhythms in, for example, Parkinson disease (PD). However, heterogeneous evidence on scaling exponent α values reported in the literature across different population groups has put into question what constitutes a healthy physiological pattern. Therefore, the purpose of this systematic review was to investigate the functional thresholds of scaling exponent α in young vs. older adults, as well as between patients with PD and age-matched asymptomatic controls. Aging and PD exhibited a negative effect size (i.e., led to decreased long-range correlations) of -0.20 and -0.53, respectively. Our meta-analysis based on 14 studies provides evidence that a mean scaling exponent α threshold of 0.86 [2 standard error (0.76, 0.96)] is able to optimally discriminate temporal organization of stride interval between young and old, whereas 0.82 (0.72, 0.92) differentiates patients with PD and age-matched asymptomatic controls. The optimal thresholds presented in this review together with the consensus guidelines for using DFA might allow a more sensitive and reliable application of this metric for understanding human walking physiology than has been achieved to date.
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Affiliation(s)
- Deepak K Ravi
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
| | - Vivien Marmelat
- Department of Biomechanics and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE, United States
| | | | - Karl M Newell
- Department of Kinesiology, University of Georgia, Athens, GA, United States
| | - Nick Stergiou
- Department of Biomechanics and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE, United States
| | - Navrag B Singh
- Institute for Biomechanics, ETH Zurich, Zurich, Switzerland
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18
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Renggli D, Graf C, Tachatos N, Singh N, Meboldt M, Taylor WR, Stieglitz L, Schmid Daners M. Wearable Inertial Measurement Units for Assessing Gait in Real-World Environments. Front Physiol 2020; 11:90. [PMID: 32153420 PMCID: PMC7044412 DOI: 10.3389/fphys.2020.00090] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Accepted: 01/27/2020] [Indexed: 11/19/2022] Open
Abstract
Background Walking patterns can provide important indications of a person’s health status and be beneficial in the early diagnosis of individuals with a potential walking disorder. For appropriate gait analysis, it is critical that natural functional walking characteristics are captured, rather than those experienced in artificial or observed settings. To better understand the extent to which setting influences gait patterns, and particularly whether observation plays a varying role on subjects of different ages, the current study investigates to what extent people walk differently in lab versus real-world environments and whether age dependencies exist. Methods The walking patterns of 20 young and 20 elderly healthy subjects were recorded with five wearable inertial measurement units (ZurichMOVE sensors) attached to both ankles, both wrists and the chest. An automated detection process based on dynamic time warping was developed to efficiently identify the relevant sequences. From the ZurichMOVE recordings, 15 spatio-temporal gait parameters were extracted, analyzed and compared between motion patterns captured in a controlled lab environment (10 m walking test) and the non-controlled ecologically valid real-world environment (72 h recording) in both groups. Results Several parameters (Cluster A) showed significant differences between the two environments for both groups, including an increased outward foot rotation, step width, number of steps per 180° turn, stance to swing ratio, and cycle time deviation in the real-world. A number of parameters (Cluster B) showed only significant differences between the two environments for elderly subjects, including a decreased gait velocity (p = 0.0072), decreased cadence (p = 0.0051) and increased cycle time (p = 0.0051) in real-world settings. Importantly, the real-world environment increased the differences in several parameters between the young and elderly groups. Conclusion Elderly test subjects walked differently in controlled lab settings compared to their real-world environments, which indicates the need to better understand natural walking patterns under ecologically valid conditions before clinically relevant conclusions can be drawn on a subject’s functional status. Moreover, the greater inter-group differences in real-world environments seem promising regarding the sensitive identification of subjects with indications of a walking disorder.
