Ethical considerations for medical applications of implantable brain-computer interfaces_Journal of Biomedical Engineering

Authors：

ZHANG Zhe ^1,2 , CHEN Yanxiao ^2,3 , ZHAO Xu ¹ , WANG Fan ^2,3 , DING Peng ^2,3 , ZHAO Lei ^2,4 ,  FU Yunfa ^2,3

1. Faculty of Marxism, Kunming University of Science and Technology, Kunming 650500, P. R. China;
2. Brain Cognition and Brain-computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, P. R. China;
3. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China;
4. Faculty of Science, Kunming University of Science and Technology, Kunming 650500, P. R. China;

Corresponding author：

Keywords：

Safety of implantable BCI; Ethics for medical applications of BCI; Implantable BCI; Medical applications of BCI

DOI：

10.7507/1001-5515.202309083

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Implantable brain-computer interfaces (BCIs) have potentially important clinical applications due to the high spatial resolution and signal-to-noise ratio of electrodes that are closer to or implanted in the cerebral cortex. However, the surgery and electrodes of implantable BCIs carry safety risks of brain tissue damage, and their medical applications face ethical challenges, with little literature to date systematically considering ethical norms for the medical applications of implantable BCIs. In order to promote the clinical translation of this type of BCI, we considered the ethics of practice for the medical application of implantable BCIs, including: reducing the risk of brain tissue damage from implantable BCI surgery and electrodes, providing patients with customized and personalized implantable BCI treatments, ensuring multidisciplinary collaboration in the clinical application of implantable BCIs, and the responsible use of implantable BCIs, among others. It is expected that this article will provide thoughts and references for the research and development of ethics of the medical application of implantable BCI.

Citation： ZHANG Zhe, CHEN Yanxiao, ZHAO Xu, WANG Fan, DING Peng, ZHAO Lei, FU Yunfa. Ethical considerations for medical applications of implantable brain-computer interfaces. Journal of Biomedical Engineering, 2024, 41(1): 177-183. doi: 10.7507/1001-5515.202309083 Copy

