TY - GEN
T1 - Walking phase recognition for people with lower limb disability
AU - Lee, Sang Wan
AU - Yi, Taeyoub
AU - Han, Jeong Su
AU - Jang, Hyoyoung
AU - Kim, Heon Hui
AU - Jung, Jin Woo
AU - Bien, Zeungnam
PY - 2007
Y1 - 2007
N2 - This paper presents a total solution on EMG signal-based walking phase recognition for people with lower limb disability. Various environmental factors such as sensed location, walking speed, and ground inclination are taken into consideration in all the phases of signal sensing, feature extraction, feature selection, and classification. Based on analysis on fourteen well-known feature extraction methods in varying environmental situation, this paper proposes a methodology for selecting a good feature set, and then demonstrates effectiveness of the proposed approach with the classification results.
AB - This paper presents a total solution on EMG signal-based walking phase recognition for people with lower limb disability. Various environmental factors such as sensed location, walking speed, and ground inclination are taken into consideration in all the phases of signal sensing, feature extraction, feature selection, and classification. Based on analysis on fourteen well-known feature extraction methods in varying environmental situation, this paper proposes a methodology for selecting a good feature set, and then demonstrates effectiveness of the proposed approach with the classification results.
UR - http://www.scopus.com/inward/record.url?scp=48349136998&partnerID=8YFLogxK
U2 - 10.1109/ICORR.2007.4428407
DO - 10.1109/ICORR.2007.4428407
M3 - Conference contribution
AN - SCOPUS:48349136998
SN - 1424413206
SN - 9781424413201
T3 - 2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07
SP - 60
EP - 67
BT - 2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07
T2 - 2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07
Y2 - 12 June 2007 through 15 June 2007
ER -