期刊
IEEE SENSORS JOURNAL
卷 21, 期 5, 页码 6679-6690出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2020.3043285
关键词
Muscles; Sensors; Senior citizens; Risk management; Electromyography; Tools; Fatigue; Body area sensor network application; elderly assistance; fall risk assessment; muscle fatigue analysis
资金
- Deanship of Research at Islamic University of Madinah through Takkamul Program [11, 96/1441-42]
This paper proposes a proactive Fall Risk Assessment mechanism for elderly by performing Muscle Fatigue Analysis on data collected using wearable sensors. It shows that muscle fatigue in two lower limb muscles could lead to falling in an elderly person, based on evaluation results and simulations on Matlab.
With the rapid growth and commercialization of wearable sensor technology, the research community foresees great potential of Body Area Sensor Network (BASN) applications in the healthcare industry, including elderly healthcare. We consider the issue of fall in elderly, which has severe consequences including death. Most of the related proposals in the literature are reactive. In this paper, we propose a proactive Fall Risk Assessment mechanism for elderly by performing Muscle Fatigue Analysis on data collected using BASN consisting of wearable sensors. We first discuss the in-house developed android application that connects with the wearable EMG sensors placed on the human body to collect data of four activities including walking, sitting and getting up from a chair, and ankle stretch (Dorsiflexion and planter flexion) in a controlled environment. Then we present our Fall Risk Assessment algorithm that computes the Fall Risk Assessment score based on various levels of muscle fatigue. We tested our algorithm using four features to determine muscle fatigue in two lower limb muscles i.e. Tibilias (TM) and Gastrocnemius (GM) muscles. The implementation results of various scenarios on Matlab are presented as the proof-of-concept. Our evaluation results of two lower limb muscles behavior in selected activities justify our claim that muscle fatigue in these two muscles could lead to falling in an elderly person.
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