Feasibility Study of a Wearable System Based on a Wireless Body Area Network for Gait Assessment in Parkinson's Disease Patients
Open accessAbstract
Parkinson's disease (PD) alters the motor performance of affected individuals. The dopaminergic denervation of the striatum, due to substantia nigra neuronal loss, compromises the speed, the automatism and smoothness of movements of PD patients. The development of a reliable tool for long-term monitoring of PD symptoms would allow the accurate assessment of the clinical status during the different PD stages and the evaluation of motor complications. Furthermore, it would be very useful both for routine clinical care as well as for testing novel therapies. Within this context we have validated the feasibility of using a Body Network Area (BAN) of wireless accelerometers to perform continuous at home gait monitoring of PD patients. The analysis addresses the assessment of the system performance working in real environments.
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The PERFORM system is a wearable platform for Parkinson's disease remote monitoring and management, based on a Body Area Network (BAN) of sensors.
“This system, called PERFORM, is based on a Body Area Network (BAN) of sensors which has already been validated both from the technical and clinical point for view.”
From Wearability Assessment of a Wearable System for Parkinson’s Disease Remote Monitoring Based on a Body Area Network of Sensors (2014) · cites this paper as [9]
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- Authors
- Cancela, J., Pastorino, M., Arredondo, M., Nikita, K., Villagra, F., & Pastor, M.
- Affiliations
- Universidad Complutense de Madrid (ES)
- Universidad Politécnica de Madrid (ES)
- Life Supporting Technologies Group, Universidad Politecnica de Madrid (UPM), Ciudad Universitaria, Madrid 28003, Spain
- National Technical University of Athens (GR)
- Centro de Investigación Médica Aplicada (ES)
- Division of Neurosciences, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona 31008, Spain
- Corresponding author
- Cancela, Jorge
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2014-03-07
- Volume
- 14
- Issue
- 3
- Pages
- 4618-4633
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC4003960
- OpenAlex
- W2149549442
- Cited by
- 63
- References
- 56
- Citations by year
- 2026: 3 · 2025: 1 · 2023: 5 · 2022: 2 · 2021: 12 · 2020: 6 · 2019: 2 · 2018: 6 · 2017: 9 · 2016: 8 · 2015: 4 · 2014: 5
- FWCI
- 22.43
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- European Commission (215952)
- Universidad de Navarra
- University of Ioannina
- Topics
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- Parkinson's disease, gait analysis, wearable sensors, wireless body area networks, accelerometer, home monitoring, motor symptoms, feasibility study
- MeSH terms
- Aged, Computer Communication Networks, Data Collection, Feasibility Studies, Female, Gait, Humans, Male, Middle Aged, Movement, Parkinson Disease, Signal Processing, Computer-Assisted, Telemetry, Wireless Technology, Accelerometry
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