ArticleAdvances in experimental medicine and biology2026
Heart Rate Variability in the Detection of Cognitive Fatigue Through Transfer Learning.
Article in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Cognitive decline is a critical area of research due to its profound impact on neural integrity, cognitive function, and its association with neurodegenerative diseases. Early identification of cognitive impairment is essential, as it often signals underlying neurological dysfunction, which, if left unaddressed, can lead to progressive mental deterioration. Moreover, cognitive decline extends beyond individual health, influencing high-demand environments where sustained cognitive performance is crucial for safety and decision-making. Heart rate variability (HRV), derived noninvasively from photoplethysmography (PPG), offers a real-time method for detecting autonomic dysregulation linked to cognitive fatigue. Continuous PPG monitoring under conditions of sleep deprivation, combined with machine learning algorithms such as Long Short-Term Memory (LSTM) networks, enabled accurate prediction of cognitive states based on HRV patterns through their ability to capture temporal dependencies. The findings reveal significant autonomic disturbances corresponding to mental fatigue, underscoring HRV's potential as a sensitive biomarker for cognitive decline and its applicability in transfer learning frameworks.
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