Ergomotion's new Sleep Assist app tracks sleep through non-contact sensors built into the bed base itself, letting users ask its AI assistant plain-language questions about their sleep instead of parsing another wearable's data dashboard.
An NIH analysis of 11 million days of Fitbit data from nearly 30,000 All of Us participants found that a year of step data predicts far more health outcomes than a single day's readout, including unexpected links to chronic pain and autoimmune disease.
Oura introduced a proprietary AI model built specifically for women's health questions inside its Oura Advisor assistant, reporting that users sent more than a million messages to the tool during testing — with 83% rating its answers reliable.
Whoop is adding on-demand video visits with licensed clinicians alongside new AI coaching features that let its algorithm remember a user's real-life context, a move that pits it directly against rival Oura's new AI health assistant.
A radar sensor called Paul has cut resident falls by an average of 66% across 11 Arizona senior communities, but even its Swiss inventor admits he can't fully rule out that better-watched staff, not the AI itself, deserve some of the credit.
University of Houston researchers had older adults sculpt their ideal AI companion robot out of clay, surfacing a finding that could reshape the industry: seniors want practical help, not surveillance dressed up as companionship.
Slingshot AI pulled its heavily funded therapy chatbot Ash out of the United Kingdom over unresolved medical device regulations, a retreat that exposes how unsettled the rules remain for AI mental health tools worldwide.
Dartmouth psychiatrist Michael Heinz built Therabot, the first generative AI mental health chatbot with published clinical trial results — but a rival psychologist warns that no algorithm can replicate the empathy real therapy requires.
Nonprofit Every Cure uses AI to score thousands of existing drugs against tens of thousands of diseases, cutting a 100-day repurposing search to 17 hours, backed by $48.3 million in ARPA-H federal funding.
A 23,132-patient study across 11 RWJBarnabas Health hospitals found an AI early warning system tied to automated rapid-response alerts cut in-hospital deaths among high-risk patients by 18%, researchers reported in NEJM AI.