Handling Gait Impairments of Persons with Parkinson’s Disease by Means of Real-Time Biofeedback in a Daily Life Environment

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• 关键词：Parkinson’s disease ; Wearable sensors ; Android APP ; Tele ; rehabilitation ; Biofeedback ; Gait
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9677
• 期：1
• 页码：250-261
• 全文大小：846 KB
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• 作者单位：Alberto Ferrari (19)
  Pieter Ginis (20)
  Alice Nieuwboer (20)
  Reynold Greenlaw (21)
  Andrew Muddiman (21)
  Lorenzo Chiari (19)
  
  19. Department of Electrical, Electronic and Information Engineering, “Guglielmo Marconi”, University of Bologna, Bologna, Italy
  20. Neuromotor Rehabilitation Research Group, Department of Rehabiliation Sciences, KU Leuven, Leuven, Belgium
  21. Oxford Computer Consultants Limited, OCC, Oxford, UK
  
• 丛书名：Inclusive Smart Cities and Digital Health
• ISBN：978-3-319-39601-9
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9677

文摘

A smartphone app with telemedicine capability integrating data from foot-mounted inertial measurement units (CuPiD-system) was developed to realize a portable gait analysis system and, on top of it, to provide people with Parkinson’s disease (PD) remote supervision and real-time feedback on gait performance. Eleven persons with PD were recommended to perform gait training for 30 min, three times per week for six weeks. The app offered praising/corrective verbal feedback, encouraging participants to keep the spatio-temporal gait parameters within a clinically determined ‘therapeutic window’. On average, persons performed 20 training sessions of 1.8 km in 24 min and received 28 corrective and 68 praising messages. The mean walking rhythm was 58 strides/min with a stride length of 1.28 m. System’s usability was determined as positive by the users. In conclusion, CuPiD resulted to be effective in promoting gait training in semi-supervised conditions, stimulating corrective actions and promoting self-efficacy to achieve optimal performance.