1.	尼克·拉姆齐. 脑-计算机接口. 伏云发, 王帆, 丁鹏, 等译. 北京: 国防工业出版社, 2023.
2.	Bergeron D, Iorio-Morin C, Bonizzato M, et al. Use of invasive brain-computer interfaces in pediatric neurosurgery: Technical and ethical considerations. J Child Neurol, 2023, 38(3-4): 223-238.
3.	伯哈德·格雷曼. 脑-机接口-革命性的人机交互. 伏云发, 郭衍龙, 张夏冰, 等译. 北京: 国防工业出版社, 2020.
4.	Wolpaw J R. 脑机接口原理与实践. 伏云发, 杨秋红, 徐宝磊, 等译. 北京: 国防工业出版社, 2017.
5.	Vansteensel M J, Klein E, van Thiel G, et al. Towards clinical application of implantable brain–computer interfaces for people with late-stage ALS: medical and ethical considerations. J Neurol, 2023, 270(3): 1323-1336.
6.	张喆, 赵旭, 马艺昕, 等. 脑机接口技术伦理规范考量. 生物医学工程学杂志, 2023, 40(2): 358-364.
7.	人工智能医疗器械创新合作平台. 脑机接口技术在医疗健康领域应用白皮书. 北京: 人工智能医疗器械创新合作平台, 2023.
8.	Klein E, Ojemann J. Informed consent in implantable BCI research: identification of research risks and recommendations for development of best practices. J Neural Eng, 2016, 13(4): 043001.
9.	Klein E, Brown T, Sample M, et al. Engineering the brain: ethical issues and the introduction of neural devices. Hastings Cent Rep, 2015, 45(6): 26-35.
10.	Vansteensel M J, Branco M P, Leinders S, et al. Methodological recommendations for studies on the daily life implementation of implantable communication-brain–computer interfaces for individuals with locked-in syndrome. Neurorehabil Neural Repair, 2022, 36(10-11): 666-677.
11.	Kübler A, Holz E M, Riccio A, et al. The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications. PLoS One, 2014, 9(12): e112392.
12.	Jarosiewicz B, Sarma A A, Bacher D, et al. Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface. Sci Transl Med, 2015, 7(313): 313ra179.
13.	Downey J E, Schwed N, Chase S M, et al. Intracortical recording stability in human brain–computer interface users. J Neural Eng, 2018, 15(4): 046016.
14.	Milekovic T, Sarma A A, Bacher D, et al. Stable long-term BCI-enabled communication in ALS and locked-in syndrome using LFP signals. J Neurophysiol, 2018, 120(7): 343-360.
15.	Perge J A, Zhang S, Malik W Q, et al. Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex. J Neural Eng, 2014, 11(4): 046007.
16.	Perge J A, Homer M L, Malik W Q, et al. Intra-day signal instabilities affect decoding performance in an intracortical neural interface system. J Neural Eng, 2013, 10(3): 036004.
17.	Colachis S C, Dunlap C F, Annetta N V, et al. Long-term intracortical microelectrode array performance in a human: A 5 year retrospective analysis. J Neural Eng, 2021, 18(4): 0460d7.
18.	Pels E G M, Aarnoutse E J, Leinders S, et al. Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis. Clin Neurophysiol, 2019, 130(10): 1798-1803.
19.	Willett F R, Kunz E M, Fan C, et al. A high-performance speech neuroprosthesis. Nature, 2023, 620(7976): 1031-1036.
20.	Ma Yixin, Gong Anmin, Nan Wenya, et al. Personalized brain–computer interface and its applications. J Pers Med, 2022, 13(1): 2-25.
21.	顾心怡, 陈少峰. 脑机接口的伦理问题研究. 科学技术哲学研究, 2021, 38(4): 79-85.
22.	Hochberg L R, Bacher D, Jarosiewicz B, et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 2012, 485(7398): 372-375.
23.	Bacher D, Jarosiewicz B, Masse N Y, et al. Neural point-and-click communication by a person with incomplete locked-in syndrome. Neurorehabil Neural Repair, 2015, 29(5): 462-471.
24.	Holz E M, Botrel L, Kaufmann T, et al. Long-term independent brain-computer interface home use improves quality of life of a patient in the locked-in state: a case study. Arch Phys Med Rehab, 2015, 96(3): S16-S26.
25.	Humphrey D R, Schmidt E M, Thompson W D. Predicting measures of motor performance from multiple cortical spike trains. Science, 1970, 170(3959): 758-762.
