arXiv Machine Learning

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection

arXiv:2606. 24985v1 Announce Type: new Abstract: Personalization in wearable-based stress detection remains challenging due to substantial inter-individual variability in physiological and behavioral responses.

arXiv AI

Jun 2

Towards a General Intelligence and Interface for Wearable Health Data

arXiv:2605. 22759v2 Announce Type: replace Abstract: While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challenging.

By Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari, Samy Abdel-Ghaffar, Marius Guerard, Kara Vaillancourt, Zhihan Zhang, Jake Garrison, Levi Albuquerque, Dimitris Spathis, Hong Yu, Hamid Palangi, Xuhai "Orson" Xu, David G. T. Barrett, Joseph Breda, Jed McGiffin, Yubin Kim, Yuwei Zhang, Naghmeh Rezaei, Samuel Solomon, Karan Ahuja, Tim Althoff, Jake Sunshine, Ming-Zher Poh, Benjamin Yetton, Ari Winbush, Nicholas B. Allen, James M. Rehg, Isaac Galatzer-Levy, Yun Liu, John Hernandez, Anupam Pathak, Conor Heneghan, Yuzhe Yang, Ahmed A. Metwally, Pushmeet Kohli, Mark Malhotra, Shwetak Patel, Xin Liu, Daniel McDuff

llms rag agents

arXiv AI

Aug 5

From Wearable Data to Personalized and Actionable Health Insights

arXiv:2608. 03251v1 Announce Type: cross Abstract: Commercial wearable devices continuously capture rich physiological data (e.

By Esther Brown, Karis Moon, Victoria Dean, Finale Doshi-Velez

arXiv AI

Aug 7

Is Self-Pretraining really useful to improve diagnosis in medical Time Series?

arXiv:2608. 06122v1 Announce Type: cross Abstract: Inspired by recent evidence that transformer architectures benefit from Self-PreTraining (SPT) on long-context benchmarks, we investigate whether similar gains extend to multimodal, multivariate, and even simple univariate medical time series.

By Omar Coser, Antonio Orvieto, Paolo Soda, Loredana Zollo

llms robotics multimodal benchmarks

arXiv Machine Learning

Jul 20

LLM4EHR: Aligning Clinical Time Series with Medical Event Sequences via Large Language Models

arXiv:2607. 15447v1 Announce Type: new Abstract: Recent research in clinical machine learning, focusing on outcome predictions in intensive care unit (ICU), has shifted from bespoke supervised models to foundation models, utilising modern representation learning methods.

By Jingteng Li, Alexander Capstick, Louise Rigny, Iona Biggart, Neil J Sebire, Payam Barnaghi

llms rag benchmarks

arXiv AI

Jul 21

Joint-Embedding Predictive Architecture for Sensor-based Activity Recognition

arXiv:2607. 16350v1 Announce Type: cross Abstract: Sensor-based human activity recognition (HAR) has achieved significant progressed in fully supervised learning settings.

By Mohd Halim Mohd Noor, Abdulrahman M. A. Baraka

rag benchmarks

arXiv AI

5d ago

DomusFM: A Foundation Model for Event-Based Behavioral Monitoring in Smart-Homes

arXiv:2602. 01910v2 Announce Type: replace Abstract: Smart-home sensor-based behavioral monitoring holds significant potential for healthcare, independent living, and early detection of functional or cognitive changes.

By Michele Fiori, Gabriele Civitarese, Flora D. Salim, Claudio Bettini

llms rag

arXiv AI

1d ago

Take it Personally: The Limits of General SSL Representations for Real-Life PPG Emotion Detection

arXiv:2608. 14675v1 Announce Type: cross Abstract: While Self-Supervised Learning (SSL) effectively extracts general representations from noisy, unconstrained physiological signals such as photoplethysmography (PPG), its suitability for highly subjective tasks remains unproven.

By Dominika Kunc, Przemys{\l}aw Kazienko, Stanis{\l}aw Saganowski

reinforcement-learning fine-tuning

Hugging Face Trending Papers

Aug 4

From Wearable Data to Personalized and Actionable Health Insights

Commercial wearable devices continuously capture rich physiological data (e. g.

arXiv Machine Learning

Jul 30

RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deployment

arXiv:2607. 26631v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports applications in healthcare, rehabilitation, fitness tracking, and smart environments.

By Hansi Karunarathna, Nirhoshan Sivaroopan, Chamara Madarasingha, Anura Jayasumana, Kanchana Thilakarathna

llms rag agents efficiency benchmarks

arXiv Machine Learning

5d ago

The Impact of Temporal Context Length and Encoding Strategies on Self-Supervised ECG Representation Learning

arXiv:2608. 12695v1 Announce Type: new Abstract: Self-supervised electrocardiogram (ECG) models are often trained on a few seconds of ECG signal and, increasingly, on discretized token sequences.

By Ahmed Sameh, Ramzi Al-Sharawi, Yogatheesan Varatharajah

llms rag efficiency

arXiv AI

Jun 15

A Comparative Study of Deep Learning Architectures for Multi-Horizon Behavioural Forecasting for Mobile Health

arXiv:2606. 14604v1 Announce Type: cross Abstract: Wearable devices and smartphones generate rich behavioural time series that can support proactive health interventions, yet systematic comparisons of modern forecasting architectures for these data are lacking.

By Pavlos Nicolaou, Kleanthis Malialis, Artemis Kontou, Panayiotis Kolios

llms fine-tuning benchmarks

arXiv Machine Learning

Jul 31

HealthCAT: An Interpretable Encoder-only Transformer Framework for Health Indicator Prediction and Temporal Interpretation of Wearable Sensor Data

arXiv:2607. 27635v1 Announce Type: cross Abstract: Wearable sensors continuously capture fine-grained multivariate time-series data, providing opportunities to model behavioural patterns associated with health outcomes.

By Xiaotong Yu, Joshua Y. Kim, HaeJin Lee, Kalina Yacef

llms safety

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