1
|
Lebleu J, Daniels K, Pauwels A, Dekimpe L, Mapinduzi J, Poilvache H, Bonnechère B. Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring after Hip and Knee Replacement. SENSORS (BASEL, SWITZERLAND) 2024; 24:1163. [PMID: 38400321 PMCID: PMC10892564 DOI: 10.3390/s24041163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 01/20/2024] [Accepted: 02/08/2024] [Indexed: 02/25/2024]
Abstract
Osteoarthritis (OA) poses a growing challenge for the aging population, especially in the hip and knee joints, contributing significantly to disability and societal costs. Exploring the integration of wearable technology, this study addresses the limitations of traditional rehabilitation assessments in capturing real-world experiences and dynamic variations. Specifically, it focuses on continuously monitoring physical activity in hip and knee OA patients using automated unsupervised evaluations within the rehabilitation process. We analyzed data from 1144 patients who used a mobile health application after surgery; the activity data were collected using the Garmin Vivofit 4. Several parameters, such as the total number of steps per day, the peak 6-minute consecutive cadence (P6MC) and peak 1-minute cadence (P1M), were computed and analyzed on a daily basis. The results indicated that cadence-based measurements can effectively, and earlier, differ among patients with hip and knee conditions, as well as in the recovery process. Comparisons based on recovery status and type of surgery reveal distinctive trajectories, emphasizing the effectiveness of P6MC and P1M in detecting variations earlier than total steps per day. Furthermore, cadence-based measurements showed a lower inter-day variability (40%) compared to the total number of steps per day (80%). Automated assessments, including P1M and P6MC, offer nuanced insights into the patients' dynamic activity profiles.
Collapse
Affiliation(s)
- Julien Lebleu
- moveUp, 1000 Brussels, Belgium; (J.L.); (A.P.); (L.D.)
| | - Kim Daniels
- Department of PXL—Healthcare, PXL University of Applied Sciences and Arts, 3500 Hasselt, Belgium;
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, 3590 Diepenbeek, Belgium;
| | | | - Lucie Dekimpe
- moveUp, 1000 Brussels, Belgium; (J.L.); (A.P.); (L.D.)
| | - Jean Mapinduzi
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, 3590 Diepenbeek, Belgium;
- Filière de Kinésithérapie et Réadaptation, Département des Sciences Clinique, Institut National de la Santé Publique, 6807 Bujumbura, Burundi
| | - Hervé Poilvache
- Orthopedic Surgery Department, CHIREC, 1420 Braine-l’Alleud, Belgium
| | - Bruno Bonnechère
- Department of PXL—Healthcare, PXL University of Applied Sciences and Arts, 3500 Hasselt, Belgium;
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, 3590 Diepenbeek, Belgium;
- Technology-Supported and Data-Driven Rehabilitation, Data Sciences Institute, Hasselt University, 3590 Diepenbeek, Belgium
| |
Collapse
|
2
|
Boma PM, Panda J, Ngoy Mande JP, Bonnechère B. Rehabilitation: a key service, yet highly underused, in the management of young patients with sickle cell disease after stroke in DR of Congo. Front Neurol 2023; 14:1104101. [PMID: 37292134 PMCID: PMC10244556 DOI: 10.3389/fneur.2023.1104101] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 05/02/2023] [Indexed: 06/10/2023] Open
Affiliation(s)
- Paul Muteb Boma
- Reference Centre for Sickle Cell Disease of Lubumbashi, Institut de Recherche en Science de la Santé, Lubumbashi, Democratic Republic of Congo
| | - Jules Panda
- Reference Centre for Sickle Cell Disease of Lubumbashi, Institut de Recherche en Science de la Santé, Lubumbashi, Democratic Republic of Congo
- Department of Surgery, Faculty of Medicine, University of Lubumbashi, Lubumbashi, Democratic Republic of Congo
| | - Jean Paul Ngoy Mande
- Department of Neurology and Psychiatry, Faculty of Medicine, University of Lubumbashi, Lubumbashi, Democratic Republic of Congo
| | - Bruno Bonnechère
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Hasselt, Belgium
- Technology-Supported and Data-Driven Rehabilitation, Data Science Institute, University of Hasselt, Hasselt, Belgium
| |
Collapse
|
3
|
Bonnechère B, Kossi O, Mapinduzi J, Panda J, Rintala A, Guidetti S, Spooren A, Feys P. Mobile health solutions: An opportunity for rehabilitation in low- and middle income countries? Front Public Health 2023; 10:1072322. [PMID: 36761328 PMCID: PMC9902940 DOI: 10.3389/fpubh.2022.1072322] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 12/27/2022] [Indexed: 01/25/2023] Open
Abstract
