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Bachman SL, Blankenship JM, Busa M, Serviente C, Lyden K, Clay I. Capturing Measures That Matter: The Potential Value of Digital Measures of Physical Behavior for Alzheimer's Disease Drug Development. J Alzheimers Dis 2023; 95:379-389. [PMID: 37545234 PMCID: PMC10578291 DOI: 10.3233/jad-230152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2023] [Indexed: 08/08/2023]
Abstract
Alzheimer's disease (AD) is a devastating neurodegenerative disease and the primary cause of dementia worldwide. Despite the magnitude of AD's impact on patients, caregivers, and society, nearly all AD clinical trials fail. A potential contributor to this high rate of failure is that established clinical outcome assessments fail to capture subtle clinical changes, entail high burden for patients and their caregivers, and ineffectively address the aspects of health deemed important by patients and their caregivers. AD progression is associated with widespread changes in physical behavior that have impacts on the ability to function independently, which is a meaningful aspect of health for patients with AD and important for diagnosis. However, established assessments of functional independence remain underutilized in AD clinical trials and are limited by subjective biases and ceiling effects. Digital measures of real-world physical behavior assessed passively, continuously, and remotely using digital health technologies have the potential to address some of these limitations and to capture aspects of functional independence in patients with AD. In particular, measures of real-world gait, physical activity, and life-space mobility captured with wearable sensors may offer value. Additional research is needed to understand the validity, feasibility, and acceptability of these measures in AD clinical research.
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Affiliation(s)
| | | | - Michael Busa
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA, USA
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Corinna Serviente
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA, USA
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2
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Cabaraux P, Agrawal SK, Cai H, Calabro RS, Casali C, Damm L, Doss S, Habas C, Horn AKE, Ilg W, Louis ED, Mitoma H, Monaco V, Petracca M, Ranavolo A, Rao AK, Ruggieri S, Schirinzi T, Serrao M, Summa S, Strupp M, Surgent O, Synofzik M, Tao S, Terasi H, Torres-Russotto D, Travers B, Roper JA, Manto M. Consensus Paper: Ataxic Gait. CEREBELLUM (LONDON, ENGLAND) 2022; 22:394-430. [PMID: 35414041 DOI: 10.1007/s12311-022-01373-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/20/2022] [Indexed: 12/19/2022]
Abstract
The aim of this consensus paper is to discuss the roles of the cerebellum in human gait, as well as its assessment and therapy. Cerebellar vermis is critical for postural control. The cerebellum ensures the mapping of sensory information into temporally relevant motor commands. Mental imagery of gait involves intrinsically connected fronto-parietal networks comprising the cerebellum. Muscular activities in cerebellar patients show impaired timing of discharges, affecting the patterning of the synergies subserving locomotion. Ataxia of stance/gait is amongst the first cerebellar deficits in cerebellar disorders such as degenerative ataxias and is a disabling symptom with a high risk of falls. Prolonged discharges and increased muscle coactivation may be related to compensatory mechanisms and enhanced body sway, respectively. Essential tremor is frequently associated with mild gait ataxia. There is growing evidence for an important role of the cerebellar cortex in the pathogenesis of essential tremor. In multiple sclerosis, balance and gait are affected due to cerebellar and spinal cord involvement, as a result of disseminated demyelination and neurodegeneration impairing proprioception. In orthostatic tremor, patients often show mild-to-moderate limb and gait ataxia. The tremor generator is likely located in the posterior fossa. Tandem gait is impaired in the early stages of cerebellar disorders and may be particularly useful in the evaluation of pre-ataxic stages of progressive ataxias. Impaired inter-joint coordination and enhanced variability of gait temporal and kinetic parameters can be grasped by wearable devices such as accelerometers. Kinect is a promising low cost technology to obtain reliable measurements and remote assessments of gait. Deep learning methods are being developed in order to help clinicians in the diagnosis and decision-making process. Locomotor adaptation is impaired in cerebellar patients. Coordinative training aims to improve the coordinative strategy and foot placements across strides, cerebellar patients benefiting from intense rehabilitation therapies. Robotic training is a promising approach to complement conventional rehabilitation and neuromodulation of the cerebellum. Wearable dynamic orthoses represent a potential aid to assist gait. The panel of experts agree that the understanding of the cerebellar contribution to gait control will lead to a better management of cerebellar ataxias in general and will likely contribute to use gait parameters as robust biomarkers of future clinical trials.
