期刊
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
卷 64, 期 4, 页码 834-843出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2016.2580705
关键词
Ankle-angle estimation; artificial neural network; blind source separation; functional neuromuscular stimulation (FNS) system; multichannel cuff electrode; muscle afferent neural signal
资金
- Korea Health Technology R&D Project through the Korea Health Industry Development Institute
- Ministry of Health & Welfare of the Republic of Korea [HI14C3477]
- National Research Foundation
- Korean government, MSIP [2015M3D5A1066100]
Cuff electrode recording has been proposed as a solution to obtain robust feedback signals for closed-loop controlled functional neuromuscular stimulation (FNS) systems. However, single-channel cuff electrode recording requires several electrodes to obtain the feedback signal related to each muscle. In this study, we propose an ankle-angle estimation method in which recording is conducted from the proximal nerve trunk with a multichannel cuff electrode to minimize cuff electrode usage. In experiments, muscle afferent signals were recorded from a rabbit's proximal sciatic nerve trunk using a multichannel cuff electrode, and blind source separation and ankle-angle estimation were performed using fast independent component analysis (PP/FastICA) combined with dynamically driven recurrent neural network (DDRNN). The experimental results indicate that the proposed method has high ankle-angle estimation accuracy for both situations when the ankle motion is generated by position servo system or neuromuscular stimulation. Furthermore, the results confirm that the proposed method is applicable to closed-loop FNS systems to control limb motion.
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