SePA: A Search-enhanced Predictive Agent for Personalized Health Coaching

• URL: http://arxiv.org/abs/2509.04752v1
• Date: Fri, 05 Sep 2025 02:07:36 GMT
• Title: SePA: A Search-enhanced Predictive Agent for Personalized Health Coaching
• Abstract summary: SePA is a novel LLM health coaching system that integrates personalized machine learning and retrieval-augmented generation.<n>In a pilot study, SePA's retrieval-based advice was preferred over a non-retrieval baseline.
• Score: 1.0742675209112622
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper introduces SePA (Search-enhanced Predictive AI Agent), a novel LLM health coaching system that integrates personalized machine learning and retrieval-augmented generation to deliver adaptive, evidence-based guidance. SePA combines: (1) Individualized models predicting daily stress, soreness, and injury risk from wearable sensor data (28 users, 1260 data points); and (2) A retrieval module that grounds LLM-generated feedback in expert-vetted web content to ensure contextual relevance and reliability. Our predictive models, evaluated with rolling-origin cross-validation and group k-fold cross-validation show that personalized models outperform generalized baselines. In a pilot expert study (n=4), SePA's retrieval-based advice was preferred over a non-retrieval baseline, yielding meaningful practical effect (Cliff's $\delta$=0.3, p=0.05). We also quantify latency performance trade-offs between response quality and speed, offering a transparent blueprint for next-generation, trustworthy personal health informatics systems.

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