{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1578"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1578","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Objective real-time motion analysis using wearable devices for post stroke rehabilitation","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Allen, Brandon J."],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Sartipi, Mina","Yang, Li; Liang, Yu; Ward, Mike","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T05:46:28Z","subjects":["Motor ability -- Testing","Cerebrovascular disease -- Patients -- Rehabilitation","Human-computer interaction"],"languages":["English","eng"],"rights":[],"rights_urls":["https://rightsstatements.org/page/InC/1.0/?language=en"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/437","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sartipi, Mina","Yang, Li; Liang, Yu; Ward, Mike","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Allen, Brandon J."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-12-01T08:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Motor ability -- Testing","Cerebrovascular disease -- Patients -- Rehabilitation","Human-computer interaction"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://rightsstatements.org/page/InC/1.0/?language=en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/437"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Objective real-time motion analysis using wearable devices for post stroke rehabilitation"]}]}],"canonical_facts":{"dc:contributor":["Sartipi, Mina","Yang, Li; Liang, Yu; Ward, Mike","College of Engineering and Computer Science"],"dc:creator":["Allen, Brandon J."],"dc:date":["2015-12-01T08:00:00Z"],"dc:description":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."],"dc:description.abstract":["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. 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