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Affiliation(s)
- Pierre Cabaraux
- Unité Des Ataxies Cérébelleuses, Department of Neurology, CHU de Charleroi, Charleroi, Belgium.
| | | | - Huaying Cai
- Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | | | - Carlo Casali
- Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy
| | - Loic Damm
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - Sarah Doss
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, USA
| | - Christophe Habas
- Université Versailles Saint-Quentin, Versailles, France.,Service de NeuroImagerie, Centre Hospitalier National des 15-20, Paris, France
| | - Anja K E Horn
- Institute of Anatomy and Cell Biology I, Ludwig Maximilians-University Munich, Munich, Germany
| | - Winfried Ilg
- Section Computational Sensomotorics, Hertie Institute for Clinical Brain Research, University Tübingen, Tübingen, Germany
| | - Elan D Louis
- Department of Neurology, University of Texas Southwestern, Dallas, TX, USA
| | - Hiroshi Mitoma
- Department of Medical Education, Tokyo Medical University, Tokyo, Japan
| | - Vito Monaco
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Maria Petracca
- Department of Human Neurosciences, University of Rome Sapienza, Rome, Italy
| | - Alberto Ranavolo
- Department of Occupational and Environmental Medicine, Epidemiology and Hygiene, INAIL, Monte Porzio Catone, Rome, Italy
| | - Ashwini K Rao
- Department of Rehabilitation & Regenerative Medicine (Programs in Physical Therapy), Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Serena Ruggieri
- Department of Human Neurosciences, University of Rome Sapienza, Rome, Italy.,Neuroimmunology Unit, IRCSS Fondazione Santa Lucia, Rome, Italy
| | - Tommaso Schirinzi
- Department of Systems Medicine, University of Roma Tor Vergata, Rome, Italy
| | - Mariano Serrao
- Department of Medico-Surgical Sciences and Biotechnologies, University of Rome Sapienza, Latina, Italy.,Movement Analysis LAB, Policlinico Italia, Rome, Italy
| | - Susanna Summa
- MARlab, Neuroscience and Neurorehabilitation Department, Bambino Gesù Children's Hospital - IRCCS, Rome, Italy
| | - Michael Strupp
- Department of Neurology and German Center for Vertigo and Balance Disorders, Hospital of the Ludwig Maximilians-University Munich, Munich, Germany
| | - Olivia Surgent
- Neuroscience Training Program and Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Matthis Synofzik
- Department of Neurodegeneration, Hertie Institute for Clinical Brain Research and Centre of Neurology, Tübingen, Germany
| | - Shuai Tao
- Dalian Key Laboratory of Smart Medical and Health, Dalian University, Dalian, 116622, China
| | - Hiroo Terasi
- Department of Neurology, Tokyo Medical University, Tokyo, Japan
| | - Diego Torres-Russotto
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, USA
| | - Brittany Travers
- Department of Kinesiology and Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Jaimie A Roper
- School of Kinesiology, Auburn University, Auburn, AL, USA
| | - Mario Manto
- Unité Des Ataxies Cérébelleuses, Department of Neurology, CHU de Charleroi, Charleroi, Belgium.,Service Des Neurosciences, University of Mons, UMons, Mons, Belgium
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Dasgupta P, VanSwearingen J, Godfrey A, Redfern M, Montero-Odasso M, Sejdic E. Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review. IEEE Trans Neural Syst Rehabil Eng 2021; 29:249-261. [PMID: 33315570 PMCID: PMC7995554 DOI: 10.1109/tnsre.2020.3044260] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion's translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults.
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Buckley C, McArdle R, Galna B, Thomas A, Rochester L, Del Din S. Evaluation of daily walking activity and gait profiles: a novel application of a time series analysis framework. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:2482-2485. [PMID: 31946401 DOI: 10.1109/embc.2019.8857250] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Wearable technology allows an in-depth analysis of gait behaviour in free-living environments. This investigation aimed to use Alzheimer's disease as an example to apply the time series analysis technique of Statistical Parametric Mapping (SPM) to create daily gait profiles and test if they differed from cognitively intact controls. A framework of macro (habitual walking behaviours) and micro characteristics (spatiotemporal gait variables) characteristics were calculated on an hourly basis. SPM showed that select micro gait characteristics differed from controls at specific hours of the day. Therefore, the application of SPM may provide a more in-depth reflection of activity and gait time-dependent fluctuations than commonly used whole day values. Considering macro and micro gait hour-by- hour may have applications towards disease management, personalized care, monitoring medication and targeted interventions for people with a range of neurodegenerative diseases.
