Related Experiment Video
Updated: Oct 21, 2025
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
Published on: May 8, 2021
A Proposal for a Data-Driven Approach to the Influence of Music on Heart Dynamics
Ennio Idrobo-Ávila1, Humberto Loaiza-Correa1, Flavio Muñoz-Bolaños2
1Escuela de Ingeniería Eléctrica y Electrónica, PSI - Percepción y Sistemas Inteligentes, Universidad del Valle, Cali, Colombia.
Insights
This study introduces a framework to analyze how sound impacts electrocardiographic (ECG) and heart rate variability (HRV) signals using artificial intelligence. It aims to standardize research methods for better understanding music
Area of Science:
- Physiology and Music Perception
- Biomedical Signal Processing
- Artificial Intelligence in Healthcare
Background:
- Electrocardiographic (ECG) and heart rate variability (HRV) signals offer insights into physiological and psychological states.
- HRV is a recognized marker for various health conditions and responses to external stimuli like music.
- Current research on ECG/HRV and sound lacks standardized methodologies, hindering comparative analysis.
Purpose of the Study:
- To establish a methodological framework for investigating the effects of sound on ECG and HRV signals.
- To associate musical structures and noise with physiological signals using artificial intelligence (AI).
- To provide guidance on subject selection, sound stimulus design, experimental planning, and data analysis.
Main Methods:
- Development of a methodological framework for sound-stimulus experiments.
- Integration of AI for analyzing the relationship between sound and ECG/HRV data.
- Guidance on subject selection, sound stimulus generation, and experimental design.
- Proposal of a data analysis framework using conventional and AI-driven tools.
Main Results:
- The study proposes a comprehensive framework for sound-ECG/HRV research.
- AI is identified as a key tool for analyzing large, diverse datasets and enabling generalization.
- The framework aims to improve the consistency and comparability of future studies.
Conclusions:
- A standardized methodological framework is crucial for advancing research on the physiological effects of sound.
- AI offers powerful capabilities for analyzing complex physiological signals and their relationship to auditory stimuli.
- This work facilitates a deeper understanding of how music and sound influence cardiovascular activity.
Abstract:
Electrocardiographic signals (ECG) and heart rate viability measurements (HRV) provide information in a range of specialist fields, extending to musical perception. The ECG signal records heart electrical activity, while HRV reflects the state or condition of the autonomic nervous system. HRV has been studied as a marker of diverse psychological and physical diseases including coronary heart disease, myocardial infarction, and stroke. HRV has also been used to observe the effects of medicines, the impact of exercise and the analysis of emotional responses and evaluation of effects of various quantifiable elements of sound and music on the human body. Variations in blood pressure, levels of stress or anxiety, subjective sensations and even changes in emotions constitute multiple aspects that may well-react or respond to musical stimuli. Although both ECG and HRV continue to feature extensively in research in health and perception, methodologies vary substantially. This makes it difficult to compare studies, with researchers making recommendations to improve experiment planning and the analysis and reporting of data. The present work provides a methodological framework to examine the effect of sound on ECG and HRV with the aim of associating musical structures and noise to the signals by means of artificial intelligence (AI); it first presents a way to select experimental study subjects in light of the research aims and then offers possibilities for selecting and producing suitable sound stimuli; once sounds have been selected, a guide is proposed for optimal experimental design. Finally, a framework is introduced for analysis of data and signals, based on both conventional as well as data-driven AI tools. AI is able to study big data at a single stroke, can be applied to different types of data, and is capable of generalisation and so is considered the main tool in the analysis.
More Related Videos
07:25Driving Under the Influence: How Music Listening Affects Driving Behaviors
Published on: March 27, 2019
10:50Behavioral Determination of Stimulus Pair Discrimination of Auditory Acoustic and Electrical Stimuli Using a Classical Conditioning and Heart-rate Approach
Published on: June 6, 2012
Related Concept Videos
01:30Factors Influencing Heart Rate
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
01:31Regulation of Heart Rates
The SNS increases heart rate through the release of norepinephrine and epinephrine, which act on beta-1 adrenergic receptors in the heart. This action increases the rate of depolarization in the sinoatrial (SA) node, the heart's...
01:29Pathophysiology of Cardiac Performance
01:19Cardiac Output I:Effect of Heart Rate on Cardiac Output
Cardiac output (CO) refers to the total amount of blood ejected by one of the ventricles in liters per minute (L/min). In a resting adult, CO ranges from 5 to 6 L/min, adjusting according to the body's metabolic requirements.
Effect of Heart Rate on Cardiac Output
Cardiac output adapts to metabolic demands during stress, physical activity, or illness. The autonomic nervous system regulates heart rate via the sinoatrial node. The parasympathetic nervous system decreases heart...
01:30Equipments Used To Measure Blood Pressure
This invasive approach involves cannulating a peripheral artery. During each cardiac contraction, pressure generates mechanical motion within the catheter, transmitted through rigid, fluid-filled tubing to a transducer. This transducer converts mechanical motion into electrical signals displayed as waveforms on a monitor. An automatic flushing system prevents blood backflow. Due to the potential risk of unexpected arterial blood loss, this method is primarily used in intensive...
01:25Correlation between ECG and Cardiac Cycle
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...