Literature DB >> 33178903

Agency and Accountability: Ethical Considerations for Brain-Computer Interfaces.

Erika J Davidoff1.   

Abstract

Brain-computer interfaces (BCIs) are systems in which a user's real-time brain activity is used to control an external device, such as a prosthetic limb. BCIs have great potential for restoring lost motor functions in a wide range of patients. However, this futuristic technology raises several ethical questions, especially concerning the degree of agency a BCI affords its user and the extent to which a BCI user ought to be accountable for actions undertaken via the device. This paper examines these and other ethical concerns found at each of the three major parts of the BCI system: the sensor that records neural activity, the decoder that converts raw data into usable signals, and the translator that uses these signals to control the movement of an external device.

Entities:  

Keywords:  agency; brain-computer interfaces; neural implants; neuroprosthetics; responsibility

Year:  2020        PMID: 33178903      PMCID: PMC7654969     

Source DB:  PubMed          Journal:  Rutgers J Bioeth        ISSN: 2475-6431


  21 in total

1.  Single unit recording capabilities of a 100 microelectrode array.

Authors:  C T Nordhausen; E M Maynard; R A Normann
Journal:  Brain Res       Date:  1996-07-08       Impact factor: 3.252

Review 2.  A Critical Review of Microelectrode Arrays and Strategies for Improving Neural Interfaces.

Authors:  Morgan Ferguson; Dhavan Sharma; David Ross; Feng Zhao
Journal:  Adv Healthc Mater       Date:  2019-08-28       Impact factor: 9.933

Review 3.  Brain-computer interfaces for communication and rehabilitation.

Authors:  Ujwal Chaudhary; Niels Birbaumer; Ander Ramos-Murguialday
Journal:  Nat Rev Neurol       Date:  2016-08-19       Impact factor: 42.937

Review 4.  Informed consent in implantable BCI research: identification of research risks and recommendations for development of best practices.

Authors:  Eran Klein; Jeffrey Ojemann
Journal:  J Neural Eng       Date:  2016-06-01       Impact factor: 5.379

5.  The utility of multichannel local field potentials for brain-machine interfaces.

Authors:  Eun Jung Hwang; Richard A Andersen
Journal:  J Neural Eng       Date:  2013-06-07       Impact factor: 5.379

Review 6.  Sensors and decoding for intracortical brain computer interfaces.

Authors:  Mark L Homer; Arto V Nurmikko; John P Donoghue; Leigh R Hochberg
Journal:  Annu Rev Biomed Eng       Date:  2013       Impact factor: 9.590

7.  Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia.

Authors:  Sung-Phil Kim; John D Simeral; Leigh R Hochberg; John P Donoghue; Michael J Black
Journal:  J Neural Eng       Date:  2008-11-18       Impact factor: 5.379

8.  Reach and grasp by people with tetraplegia using a neurally controlled robotic arm.

Authors:  Leigh R Hochberg; Daniel Bacher; Beata Jarosiewicz; Nicolas Y Masse; John D Simeral; Joern Vogel; Sami Haddadin; Jie Liu; Sydney S Cash; Patrick van der Smagt; John P Donoghue
Journal:  Nature       Date:  2012-05-16       Impact factor: 49.962

9.  Automatic spike sorting for high-density microelectrode arrays.

Authors:  Roland Diggelmann; Michele Fiscella; Andreas Hierlemann; Felix Franke
Journal:  J Neurophysiol       Date:  2018-09-12       Impact factor: 2.714

10.  Wireless Cortical Brain-Machine Interface for Whole-Body Navigation in Primates.

Authors:  Sankaranarayani Rajangam; Po-He Tseng; Allen Yin; Gary Lehew; David Schwarz; Mikhail A Lebedev; Miguel A L Nicolelis
Journal:  Sci Rep       Date:  2016-03-03       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.