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Guo Y, Wang L, Li Y, Guo L, Meng F. The Detection of Freezing of Gait in Parkinson's Disease Using Asymmetric Basis Function TV-ARMA Time-Frequency Spectral Estimation Method. IEEE Trans Neural Syst Rehabil Eng 2019; 27:2077-2086. [PMID: 31478865 DOI: 10.1109/tnsre.2019.2938301] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Freezing of gait (FOG) is an episodic gait disturbance affecting locomotion in Parkinson's disease. As a biomarker to detect FOG, the Freeze index (FI), which is defined as the ratio of the areas under power spectra in 'freeze' band and in 'locomotion' band, can negatively be affected by poor time and frequency resolution of time-frequency spectrum estimate when short-time Fourier transform (STFT) or Wavelet transform (WT) is used. In this study, a novel high-resolution parametric time-frequency spectral estimation method is proposed to improve the accuracy of FI. A time-varying autoregressive moving average model (TV-ARMA) is first identified where the time-varying parameters are estimated using an asymmetric basis function expansion method. The TV-ARMA model is then transformed into frequency domain to estimate the time-frequency spectrum and calculate the FI. Results evaluated on the Daphnet Freezing of Gait Dataset show that the new method improves the time and frequency resolutions of the time-frequency spectrum and the associate FI has better performance in the detection of FOG than its counterparts based on STFT and WT methods do. Moreover, FOGs can be predicted in advance of its occurrence in most cases using the new method.
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McCarthy I, Suzuki T, Holloway C, Poole T, Frost C, Carton A, Tyler N, Crutch S, Yong K. Detection and localisation of hesitant steps in people with Alzheimer's disease navigating routes of varying complexity. Healthc Technol Lett 2019; 6:42-47. [PMID: 31119037 PMCID: PMC6498402 DOI: 10.1049/htl.2018.5034] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 12/19/2018] [Accepted: 01/03/2019] [Indexed: 12/11/2022] Open
Abstract
People with Alzheimer's disease (AD) have characteristic problems navigating everyday environments. While patients may exhibit abnormal gait parameters, adaptive gait irregularities when navigating environments are little explored or understood. The aim of this study was to assess adaptive locomotor responses of AD subjects in a complex environment requiring spatial navigation. A controlled environment of three corridors was set up: straight (I), U-shaped (U) and dog-leg (S). Participants were asked to walk along corridors as part of a counterbalanced repeated-measures design. Three groups were studied: 11 people with posterior cortical atrophy (PCA), 10 with typical Alzheimer's disease (tAD) and 13 controls. Spatio-temporal gait parameters and position within the corridors were monitored with shoe-mounted inertial measurement units (IMUs). Hesitant steps were identified from statistical analysis of the distribution of step time data. Walking paths were generated from position data calculated by double integration of IMU acceleration. People with PCA and tAD had similar gait characteristics, having shorter steps and longer step times than controls. Hesitant steps tended to be clustered within certain regions of the walking paths. IMUs enabled identification of key gait characteristics in this clinical population (step time, length and step hesitancy) and environmental conditions (route complexity) modifying their expression.
