TY - GEN
T1 - NASA-TLX Assessment for a Haptic Adaptive Platform for Upper Extremity Motor Rehabilitation
AU - Ramirez-Zamora, Juan D.
AU - Dominguez-Ramirez, Omar A.
AU - Sepulveda-Cervantes, Gabriel
AU - Ramos-Velasco, Luis E.
AU - Fernandez-Ramirez, José M.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the help of platforms with haptic devices, rehabilitation areas for cerebrovascular accident patients can be attended with practices such as upper and lower extremity training. The application of training and/or rehabilitation protocols generates in disabled people the capacity for motor learning (movements executed quickly and accurately through practice). In this research article, we present the integration of a rehabilitation platform for upper limb, which is used by a pilot sample of users, who perform the evaluation of the user's workload during human-robot interaction using the NASA-TLX protocol, which is based on the assessment of load and mental fatigue. To generate the rehabilitation tasks from trajectory planning in the workspace of the haptic device and guarantee position convergence, a wavenet control (Multiresolution PID control based on wavelet transform and second generation neural networks as identification scheme) was implemented. The proposed adaptive control is evaluated on a 6-degree-of-freedom haptic device with high technological performance (Cyberforce) designed to position an exoskeleton CyberGrasp with the human operator in the loop.
AB - With the help of platforms with haptic devices, rehabilitation areas for cerebrovascular accident patients can be attended with practices such as upper and lower extremity training. The application of training and/or rehabilitation protocols generates in disabled people the capacity for motor learning (movements executed quickly and accurately through practice). In this research article, we present the integration of a rehabilitation platform for upper limb, which is used by a pilot sample of users, who perform the evaluation of the user's workload during human-robot interaction using the NASA-TLX protocol, which is based on the assessment of load and mental fatigue. To generate the rehabilitation tasks from trajectory planning in the workspace of the haptic device and guarantee position convergence, a wavenet control (Multiresolution PID control based on wavelet transform and second generation neural networks as identification scheme) was implemented. The proposed adaptive control is evaluated on a 6-degree-of-freedom haptic device with high technological performance (Cyberforce) designed to position an exoskeleton CyberGrasp with the human operator in the loop.
KW - CyberForce
KW - Force Feedback
KW - Haptic Interface
KW - NASA TLX
UR - http://www.scopus.com/inward/record.url?scp=85143980989&partnerID=8YFLogxK
U2 - 10.1109/COMRob57154.2022.9962313
DO - 10.1109/COMRob57154.2022.9962313
M3 - Contribución a la conferencia
AN - SCOPUS:85143980989
T3 - Proceedings of the 24th Robotics Mexican Congress, COMRob 2022
SP - 36
EP - 41
BT - Proceedings of the 24th Robotics Mexican Congress, COMRob 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th Robotics Mexican Congress, COMRob 2022
Y2 - 9 November 2022 through 11 November 2022
ER -