@inproceedings{b58671f8fd0a43ccae3cec7e863720f5,
title = "Improvement of stability in long-term motor decoding forelimb movement with a sequence imputation of temporal-based spike patterns",
abstract = "Instability of neural signals is a vital issue in intracortical brain machine interface (iBMI) systems which caused by missing neuron day by day. This study proposed mean-perturbation to impute missing neural spike train during rat forelimb movement. Our results showed that the proposed mean-perturbation for sequence imputation of missing neural spikes was used to enhance the long-term decoding performance.",
author = "Kuo, {Yun Ting} and Yang, {Shih Hung} and Chou, {Chin Yu} and Chang, {Hao Cheng} and Chen, {Kuan Yu} and Chen, {You Yin}",
note = "Funding Information: ACKNOWLEDGMENT This work is financially supported by the Ministry of Science and Technology of Taiwan under Contract numbers of MOST 111-2622-8-A49-011-TE2, 111-2321-B-A49-005, 110-2321-B-010-006, 109-2221-E-010-004-MY2, 109-2314-B-303-016, and 109-2636-E-006-010 (Young Scholar Fellowship Program). We also are grateful for support from the Headquarters of University Advancement at the National Cheng Kung University, which is sponsored by the Ministry of Education, Taiwan. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Biomedical Circuits and Systems Conference, BioCAS 2022 ; Conference date: 13-10-2022 Through 15-10-2022",
year = "2022",
doi = "10.1109/BioCAS54905.2022.9948606",
language = "English",
series = "BioCAS 2022 - IEEE Biomedical Circuits and Systems Conference: Intelligent Biomedical Systems for a Better Future, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "625--629",
booktitle = "BioCAS 2022 - IEEE Biomedical Circuits and Systems Conference",
address = "United States",
}