Brain–computer interface for amyotrophic lateral sclerosis patients using deep learning network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-020-05026-y.pdf
Reference59 articles.
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2. Grollemund V, Pradat PF, Querin G, Delbot F, Le Chat G, Pradat-Peyre JF, Bede P (2019) Machine learning in amyotrophic lateral sclerosis: achievements, pitfalls, and future directions. Front Neurosci 13:1–28
3. Gordon J, Lerner B (2019) Insights into amyotrophic lateral sclerosis from a machine learning perspective. J Clin Med 8(10):1578
4. Arthur KC, Calvo A, Price TR, Geiger JT, Chio A, Traynor BJ (2016) Projected increase in amyotrophic lateral sclerosis from 2015 to 2040. Nat Commun 7(1):1–6
5. Zhang R, He S, Yang X, Wang X, Li K, Huang Q, Yu Z, Zhang X, Tang D, Li Y (2019) An EOG-based human–machine interface to control a smart home environment for patients with severe spinal cord injuries. IEEE Trans Biomed Eng 66(1):89–100
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