Stroke patient balance assessment using waist-mounted wearable inertial sensor

• Main Authors: Ganbold Galsandamdin, 丹尼
• Other Authors: Tien-Lung Sun
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/88htfr

碩士 === 元智大學 === 工業工程與管理學系 === 107 === Recent technological developments have led to the production of inexpensive, wearable accelerometer sensors with potential use in applications related human balance assessment. PURPOSE: The purpose of this study was to develop a timely detection at the home environment approach for stroke patient balance assessment measures from wearable accelerometer sensors. METHOD: Data collected from the central area of Taiwan between April 2018 and October 2018. Total 97 elderly stroke patient (57±15.2 year). Data collection use a waist mounted accelerometer when the stroke patient conducted time up and go test. RESULT: Data file labeled based on participant SFBBS scores. Stroke patient balance assessment using machine learning random forest classification approach X-y-20/80 model accuracy is 0.7948.