A Wearable Solution of Muscle Atrophy Assessment: Oriented Toward Upper Limb Rehabilitation

被引:0
|
作者
Wang, Qin [1 ]
Wang, Daomiao [1 ]
Yang, Cuiwei [1 ,2 ]
Huang, Xiaonan [3 ]
Fang, Fanfu [3 ]
Song, Zilong [1 ]
Xiang, Wei [1 ]
机构
[1] Fudan Univ, Sch Informat Sci & Technol, Dept Biomed Engn, Shanghai 200433, Peoples R China
[2] Shanghai Inst Intelligent Elect & Syst, Shanghai 200433, Peoples R China
[3] Naval Med Univ, Changhai Hosp, Shanghai 200433, Peoples R China
关键词
bioimpedance; upper limb rehabilitation; muscle atrophy; machine learning; wearable device; ELECTRICAL-IMPEDANCE; SEVERITY;
D O I
10.3390/electronics13204138
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the process of the upper limb rehabilitation, the rehabilitation effect is often evaluated from the perspective of the motor function of limbs. However, the state of muscle atrophy is also a noteworthy indicator reflecting the rehabilitation effect. We proposed a wearable solution for the monitoring and grade assessing of local muscle atrophy based on wearable bioimpedance (BioZ) sensors. This work elaborates on the theoretical basis, procedure, and key influencing factors of the proposed solution, and the feasibility and effectiveness have been verified through in vitro and in vivo experiments. A total of 25 phantoms in different CSA (cross-sectional area) and FMR (fat-to-muscle ratio) values were designed to simulate different stages of muscular atrophy, and a linear correlation was observed between BioZ, CSA, and FMR, with an R-squared value of 0.898. The relative impedance difference of 38 patients with unilateral muscle atrophy was 5.231% larger than that of 30 healthy control samples on average (p < 0.05). These results demonstrate the correlation between muscle atrophy and BioZ. As the proof-of-concept for graded assessment, the results analyzed by support vector machines (SVMs) show that the accuracy of three-level classification can reach 94.1% using the five-fold cross-validation.
引用
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页数:16
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