Using wavelet analysis to reveal the muscle functional recovery following nerve reinnervation in a rat model

Author

Hui Zhou ; Lin Yang ; Liangqing Zhang ; Fengxia Wu ; Jianping Huang ; Guanglin Li

Author_Institution

Key Lab. of Human-Machine-Intell. Synergic Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China

fYear

2014

fDate

26-30 Aug. 2014

Firstpage

2549

Lastpage

2552

Abstract

Targeted muscle reinnervation (TMR) technique has been successful in many amputees for providing sufficient electromyography (EMG) signal to control advanced prosthetics. However, it seems to lack further understanding of the recovery progress of muscle functions after targeted muscle reinneveration surgery. In this study, a rat TMR model was developed to investigate intramuscular EMG activity changes after reinnervation. Using the discrete wavelet decomposition and average rectified algorithm, the recorded EMG showed a gradual improvement in the reinnervated muscle within four weeks. Future work will be performed to further assess the efficiency of reinnveration therapy after the surgery.

Keywords

discrete wavelet transforms; electromyography; medical signal processing; neurophysiology; prosthetics; surgery; advanced prosthetics; amputees; average rectified algorithm; discrete wavelet decomposition; electromyography signal; intramuscular EMG activity changes; muscle functional recovery; muscle functions; nerve reinnervation; rat TMR model; recovery progress; reinnervated muscle; reinnveration therapy; targeted muscle reinnervation technique; targeted muscle reinneveration surgery; time 4 week; wavelet analysis; Discrete wavelet transforms; Electromyography; Muscles; Noise; Rats; Surgery; Tunneling magnetoresistance;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE

Conference_Location

Chicago, IL

ISSN

1557-170X

Type

conf

DOI

10.1109/EMBC.2014.6944142

Filename

6944142