TY - GEN
T1 - Adaptations of Neuroprostheses for Training
T2 - 30th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
AU - Cruz-Anchiraico, Jose A.
AU - Aguirre-Cangalaya, Juan D.
AU - Cahuana-Ochoa, Jean J.
AU - Huamanchahua, Deyby
AU - Valcarcel-Castillo, Hector
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Certain medical conditions, genetic disabilities, and/or accidents limit certain parts of the body, such as the upper and/or lower extremities. This has seen technological advancement and has provided the development of various robotic devices (Neuroprosthetics) to assist in the rehabilitation process. Likewise, the use of Neural Networks, Supervised Machine Learning, or motion testing has the purpose of training the device itself to connect through sensors that capture biological signals to be pre-processed in controllers to target the movement to be performed. This research aims to analyze the characteristics of the components, control, and type of training for developing an efficient Neuroprosthesis. As a result of this research, different databases and search engines were used to collect information from various research from 2020 to 2023. Finally, it is concluded that the study aims to provide the most relevant information possible in the field of Neuroprosthesis concerning its training to be used in future research works and to be able to build and/or adapt a device with better characteristics for daily activities of the user and in the rehabilitation process.
AB - Certain medical conditions, genetic disabilities, and/or accidents limit certain parts of the body, such as the upper and/or lower extremities. This has seen technological advancement and has provided the development of various robotic devices (Neuroprosthetics) to assist in the rehabilitation process. Likewise, the use of Neural Networks, Supervised Machine Learning, or motion testing has the purpose of training the device itself to connect through sensors that capture biological signals to be pre-processed in controllers to target the movement to be performed. This research aims to analyze the characteristics of the components, control, and type of training for developing an efficient Neuroprosthesis. As a result of this research, different databases and search engines were used to collect information from various research from 2020 to 2023. Finally, it is concluded that the study aims to provide the most relevant information possible in the field of Neuroprosthesis concerning its training to be used in future research works and to be able to build and/or adapt a device with better characteristics for daily activities of the user and in the rehabilitation process.
KW - Biological Signals
KW - Exoskeleton
KW - Neural Network
KW - Neuro-prosthesis
UR - http://www.scopus.com/inward/record.url?scp=85179893187&partnerID=8YFLogxK
U2 - 10.1109/INTERCON59652.2023.10326054
DO - 10.1109/INTERCON59652.2023.10326054
M3 - Conference contribution
AN - SCOPUS:85179893187
T3 - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
BT - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 November 2023 through 4 November 2023
ER -