Mobile health (mHealth) development has advanced rapidly, indicating promise as an effective patient intervention. mHealth has many potential benefits that could help the treatment of patients, and the development of rehabilitation in low- and middle-income countries (LMICs). mHealth is a low-cost option that does not need rapid access to healthcare clinics or employees. It increases the feasibility and rationality of clinical treatment expectations in comparison to the conventional clinical model of management by promoting patient adherence to the treatment plan. mHealth can also serve as a basis for formulating treatment plans and partially compensate for the shortcomings of the traditional model. In addition, mHealth can help achieve universal rehabilitation service coverage by overcoming geographical barriers, thereby increasing the number of ways patients can benefit from the rehabilitation service, and by providing rehabilitation to individuals in remote areas and communities with insufficient healthcare services. However, despite these positive potential aspects, there is currently only a very limited number of studies performed in LMICs using mHealth. In this study, we first reviewed the current evidence supporting the use of mHealth in rehabilitation to identify the countries where studies have been carried out. Then, we identify the current limitations of the implementation of such mHealth solutions and propose a 10-point action plan, focusing on the macro (e.g., policymakers), meso (e.g., technology and healthcare institutions), and micro (e.g., patients and relatives) levels to ease the use, validation, and implementation in LMICs and thus participate in the development and recognition of public health and rehabilitation in these countries.
Collapse
Affiliation(s)
- Bruno Bonnechère
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University (UHasselt), Hasselt, Belgium,Technology-Supported and Data-Driven Rehabilitation, Data Science Institute, UHasselt, Hasselt, Belgium,*Correspondence: Bruno Bonnechère ✉
| | - Oyene Kossi
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University (UHasselt), Hasselt, Belgium,ENATSE, National School of Public Health and Epidemiology, University of Parakou, Parakou, Benin
| | - Jean Mapinduzi
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University (UHasselt), Hasselt, Belgium,INSP, Institut National de la Santé Publique, Bujumbura, Burundi,CKAO-AMAHORO, Cabinet de Kinésithérapie et d'Appareillage Orthopédique, Bujumbura, Burundi
| | - Jules Panda
- University of Lubumbashi, Lubumbashi, Democratic Republic of Congo,Institut de Recherche en Science de la Santé, Lubumbashi, Democratic Republic of Congo
| | - Aki Rintala
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University (UHasselt), Hasselt, Belgium,Faculty of Social Services and Health Care, LAB University of Applied Sciences, Lahti, Finland
| | - Susanne Guidetti
- Department of Neurobiology, Care Sciences and Society, Division for Occupational Therapy, Karolinska Institutet, Stockholm, Sweden,Women's Health and Allied Health Professionals Theme, Medical Unit Occupational Therapy and Physiotherapy, Karolinska University Hospital, Stockholm, Sweden
| | - Annemie Spooren
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University (UHasselt), Hasselt, Belgium
| | - Peter Feys
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University (UHasselt), Hasselt, Belgium
| |
Collapse
|
4
|
Bonnechère B, Timmermans A, Michiels S. Current Technology Developments Can Improve the Quality of Research and Level of Evidence for Rehabilitation Interventions: A Narrative Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23020875. [PMID: 36679672 PMCID: PMC9866361 DOI: 10.3390/s23020875] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/19/2022] [Accepted: 01/05/2023] [Indexed: 06/01/2023]
Abstract
The current important limitations to the implementation of Evidence-Based Practice (EBP) in the rehabilitation field are related to the validation process of interventions. Indeed, most of the strict guidelines that have been developed for the validation of new drugs (i.e., double or triple blinded, strict control of the doses and intensity) cannot-or can only partially-be applied in rehabilitation. Well-powered, high-quality randomized controlled trials are more difficult to organize in rehabilitation (e.g., longer duration of the intervention in rehabilitation, more difficult to standardize the intervention compared to drug validation studies, limited funding since not sponsored by big pharma companies), which reduces the possibility of conducting systematic reviews and meta-analyses, as currently high levels of evidence are sparse. The current limitations of EBP in rehabilitation are presented in this narrative review, and innovative solutions are suggested, such as technology-supported rehabilitation systems, continuous assessment, pragmatic trials, rehabilitation treatment specification systems, and advanced statistical methods, to tackle the current limitations. The development and implementation of new technologies can increase the quality of research and the level of evidence supporting rehabilitation, provided some adaptations are made to our research methodology.
