TY - GEN
T1 - Analysis of Electromyography Signals for Control Models of Power-Assisted Stroke Rehabilitation Devices of Upper Limb System
AU - Bonifacio, Paulo
AU - Vassilenko, Valentina
AU - Marques, Guilherme
AU - Casal, Diogo
N1 - Funding Information:
info:eu-repo/grantAgreement/FCT/OE/PD%2FBDE%2F130083%2F2017/PT#
Funding Information:
Acknowledgments. The authors thank all volunteers for participating in the study; and the support from the combined effort of NOVA School of Science and Technology and NMT, S.A. Partial support comes from Fundação para a Ciência e Tecnologia (FCT, Portugal) through the PhD grant (PD/BDE/130083/2017) of the Doctoral NOVA I4H Program.
Publisher Copyright:
© 2021, IFIP International Federation for Information Processing.
PY - 2021
Y1 - 2021
N2 - Stroke is a significant affliction that can affect people with varying degrees of severity. One of the most common consequences of stroke is the impairment of the muscular motor function to some degree with two-thirds of the patients being affected by upper-limb paralysis. For those cases, the most effective forms of regaining muscular motor function are through rehabilitation therapy, traditionally this must be done in a clinical environment. Developments in robotics, batteries and electronics have made accessible the prototyping, production, and utilization of exoskeleton type devices technically adapted for personal and residential rehabilitation. This paper presents and discusses the results of EMG signals from upper limb of brachial biceps muscle, obtained from a cohort of healthy volunteers. The methodology for testing is presented and explained, additionally, a preliminary discussion is made on the obtained data. Some control considerations, variables and methods are also presented and discussed.
AB - Stroke is a significant affliction that can affect people with varying degrees of severity. One of the most common consequences of stroke is the impairment of the muscular motor function to some degree with two-thirds of the patients being affected by upper-limb paralysis. For those cases, the most effective forms of regaining muscular motor function are through rehabilitation therapy, traditionally this must be done in a clinical environment. Developments in robotics, batteries and electronics have made accessible the prototyping, production, and utilization of exoskeleton type devices technically adapted for personal and residential rehabilitation. This paper presents and discusses the results of EMG signals from upper limb of brachial biceps muscle, obtained from a cohort of healthy volunteers. The methodology for testing is presented and explained, additionally, a preliminary discussion is made on the obtained data. Some control considerations, variables and methods are also presented and discussed.
KW - Control
KW - Electromyography EMG
KW - Rehabilitation
KW - Signals
KW - Stroke
KW - Upper-Limb
UR - http://www.scopus.com/inward/record.url?scp=85111970119&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-78288-7_29
DO - 10.1007/978-3-030-78288-7_29
M3 - Conference contribution
AN - SCOPUS:85111970119
SN - 978-3-030-78287-0
T3 - IFIP Advances in Information and Communication Technology
SP - 307
EP - 315
BT - Technological Innovation for Applied AI Systems - 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Proceedings
A2 - Camarinha-Matos, Luis M.
A2 - Ferreira, Pedro
A2 - Brito, Guilherme
PB - Springer
CY - Cham
T2 - 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021
Y2 - 7 July 2021 through 9 July 2021
ER -