LATIDIA · Robótica

The Athlete as a Scientist of One: Agentic Bayesian Experimental Design for Individualized Physiology from Consumer Wearables

arXiv:2610.40370v1 Tipo de anuncio: nuevo Resumen: Los agentes del modelo de lenguaje grande (LLM) para la salud personal leen los datos portátiles y los recomiendan, pero no aprenden sobre el individuo de una manera que pueda ser auditada o falsificada.

La noticia

arXiv:2610.40370v1 Announce Type: new Abstract: Large language model (LLM) agents for personal health read wearable data and recommend, but do not learn about the individual in a way that can be audited or falsified. We present EpiCoach, an agentic system that treats one athlete, a cross-country mountain biker, as the subject of accountable N-of-1 science. Claims about the athlete live in an evidence-gated hypothesis registry: each must issue a probabilistic prediction about a future session before it occurs, and its belief moves only through computed evidence from a logged statistical fit. Predictions come from a mechanistic digital twin inferred from heart rate, GPS and barometric altitude: a lagged heart-rate response