Collapse
Affiliation(s)
- Bruno Bonnechère
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, 3590 Diepenbeek, Belgium
- Technology-Supported and Data-Driven Rehabilitation, Data Science Institute, Hasselt University, 3590 Diepenbeek, Belgium
| | - Annick Timmermans
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, 3590 Diepenbeek, Belgium
| | - Sarah Michiels
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, 3590 Diepenbeek, Belgium
- Department of Otorhinolaryngology, Antwerp University Hospital, 2650 Edegem, Belgium
| |
Collapse
|
5
|
Bonnechère B. Integrating Rehabilomics into the Multi-Omics Approach in the Management of Multiple Sclerosis: The Way for Precision Medicine? Genes (Basel) 2022; 14:63. [PMID: 36672802 PMCID: PMC9858788 DOI: 10.3390/genes14010063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/05/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022] Open
Abstract
Over recent years, significant improvements have been made in the understanding of (epi)genetics and neuropathophysiological mechanisms driving the different forms of multiple sclerosis (MS). For example, the role and importance of the bidirectional communications between the brain and the gut-also referred to as the gut-brain axis-in the pathogenesis of MS is receiving increasing interest in recent years and is probably one of the most promising areas of research for the management of people with MS. However, despite these important advances, it must be noted that these data are not-yet-used in rehabilitation. Neurorehabilitation is a cornerstone of MS patient management, and there are many techniques available to clinicians and patients, including technology-supported rehabilitation. In this paper, we will discuss how new findings on the gut microbiome could help us to better understand how rehabilitation can improve motor and cognitive functions. We will also see how the data gathered during the rehabilitation can help to get a better diagnosis of the patients. Finally, we will discuss how these new techniques can better guide rehabilitation to lead to precision rehabilitation and ultimately increase the quality of patient care.
Collapse
Affiliation(s)
- Bruno Bonnechère
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, 3590 Diepenbeek, Belgium;
- Technology-Supported and Data-Driven Rehabilitation, Data Science Institute, Hasselt University, 3590 Diepenbeek, Belgium
| |
Collapse
|
6
|
Clark CCT, Bisi MC, Duncan MJ, Stagni R. Technology-based methods for the assessment of fine and gross motor skill in children: A systematic overview of available solutions and future steps for effective in-field use. J Sports Sci 2021; 39:1236-1276. [PMID: 33588689 DOI: 10.1080/02640414.2020.1864984] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
The present review aims at providing researchers and practitioners with a holistic overview of technology-based methods for the assessment of fine and gross motor skill in children. We conducted a search of electronic databases using Web of Science, PubMed and Google Scholar, including studies published up to March 2020, that assessed fine and/or gross motor skills, and utilized technological assessment of varying study design. A total of 739 papers were initially retrieved, and after title/abstract screening, removal of duplicates, and full-text screening, 47 were included. Results suggest that motor skills can be quantitatively estimated using objective methods based on a wearable- and/or laboratory-based technology, for typically developing (TD) and non-TD children. Fine motor skill assessment solutions were; force transducers, instrumented tablets and pens, surface electromyography, and optoelectronic systems. Gross motor skill assessment solutions were; inertial measurements units, optoelectronic systems, baropodometric mats, and force platforms. This review provides a guide in identifying and evaluating the plethora of available technological solutions to motor skill assessment. Although promising, there is still a need for large-scale studies to validate these approaches in terms of accuracy, repeatability, and usability, where interdisciplinary collaborations between researchers and practitioners and transparent reporting practices should be advocated.
