Jin-Chern Chiou; Liang-Kung Chen, MD, PhD; Tzai-Wen Chiu, PhD
Competition Sponsor: Academia Sinica
Sarcopenia has identified as a skeletal muscle disease in the international classification diseases (ICD-10). But its etiology and underlying mechanisms and effective treatment remain unavailable. The Dual-Energy X-Ray Absorptiometry (DXA), currently used for diagnosis, can’t apply for daily basis chronic monitoring. Furthermore, it can’t assess the neural and muscular functions as well as the behaviors simultaneously. Therefore, a new integrated measuring system combined with the automatic intelligent-based analysis to assess the sarcopenia-related changes in neuromuscular functions and behaviors are obligatory. In this proposal, we are going to develop a novel top-to-toe system (TtT system) that is capable of determining the longitudinal causal links between sarcopenia and the age-related neuromuscular changes by establishing the active marker for early detecting of sarcopenia. The TtT system consists of three important modules: high-density insole-based balance sensing, EMG and EEG module, for assessing the static and dynamic changes of balance, muscle kinetic activities and cortical activities. With the proposed system, the protocol of clinical trial for various human movements and excises will be designed in order to acquire effective biomarkers from sarcopenic and non-sarcopenic subjects. Upon the clinical data is obtained, an AI deep learning-based analysis will be performed and determined the causal links between sarcopenia and the age-related neuromuscular changes, which can help the elderly community to early detect this age-related disease, bringing benefits to the aging society.