脑机接口的范式、算法与编解码概念探讨与研究

doi:10.12267/j.issn.2096-5931.2024.05.009

信息通信技术与政策 ›› 2024, Vol. 50 ›› Issue (5): 61-70.doi: 10.12267/j.issn.2096-5931.2024.05.009

脑机接口的范式、算法与编解码概念探讨与研究

Exploration and research on paradigm, algorithm, as well as encoding and decoding concepts of brain-computer interface

梁栗炎¹, 孔姝懿², 张倩¹, 成苈委¹, 周洁¹, 孙艺珂³

1.中国信息通信研究院知识产权与创新发展中心,北京 100191
2.北京理工大学自动化学院,北京 100081
3.清华大学医学院,北京 100084

收稿日期:2024-04-30 出版日期:2024-05-25 发布日期:2024-05-31
通讯作者: 张倩,中国信息通信研究院知识产权与创新发展中心高级工程师,主要从事知识产权、脑机接口、未来产业等方面的研究工作
作者简介:
梁栗炎,中国信息通信研究院知识产权与创新发展中心工程师,主要从事脑机接口、生物医学信号处理等方面的研究工作
孔姝懿,北京理工大学自动化学院本科生在读,主要研究方向为控制系统设计、PID控制算法优化以及自动化系统开发
成苈委,中国信息通信研究院知识产权与创新发展中心工程师,主要从事脑机接口、智能穿戴设备等方面的研究工作
周洁,中国信息通信研究院知识产权与创新发展中心高级工程师,主要从事知识产权、脑机接口、未来产业等方面的研究工作
孙艺珂,清华大学医学院博士研究生在读,主要从事脑机接口、生物医学信号处理等方面的研究工作

LIANG Liyan¹, KONG Shuyi², ZHANG Qian¹, CHENG Liwei¹, ZHOU Jie¹, SUN Yike³

1. Intellectual Property and Innovation Development Center, China Academy of Information and Communications Technology, Beijing 100191, China
2. School of Automation, Beijing Institute of Technology, Beijing 100081, China
3. School of Medicine, Tsinghua University, Beijing 100084, China

Received:2024-04-30 Online:2024-05-25 Published:2024-05-31

摘要/Abstract

摘要：

脑机接口(Brain-Computer Interface,BCI)是脑科学、信息通信技术与人工智能的交叉领域,可实现大脑与外部设备的直接信息交互。经过数十年的理论研究与工程验证,BCI正逐渐由科学研究走向产业应用。随着创新链与产业链热度的上升,BCI得到了各方交叉领域的广泛关注,但BCI技术在范式编码、算法解码等方面的概念与人工智能、信息通信领域存在一定的差异,因而对多领域的交流合作造成了一定的限制。为进一步促进BCI的跨界交流合作,推动该领域技术链与创新链的协同发展,对BCI的范式、算法及编解码基础概念与原理开展了探讨,进而基于对范式算法的研究思考,设计了一种基于左右视野刺激的稳态视觉诱发电位BCI。

关键词: 脑机接口, 范式, 算法, 编码, 解码

Abstract:

Brain-computer interface (BCI) is an interdisciplinary field combining brain science, information and communication technology, and artificial intelligence, enabling a direct information exchange between the brain and external devices. After decades of theoretical research and engineering validation, BCI is gradually moving from scientific research to industrial applications. With the increasing interest in the innovation chain and industrial chain, BCI has received widespread attention from various interdisciplinary fields. However, there are certain differences in the concepts of BCI technology in areas such as paradigm encoding and algorithm decoding compared with those in artificial intelligence and information and communication fields, which has caused some limitations on cooperation and exchange among multiple fields. To further promote the cross-field cooperation and exchange of BCI, and to drive the coordinated development of the technical chain and innovation chain in this field, this paper explores the paradigms, algorithms, as well as basic concepts and principles of encoding and decoding of BCI. Then, it designs a steady-state visual evoked potentials BCI based on left and right visual field stimulation.

Key words: BCI, paradigm, algorithm, encoding, decoding

中图分类号:

梁栗炎, 孔姝懿, 张倩, 成苈委, 周洁, 孙艺珂. 脑机接口的范式、算法与编解码概念探讨与研究[J]. 信息通信技术与政策, 2024, 50(5): 61-70.

LIANG Liyan, KONG Shuyi, ZHANG Qian, CHENG Liwei, ZHOU Jie, SUN Yike. Exploration and research on paradigm, algorithm, as well as encoding and decoding concepts of brain-computer interface[J]. Information and Communications Technology and Policy, 2024, 50(5): 61-70.

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链接本文:

http://ictp.caict.ac.cn/CN/10.12267/j.issn.2096-5931.2024.05.009

http://ictp.caict.ac.cn/CN/Y2024/V50/I5/61

图/表 5

参考文献 31

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被试	在线训练阶段(5 s窗)		在线测试阶段(3 s窗)
被试	准确率	ITR/bits/min	准确率	ITR/bits/min
被试1	97.22%	36.06	100.00%	61.46
被试2	80.00%	23.69	91.67%	49.42
被试3	88.33%	29.03	91.67%	49.42
被试4	61.67%	14.17	83.33%	40.43
被试5	83.33%	25.73	91.67%	49.42
被试6	58.33%	12.69	83.33%	40.43
被试7	86.67%	27.90	83.33%	40.43
被试8	100.00%	39.11	100.00%	61.46
平均±标准差	81.94%±14.13%	26.05±8.72	90.63%±6.51%	49.06±8.15

被试	在线训练阶段(5 s窗)		在线测试阶段(3 s窗)
被试	准确率	ITR/bits/min	准确率	ITR/bits/min
被试1	97.22%	36.06	100.00%	61.46
被试2	80.00%	23.69	91.67%	49.42
被试3	88.33%	29.03	91.67%	49.42
被试4	61.67%	14.17	83.33%	40.43
被试5	83.33%	25.73	91.67%	49.42
被试6	58.33%	12.69	83.33%	40.43
被试7	86.67%	27.90	83.33%	40.43
被试8	100.00%	39.11	100.00%	61.46
平均±标准差	81.94%±14.13%	26.05±8.72	90.63%±6.51%	49.06±8.15

研究工作	被试数	目标数	识别准确率	ITR/bits/min	验证方式
Wang^[26]等	5	12	84.08%	30.21	在线
Kwak^[27]等	11	3	78.79%	18.07	在线
Ahn^[28]等	6	6	79.90%	11.03	离线
Floriano^[29]等	4	2	91.60%	5.30	在线
Liang^[30]等	16	12	84.20%	17.80	在线
本文工作	8	12	90.63%	49.06	在线

研究工作	被试数	目标数	识别准确率	ITR/bits/min	验证方式
Wang^[26]等	5	12	84.08%	30.21	在线
Kwak^[27]等	11	3	78.79%	18.07	在线
Ahn^[28]等	6	6	79.90%	11.03	离线
Floriano^[29]等	4	2	91.60%	5.30	在线
Liang^[30]等	16	12	84.20%	17.80	在线
本文工作	8	12	90.63%	49.06	在线

脑机接口的范式、算法与编解码概念探讨与研究

Exploration and research on paradigm, algorithm, as well as encoding and decoding concepts of brain-computer interface

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参考文献 31

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