Collapse
Affiliation(s)
- Cain C T Clark
- Faculty of Health and Life Sciences, Coventry University, Coventry, UK.,Warwickshire InStitute for Diabetes, Endocrinology & Metabolism (WISDEM), University Hospitals Coventry & Warwickshire (UHCW) NHS Trust, Coventry, UK
| | - Maria Cristina Bisi
- Department of Electric, Electronic and Information Engineering "Guglielmo Marconi" - DEI, University of Bologna, Bologna, Italy
| | - Michael J Duncan
- Faculty of Health and Life Sciences, Coventry University, Coventry, UK
| | - Rita Stagni
- Department of Electric, Electronic and Information Engineering "Guglielmo Marconi" - DEI, University of Bologna, Bologna, Italy
| |
Collapse
|
7
|
Aguilar-Lazcano CA, Rechy-Ramirez EJ, Hu H, Rios-Figueroa HV, Marin-Hernandez A. Interaction Modalities Used on Serious Games for Upper Limb Rehabilitation: A Systematic Review. Games Health J 2019; 8:313-325. [PMID: 31287734 DOI: 10.1089/g4h.2018.0129] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
This systematic review aims to analyze the state-of-the-art regarding interaction modalities used on serious games for upper limb rehabilitation. A systematic search was performed in IEEE Xplore and Web of Science databases. PRISMA and QualSyst protocols were used to filter and assess the articles. Articles must meet the following inclusion criteria: they must be written in English; be at least four pages in length; use or develop serious games; focus on upper limb rehabilitation; and be published between 2007 and 2017. Of 121 articles initially retrieved, 33 articles met the inclusion criteria. Three interaction modalities were found: vision systems (42.4%), complementary vision systems (30.3%), and no-vision systems (27.2%). Vision systems and no-vision systems obtained a similar mean QualSyst (86%) followed by complementary vision systems (85.7%). Almost half of the studies used vision systems as the interaction modality (42.4%) and used the Kinect sensor to collect the body movements (48.48%). The shoulder was the most treated body part in the studies (19%). A key limitation of vision systems and complementary vision systems is that their device performances might be affected by lighting conditions. A main limitation of the no-vision systems is that the range-of-motion in angles of the body movement might not be measured accurately. Due to a limited number of studies, fruitful areas for further research could be the following: serious games focused on finger rehabilitation and trauma injuries, game difficulty adaptation based on user's muscle strength and posture, and multisensor data fusion on interaction modalities.
Collapse
Affiliation(s)
| | | | - Huosheng Hu
- School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom
| | | | | |
Collapse
|
8
|
Sielużycki C, Maśliński J, Kaczmarczyk P, Kubacki R, Cieśliński WB, Witkowski K. Can Kinect aid motor learning in sportsmen? A study for three standing techniques in judo. PLoS One 2019; 14:e0210260. [PMID: 30726211 PMCID: PMC6364886 DOI: 10.1371/journal.pone.0210260] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 12/19/2018] [Indexed: 11/18/2022] Open
Abstract
Our objective was to examine how exercises with the second generation of the Microsoft Kinect sensor may aid in the process of motor learning in young judo practitioners. We addressed improvements in spatio-temporal accuracy during execution of three standing techniques in judo, in a simple paradigm designed to study short-term practice effects. Two groups of judokas, 12 athletes each—one aided with Kinect and our dedicated software vs a group of controls—were asked to mimic previously recorded master-level performances of the three techniques, established as benchmarks by a two times world champion in judo. In five training sessions, athletes of the aided group used a virtual-reality setup in which they trained with a virtual representation of the master displayed on a large screen with a simultaneous real-time visualisation of their own movements in the form of an avatar based on body joint localisation, as determined by Kinect, which also measured their performance. The control group used Kinect in the 1st and 5th session, which was necessary for the measurements that constituted the basis for subsequent statistical comparisons, whereas the 2nd, 3rd, and 4th session in this group was guided by a coach, without the use of the Kinect setup. In addition, athletes of the two groups had unrestricted access to a video recording of the master performing the three throws. We found statistically significant improvements (p < 0.05) in the accuracy of executing the three techniques between the 1st and the 5th training session for the aided group but not for the control group. We conclude that incorporating Kinect based exercises into a judo training programme may be a useful means to supporting motor learning, therefore enhancing training efficiency, and thus improving performance.