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Affiliation(s)
- Ian McCarthy
- Pedestrian Accessibility and Movement Environment Laboratory, Department of Civil Environmental and Geomatic Engineering, University College London, London N19 5UN, UK
| | - Tatsuto Suzuki
- Pedestrian Accessibility and Movement Environment Laboratory, Department of Civil Environmental and Geomatic Engineering, University College London, London N19 5UN, UK
| | - Catherine Holloway
- UCL Interaction Centre, Department of Computer Science, University College London, London, UK
| | - Teresa Poole
- Department of Medical Statistics, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Chris Frost
- Department of Medical Statistics, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Amelia Carton
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Nick Tyler
- Pedestrian Accessibility and Movement Environment Laboratory, Department of Civil Environmental and Geomatic Engineering, University College London, London N19 5UN, UK
| | - Sebastian Crutch
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Keir Yong
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
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Benson LC, Clermont CA, Bošnjak E, Ferber R. The use of wearable devices for walking and running gait analysis outside of the lab: A systematic review. Gait Posture 2018; 63:124-138. [PMID: 29730488 DOI: 10.1016/j.gaitpost.2018.04.047] [Citation(s) in RCA: 118] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 03/20/2018] [Accepted: 04/28/2018] [Indexed: 02/02/2023]
Abstract
BACKGROUND Quantitative gait analysis is essential for evaluating walking and running patterns for markers of pathology, injury, or other gait characteristics. It is expected that the portability, affordability, and applicability of wearable devices to many different populations will have contributed advancements in understanding the real-world gait patterns of walkers and runners. Therefore, the purpose of this systematic review was to identify how wearable devices are being used for gait analysis in out-of-lab settings. METHODS A systematic search was conducted in the following scientific databases: PubMed, Medline, CINAHL, EMBASE, and SportDiscus. Each of the included articles was assessed using a custom quality assessment. Information was extracted from each included article regarding the participants, protocol, sensor(s), and analysis. RESULTS A total of 61 articles were reviewed: 47 involved gait analysis during walking, 13 involved gait analysis during running, and one involved both walking and running. Most studies performed adequately on measures of reporting, and external and internal validity, but did not provide a sufficient description of power. Small, unobtrusive wearable devices have been used in retrospective studies, producing unique measures of gait quality. Walking, but not running, studies have begun to use wearable devices for gait analysis among large numbers of participants in their natural environment. CONCLUSIONS Despite the advantages provided by the portability and accessibility of wearable devices, more studies monitoring gait over long periods of time, among large numbers of participants, and in natural walking and running environments are needed to analyze real-world gait patterns, and would facilitate prospective, subject-specific, and subgroup investigations. The development of wearables-specific metrics for gait analysis provide insights regarding the quality of gait that cannot be determined using traditional components of in-lab gait analyses. However, guidelines for the usability of wearable devices and the validity of wearables-based measurements of gait quality need to be established.
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Affiliation(s)
- Lauren C Benson
- Faculty of Kinesiology, University of Calgary, 2500 University Dr. NW, Calgary, AB, T2N 1N4, Canada.
| | - Christian A Clermont
- Faculty of Kinesiology, University of Calgary, 2500 University Dr. NW, Calgary, AB, T2N 1N4, Canada.
| | - Eva Bošnjak
- Faculty of Kinesiology, University of Calgary, 2500 University Dr. NW, Calgary, AB, T2N 1N4, Canada.
| | - Reed Ferber
- Faculty of Kinesiology, University of Calgary, 2500 University Dr. NW, Calgary, AB, T2N 1N4, Canada; Faculty of Nursing, University of Calgary, 2500 University Dr. NW, Calgary, AB, T2N 1N4, Canada; Running Injury Clinic, 2500 University Dr. NW, Calgary, AB, T2N 1N4, Canada.
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8
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FitzGerald JJ, Lu Z, Jareonsettasin P, Antoniades CA. Quantifying Motor Impairment in Movement Disorders. Front Neurosci 2018; 12:202. [PMID: 29695949 PMCID: PMC5904266 DOI: 10.3389/fnins.2018.00202] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2017] [Accepted: 03/14/2018] [Indexed: 02/05/2023] Open
Abstract
Until recently the assessment of many movement disorders has relied on clinical rating scales that despite careful design are inherently subjective and non-linear. This makes accurate and truly observer-independent quantification difficult and limits the use of sensitive parametric statistical methods. At last, devices capable of measuring neurological problems quantitatively are becoming readily available. Examples include the use of oculometers to measure eye movements and accelerometers to measure tremor. Many applications are being developed for use on smartphones. The benefits include not just more accurate disease quantification, but also consistency of data for longitudinal studies, accurate stratification of patients for entry into trials, and the possibility of automated data capture for remote follow-up. In this mini review, we will look at movement disorders with a particular focus on Parkinson's disease, describe some of the limitations of existing clinical evaluation tools, and illustrate the ways in which objective metrics have already been successful.
