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OpenMHC dataset and models accelerate open science in wearable health AI

Researchers have introduced OpenMHC, a large-scale, open-access dataset for wearable health data, aiming to accelerate AI research in this domain. The dataset comprises over 60 million hours of sensor data from 11,894 participants, linked with health, lifestyle, and behavioral information. Alongside the data, the project releases open-source implementations of recent wearable foundation models and a standardized benchmark for evaluating these models across various health-related tasks. AI

IMPACT Democratizes wearable health AI research by providing a large open dataset and models, potentially accelerating new discoveries and applications.

RANK_REASON The cluster describes a new research paper releasing a dataset and models for AI research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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OpenMHC dataset and models accelerate open science in wearable health AI

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Narayan Schuetz, Yuze Bai, Lianggang Pan, Edgar Eggert, Favour Nerrise, Juan Delgado-SanMartin, Max Rosenblattl, Milana Gurbanova, Mohammad Asadi, Anders Johnson, Paul Schmiedmayer, Dennis Wang, Allan Lawrie, Daniel Seung Kim, Xin Liu, Akshay Paruchuri, … ·

    OpenMHC: Accelerating the Science of Wearable Foundation Models

    arXiv:2607.16235v1 Announce Type: cross Abstract: Mobile and wearable devices offer an unprecedented opportunity for continuous, passive health monitoring and active health coaching. However, the largest wearable datasets are not publicly available for research, and leading weara…