Data analysis and study of human motions in activity of daily living for stroke rehabilitation

• Main Author: Amira Mohamed Tamiri
• Other Authors: Chen I-Ming
• Format: Final Year Project
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Mechanical engineering::Assistive technology
• Online Access: http://hdl.handle.net/10356/61387
• Institution: Nanyang Technological University

With the world’s population becoming an aging population, the incidence of stroke is increasing. The need to automate the rehabilitation process of stroke grows. With motion analysis of the movements of stroke patients, it is also possible for a development of stroke assessment scales using instrumentation like sensors. This report analyses the upper extremity motion of stroke patients executing five Activities of Daily Living tasks. Using programs like Python and Matlab, measurements of the motions were analysed to determine the Range of Motion (ADL), Peak Velocity and Completion Time of all patients along with healthy subjects, for comparison. With these, an instrumentation assessment scale would be able to determine the degree of disability of a stroke patient. However, these findings can be further developed with determining linearity of motion and jerk score movement so that an accurate instrumentation scale can be developed.