Collapse
Affiliation(s)
- Cezary Sielużycki
- Department of Biomedical Engineering, Faculty of Fundamental Problems of Technology, Wrocław University of Science and Technology, Wrocław, Poland.,Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland
| | - Jarosław Maśliński
- Faculty of Sport Sciences, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Patryk Kaczmarczyk
- Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland
| | - Rafał Kubacki
- Faculty of Sport Sciences, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Wojciech B Cieśliński
- Faculty of Sport Sciences, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Kazimierz Witkowski
- Faculty of Sport Sciences, University School of Physical Education in Wrocław, Wrocław, Poland
| |
Collapse
|
9
|
Bonnechère B, Jansen B, Haack I, Omelina L, Feipel V, Van Sint Jan S, Pandolfo M. Automated functional upper limb evaluation of patients with Friedreich ataxia using serious games rehabilitation exercises. J Neuroeng Rehabil 2018; 15:87. [PMID: 30286776 PMCID: PMC6172838 DOI: 10.1186/s12984-018-0430-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 09/19/2018] [Indexed: 11/10/2022] Open
Abstract
Background Friedreich ataxia (FRDA) is a disease with neurological and systemic involvement. Clinical assessment tools commonly used for FRDA become less effective in evaluating decay in patients with advanced FRDA, particularly when they are in a wheelchair. Further motor worsening mainly impairs upper limb function. In this study, we tested if serious games (SG) developed for rehabilitation can be used as an assessment tool for upper limb function even in patients with advanced FRDA. Methods A specific SG has been developed for physical rehabilitation of patients suffering from neurologic diseases. The use of this SG, coupled with Kinect sensor, has been validated to perform functional evaluation of the upper limbs with healthy subjects across lifespan. Twenty-seven FRDA patients were included in the study. Patients were invited to perform upper limb rehabilitation exercises embedded in SG. Motions were recorded by the Kinect and clinically relevant parameters were extracted from the collected motions. We tested if the existence of correlations between the scores from the serious games and the severity of the disease using clinical assessment tools commonly used for FRDA. Results of patients were compared with a group a healthy subjects of similar age. Results Very highly significant differences were found for time required to perform the exercise (increase of 76%, t(68) = 7.22, P < 0.001) and for accuracy (decrease of 6%, t(68) = − 3.69, P < 0.001) between patients and healthy subjects. Concerning the patients significant correlations were found between age and time (R = 0.65, p = 0.015), accuracy (R = − 0.75, p = 0.004) and the total displacement of upper limbs. (R = 0.55, p = 0.031). Statistically significant correlations were found between the age of diagnosis and speed related parameters. Conclusions The results of this study indicate that SG reliably captures motor impairment of FRDA patients due to cerebellar and pyramidal involvement. Results also show that functional evaluation of FRDA patients can be performed during rehabilitation therapy embedded in games with the patient seated in a wheelchair. Trial registration The study was approved as a component of the EFACTS study (Clinicaltrials.gov identifier NCT02069509, registered May 2010) by the local institutional Ethics Committee (ref. P2010/132).
