Gait analysis and fall detection by inertia sensing

• Main Authors: Nong Hsiang Hong, 洪農翔
• Other Authors: H. L. Chan
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/52996089776950966810

碩士 === 長庚大學 === 電機工程學系 === 105 === In recent years, population aging becomes much severer. Besides the amending of medical quality, home care and care for the elderly and patient should also be upgraded. In this thesis “inertial measurement unit” was used to analyze fall detection and gait analysis for the elderly and patients with Parkinson's disease, which can be beneficial to the rehabilitation of patients with Parkinson's disease as well as home care for elders. The wearable devices with “inertial measurement unit” were placed on different locations of human body. Fall detection is identified based on 3-axes accelerations which reveal the direction related to the gravity and the impact phenomenon. The post-impact information was used to make sure a true fall. By analyzing the angular velocities, on the feet the gait parameters of patients with Parkinson's disease, such as the stride length, cadence, etc, can be derived for further determining whether the walking state is normal or unstable, which may be useful for the assessment of patients’ gait status.