Objective real-time motion analysis using wearable devices for post stroke rehabilitation

With the growing population of the elderly, there is an increasing need for reliable, inexpensive, and quantifiable clinical measures. This thesis proposes mStroke, a practical, accurate, and mobile health system that remotely measures a stroke patient's proficiency in standard post-stroke therapy activities. The proposed system is delivered as an application (App) running on a hardware system consisting of two bluetooth low energy (BLE) modular sensor devices and an iPad. The system uses accelerometers, gyroscopes, and magnetometers to measure movement during three single-tasked clinical activities: the functional reach test, the NIHSS motor arm test, and the NIHSS motor leg test. The proposed system has been extensively tested using emulated and real data from physical therapy students. Key Words: Motion Analysis, Stroke, Functional Reach, NIHSS.

Grantor dc:publisher

University of Tennessee at Chattanooga

Author dc:creator

• Allen, Brandon J.

Contributors dc:contributor

• Sartipi, Mina
• Yang, Li; Liang, Yu; Ward, Mike
• College of Engineering and Computer Science

• Motor ability -- Testing
• Cerebrovascular disease -- Patients -- Rehabilitation
• Human-computer interaction

Licence

• https://rightsstatements.org/page/InC/1.0/?language=en

Language dc:language

English, eng

Repository record dc:identifier

https://scholar.utc.edu/theses/437

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-1578