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Affiliation(s)
- James J FitzGerald
- NeuroMetrology Lab, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Zhongjiao Lu
- NeuroMetrology Lab, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Department of Neurology, West China Hospital of Medicine, Sichuan University, Chengdu, China
| | - Prem Jareonsettasin
- NeuroMetrology Lab, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Exeter College, University of Oxford, Oxford, United Kingdom
| | - Chrystalina A Antoniades
- NeuroMetrology Lab, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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Jarchi D, Pope J, Lee TKM, Tamjidi L, Mirzaei A, Sanei S. A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications. IEEE Rev Biomed Eng 2018; 11:177-194. [PMID: 29994786 DOI: 10.1109/rbme.2018.2807182] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modeling, and many other fields. There are established methods using various sensors for gait analysis, of which accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. Commonly used gait phases and parameters are enumerated. The details of selecting the papers for review are provided. We also review several gait analysis software. Then we provide an extensive report of accelerometry-based gait analysis systems and applications, with additional emphasis on trunk accelerometry. We conclude this review with future research directions.
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Rovini E, Maremmani C, Cavallo F. How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review. Front Neurosci 2017; 11:555. [PMID: 29056899 PMCID: PMC5635326 DOI: 10.3389/fnins.2017.00555] [Citation(s) in RCA: 192] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Accepted: 09/21/2017] [Indexed: 01/15/2023] Open
Abstract
Background: Parkinson's disease (PD) is a common and disabling pathology that is characterized by both motor and non-motor symptoms and affects millions of people worldwide. The disease significantly affects quality of life of those affected. Many works in literature discuss the effects of the disease. The most promising trends involve sensor devices, which are low cost, low power, unobtrusive, and accurate in the measurements, for monitoring and managing the pathology. OBJECTIVES This review focuses on wearable devices for PD applications and identifies five main fields: early diagnosis, tremor, body motion analysis, motor fluctuations (ON-OFF phases), and home and long-term monitoring. The concept is to obtain an overview of the pathology at each stage of development, from the beginning of the disease to consider early symptoms, during disease progression with analysis of the most common disorders, and including management of the most complicated situations (i.e., motor fluctuations and long-term remote monitoring). DATA SOURCES The research was conducted within three databases: IEEE Xplore®, Science Direct®, and PubMed Central®, between January 2006 and December 2016. STUDY ELIGIBILITY CRITERIA Since 1,429 articles were found, accurate definition of the exclusion criteria and selection strategy allowed identification of the most relevant papers. RESULTS Finally, 136 papers were fully evaluated and included in this review, allowing a wide overview of wearable devices for the management of Parkinson's disease.
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Affiliation(s)
- Erika Rovini
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
| | - Carlo Maremmani
- U.O. Neurologia, Ospedale delle Apuane (AUSL Toscana Nord Ovest), Massa, Italy
| | - Filippo Cavallo
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
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11
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Nieto-Reyes A, Duque R, Montaña JL, Lage C. Classification of Alzheimer's Patients through Ubiquitous Computing. SENSORS 2017; 17:s17071679. [PMID: 28753975 PMCID: PMC5539862 DOI: 10.3390/s17071679] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2017] [Revised: 07/13/2017] [Accepted: 07/18/2017] [Indexed: 11/17/2022]
Abstract
Functional data analysis and artificial neural networks are the building blocks of the proposed methodology that distinguishes the movement patterns among c’s patients on different stages of the disease and classifies new patients to their appropriate stage of the disease. The movement patterns are obtained by the accelerometer device of android smartphones that the patients carry while moving freely. The proposed methodology is relevant in that it is flexible on the type of data to which it is applied. To exemplify that, it is analyzed a novel real three-dimensional functional dataset where each datum is observed in a different time domain. Not only is it observed on a difference frequency but also the domain of each datum has different length. The obtained classification success rate of 83% indicates the potential of the proposed methodology.
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Affiliation(s)
- Alicia Nieto-Reyes
- Department of Mathematics, Statistics and Computer Science, Universidad de Cantabria, 39005 Santander, Spain.
| | - Rafael Duque
- Department of Mathematics, Statistics and Computer Science, Universidad de Cantabria, 39005 Santander, Spain.
| | - José Luis Montaña
- Department of Mathematics, Statistics and Computer Science, Universidad de Cantabria, 39005 Santander, Spain.
| | - Carmen Lage
- Cognitive Disorders Unit, Department of Neurology, Marqués de Valdecilla University Hospital (HUMV) Valdecilla Biomedical Research Institute (IDIVAL), 39008 Santander, Spain.
