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This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3540) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1994) Infodemiology and Infoveillance (1613) Natural Language Processing (981) Brain-Machine Interfaces (24)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60859, first published .
Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study

Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study

Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study

Authors of this article:

Mohammed A Almanna1, 2 Author Orcid Image ;   Lior M Elkaim3 Author Orcid Image ;   Mohammed A Alvi4, 5, 6 Author Orcid Image ;   Jordan J Levett7 Author Orcid Image ;   Ben Li8, 9, 10, 11 Author Orcid Image ;   Muhammad Mamdani10, 11, 12, 13, 14, 15, 16 Author Orcid Image ;   Mohammed Al‑Omran8, 9, 10, 11, 15, 17, 18 Author Orcid Image ;   Naif M Alotaibi17, 19 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Frascaria G, Jaramillo-Dent D, Latzer M. Adoption of Human Augmentation Technologies for Non-Medical Applications: A Systematic Review of Empirical Literature. International Journal of Human–Computer Interaction 2026:1 View
  2. Jha N, Liu C, Rogers A, Lozano A. Payers, Proof, and Public Trust: Lessons from Deep Brain Stimulation for Scaling Brain Computer Interfaces. Mayo Clinic Proceedings: Digital Health 2026:100366 View

Conference Proceedings

  1. Frascaria G, Festic N, Latzer M. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. Evolving User Profiles and Adoption of Cyborg Technologies: Evidence from a Repeated Cross-Sectional Study in Switzerland View