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Affiliation(s)
- David Renggli
- Product Development Group Zurich, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland
| | - Christina Graf
- Product Development Group Zurich, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland
| | - Nikolaos Tachatos
- Product Development Group Zurich, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland
| | - Navrag Singh
- Institute for Biomechanics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Mirko Meboldt
- Product Development Group Zurich, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland
| | - William R Taylor
- Institute for Biomechanics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Lennart Stieglitz
- Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland
| | - Marianne Schmid Daners
- Product Development Group Zurich, Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland
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19
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Gaßner H, Jensen D, Marxreiter F, Kletsch A, Bohlen S, Schubert R, Muratori LM, Eskofier B, Klucken J, Winkler J, Reilmann R, Kohl Z. Gait variability as digital biomarker of disease severity in Huntington's disease. J Neurol 2020; 267:1594-1601. [PMID: 32048014 PMCID: PMC7293689 DOI: 10.1007/s00415-020-09725-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Revised: 01/20/2020] [Accepted: 01/22/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND Impaired gait plays an important role for quality of life in patients with Huntington's disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments. OBJECTIVE To objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particularly, gait parameters were correlated to the Unified Huntington's Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC). METHODS Patients with manifest HD at two German sites (n = 43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age- and gender-matched controls performed a defined gait test (4 × 10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefficient of variance (CV). RESULTS Stride length (- 15%) and gait velocity (- 19%) were reduced, while stride (+ 7%) and stance time (+ 2%) were increased in patients with HD. However, parameters reflecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416 ≤ rSp ≤ 0.690). Objective gait variability parameters correlated with disease stage based upon TFC. CONCLUSIONS Sensor-based gait variability parameters were identified as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity.
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Affiliation(s)
- Heiko Gaßner
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany
| | - Dennis Jensen
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany
| | - F Marxreiter
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany
| | - Anja Kletsch
- George-Huntington Institute (GHI) GmbH, Münster, Germany
| | - Stefan Bohlen
- George-Huntington Institute (GHI) GmbH, Münster, Germany
| | - Robin Schubert
- George-Huntington Institute (GHI) GmbH, Münster, Germany
| | - Lisa M Muratori
- George-Huntington Institute (GHI) GmbH, Münster, Germany
- Rehabilitation Research and Movement Performance Laboratory (RRAMP Lab), Stony Brook University, Stony Brook, NY, USA
| | - Bjoern Eskofier
- Machine Learning and Data Analytics Lab, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jochen Klucken
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany
- Medical Valley-Digital Health Application Center GmbH, Bamberg, Germany
- Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany
| | - Jürgen Winkler
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany
| | - Ralf Reilmann
- George-Huntington Institute (GHI) GmbH, Münster, Germany
- Department of Radiology, University of Muenster, Muenster, Germany
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany
| | - Zacharias Kohl
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054, Erlangen, Germany.
- Center for Rare Diseases Erlangen, University Hospital Erlangen, Erlangen, Germany.
- Department of Neurology, University of Regensburg, Regensburg, Germany.
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20
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Ravi DK, Gwerder M, König Ignasiak N, Baumann CR, Uhl M, van Dieën JH, Taylor WR, Singh NB. Revealing the optimal thresholds for movement performance: A systematic review and meta-analysis to benchmark pathological walking behaviour. Neurosci Biobehav Rev 2019; 108:24-33. [PMID: 31639377 DOI: 10.1016/j.neubiorev.2019.10.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 10/07/2019] [Accepted: 10/11/2019] [Indexed: 01/29/2023]
Abstract
In order to address whether increased levels of movement output variability indicate pathological performance, we systematically reviewed and synthesized meta-analysis data on healthy and pathological motor behavior. After screening up to 24'000 reports from four databases, 85 studies were included containing 2409 patients and 2523 healthy asymptomatic controls. The optimal thresholds of variability with uncertainty boundaries (in % Coefficient of Variation ± Standard Error) were estimated in 7 parameters: stride time (2.34 ± 0.21), stride length (2.99 ± 0.37), step length (3.34 ± 0.84), swing time (2.94 ± 0.60), step time (3.35 ± 0.23), step width (15.87 ± 1.86), and dual-limb support time (6.08 ± 2.83). All spatio-temporal parameters exhibited a positive effect size (pathology led to increased variability) except step width variability (Effect Size = -0.21). By objectively benchmarking thresholds for pathological motor variability also presented through a case-study, this review provides access to movement signatures to understand neurological changes in an individual that are apparent in movement variability. The comprehensive evidence presented now qualifies stride time variability as a movement biomarker, endorsing its applicability as a viable outcome measure in clinical trials.
