TY - GEN
T1 - Walking speed intention model using soleus electromyogram signal of nondisabled and post-stroke hemiparetic patients
AU - Chung, Sang Hun
AU - Choi, Taejin
AU - Hwang, Yoha
AU - Kim, Hyungmin
AU - Kim, Seung Jong
AU - Chun, Min Ho
AU - Lee, Jong Min
N1 - Funding Information:
*Resrach supported by the Industrial Core Technology Development Program through the Ministry and Trade Industry and Energy (Grant Number: 10045164) and the Korea Institute of Science and Technology Institutional Program (Grant Number: 2E26890).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/11
Y1 - 2017/8/11
N2 - It is well known that the activation of plantar flexors have a strong influence on the walking speed. If the gait speed can be predicted using this relationship, a post-stroke hemiparetic patient could control a gait rehabilitation robot according to his or her gait intention, and the robotic gait rehabilitation effect could be further improved. To find out this relationship, 9 nondisabled subjects and 4 chronic post-stroke hemiparetic subjects performed overground level walking at a comfortable pace, a slow pace, a fast pace, and an increasing pace with electromyogram sensors attached on plantar flexors. Soleus among plantar flexors showed the most stable relationship with walking speed. The relationship between maximum activation level of soleus electromyogram during stance phase before toe-off and walking speed during swing phase after the same toe-off was modeled by a polynomial regression model. The model outputs were then compared to the measured walking speeds using coefficients of determination (R2). The average R2 values are 0.594 and 0.692 for 1st· and 2nd order models respectively in the nondisabled subjects. The average R2 values are 0.598 and 0.623 for the unaffected side and 0.388 and 0.394 for the affected side in the chronic subjects. The results show the feasibility of applying the soleus-walking speed relationship to control the robot gait speed at will. A walking speed estimation method is proposed using only a walking step in real time.
AB - It is well known that the activation of plantar flexors have a strong influence on the walking speed. If the gait speed can be predicted using this relationship, a post-stroke hemiparetic patient could control a gait rehabilitation robot according to his or her gait intention, and the robotic gait rehabilitation effect could be further improved. To find out this relationship, 9 nondisabled subjects and 4 chronic post-stroke hemiparetic subjects performed overground level walking at a comfortable pace, a slow pace, a fast pace, and an increasing pace with electromyogram sensors attached on plantar flexors. Soleus among plantar flexors showed the most stable relationship with walking speed. The relationship between maximum activation level of soleus electromyogram during stance phase before toe-off and walking speed during swing phase after the same toe-off was modeled by a polynomial regression model. The model outputs were then compared to the measured walking speeds using coefficients of determination (R2). The average R2 values are 0.594 and 0.692 for 1st· and 2nd order models respectively in the nondisabled subjects. The average R2 values are 0.598 and 0.623 for the unaffected side and 0.388 and 0.394 for the affected side in the chronic subjects. The results show the feasibility of applying the soleus-walking speed relationship to control the robot gait speed at will. A walking speed estimation method is proposed using only a walking step in real time.
UR - http://www.scopus.com/inward/record.url?scp=85034844227&partnerID=8YFLogxK
U2 - 10.1109/ICORR.2017.8009265
DO - 10.1109/ICORR.2017.8009265
M3 - Conference contribution
C2 - 28813837
AN - SCOPUS:85034844227
T3 - IEEE International Conference on Rehabilitation Robotics
SP - 308
EP - 313
BT - 2017 International Conference on Rehabilitation Robotics, ICORR 2017
A2 - Ajoudani, Arash
A2 - Artemiadis, Panagiotis
A2 - Beckerle, Philipp
A2 - Grioli, Giorgio
A2 - Lambercy, Olivier
A2 - Mombaur, Katja
A2 - Novak, Domen
A2 - Rauter, Georg
A2 - Rodriguez Guerrero, Carlos
A2 - Salvietti, Gionata
A2 - Amirabdollahian, Farshid
A2 - Balasubramanian, Sivakumar
A2 - Castellini, Claudio
A2 - Di Pino, Giovanni
A2 - Guo, Zhao
A2 - Hughes, Charmayne
A2 - Iida, Fumiya
A2 - Lenzi, Tommaso
A2 - Ruffaldi, Emanuele
A2 - Sergi, Fabrizio
A2 - Soh, Gim Song
A2 - Caimmi, Marco
A2 - Cappello, Leonardo
A2 - Carloni, Raffaella
A2 - Carlson, Tom
A2 - Casadio, Maura
A2 - Coscia, Martina
A2 - De Santis, Dalia
A2 - Forner-Cordero, Arturo
A2 - Howard, Matthew
A2 - Piovesan, Davide
A2 - Siqueira, Adriano
A2 - Sup, Frank
A2 - Lorenzo, Masia
A2 - Catalano, Manuel Giuseppe
A2 - Lee, Hyunglae
A2 - Menon, Carlo
A2 - Raspopovic, Stanisa
A2 - Rastgaar, Mo
A2 - Ronsse, Renaud
A2 - van Asseldonk, Edwin
A2 - Vanderborght, Bram
A2 - Venkadesan, Madhusudhan
A2 - Bianchi, Matteo
A2 - Braun, David
A2 - Godfrey, Sasha Blue
A2 - Mastrogiovanni, Fulvio
A2 - McDaid, Andrew
A2 - Rossi, Stefano
A2 - Zenzeri, Jacopo
A2 - Formica, Domenico
A2 - Karavas, Nikolaos
A2 - Marchal-Crespo, Laura
A2 - Reed, Kyle B.
A2 - Tagliamonte, Nevio Luigi
A2 - Burdet, Etienne
A2 - Basteris, Angelo
A2 - Campolo, Domenico
A2 - Deshpande, Ashish
A2 - Dubey, Venketesh
A2 - Hussain, Asif
A2 - Sanguineti, Vittorio
A2 - Unal, Ramazan
A2 - Caurin, Glauco Augusto de Paula
A2 - Koike, Yasuharu
A2 - Mazzoleni, Stefano
A2 - Park, Hyung-Soon
A2 - Remy, C. David
A2 - Saint-Bauzel, Ludovic
A2 - Tsagarakis, Nikos
A2 - Veneman, Jan
A2 - Zhang, Wenlong
PB - IEEE Computer Society
T2 - 2017 International Conference on Rehabilitation Robotics, ICORR 2017
Y2 - 17 July 2017 through 20 July 2017
ER -