26.	Pandarinath C, Nuyujukian P, Blabe C H, et al. High performance communication by people with paralysis using an intracortical brain-computer interface. Elife, 2017, 6: e18554.
27.	Willett F R, Avansino D T, Hochberg L R, et al. High-performance brain-to-text communication via handwriting. Nature, 2021, 593(7858): 249-254.
28.	Ford P J, Kubu C S. Stimulating debate: ethics in a multidisciplinary functional neurosurgery committee. J Med Ethics, 2006, 32(2): 106-109.
29.	Kübler A, Nijboer F, Kleih S. Hearing the needs of clinical users. Handb Clin Neurol, 2020, 168: 353-368.
30.	Branco M P, Pels E G M, Sars R H, et al. Brain-computer interfaces for communication: preferences of individuals with locked-in syndrome. Neurorehabil Neural Repair, 2021, 35(3): 267-279.
31.	Burwell S, Sample M, Racine E. Ethical aspects of brain computer interfaces: a scoping review. BMC Med Ethics, 2017, 18(1): 1-11.
32.	Tamburrini G. Brain to computer communication: Ethical perspectives on interaction models. Neuroethics, 2009, 2: 137-149.
33.	Nijboer F, Clausen J, Allison B Z, et al. The asilomar survey: Stakeholders’ opinions on ethical issues related to brain-computer interfacing. Neuroethics, 2013, 6: 541-578.
34.	Chan A K, McGovern R A, Brown L T, et al. Disparities in access to deep brain stimulation surgery for Parkinson disease: interaction between African American race and Medicaid use. JAMA Neurol, 2014, 71(3): 291-299.
35.	Lázaro-Muñoz G, Yoshor D, Beauchamp M S, et al. Continued access to investigational brain implants. Nat Rev Neurosci, 2018, 19(6): 317-318.
36.	Hendriks S, Grady C, Ramos K M, et al. Ethical challenges of risk, informed consent, and posttrial responsibilities in human research with neural devices: a review. JAMA Neurol, 2019, 76(12): 1506-1514.
37.	Rossi P J, Giordano J, Okun M S. The problem of funding off-label deep brain stimulation: bait-and-switch tactics and the need for policy reform. JAMA Neurol, 2017, 74(1): 9-10.
38.	Thenaisie Y, Palmisano C, Canessa A, et al. Towards adaptive deep brain stimulation: clinical and technical notes on a novel commercial device for chronic brain sensing. J Neural Eng, 2021, 18(4): 042002.
39.	王高峰, 张志领. 算法伦理视域下的脑机接口伦理问题研究. 自然辩证法研究, 2022, 38(7): 68-73.
40.	Luo Shiyu, Qinwan R, Crone N E. Brain-computer interface: Applications to speech decoding and synthesis to augment communication. Neurotherapeutics, 2022, 19(1): 263-273.
41.	董煜阳, 龚安民, 丁鹏, 等. 一种新型结合下肢动觉运动想象和视觉运动想象的脑机接口. 南京大学学报(自然科学), 2022, 58(3): 460-468.
42.	Pandarinath C, Bensmaia S J. The science and engineering behind sensitized brain-controlled bionic hands. Physiol Rev, 2021, 102(2): 551-604.
43.	Khan M A, Das R, Hansen J P, et al. Brain and behaviour computing. Boca Raton: CRC Press, 2021.
44.	艾丽森 B Z, 邓恩 S, 莱布 R., 等. 面向实用的脑-机接口: 缩小研究与实际应用之间的差距. 伏云发, 龚安民, 陈超, 等译. 北京: 电子工业出版社, 2022: 45-47.
45.	Vaughan T M. Brain-computer interfaces for people with amyotrophic lateral sclerosis. Handb Clin Neurol, 2020, 168: 33-38.
46.	Metzger S L, Littlejohn K T, Silva A B, et al. A high-performance neuroprosthesis for speech decoding and avatar control. Nature, 2023, 620(7976): 1037-1046.
47.	Vansteensel M J, Jarosiewicz B. Brain-computer interfaces for communication. Handb Clin Neurol, 2020, 168: 67-85.
48.	Mitchell K T, Starr P A. Smart neuromodulation in movement disorders. Handb Clin Neurol, 2020, 168: 153-161.
49.	Nakayama Y, Shimizu T, Mochizuki Y, et al. Predictors of impaired communication in amyotrophic lateral sclerosis patients with tracheostomy-invasive ventilation. Amyotroph Lateral Scler Frontotemporal Degener, 2015, 17(1-2): 38-46.