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Affiliation(s)
- Deepak K Ravi
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland
| | - Michelle Gwerder
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland
| | - Niklas König Ignasiak
- Department of Physical Therapy, Chapman University, Rinker Health Science Campus, 9401 Jeronimo Rd, Irvine, CA, 92618, USA
| | - Christian R Baumann
- Department of Neurology, University Hospital Zurich, 8091, Zürich, Switzerland
| | - Mechtild Uhl
- Department of Neurology, University Hospital Zurich, 8091, Zürich, Switzerland
| | - Jaap H van Dieën
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, van der Boechorststraat 9, 1081 BT, Amsterdam, the Netherlands
| | - William R Taylor
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland.
| | - Navrag B Singh
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland
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21
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Orter S, Ravi DK, Singh NB, Vogl F, Taylor WR, König Ignasiak N. A method to concatenate multiple short time series for evaluating dynamic behaviour during walking. PLoS One 2019; 14:e0218594. [PMID: 31226152 PMCID: PMC6588245 DOI: 10.1371/journal.pone.0218594] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Accepted: 06/05/2019] [Indexed: 11/18/2022] Open
Abstract
Gait variability is a sensitive metric for assessing functional deficits in individuals with mobility impairments. To correctly represent the temporal evolution of gait kinematics, nonlinear measures require extended and uninterrupted time series. In this study, we present and validate a novel algorithm for concatenating multiple time-series in order to allow the nonlinear analysis of gait data from standard and unrestricted overground walking protocols. The full-body gait patterns of twenty healthy subjects were captured during five walking trials (at least 5 minutes) on a treadmill under different weight perturbation conditions. The collected time series were cut into multiple shorter time series of varying lengths and subsequently concatenated using a novel algorithm that identifies similar poses in successive time series in order to determine an optimal concatenation time point. After alignment of the datasets, the approach then concatenated the data to provide a smooth transition. Nonlinear measures to assess stability (Largest Lyapunov Exponent, LyE) and regularity (Sample Entropy, SE) were calculated in order to quantify the efficacy of the concatenation approach using intra-class correlation coefficients, standard error of measurement and paired effect sizes. Our results indicate overall good agreement between the full uninterrupted and the concatenated time series for LyE. However, SE was more sensitive to the proposed concatenation algorithm and might lead to false interpretation of physiological gait signals. This approach opens perspectives for analysis of dynamic stability of gait data from physiological overground walking protocols, but also the re-processing and estimation of nonlinear metrics from previously collected datasets.
