Ethical implications of brain-computer interfaces with emotion, motor imagery, and subvocal speech classification

被引:1
作者
O'Neill, Joseph [1 ]
Johnson, Jenario
Detyens, Rutledge [2 ]
Batista, Roberto W.
Oprisan, Sorinel [3 ]
Chatterjee, Prosenjit [4 ]
Integlia, Ryan [2 ]
机构
[1] Coll Charleston, Dept Comp Sci, Charleston, SC 29401 USA
[2] The Citadel, Dept Elect & Comp Engn, Charleston, SC 29409 USA
[3] Coll Charleston, Dept Phys, Charleston, SC 29401 USA
[4] The Citadel, Dept Cyber & Comp Sci, Charleston, SC 29409 USA
来源
2021 IEEE INTERNATIONAL SYMPOSIUM ON TECHNOLOGY AND SOCIETY (ISTAS21): TECHNOLOGICAL STEWARDSHIP & RESPONSIBLE INNOVATION | 2021年
关键词
Brain-Computer Interfaces; electroencephalogram; emerging technology; ethics; Event-related potentials;
D O I
10.1109/ISTAS52410.2021.9629168
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Research for Brain-Computer Interfaces (BCIs) has rapidly developed in recent years. Significant advances in this field include brain-controlled bionic limbs and wheelchairs. With these devices, there is a potential benefit for patients with neurologic and neuromuscular diseases, such as Amyotrophic Lateral Sclerosis (ALS). ALS involves the degeneration of motor neurons rapidly over time, leading to paralysis and loss of speech. BCIs have the potential to allow ALS patients to continue to communicate and move with the help of subvocal speech classification and motor imagery control applications. Despite the promise of these devices to improve the quality of life, we must evaluate the ethical implications that will arise due to the advancement of these devices. More advanced and accurate devices that can restore speech could also easily be used to read or listen in on the thoughts of its users, thereby presenting a unique question of ethics. In this paper, we will discuss the current progress, trends, and future ethical implications of current advancements in BCIs. We will also introduce a conceptual BCI-based device with emotion classification, subvocal speech classification, and motor imagery applications.
引用
收藏
页数:5
相关论文
共 20 条
  • [1] Big healthcare data: preserving security and privacy
    Abouelmehdi, Karim
    Beni-Hessane, Abderrahim
    Khaloufi, Hayat
    [J]. JOURNAL OF BIG DATA, 2018, 5 (01)
  • [2] eHealth Cloud Security Challenges: A Survey
    Al-Issa, Yazan
    Ottom, Mohammad Ashraf
    Tamrawi, Ahmed
    [J]. JOURNAL OF HEALTHCARE ENGINEERING, 2019, 2019
  • [3] Alakus T. B., 2019, 2019 4 INT C COMP SC
  • [4] Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces
    Cecotti, Hubert
    Graeser, Axel
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2011, 33 (03) : 433 - 445
  • [5] Single-trial classification of vowel speech imagery using common spatial patterns
    DaSalla, Charles S.
    Kambara, Hiroyuki
    Sato, Makoto
    Koike, Yasuharu
    [J]. NEURAL NETWORKS, 2009, 22 (09) : 1334 - 1339
  • [6] Eidel M., 2021, 2021 9 INT WINT C BR, P1
  • [7] Deep Learning in EEG: Advance of the Last Ten-Year Critical Period
    Gong, Shu
    Xing, Kaibo
    Cichocki, Andrzej
    Li, Junhua
    [J]. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2022, 14 (02) : 348 - 365
  • [8] Grieves M., 2015, White Paper
  • [9] DEAP: A Database for Emotion Analysis Using Physiological Signals
    Koelstra, Sander
    Muhl, Christian
    Soleymani, Mohammad
    Lee, Jong-Seok
    Yazdani, Ashkan
    Ebrahimi, Touradj
    Pun, Thierry
    Nijholt, Anton
    Patras, Ioannis
    [J]. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2012, 3 (01) : 18 - 31
  • [10] EEG-Based Brain-Computer Interfaces for Communication and Rehabilitation of People with Motor Impairment: A Novel Approach of the 21st Century
    Lazarou, Ioulietta
    Nikolopoulos, Spiros
    Petrantonakis, Panagiotis C.
    Kompatsiaris, Ioannis
    Tsolaki, Magda
    [J]. FRONTIERS IN HUMAN NEUROSCIENCE, 2018, 12