Collapse
Affiliation(s)
- Bruno Bonnechère
- Laboratory of Anatomy, Biomechanics and Organogenesis (LABO) [CP 619], Université Libre de Bruxelles, Lennik Street 808, 1070, Brussels, Belgium. .,Department of Electronics and Informatics - ETRO, Vrije Universiteit Brussel, Brussels, Belgium. .,imec, Leuven, Belgium.
| | - Bart Jansen
- Department of Electronics and Informatics - ETRO, Vrije Universiteit Brussel, Brussels, Belgium.,imec, Leuven, Belgium
| | - Inès Haack
- Laboratory of Anatomy, Biomechanics and Organogenesis (LABO) [CP 619], Université Libre de Bruxelles, Lennik Street 808, 1070, Brussels, Belgium
| | - Lubos Omelina
- Department of Electronics and Informatics - ETRO, Vrije Universiteit Brussel, Brussels, Belgium.,imec, Leuven, Belgium
| | - Véronique Feipel
- Laboratory of Functional Anatomy (LAF), Université Libre de Bruxelles, Brussels, Belgium
| | - Serge Van Sint Jan
- Laboratory of Anatomy, Biomechanics and Organogenesis (LABO) [CP 619], Université Libre de Bruxelles, Lennik Street 808, 1070, Brussels, Belgium
| | | |
Collapse
|
10
|
Bonnechère B, Sholukha V, Omelina L, Van Sint Jan S, Jansen B. 3D Analysis of Upper Limbs Motion during Rehabilitation Exercises Using the Kinect TM Sensor: Development, Laboratory Validation and Clinical Application. SENSORS 2018; 18:s18072216. [PMID: 29996533 PMCID: PMC6069223 DOI: 10.3390/s18072216] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 06/29/2018] [Accepted: 07/06/2018] [Indexed: 01/05/2023]
Abstract
Optoelectronic devices are the gold standard for 3D evaluation in clinics, but due to the complexity of this kind of hardware and the lack of access for patients, affordable, transportable, and easy-to-use systems must be developed to be largely used in daily clinics. The KinectTM sensor has various advantages compared to optoelectronic devices, such as its price and transportability. However, it also has some limitations: (in)accuracy of the skeleton detection and tracking as well as the limited amount of available points, which makes 3D evaluation impossible. To overcome these limitations, a novel method has been developed to perform 3D evaluation of the upper limbs. This system is coupled to rehabilitation exercises, allowing functional evaluation while performing physical rehabilitation. To validate this new approach, a two-step method was used. The first step was a laboratory validation where the results obtained with the KinectTM were compared with the results obtained with an optoelectronic device; 40 healthy young adults participated in this first part. The second step was to determine the clinical relevance of this kind of measurement. Results of the healthy subjects were compared with a group of 22 elderly adults and a group of 10 chronic stroke patients to determine if different patterns could be observed. The new methodology and the different steps of the validations are presented in this paper.
Collapse
Affiliation(s)
- Bruno Bonnechère
- Laboratory of Anatomy, Biomechanics and Organogenesis (LABO), Université Libre de Bruxelles, 1050 Brussels, Belgium.
- Department of Electronics and Informatics-ETRO, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
- International Medical Equipment Collaborative (IMEC), Kapeldreef 75, B-3001 Leuven, Belgium.
| | - Victor Sholukha
- Laboratory of Anatomy, Biomechanics and Organogenesis (LABO), Université Libre de Bruxelles, 1050 Brussels, Belgium.
- Department of Applied Mathematics, Peter the Great St. Petersburg Polytechnic University (SPbPU), 195251 Sankt-Peterburg, Russia.
| | - Lubos Omelina
- Department of Electronics and Informatics-ETRO, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
- International Medical Equipment Collaborative (IMEC), Kapeldreef 75, B-3001 Leuven, Belgium.
- Institute of Computer Science and Mathematics, Slovak University of Technology, 81237 Bratislava, Slovakia.
| | - Serge Van Sint Jan
- Laboratory of Anatomy, Biomechanics and Organogenesis (LABO), Université Libre de Bruxelles, 1050 Brussels, Belgium.
| | - Bart Jansen
- Department of Electronics and Informatics-ETRO, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
- International Medical Equipment Collaborative (IMEC), Kapeldreef 75, B-3001 Leuven, Belgium.
| |
Collapse
|