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Affiliation(s)
- Stefan Orter
- Institute for Biomechanics, ETH Zürich, Zurich, Switzerland
| | - Deepak K. Ravi
- Institute for Biomechanics, ETH Zürich, Zurich, Switzerland
| | | | - Florian Vogl
- Institute for Biomechanics, ETH Zürich, Zurich, Switzerland
| | - William R. Taylor
- Institute for Biomechanics, ETH Zürich, Zurich, Switzerland
- * E-mail:
| | - Niklas König Ignasiak
- Institute for Biomechanics, ETH Zürich, Zurich, Switzerland
- Department of Physical Therapy, Chapman University, Irvine, California, United States of America
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22
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König Ignasiak N, Ravi DK, Orter S, Hosseini Nasab SH, Taylor WR, Singh NB. Does variability of footfall kinematics correlate with dynamic stability of the centre of mass during walking? PLoS One 2019; 14:e0217460. [PMID: 31150452 PMCID: PMC6544240 DOI: 10.1371/journal.pone.0217460] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 05/13/2019] [Indexed: 01/22/2023] Open
Abstract
A stable walking pattern is presumably essential to avoid falls. Stability of walking is most accurately determined by the short-term local dynamic stability (maximum Lyapunov exponent) of the body centre of mass. In many studies related to fall risk, however, variability of step width is considered to be indicative of the stability of the centre of mass during walking. However, other footfall parameters, in particular variability of stride time, have also been associated with increased risk for falling. Therefore, the aim of this study was to investigate the association between short-term local dynamic stability of the body centre of mass and different measures of footfall variability. Twenty subjects performed unperturbed walking trials on a treadmill and under increased (addition of 40% body weight) and decreased (harness system) demands to stabilise the body centre of mass. Association between stability of the centre of mass and footfall parameters was established using a structural equation model. Walking with additional body weight lead to greater instability of the centre of mass and increased stride time variability, however had no effect on step width variability. Supported walking in the harness system did not increase centre of mass stability further, however, led to a significant decrease of step width and increase in stride time variability. A structural equation model could only predict 8% of the variance of the centre of mass stability after variability of step width, stride time and stride length were included. A model which included only step width variability as exogenous variable, failed to predict centre of mass stability. Because of the failure to predict centre of mass stability in this study, it appears, that the stability of the centre of mass is controlled by more complex interaction of sagittal and frontal plane temporal and spatial footfall parameters, than those observed by standard variability measures. Anyway, this study does not support the application of step width variability as indicator for medio-lateral stability of the centre of mass during walking.
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Affiliation(s)
- Niklas König Ignasiak
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, Zurich, Switzerland
- Department of Physical Therapy, Chapman University, Irvine, California, United States of America
| | - Deepak K. Ravi
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, Zurich, Switzerland
| | - Stefan Orter
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, Zurich, Switzerland
| | | | - William R. Taylor
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, Zurich, Switzerland
- * E-mail:
| | - Navrag B. Singh
- Institute for Biomechanics, ETH Zürich, Leopold-Ruzicka-Weg 4, Zurich, Switzerland
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23
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Kroneberg D, Elshehabi M, Meyer AC, Otte K, Doss S, Paul F, Nussbaum S, Berg D, Kühn AA, Maetzler W, Schmitz-Hübsch T. Less Is More - Estimation of the Number of Strides Required to Assess Gait Variability in Spatially Confined Settings. Front Aging Neurosci 2019; 10:435. [PMID: 30719002 PMCID: PMC6348278 DOI: 10.3389/fnagi.2018.00435] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 12/20/2018] [Indexed: 12/19/2022] Open
Abstract
Background: Gait variability is an established marker of gait function that can be assessed using sensor-based approaches. In clinical settings, spatial constraints and patient condition impede the execution of longer distance walks for the recording of gait parameters. Turning paradigms are often used to overcome these constraints and commercial gait analysis systems algorithmically exclude turns for gait parameters calculations. We investigated the effect of turns in sensor-based assessment of gait variability. Methods: Continuous recordings from 31 patients with movement disorders (ataxia, essential tremor and Parkinson’s disease) and 162 healthy elderly (HE) performing level walks including 180° turns were obtained using an inertial sensor system. Accuracy of the manufacturer’s algorithm of turn-detection was verified by plotting stride time series. Strides before and after turn events were extracted and compared to respective average of all strides. Coefficient of variation (CoV) of stride length and stride time was calculated for entire set of strides, segments between turns and as cumulative values. Their variance and congruency was used to estimate the number of strides required to reliably assess the magnitude of stride variability. Results: Non-detection of turns in 5.8% of HE lead to falsely increased CoV for these individuals. Even after exclusion of these, strides before/after turns tended to be spatially shorter and temporally longer in all groups, contributing to an increase of CoV at group level and widening of confidence margins with increasing numbers of strides. This could be attenuated by a more generous turn excision as an alternative approach. Correlation analyses revealed excellent consistency for CoVs after at most 20 strides in all groups. Respective stride counts were even lower in patients using a more generous turn excision. Conclusion: Including turns to increase continuous walking distance in spatially confined settings does not necessarily improve the validity and reliability of gait variability measures. Specifically with gait pathology, perturbations of stride characteristics before/after algorithmically excised turns were observed that may increase gait variability with this paradigm. We conclude that shorter distance walks of around 15 strides suffice for reliable and valid recordings of gait variability in the groups studied here.
