Towards lightweight stress monitoring on biometric data for IoMT environments

The results show that accurate and personalized stress detection is feasible using reduced feature sets, enabling efficient, interpretable, and real-time deployment of ML models in wearable and IoMT-based monitoring systems.

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Publication Details

Journal
Computer Methods and Programs in Biomedicine
Published
2026-02-16
DOI
https://doi.org/10.1016/j.cmpb.2026.109287
Primary Topic
Emotion and Mood Recognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Towards lightweight stress monitoring on biometric data for IoMT environments

Jose L. López, Juan Francisco Gaitán Guerrero, Carlos Montoya Peña
Computer Methods and Programs in Biomedicine
Emotion and Mood Recognition
article

Towards lightweight stress monitoring on biometric data for IoMT environments

Jose L. López, Juan Francisco Gaitán Guerrero, Carlos Montoya Peña
article en

Abstract

The results show that accurate and personalized stress detection is feasible using reduced feature sets, enabling efficient, interpretable, and real-time deployment of ML models in wearable and IoMT-based monitoring systems.

Computer Methods and Programs in BiomedicineVol. 279
Universidad de Jaén (ES), Universidad Don Bosco (SV)
Openalex Percentile: Top 56%
Emotion and Mood Recognition
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Towards lightweight stress monitoring on biometric data for IoMT environments — Jose L. López, Juan Francisco Gaitán Guerrero, et al. · Computer Methods and Programs in Biomedicine (2026) | TGRS Research Map | TGRS