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Related Concept Videos

Factors Influencing Heart Rate01:30

Factors Influencing Heart Rate

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The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
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Regulation of Heart Rates01:31

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The regulation of heart rate is a complex process controlled by the autonomic nervous system (ANS), hormonal influences, and intrinsic cardiac mechanisms. The ANS has two main components: the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS).
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Pulse rhythm01:30

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Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
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Increased pulse rate01:17

Increased pulse rate

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Tachycardia is a condition marked by an abnormally fast or irregular heart rate, surpassing the typical resting rate. In adults, tachycardia is characterized by a pulse rate ranging from 100 to 180 beats per minute. The increased heart rate can result in inadequate blood flow to various body parts, ultimately diminishing the oxygen supply to organs and tissues.
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Cardiac Output I:Effect of Heart Rate on Cardiac Output01:19

Cardiac Output I:Effect of Heart Rate on Cardiac Output

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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.
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Regulation of Pulse01:20

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Pulse regulation involves physiological mechanisms that ensure adequate blood flow throughout the body. The heartbeat, regulated by the autonomic nervous system, is influenced by hormonal balance, physical activity, and emotional state.
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Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
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Heart Rate Variability Control Using a Biofeedback and Wearable System.

Eduardo Viera1, Hector Kaschel1, Claudio Valencia1

  • 1Universidad de Santiago de Chile, Av. Víctor Jara N° 3519, Estación Central, Región Metropolitana, Santiago 9170124, Chile.

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Summary

This study introduces a novel method for modeling and controlling heart rate variability (HRV) using heart rate acceleration. The biofeedback system enables self-regulation of physiological state, synchronizing with homeostasis.

Keywords:
MRACbiofeedbackcontrol systemheart rateheart rate variabilityinstrumental variables

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Area of Science:

  • Physiological modeling
  • Biofeedback systems
  • Automated control

Background:

  • Heart rate variability (HRV) is a key medical parameter indicating well-being and pathology.
  • Biofeedback research combines biological applications, system modeling, and control theory.
  • Effective HRV control is crucial for physiological self-regulation.

Purpose of the Study:

  • To develop a new frequency-domain model for heart rate variability as heart rate acceleration.
  • To design an adaptive controller for HRV regulation using light actuators.
  • To validate the model and controller in a target population (firefighters) via an indoor cycling experiment.

Main Methods:

  • Modeling HRV using instrumental variables and cost function minimization to derive a transfer function.
  • Designing an adaptive controller based on a reference model.
  • Implementing a biofeedback system with light actuators for conditioned reflex generation.
  • Conducting experiments with indoor cycling segments (inertia, non-controlled, actively controlled).

Main Results:

  • A validated transfer function model representing HRV as heart rate acceleration.
  • Successful design and validation of an adaptive controller for HRV.
  • Demonstration of self-regulation through biofeedback synchronization with homeostasis.
  • Experimental validation in middle-aged male firefighters during indoor cycling.

Conclusions:

  • The proposed frequency-domain model accurately represents HRV dynamics.
  • The adaptive controller effectively regulates HRV via biofeedback.
  • The system facilitates self-regulation and homeostasis synchronization.
  • The approach shows promise for applications in occupational health and performance.