Feature Extraction Methods Using Lower-limb Electromyogram Signals for Intention Recognition of Gait Initiation

Title
Feature Extraction Methods Using Lower-limb Electromyogram Signals for Intention Recognition of Gait Initiation
Authors
정상훈김영훈김형민황요하김승종안진웅이종민
Issue Date
2015-08
Publisher
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Abstract
Intention recognition of gait initiation is important for first step control of lower-limb exoskeleton gait. Using surface electromyogram (sEMG) signals from the soleus and gluteus medius, we were able to detect gait initiation in conjunction with the side of first step. Two feature extraction methods are suggested; waveform lengths of soleus sEMG signals, and statistics of cross-correlation coefficients between sEMG signals of two muscles. Our results indicate that the performances of both methods make them suitable for first step control of exoskeleton gait with delay times less than 300 msec and detection rates above 90%.
URI
http://pubs.kist.re.kr/handle/201004/50296
Appears in Collections:
KIST Publication > Conference Paper
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