1. 尼克·拉姆齐. 脑-计算机接口. 伏云发, 王帆, 丁鹏, 等译. 北京: 国防工业出版社, 2023.
2. Bergeron D, Iorio-Morin C, Bonizzato M, et al. Use of invasive brain-computer interfaces in pediatric neurosurgery: Technical and ethical considerations. J Child Neurol, 2023, 38(3-4): 223-238.
3. 伯哈德·格雷曼. 脑-机接口-革命性的人机交互. 伏云发, 郭衍龙, 张夏冰, 等译. 北京: 国防工业出版社, 2020.
4. Wolpaw J R. 脑机接口原理与实践. 伏云发, 杨秋红, 徐宝磊, 等译. 北京: 国防工业出版社, 2017.
5. Vansteensel M J, Klein E, van Thiel G, et al. Towards clinical application of implantable brain–computer interfaces for people with late-stage ALS: medical and ethical considerations. J Neurol, 2023, 270(3): 1323-1336.
6. 张喆, 赵旭, 马艺昕, 等. 脑机接口技术伦理规范考量. 生物医学工程学杂志, 2023, 40(2): 358-364.
7. 人工智能医疗器械创新合作平台. 脑机接口技术在医疗健康领域应用白皮书. 北京: 人工智能医疗器械创新合作平台, 2023.
8. Klein E, Ojemann J. Informed consent in implantable BCI research: identification of research risks and recommendations for development of best practices. J Neural Eng, 2016, 13(4): 043001.
9. Klein E, Brown T, Sample M, et al. Engineering the brain: ethical issues and the introduction of neural devices. Hastings Cent Rep, 2015, 45(6): 26-35.
10. Vansteensel M J, Branco M P, Leinders S, et al. Methodological recommendations for studies on the daily life implementation of implantable communication-brain–computer interfaces for individuals with locked-in syndrome. Neurorehabil Neural Repair, 2022, 36(10-11): 666-677.
11. Kübler A, Holz E M, Riccio A, et al. The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications. PLoS One, 2014, 9(12): e112392.
12. Jarosiewicz B, Sarma A A, Bacher D, et al. Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface. Sci Transl Med, 2015, 7(313): 313ra179.
13. Downey J E, Schwed N, Chase S M, et al. Intracortical recording stability in human brain–computer interface users. J Neural Eng, 2018, 15(4): 046016.
14. Milekovic T, Sarma A A, Bacher D, et al. Stable long-term BCI-enabled communication in ALS and locked-in syndrome using LFP signals. J Neurophysiol, 2018, 120(7): 343-360.
15. Perge J A, Zhang S, Malik W Q, et al. Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex. J Neural Eng, 2014, 11(4): 046007.
16. Perge J A, Homer M L, Malik W Q, et al. Intra-day signal instabilities affect decoding performance in an intracortical neural interface system. J Neural Eng, 2013, 10(3): 036004.
17. Colachis S C, Dunlap C F, Annetta N V, et al. Long-term intracortical microelectrode array performance in a human: A 5 year retrospective analysis. J Neural Eng, 2021, 18(4): 0460d7.
18. Pels E G M, Aarnoutse E J, Leinders S, et al. Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis. Clin Neurophysiol, 2019, 130(10): 1798-1803.
19. Willett F R, Kunz E M, Fan C, et al. A high-performance speech neuroprosthesis. Nature, 2023, 620(7976): 1031-1036.
20. Ma Yixin, Gong Anmin, Nan Wenya, et al. Personalized brain–computer interface and its applications. J Pers Med, 2022, 13(1): 2-25.
21. 顾心怡, 陈少峰. 脑机接口的伦理问题研究. 科学技术哲学研究, 2021, 38(4): 79-85.
22. Hochberg L R, Bacher D, Jarosiewicz B, et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 2012, 485(7398): 372-375.
23. Bacher D, Jarosiewicz B, Masse N Y, et al. Neural point-and-click communication by a person with incomplete locked-in syndrome. Neurorehabil Neural Repair, 2015, 29(5): 462-471.
24. Holz E M, Botrel L, Kaufmann T, et al. Long-term independent brain-computer interface home use improves quality of life of a patient in the locked-in state: a case study. Arch Phys Med Rehab, 2015, 96(3): S16-S26.
25. Humphrey D R, Schmidt E M, Thompson W D. Predicting measures of motor performance from multiple cortical spike trains. Science, 1970, 170(3959): 758-762.
