Vision wearables with artificial intelligence to close the sensory gap in patient characterization
Artificial intelligence (AI) for precision medicine remains constrained by sparse, subjective data. Clinician-worn, egocentric audio-visual sensing with multimodal AI is poised to capture movement, affect, and context. We propose a translational framework from continuous capture to feature extraction, digital biomarkers, and eventual real-time alerts that supports the generation of objective clinical outcome types. We further outline clinical usability, validation, and ethical challenges around the deployment of vision wearables.
Authors
- Matteo Danieletto (ORCID: https://orcid.org/0000-0002-5178-9182)
- Ariel Dora Stern (ORCID: https://orcid.org/0000-0002-3586-1041)
- Benjamin Scott Glicksberg (ORCID: https://orcid.org/0000-0003-4515-8090)
- Eyal Klang (ORCID: https://orcid.org/0000-0002-4567-3108)
- Joel T. Dudley (ORCID: https://orcid.org/0000-0002-7036-6492)
- Girish N. Nadkarni (ORCID: https://orcid.org/0000-0001-6319-4314)
- Bert Arnrich (ORCID: https://orcid.org/0000-0001-8380-7667)
- Felix Richter (ORCID: https://orcid.org/0000-0003-3429-9621)
- Beau Norgeot (ORCID: https://orcid.org/0000-0003-2629-701X)
- Ankit Sakhuja (ORCID: https://orcid.org/0000-0002-2045-518X)
- Morgan Cheatham (ORCID: https://orcid.org/0000-0002-4688-058X)
- Marinka Žitnik (ORCID: https://orcid.org/0000-0001-8530-7228)
- Alexander W. Charney (ORCID: https://orcid.org/0000-0001-8135-6858)
- Julia Maslinski
- Joshua Lampert
- Anthony Costa
- Kenneth Nelson
- Amee Kapadia
Institutions
- Broad Institute (US)
- Boston Children's Hospital (US)
- Beth Israel Deaconess Medical Center (US)
- Children's Hospital of Philadelphia (US)
- Harvard University (US)
- Hasso Plattner Institute (DE)
- University of Potsdam (DE)
- Comagine Health (US)
- Child Health and Development Institute (US)
- Nvidia (United States) (US)
- University of Greenwich (GB)
- Icahn School of Medicine at Mount Sinai (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-09-30
- DOI
- https://doi.org/10.1038/s41746-026-03156-6
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00