AIMC Topic: Heart Rate

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Advancing training effectiveness prediction in mass sport through longitudinal data: A mathematical model approach based on the Fitness-Fatigue Model.

PloS one
Despite the critical need for scientific training load assessment in mass sports, the Fitness-Fatigue Model (FFM) requires further mathematical optimization and practical output indicators. The aim of this study was to optimize the mathematical relat...

Reducing Artifact Preprocessing in Heart Rate Variability-Based Personalized Psychosis Prediction Using Adaptive Long Short-Term Memory Models.

International journal of neural systems
This research looks at the use of long-short-term memory (LSTM) networks to predict psychosis, in patients within the schizophrenia spectrum, based on Heart Rate Variability (HRV) data acquired from wearable devices. Our primary objective is to test ...

Deep Learning-Based Continuous QT Monitoring to Identify High-Risk Prolongation Events After Class III Antiarrhythmic Initiation.

Circulation
BACKGROUND: Drug-induced QT prolongation after successful inpatient loading of class III antiarrhythmics may occur during routine outpatient care. Insertable cardiac monitors offer continuous signals but are limited by single-lead configuration. We h...

AI-based approach for heart failure readmission prediction using SCG, ECG, and GSR signals.

Physiological measurement
Heart failure (HF) is considered a global pandemic because of increasing prevalence, high mortality rate, frequent hospitalization, and associated economic burden. This study explores a noninvasive method that may help in managing HF patients by pred...

Artificial intelligence capabilities in identifying atrial fibrillation using baseline sinus rhythm ECG : a systematic review.

Open heart
BACKGROUND: Atrial fibrillation (AF) is a prevalent arrhythmia associated with adverse outcomes, often presenting paroxysmally. The lack of an efficient method to promptly detect paroxysmal AF and the absence of a unified screening approach necessita...

Inequity aversion toward AI counterparts.

Scientific reports
Human moral interactions often assume that resources should be allocated equitably, i.e., one should not take more than one's fair share. To what extent do people apply this assumption to social AI entities? Using a 21-round Ultimatum Game, we invest...

Deep learning-driven contactless ECG in MRI via beat pilot tone for motion-resolved image reconstruction and heart rate monitoring.

Physics in medicine and biology
Electrocardiogram (ECG) is crucial for synchronizing cardiovascular magnetic resonance imaging (CMRI) acquisition with the cardiac cycle and for continuous heart rate monitoring during prolonged scans. However, conventional electrode-based ECG system...

Improved non-invasive detection of sleep stages when combining skin sympathetic nerve activity and heart rate variability analysis with AI.

Scientific reports
Sleep is a cyclic physiological process that goes into different stages, and every stage has its' importance in the construction or recovery of physiological function. Sleep scoring is performed from polysomnography recordings which requires signals ...

Interpretable deep learning for personalized energy expenditure prediction using ECG and acceleration signals in incremental exercise.

Scientific reports
Energy expenditure (EE) assessment is crucial in both sports science and health management. However, current EE prediction models often overlook individual differences and lack dynamic correlation analysis between multi-modal data and EE. Building up...

ECG beat classification with fractional order differentiator and machine learning techniques.

Biomedical physics & engineering express
Electrocardiogram (ECG) is essential for assessing heart function, but manual analysis is time-consuming and error-prone. Automated ECG analysis can improve early detection of cardiovascular diseases by accurately identifying abnormal beats despite s...