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Vienne A, Barrois RP, Buffat S, Ricard D, Vidal PP. Inertial Sensors to Assess Gait Quality in Patients with Neurological Disorders: A Systematic Review of Technical and Analytical Challenges. Front Psychol 2017; 8:817. [PMID: 28572784 PMCID: PMC5435996 DOI: 10.3389/fpsyg.2017.00817] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Accepted: 05/04/2017] [Indexed: 11/13/2022] Open
Abstract
Gait disorders are major causes of falls in patients with neurological diseases. Understanding these disorders allows prevention and better insights into underlying diseases. InertiaLocoGraphy (ILG) -the quantification of gait by using inertial measurement units (IMUs) -shows great potential to address this public health challenge, but protocols vary widely and normative values of gait parameters are still unavailable. This systematic review critically compares ILG protocols, questions features extracted from inertial signals and proposes a semeiological analysis of clinimetric characteristics for use in neurological clinical routine. For this systematic review, PubMed, Cochrane and EMBASE were searched for articles assessing gait quality by using IMUs that were published from January 1, 2014 to August 31, 2016. ILG was used to assess gait in a wide range of neurological disorders - including Parkinson disease, mild cognitive impairment, Alzheimer disease, cerebral palsy, and cerebellar atrophy - as well as in the faller or frail older population and in people presenting rheumatological pathologies. However, results have not yet been driving changes in clinical practice. One reason could be that studies mainly aimed at comparing pathological gait to healthy gait, but there is stronger need for semiological descriptions of gait perturbation, severity or prognostic assessment. Furthermore, protocols used to assess gait using IMUs are too many. Likely, outcomes are highly heterogeneous and difficult to compare across large panels of studies. Therefore, homogenization is needed to foster the use of ILG to assess gait quality in neurological routine practice. The pros and cons of each protocol are emphasized so that a compromise can be reached. As well, analysis of seven complementary clinical criteria (springiness, sturdiness, smoothness, steadiness, stability, symmetry, synchronization) is advocated.
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Affiliation(s)
- Aliénor Vienne
- CNRS UMR 8257, Cognition and Action Group, Cognac-G, Université Paris Descartes, Service de Santé des ArméesParis, France
| | - Rémi P Barrois
- CNRS UMR 8257, Cognition and Action Group, Cognac-G, Université Paris Descartes, Service de Santé des ArméesParis, France
| | - Stéphane Buffat
- CNRS UMR 8257, Cognition and Action Group, Cognac-G, Université Paris Descartes, Service de Santé des ArméesParis, France.,Institut de Recherche Biomédicale des Armées, Service de Santé des ArméesBrétigny-sur-Orge, France.,Ecole du Val-de-Grâce, Service de Santé des ArméesParis, France
| | - Damien Ricard
- CNRS UMR 8257, Cognition and Action Group, Cognac-G, Université Paris Descartes, Service de Santé des ArméesParis, France.,Ecole du Val-de-Grâce, Service de Santé des ArméesParis, France.,Service de Neurologie de l'Hôpital d'Instruction des Armées de Percy, Service de Santé des ArméesClamart, France
| | - Pierre-Paul Vidal
- CNRS UMR 8257, Cognition and Action Group, Cognac-G, Université Paris Descartes, Service de Santé des ArméesParis, France
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Higuma M, Sanjo N, Mitoma H, Yoneyama M, Yokota T. Whole-Day Gait Monitoring in Patients with Alzheimer's Disease: A Relationship between Attention and Gait Cycle. J Alzheimers Dis Rep 2017; 1:1-8. [PMID: 30480224 PMCID: PMC6159725 DOI: 10.3233/adr-170001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Background: Gait impairment in patients with Alzheimer's disease (AD) and its relationship with cognitive function has been described, but reports of gait analysis in AD in daily living are limited. Objective: To investigate whether gait pattern of patients with AD in daily living is associated with cognitive function. Methods: Gait was recorded in 24 patients with AD and 9 healthy controls (HC) for 24 hours by using a portable gait rhythmogram. Mean gait cycle and gait acceleration were compared between the AD and HC groups. For the AD group, these gait metrics were assessed for correlations with cognitive function, as determined by the Mini Mental State Examination and Wechsler Memory Scale-Revised (WMS-R). Results: Although both gait parameters were not different between the patients with AD and HC, gait cycle in patients with AD was positively correlated with attention/concentration scores on the WMS-R (r = 0.578), and not with memory function. Patients with AD with attention scores as high as HC displayed a longer gait cycle than both HC (p = 0.048) and patients with AD with lower attention scores (p = 0.011). The patients with AD with lower attention scores showed a similar gait cycle with HC (p = 0.994). Conclusion: Patients with AD with impaired attentional function walk with faster gait cycle comparable to HC in daily living walking, which was unexpected based on previous gait analysis in clinical settings. This result probably reflects diminished consciousness to either the environment or instability of gait in the patients with AD with impaired attention.
