脑机接口在失语症康复中的有效性综述

凌 孝语
麦吉尔大学

摘要

失语症是一种由大脑皮层损伤引起的言语和语言障碍，影响着很大一部分中风幸存者，阻碍了
他们的独立性和社会融入。传统言语治疗 (SLT) 仍然是一种普遍的治疗形式，但其有效性依赖于高强度和剂量，
导致较高的退出率。在这篇综述中，我们探索了一种有前途的干预措施——脑机接口（BCI）——它具有更高
效和有效的失语症康复的潜力，并概述了当前的研究和潜在的未来方向。我们的目标是阐明整合脑机接口技术
如何增强失语症康复效果并改善受该疾病影响的个人的生活质量。

关键词

失语症；脑机接口

参考

[1]Anumanchipalli, G. K., Chartier, J., & Chang, E.

F. (2019). Speech synthesis from neural decoding of spoken

sentences. Nature, 568(7753),493-498.

[2]Bocquelet, F., Hueber, T., Girin, L., Chabardès,

S., & Yvert, B. (2016). Key considerations in designing a

speech brain-computer interface. Journal of Physiology,

Paris, 110(4 Pt , 392–401.

[3]Brady, M. C., Kelly, H., Godwin, J., Enderby,

P., & Campbell, P. (2016). Speech and language therapy

for aphasia following stroke. The Cochrane Database of

Systematic Reviews, 2016(6), CD000425.

[4]Carelli, L., Solca, F., Faini, A., Meriggi, P., Sangalli,

D., Cipresso, P., Riva, G., Ticozzi, N., Ciammola, A., Silani,

V., & Poletti, B. (2017). Brain-computer interface for clinical

purposes: cognitive assessment and rehabilitation. BioMed

Research International, 2017, 1695290.

[5]Huang, W., Yan, H., Cheng, K., Wang, C., Li,

J., Wang, Y., Li, C., Li, C., Li, Y., Zuo, Z., & Chen,

H. (2021). A neural decoding algorithm that generates

language from visual activity evoked by natural images.

Neural Networks: The Official Journal of the International

Neural Network Society, 144, 90–100.

[6]Lee, S. H., Lee, M., & Lee, S. W. (2020). Neural

decoding of imagined speech and visual imagery as intuitive

paradigms for BCI communication. IEEE Transactions

on Neural Systems and Rehabilitation Engineering: A

Publication of the IEEE Engineering in Medicine and

Biology Society, 28(12), 2647–2659.

[7]Morooka, T., Ishizuka, K., Kobayashi, N. (2018).

Electroencephalographic analysis of auditory imagination to

realize silent speech BCI. IEEE 7th Global Conference on

Consumer Electronics (GCCE), 2018, 683-686.

[8]Mridha, M. F., Das, S. C., Kabir, M. M., Lima, A.

A., Islam, M. R., & Watanobe, Y. (2021). Brain-computer

interface: Advancement and challenges. Sensors (Basel,

Switzerland), 21(17), 5746.

[9]Musso, M., Hübner, D., Schwarzkopf, S.,

Bernodusson, M., LeVan, P., Weiller, C., & Tangermann,

M. (2022). Aphasia recovery by language training using

a brain-computer interface: a proof-of-concept study.

Brain Communications, 4(1), fcac008.