TY - GEN
T1 - Change detection technique for muscle tone during static stretching by continuous muscle viscoelasticity monitoring using wearable indentation tester
AU - Okamura, Naomi
AU - Kobayashi, Yo
AU - Sugano, Shigeki
AU - Fujie, Masakatsu G.
N1 - Funding Information:
This work was supported in part by the Program for Leading Graduate Schools, “Graduate Program for Embodiment Informatics” of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan, a Scientific Research Grant (S) (No. 25220005) from the MEXT of Japan, and the "Institute of Advanced Active Aging Research", Organization for University Research Initiatives, Waseda University, Tokyo, Japan, and Research Institute for Science and Engineering, Waseda University, Tokyo, Japan.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/11
Y1 - 2017/8/11
N2 - Static stretching is widely performed to decrease muscle tone as a part of rehabilitation protocols. Finding out the optimal duration of static stretching is important to minimize the time required for rehabilitation therapy and it would be helpful for maintaining the patient's motivation towards daily rehabilitation tasks. Several studies have been conducted for the evaluation of static stretching; however, the recommended duration of static stretching varies widely between 15-30 s in general, because the traditional methods for the assessment of muscle tone do not monitor the continuous change in the target muscle's state. We have developed a method to monitor the viscoelasticity of one muscle continuously during static stretching, using a wearable indentation tester. In this study, we investigated a suitable signal processing method to detect the time required to change the muscle tone, utilizing the data collected using a wearable indentation tester. By calculating a viscoelastic index with a certain time window, we confirmed that the stretching duration required to bring about a decrease in muscle tone could be obtained with an accuracy in the order of 1 s.
AB - Static stretching is widely performed to decrease muscle tone as a part of rehabilitation protocols. Finding out the optimal duration of static stretching is important to minimize the time required for rehabilitation therapy and it would be helpful for maintaining the patient's motivation towards daily rehabilitation tasks. Several studies have been conducted for the evaluation of static stretching; however, the recommended duration of static stretching varies widely between 15-30 s in general, because the traditional methods for the assessment of muscle tone do not monitor the continuous change in the target muscle's state. We have developed a method to monitor the viscoelasticity of one muscle continuously during static stretching, using a wearable indentation tester. In this study, we investigated a suitable signal processing method to detect the time required to change the muscle tone, utilizing the data collected using a wearable indentation tester. By calculating a viscoelastic index with a certain time window, we confirmed that the stretching duration required to bring about a decrease in muscle tone could be obtained with an accuracy in the order of 1 s.
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U2 - 10.1109/ICORR.2017.8009490
DO - 10.1109/ICORR.2017.8009490
M3 - Conference contribution
C2 - 28814062
AN - SCOPUS:85034859441
T3 - IEEE International Conference on Rehabilitation Robotics
SP - 1686
EP - 1691
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 -