Electromyography signal processing techniques applied in gait analysis for frailty detection

• Main Author: Li, Gaofeng
• Other Authors: Wang Ping
• Format: Final Year Project
• Language: English
• Published: 2016
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/66806
• Institution: Nanyang Technological University

Currently, frailty is identified as a prevalent group that distinguished from comorbidity or disability, which has large potential to lead serious clinical outcomes including falls, functional declines, and institutionalization [1]. Frailty detection using gait analysis in community-dwelling elderly has achieved considerable results in biomechanical research. Among all the gait characteristics, gait velocity is the most prominent factor that contribute to reveal the frailty status of the subject [1]. While other potential meaningful clinical gait parameters beyond velocity have received little attention in frailty research. Electromyography (EMG) approach in kinesiological study is one of the popular solution adopted in gait analysis. It provides objective evaluation of neuromuscular activation of muscles within various activities, such as work conditions, functional movements, treatment and training regimes, etc. As an evaluation tool for biomechanical study, kinesiological EMG may be existed as a potential solution for systematic gait analysis associated with frailty detection.