TY - GEN
T1 - Rehabilitation robot with a new diagnostic and control protocol
AU - Abdallah, Ismail Ben
AU - Bouteraa, Yassine
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Using a connected robot for wrist and forearm rehabilitation, a new rehabilitation system is developed. Forearm and wrist biomechanics are studied as part of a rehabilitation protocol. An integrated wrist-forearm joint mathematical model is developed and integrated into the main controller. The proposed new rehabilitation protocol is composed of three main sessions: the first is dedicated to the extraction of the passive components of the dynamic model of the wrist-forearm biomechanics while the active components are extracted in the second session. The third session consists of performing the continuous exercises using the determined dynamic model of the forearm-wrist joints taking into account the torque due to muscle fatigue. In addition to determining the wrist condition and capturing the torque produced by the robot and that provided by the patient, this protocol aims to identify the level of fatigue faced by the wrist. An EMG signal is used to estimate muscle fatigue using a fuzzy classifier designed and implemented for this purpose. The results show that the rehabilitation system developed allows a good progression of the articular amplitudes as well as the resistive-active couple.
AB - Using a connected robot for wrist and forearm rehabilitation, a new rehabilitation system is developed. Forearm and wrist biomechanics are studied as part of a rehabilitation protocol. An integrated wrist-forearm joint mathematical model is developed and integrated into the main controller. The proposed new rehabilitation protocol is composed of three main sessions: the first is dedicated to the extraction of the passive components of the dynamic model of the wrist-forearm biomechanics while the active components are extracted in the second session. The third session consists of performing the continuous exercises using the determined dynamic model of the forearm-wrist joints taking into account the torque due to muscle fatigue. In addition to determining the wrist condition and capturing the torque produced by the robot and that provided by the patient, this protocol aims to identify the level of fatigue faced by the wrist. An EMG signal is used to estimate muscle fatigue using a fuzzy classifier designed and implemented for this purpose. The results show that the rehabilitation system developed allows a good progression of the articular amplitudes as well as the resistive-active couple.
KW - Human Robot Interaction
KW - Remote Control
KW - Robotic Rehabilitation
KW - Wrist-Forearm biomechanics
UR - http://www.scopus.com/inward/record.url?scp=85185831454&partnerID=8YFLogxK
U2 - 10.1109/SSD58187.2023.10411177
DO - 10.1109/SSD58187.2023.10411177
M3 - Conference contribution
AN - SCOPUS:85185831454
T3 - 2023 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023
SP - 151
EP - 156
BT - 2023 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023
Y2 - 20 February 2023 through 23 February 2023
ER -