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Multi-day heart rate variability monitoring via Holter electrocardiogram for depression detection: Clinical validation and translational challenges
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DOI：10.1016/j.comppsych.2026.152719.png)
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Abstract
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• Developed a model to detect MDD using HRV & respiration from wearable ECG sensors. • Night-time data with majority voting yielded the highest AUC of 0.802 for MDD detection. • HRV features like TINN and pNN20 were significantly reduced in patients with MDD. • No correlation found between model predictions and BDI-II scores in healthy workers. • Certified device enabled reliable monitoring; future work needed for broader use.
Keywords:
MDD detection
HRV features
wearable ECG sensors
night-time data
depression monitoring
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