TY - JOUR
T1 - The LIBRA NeuroLimb
T2 - Hybrid Real-Time Control and Mechatronic Design for Affordable Prosthetics in Developing Regions
AU - Cifuentes-Cuadros, Alonso A.
AU - Romero, Enzo
AU - Caballa, Sebastian
AU - Vega-Centeno, Daniela
AU - Elias, Dante A.
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2024/1
Y1 - 2024/1
N2 - Globally, 2.5% of upper limb amputations are transhumeral, and both mechanical and electronic prosthetics are being developed for individuals with this condition. Mechanics often require compensatory movements that can lead to awkward gestures. Electronic types are mainly controlled by superficial electromyography (sEMG). However, in proximal amputations, the residual limb is utilized less frequently in daily activities. Muscle shortening increases with time and results in weakened sEMG readings. Therefore, sEMG-controlled models exhibit a low success rate in executing gestures. The LIBRA NeuroLimb prosthesis is introduced to address this problem. It features three active and four passive degrees of freedom (DOF), offers up to 8 h of operation, and employs a hybrid control system that combines sEMG and electroencephalography (EEG) signal classification. The sEMG and EEG classification models achieve up to 99% and 76% accuracy, respectively, enabling precise real-time control. The prosthesis can perform a grip within as little as 0.3 s, exerting up to 21.26 N of pinch force. Training and validation sessions were conducted with two volunteers. Assessed with the “AM-ULA” test, scores of 222 and 144 demonstrated the prosthesis’s potential to improve the user’s ability to perform daily activities. Future work will prioritize enhancing the mechanical strength, increasing active DOF, and refining real-world usability.
AB - Globally, 2.5% of upper limb amputations are transhumeral, and both mechanical and electronic prosthetics are being developed for individuals with this condition. Mechanics often require compensatory movements that can lead to awkward gestures. Electronic types are mainly controlled by superficial electromyography (sEMG). However, in proximal amputations, the residual limb is utilized less frequently in daily activities. Muscle shortening increases with time and results in weakened sEMG readings. Therefore, sEMG-controlled models exhibit a low success rate in executing gestures. The LIBRA NeuroLimb prosthesis is introduced to address this problem. It features three active and four passive degrees of freedom (DOF), offers up to 8 h of operation, and employs a hybrid control system that combines sEMG and electroencephalography (EEG) signal classification. The sEMG and EEG classification models achieve up to 99% and 76% accuracy, respectively, enabling precise real-time control. The prosthesis can perform a grip within as little as 0.3 s, exerting up to 21.26 N of pinch force. Training and validation sessions were conducted with two volunteers. Assessed with the “AM-ULA” test, scores of 222 and 144 demonstrated the prosthesis’s potential to improve the user’s ability to perform daily activities. Future work will prioritize enhancing the mechanical strength, increasing active DOF, and refining real-world usability.
KW - brain–computer interface
KW - machine learning
KW - myoelectric control
KW - pattern recognition
KW - sensor fusion
KW - transhumeral prosthesis
UR - http://www.scopus.com/inward/record.url?scp=85181887907&partnerID=8YFLogxK
U2 - 10.3390/s24010070
DO - 10.3390/s24010070
M3 - Article
C2 - 38202932
AN - SCOPUS:85181887907
SN - 1424-8220
VL - 24
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 1
M1 - 70
ER -