Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer
Abstract Heart Rate Variability (HRV) serves as a vital marker of stress levels, with lower HRV indicating higher stress. It measures the variation in the time between heartbeats and offers insights into health. Artificial intelligence (AI) research aims to use HRV data for accurate stress level cla...
Saved in:
| Main Authors: | Ayan Chatterjee, Michael A. Riegler, K. Ganesh, Pål Halvorsen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-87510-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predicting Olive Tree Chlorophyll Fluorescence Using Explainable AI with Sentinel-2 Imagery in Mediterranean Environment
by: Leonardo Costanza, et al.
Published: (2025-03-01) -
Optimal frequency bands for pupillography for maximal correlation with HRV
by: Júlio Medeiros, et al.
Published: (2025-01-01) -
Artificial Intelligence (AI) in Neurofeedback Therapy Using Electroencephalography (EEG), Heart Rate Variability (HRV), and Galvanic Skin Response (GSR): A Review
by: Teddy Marcus Zakaria, et al.
Published: (2025-01-01) -
Physiological impact of the facial mask at rest (2): Modification of Cardiac Variability (HRV) in young athletes
by: Ignasi de Yzaguirre Maura, et al.
Published: (2025-04-01) -
FloodGenome: interpretable machine learning for decoding features shaping property flood risk predisposition in cities
by: Chenyue Liu, et al.
Published: (2025-01-01)