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Affiliation(s)
- Daniel Kroneberg
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany
| | - Morad Elshehabi
- Department of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, Germany.,Department of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Anne-Christiane Meyer
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany
| | - Karen Otte
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, Germany
| | - Sarah Doss
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany
| | - Friedemann Paul
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany.,Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Susanne Nussbaum
- Department of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Daniela Berg
- Department of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, Germany.,Department of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Andrea A Kühn
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Neurology, Berlin, Germany.,Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin School of Mind and Brain, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Walter Maetzler
- Department of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, Germany.,Department of Neurodegenerative Diseases, Center for Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Tanja Schmitz-Hübsch
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany
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24
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Zhang M, Artan NS, Gu H, Dong Z, Burina Ganatra L, Shermon S, Rabin E. Gait Study of Parkinson's Disease Subjects Using Haptic Cues with A Motorized Walker. SENSORS (BASEL, SWITZERLAND) 2018; 18:E3549. [PMID: 30347753 PMCID: PMC6210411 DOI: 10.3390/s18103549] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 10/16/2018] [Accepted: 10/17/2018] [Indexed: 11/23/2022]
Abstract
Gait abnormalities are one of the distinguishing symptoms of patients with Parkinson's disease (PD) that contribute to fall risk. Our study compares the gait parameters of people with PD when they walk through a predefined course under different haptic speed cue conditions (1) without assistance, (2) pushing a conventional rolling walker, and (3) holding onto a self-navigating motorized walker under different speed cues. Six people with PD were recruited at the New York Institute of Technology College of Osteopathic Medicine to participate in this study. Spatial posture and gait data of the test subjects were collected via a VICON motion capture system. We developed a framework to process and extract gait features and applied statistical analysis on these features to examine the significance of the findings. The results showed that the motorized walker providing a robust haptic cue significantly improved gait symmetry of PD subjects. Specifically, the asymmetry index of the gait cycle time was reduced from 6.7% when walking without assistance to 0.56% and below when using a walker. Furthermore, the double support time of a gait cycle was reduced by 4.88% compared to walking without assistance.
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Affiliation(s)
- Minhua Zhang
- College of Engineering and Computing Sciences, New York Institute of Technology, New York, NY 10023, USA.
| | - N Sertac Artan
- College of Engineering and Computing Sciences, New York Institute of Technology, New York, NY 10023, USA.
| | - Huanying Gu
- College of Engineering and Computing Sciences, New York Institute of Technology, New York, NY 10023, USA.
| | - Ziqian Dong
- College of Engineering and Computing Sciences, New York Institute of Technology, New York, NY 10023, USA.
| | - Lyudmila Burina Ganatra
- College of Osteopathic Medicine, New York Institute of Technology, 101 Northern Blvd, Glen Head, NY 11545, USA.
| | - Suzanna Shermon
- College of Osteopathic Medicine, New York Institute of Technology, 101 Northern Blvd, Glen Head, NY 11545, USA.
| | - Ely Rabin
- College of Osteopathic Medicine, New York Institute of Technology, 101 Northern Blvd, Glen Head, NY 11545, USA.