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Affiliation(s)
- Maya Higuma
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Nobuo Sanjo
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hiroshi Mitoma
- Department of Medical Education, Tokyo Medical University, Tokyo, Japan
| | | | - Takanori Yokota
- Department of Neurology and Neurological Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
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Hagner-Derengowska M, Kałużny K, Hagner W, Kałużna A, Kochański B, Borkowska A, Budzyński J. The Effect of Two Different Cognitive Tests on Gait Parameters during Dual Tasks in Healthy Postmenopausal Women. BIOMED RESEARCH INTERNATIONAL 2016; 2016:1205469. [PMID: 27022602 PMCID: PMC4789027 DOI: 10.1155/2016/1205469] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2015] [Revised: 01/19/2016] [Accepted: 02/02/2016] [Indexed: 11/18/2022]
Abstract
INTRODUCTION The paper aims to evaluate the influence of two different demanding cognitive tasks on gait parameters using BTS SMART system analysis. PATIENTS AND METHODS The study comprised 53 postmenopausal women aged 64.5 ± 6.7 years (range: 47-79). For every subject, gait analysis using a BTS SMART system was performed in a dual-task study design under three conditions: (I) while walking only (single task), (II) walking while performing a simultaneous simple cognitive task (SCT) (dual task), and (III) walking while performing a simultaneous complex cognitive task (CCT) (dual task). Time-space parameters of gait pertaining to the length of a single support phase, double support phase, gait speed, step length, step width, and leg swing speed were analyzed. RESULTS Performance of cognitive tests during gait resulted in a statistically significant prolongation of the left (by 7%) and right (by 7%) foot gait cycle, shortening of the length of steps made with the right extremity (by 4%), reduction of speed of swings made with the left (by 11%) and right (by 8%) extremity, and reduction in gait speed (by 6%). CONCLUSIONS Performance of cognitive tests during gait changes its individual pattern in relation to the level of the difficulty of the task.
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Affiliation(s)
- Magdalena Hagner-Derengowska
- Chair of Clinical Neuropsychology, Faculty of Health Sciences, Nicolaus Copernicus University in Toruń, M. Skłodowskiej-Curie 9 Street, 85-094 Bydgoszcz, Poland
| | - Krystian Kałużny
- Chair and Clinic of Rehabilitation, Faculty of Health Sciences, Nicolaus Copernicus University in Toruń, M. Skłodowskiej-Curie 9 Street, 85-094 Bydgoszcz, Poland
| | - Wojciech Hagner
- Chair and Clinic of Rehabilitation, Faculty of Health Sciences, Nicolaus Copernicus University in Toruń, M. Skłodowskiej-Curie 9 Street, 85-094 Bydgoszcz, Poland
| | - Anna Kałużna
- Chair and Clinic of Rehabilitation, Faculty of Health Sciences, Nicolaus Copernicus University in Toruń, M. Skłodowskiej-Curie 9 Street, 85-094 Bydgoszcz, Poland
| | - Bartosz Kochański
- Chair and Clinic of Rehabilitation, Faculty of Health Sciences, Nicolaus Copernicus University in Toruń, M. Skłodowskiej-Curie 9 Street, 85-094 Bydgoszcz, Poland
| | - Alina Borkowska
- Chair of Clinical Neuropsychology, Faculty of Health Sciences, Nicolaus Copernicus University in Toruń, M. Skłodowskiej-Curie 9 Street, 85-094 Bydgoszcz, Poland
| | - Jacek Budzyński
- Chair of Vascular and Internal Diseases, Faculty of Health Sciences, Nicolaus Copernicus University in Toruń, Ujejskiego 75 Street, 85-168 Bydgoszcz, Poland
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