Multi-finger motion inference using M1 neural decoding

초록

This paper proposed a novel decoding method, which is the decoding technique for inferring multi-finger motions trained by the neural activities acquired in single finger motions. We have exploited the relationship between single and multi-finger motions. Then the model for multi-finger motions was built. The proposed method decoded multi-finger motions with 100% accuracy without a priori training information of multi-finger. These results suggest that only with the neural activities on single finger motions we can infer multi-finger motions. © 2018 IEEE.

제목
Multi-finger motion inference using M1 neural decoding
저자
Choi, H.; You, K.-J.; Shin, H.-C.
DOI
10.1109/ICOIN.2018.8343076
발행일
2018-01
학회명
32nd International Conference on Information Networking, ICOIN 2018
개최국가
미국
학회 개최일
2018-01-10 ~ 2018-01-12