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25
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Beck Y, Herman T, Brozgol M, Giladi N, Mirelman A, Hausdorff JM. SPARC: a new approach to quantifying gait smoothness in patients with Parkinson's disease. J Neuroeng Rehabil 2018; 15:49. [PMID: 29914518 PMCID: PMC6006701 DOI: 10.1186/s12984-018-0398-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 06/11/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Impairments in biomechanics and neural control can disrupt the timing and muscle pattern activation necessary for smooth gait. Gait is one of the most affected motor characteristics in Parkinson's disease (PD), but its smoothness has not been well-studied. This work applies the recently proposed spectral arc length measure (SPARC) to study, for the first time, gait in patients with PD. We hypothesized that the gait of patients with PD would be less smooth than that of healthy controls, as reflected in the SPARC measures. METHODS The gait of 101 PD patients and 39 healthy controls was assessed using an inertial sensor. Smoothness of gait was estimated with SPARC (respectively from acceleration and angular velocity signals, SPARC-Acc and SPARC-Gyro) and harmonic ratios. Correlations between SPARC, traditional gait measures and the motor part of the Unified Parkinson's Disease Rating Scale (UPDRS) were evaluated. Measurements and analysis were conducted with and without anti-PD medication. RESULTS SPARC measures were lower (less smooth) in PD than in controls (SPARC-Acc: PD: - 6.11 ± 0.74; CO: -5.17 ± 0.79; p < 0.001). When comparing PD to controls, SPARC-Acc differed more than other measures of gait (i.e., largest effect size, which was > 1). SPARC measures were correlated with UPDRS motor score (r = - 0.65), while they were independent of other measures of gait smoothness. PD gait in the on state was smoother than in the off state (p < 0.001). CONCLUSIONS SPARC calculated from trunk acceleration and angular velocity signals provide valid measures of walking smoothness in PD. SPARC is sensitive to Parkinson's disease and PD medications and can be used of as another, complementary measure of the motor control of walking in PD.
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Affiliation(s)
- Yoav Beck
- Center for the study of Movement, Cognition, and Mobility, Neurological Institute, Department of Neurology, Tel Aviv Sourasky Medical Center, 6 Weizmann street, 64239 Tel Aviv, Israel
- Graduate Training Centre of Neuroscience/ IMPRS for Cognitive and Systems Neuroscience, Tübingen, Germany
| | - Talia Herman
- Center for the study of Movement, Cognition, and Mobility, Neurological Institute, Department of Neurology, Tel Aviv Sourasky Medical Center, 6 Weizmann street, 64239 Tel Aviv, Israel
| | - Marina Brozgol
- Center for the study of Movement, Cognition, and Mobility, Neurological Institute, Department of Neurology, Tel Aviv Sourasky Medical Center, 6 Weizmann street, 64239 Tel Aviv, Israel
| | - Nir Giladi
- Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Department of Neurology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Anat Mirelman
- Center for the study of Movement, Cognition, and Mobility, Neurological Institute, Department of Neurology, Tel Aviv Sourasky Medical Center, 6 Weizmann street, 64239 Tel Aviv, Israel
- Department of Neurology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Jeffrey M. Hausdorff
- Center for the study of Movement, Cognition, and Mobility, Neurological Institute, Department of Neurology, Tel Aviv Sourasky Medical Center, 6 Weizmann street, 64239 Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Physical Therapy, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Rush Alzheimer’s Disease Center and Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, USA
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26
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Viewpoint and practical recommendations from a movement disorder specialist panel on objective measurement in the clinical management of Parkinson's disease. NPJ PARKINSONS DISEASE 2018; 4:14. [PMID: 29761156 PMCID: PMC5945844 DOI: 10.1038/s41531-018-0051-7] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 04/11/2018] [Accepted: 04/12/2018] [Indexed: 02/02/2023]
Abstract
Motor aspects of Parkinson's disease, such as fluctuations and dyskinesia, can be reliably evaluated using a variety of "wearable" technologies, but practical guidance on objective measurement (OM) and the optimum use of these devices is lacking. Therefore, as a first step, a panel of movement disorder specialists met to provide guidance on how OM could be assessed and incorporated into clinical guidelines. A key aspect of the incorporation of OM into the management of Parkinson's disease (PD) is defining cutoff values that separate "controlled" from "uncontrolled" symptoms that can be modified by therapy and that relate to an outcome that is relevant to the person with PD (such as quality of life). Defining cutoffs by consensus, which can be subsequently tested and refined, is the first step to optimizing OM in the management of PD. OM should be used by all clinicians that treat people with PD but the least experienced may find the most value, but this requires guidance from experts to allow non-experts to apply guidelines. While evidence is gained for devices that produce OM, expert opinion is needed to supplement the evidence base.