26. Pandarinath C, Nuyujukian P, Blabe C H, et al. High performance communication by people with paralysis using an intracortical brain-computer interface. Elife, 2017, 6: e18554.
27. Willett F R, Avansino D T, Hochberg L R, et al. High-performance brain-to-text communication via handwriting. Nature, 2021, 593(7858): 249-254.
28. Ford P J, Kubu C S. Stimulating debate: ethics in a multidisciplinary functional neurosurgery committee. J Med Ethics, 2006, 32(2): 106-109.
29. Kübler A, Nijboer F, Kleih S. Hearing the needs of clinical users. Handb Clin Neurol, 2020, 168: 353-368.
30. Branco M P, Pels E G M, Sars R H, et al. Brain-computer interfaces for communication: preferences of individuals with locked-in syndrome. Neurorehabil Neural Repair, 2021, 35(3): 267-279.
31. Burwell S, Sample M, Racine E. Ethical aspects of brain computer interfaces: a scoping review. BMC Med Ethics, 2017, 18(1): 1-11.
32. Tamburrini G. Brain to computer communication: Ethical perspectives on interaction models. Neuroethics, 2009, 2: 137-149.
33. Nijboer F, Clausen J, Allison B Z, et al. The asilomar survey: Stakeholders’ opinions on ethical issues related to brain-computer interfacing. Neuroethics, 2013, 6: 541-578.
34. Chan A K, McGovern R A, Brown L T, et al. Disparities in access to deep brain stimulation surgery for Parkinson disease: interaction between African American race and Medicaid use. JAMA Neurol, 2014, 71(3): 291-299.
35. Lázaro-Muñoz G, Yoshor D, Beauchamp M S, et al. Continued access to investigational brain implants. Nat Rev Neurosci, 2018, 19(6): 317-318.
36. Hendriks S, Grady C, Ramos K M, et al. Ethical challenges of risk, informed consent, and posttrial responsibilities in human research with neural devices: a review. JAMA Neurol, 2019, 76(12): 1506-1514.
37. Rossi P J, Giordano J, Okun M S. The problem of funding off-label deep brain stimulation: bait-and-switch tactics and the need for policy reform. JAMA Neurol, 2017, 74(1): 9-10.
38. Thenaisie Y, Palmisano C, Canessa A, et al. Towards adaptive deep brain stimulation: clinical and technical notes on a novel commercial device for chronic brain sensing. J Neural Eng, 2021, 18(4): 042002.
39. 王高峰, 张志领. 算法伦理视域下的脑机接口伦理问题研究. 自然辩证法研究, 2022, 38(7): 68-73.
40. Luo Shiyu, Qinwan R, Crone N E. Brain-computer interface: Applications to speech decoding and synthesis to augment communication. Neurotherapeutics, 2022, 19(1): 263-273.
41. 董煜阳, 龚安民, 丁鹏, 等. 一种新型结合下肢动觉运动想象和视觉运动想象的脑机接口. 南京大学学报(自然科学), 2022, 58(3): 460-468.
42. Pandarinath C, Bensmaia S J. The science and engineering behind sensitized brain-controlled bionic hands. Physiol Rev, 2021, 102(2): 551-604.
43. Khan M A, Das R, Hansen J P, et al. Brain and behaviour computing. Boca Raton: CRC Press, 2021.
44. 艾丽森 B Z, 邓恩 S, 莱布 R., 等. 面向实用的脑-机接口: 缩小研究与实际应用之间的差距. 伏云发, 龚安民, 陈超, 等译. 北京: 电子工业出版社, 2022: 45-47.
45. Vaughan T M. Brain-computer interfaces for people with amyotrophic lateral sclerosis. Handb Clin Neurol, 2020, 168: 33-38.
46. Metzger S L, Littlejohn K T, Silva A B, et al. A high-performance neuroprosthesis for speech decoding and avatar control. Nature, 2023, 620(7976): 1037-1046.
47. Vansteensel M J, Jarosiewicz B. Brain-computer interfaces for communication. Handb Clin Neurol, 2020, 168: 67-85.
48. Mitchell K T, Starr P A. Smart neuromodulation in movement disorders. Handb Clin Neurol, 2020, 168: 153-161.
49. Nakayama Y, Shimizu T, Mochizuki Y, et al. Predictors of impaired communication in amyotrophic lateral sclerosis patients with tracheostomy-invasive ventilation. Amyotroph Lateral Scler Frontotemporal Degener, 2015, 17(1-2): 38-46.

Journal of Biomedical Engineering

Ethical considerations for medical applications of implantable brain-computer interfaces

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