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Jafarzadeh Esfahani M, Sikder N, Ter Horst R, Daraie AH, Appel K, Weber FD, Bevelander KE, Dresler M. Citizen neuroscience: Wearable technology and open software to study the human brain in its natural habitat. Eur J Neurosci 2024; 59:948-965. [PMID: 38328991 DOI: 10.1111/ejn.16227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 11/09/2023] [Accepted: 11/30/2023] [Indexed: 02/09/2024]
Abstract
Citizen science allows the public to participate in various stages of scientific research, including study design, data acquisition, and data analysis. Citizen science has a long history in several fields of the natural sciences, and with recent developments in wearable technology, neuroscience has also become more accessible to citizen scientists. This development was largely driven by the influx of minimal sensing systems in the consumer market, allowing more do-it-yourself (DIY) and quantified-self (QS) investigations of the human brain. While most subfields of neuroscience require sophisticated monitoring devices and laboratories, the study of sleep characteristics can be performed at home with relevant noninvasive consumer devices. The strong influence of sleep quality on waking life and the accessibility of devices to measure sleep are two primary reasons citizen scientists have widely embraced sleep research. Their involvement has evolved from solely contributing to data collection to engaging in more collaborative or autonomous approaches, such as instigating ideas, formulating research inquiries, designing research protocols and methodology, acting upon their findings, and disseminating results. In this article, we introduce the emerging field of citizen neuroscience, illustrating examples of such projects in sleep research. We then provide overviews of the wearable technologies for tracking human neurophysiology and various open-source software used to analyse them. Finally, we discuss the opportunities and challenges in citizen neuroscience projects and suggest how to improve the study of the human brain outside the laboratory.
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Affiliation(s)
| | - Niloy Sikder
- Donders Institute for Brain, Behaviour, and Cognition, Radboudumc, Nijmegen, The Netherlands
- Faculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, Kleve, Germany
| | - Rob Ter Horst
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Amir Hossein Daraie
- Donders Institute for Brain, Behaviour, and Cognition, Radboudumc, Nijmegen, The Netherlands
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | | | - Frederik D Weber
- Donders Institute for Brain, Behaviour, and Cognition, Radboudumc, Nijmegen, The Netherlands
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Kirsten E Bevelander
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
- Primary and Community Care, Radboud University and Medical Center, Nijmegen, The Netherlands
| | - Martin Dresler
- Donders Institute for Brain, Behaviour, and Cognition, Radboudumc, Nijmegen, The Netherlands
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King BJ, Read GJM, Salmon PM. Identifying risk controls for future advanced brain-computer interfaces: A prospective risk assessment approach using work domain analysis. APPLIED ERGONOMICS 2023; 111:104028. [PMID: 37148587 DOI: 10.1016/j.apergo.2023.104028] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 05/08/2023]
Abstract
Brain-computer interface (BCI) technologies are progressing rapidly and may eventually be implemented widely within society, yet their risks have arguably not yet been comprehensively identified, nor understood. This study analysed an anticipated invasive BCI system lifecycle to identify the individual, organisational, and societal risks associated with BCIs, and controls that could be used to mitigate or eliminate these risks. A BCI system lifecycle work domain analysis model was developed and validated with 10 subject matter experts. The model was subsequently used to undertake a systems thinking-based risk assessment approach to identify risks that could emerge when functions are either undertaken sub-optimally or not undertaken at all. Eighteen broad risk themes were identified that could negatively impact the BCI system lifecycle in a variety of unique ways, while a larger number of controls for these risks were also identified. The most concerning risks included inadequate regulation of BCI technologies and inadequate training of BCI stakeholders, such as users and clinicians. In addition to specifying a practical set of risk controls to inform BCI device design, manufacture, adoption, and utilisation, the results demonstrate the complexity involved in managing BCI risks and suggests that a system-wide coordinated response is required. Future research is required to evaluate the comprehensiveness of the identified risks and the practicality of implementing the risk controls.
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Affiliation(s)
- Brandon J King
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Australia.
| | - Gemma J M Read
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Australia; School of Health, University of the Sunshine Coast, Australia. https://twitter.com/gemma_read
| | - Paul M Salmon
- Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Australia. https://twitter.com/DrPaulSalmon
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