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27
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Seo K, Lee A, Kim J, Ryu H, Choi H. Measuring the Kinematics of Daily Living Movements with Motion Capture Systems in Virtual Reality. J Vis Exp 2018. [PMID: 29683456 DOI: 10.3791/57284] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
The inability to complete instrumental activities of daily living (IADL) is a precursor to various neuropsychological diseases. Questionnaire-based assessments of IADL are easy to use but prone to subjective bias. Here, we describe a novel virtual reality (VR) test to assess two complex IADL tasks: handling financial transactions and using public transportation. While a participant performs the tasks in a VR setting, a motion capture system traces the position and orientation of the dominant hand and head in a three-dimensional Cartesian coordinate system. Kinematic raw data are collected and converted into 'kinematic performance measures,' i.e., motion trajectory, moving distance, and time to completion. Motion trajectory is the path of a particular body part (e.g., dominant hand or head) in space. Moving distance refers to the total distance of the trajectory, and time to completion is how long it took to complete an IADL task. These kinematic measures could discriminate patients with cognitive impairment from healthy controls. The development of this kinematic measuring protocol allows detection of early IADL-related cognitive impairments.
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Affiliation(s)
- Kyoungwon Seo
- Department of Industrial Engineering, Hanyang University
| | - Ahreum Lee
- Department of Industrial Engineering, Hanyang University
| | | | - Hokyoung Ryu
- Department of Arts & Technology, Hanyang University;
| | - Hojin Choi
- Department of Neurology, College of Medicine, Hanyang University
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28
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Matias R, Paixão V, Bouça R, Ferreira JJ. A Perspective on Wearable Sensor Measurements and Data Science for Parkinson's Disease. Front Neurol 2017; 8:677. [PMID: 29312115 PMCID: PMC5732915 DOI: 10.3389/fneur.2017.00677] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 11/28/2017] [Indexed: 01/07/2023] Open
Abstract
Miniaturized and wearable sensor-based measurements enable the assessment of Parkinson's disease (PD) motor-related features like never before and hold great promise as non-invasive biomarkers for early and accurate diagnosis, and monitoring the progression of PD. High-fidelity human movement reconstruction and simulation can already be conducted in a clinical setting with increasingly precise and affordable motion technology enabling access to high-quality labeled data on patients' subcomponents of movement (kinematics and kinetics). At the same time, body-worn sensors now allow us to extend some quantitative movement-related measurements to patients' daily living activities. This era of patient movement "cognification" is bringing us previously inaccessible variables that encode patients' movement, and that, together with measures from clinical examinations, poses new challenges in data analysis. We present herein examples of the application of an unsupervised methodology to classify movement behavior in healthy individuals and patients with PD where no specific knowledge on the type of behaviors recorded is needed. We are most certainly leaving the early stage of the exponential curve that describes the current technological evolution and soon will be entering its steep ascent. But there is already a benefit to be derived from current motion technology and sophisticated data science methods to objectively measure parkinsonian impairments.
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Affiliation(s)
- Ricardo Matias
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
- Escola Superior Saúde – Instituto Politécnico de Setúbal, Setúbal, Portugal
| | - Vitor Paixão
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Raquel Bouça
- Faculty of Medicine, Clinical Pharmacological Unit, Instituto de Medicina Molecular, University of Lisbon, Lisbon, Portugal
| | - Joaquim J. Ferreira
- Faculty of Medicine, Clinical Pharmacological Unit, Instituto de Medicina Molecular, University of Lisbon, Lisbon, Portugal
- Campus Neurológico Sénior (CNS), Torres Vedras, Portugal
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