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Related Concept Videos

Physiological Foundation of Stress01:24

Physiological Foundation of Stress

247
Stress triggers a coordinated physiological response involving the sympathetic nervous system (SNS) and the hypothalamic-pituitary-adrenal (HPA) axis. This dual activation ensures that the body is prepared for both immediate and prolonged stress management. The process begins with the perception of a stressor. This initial phase activates the SNS, leading to the rapid release of adrenaline (epinephrine) from the adrenal glands.
Role of the Sympathetic Nervous System
Adrenaline triggers the...
247
Exercise Stress Test01:26

Exercise Stress Test

650
Introduction
Exercise stress testing, commonly known as a treadmill test, is a noninvasive procedure used to evaluate cardiovascular function and diagnose heart conditions.
Definition
An exercise stress test measures the heart's response to exertion using a treadmill or stationary bicycle. Chest electrodes record the heart's electrical activity through an ECG, and blood pressure is monitored regularly.
Purposes
650
Stress Response System01:21

Stress Response System

434
The stress response system, also known as the fight-or-flight response, is the body's automatic physiological reaction to perceived threats. Hans Selye introduced the concept of General Adaptation Syndrome (GAS) to describe the predictable pattern of changes that occur in response to stress. GAS consists of three sequential stages: alarm, resistance, and exhaustion. This model helps explain how chronic stress can contribute to health problems.
Alarm stage
In the alarm stage, the body's...
434
Introduction to Stress and Lifestyle01:27

Introduction to Stress and Lifestyle

319
Stress is a multifaceted response to events perceived as challenging or threatening, highlighting physical, emotional, cognitive, and behavioral reactions. Physically, stress can lead to fatigue, sleep disruptions, and various health issues such as frequent colds, chest pains, and nausea. Emotionally, it can manifest as anxiety, depression, irritability, and anger triggered by both minor and major life events. Cognitively, it may result in difficulty in concentration, memory, and...
319
Psychological Responses to Stress01:20

Psychological Responses to Stress

298
Psychological responses to stress encompass the various cognitive and emotional reactions individuals experience when faced with challenging or threatening situations, such as a job loss. Prolonged exposure to stressors can disturb emotional balance, increasing negative emotions (e.g., anxiety and sadness) and diminishing positive emotions (e.g., joy and satisfaction). These persistent emotional shifts are associated with an increased risk of both physical illness and mental health issues, such...
298
Components of Stress01:23

Components of Stress

342
Stress analysis under multiple loading conditions is intricate, necessitating a comprehensive grasp of normal and shearing stresses. Consider a small cube at point O, subjected to stress on all six faces, visible or not. Normal stress components σx, σy, σz act perpendicularly to the x, y, and z axes. Shearing stress components τxy and τxz are exerted on faces perpendicular to these axes.
Interestingly, the hidden cube faces also experience these stresses, equal and...
342

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Related Experiment Video

Updated: Nov 7, 2025

A Community-based Stress Management Program: Using Wearable Devices to Assess Whole Body Physiological Responses in Non-laboratory Settings
10:45

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HRV Features as Viable Physiological Markers for Stress Detection Using Wearable Devices.

Kayisan M Dalmeida1, Giovanni L Masala1

  • 1Department of Computing and Mathematics, Manchester Metropolitan University, Manchester M15 6BH, UK.

Sensors (Basel, Switzerland)
|April 30, 2021
PubMed
Summary

This study shows heart rate variability (HRV) features are effective stress markers. Machine learning models accurately detected stress from HRV data, paving the way for non-invasive stress monitoring in various applications.

Keywords:
electrocardiogramheart rate variabilitymachine learningsmart watchstresswearable device

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Area of Science:

  • Physiological monitoring
  • Machine learning applications
  • Automotive safety

Background:

  • Stress is a significant factor in automobile accidents, leading to injuries and fatalities.
  • Physiological measurements, particularly heart rate variability (HRV), offer a quantifiable method for stress assessment.
  • Wearable devices provide accessible platforms for continuous physiological data collection.

Purpose of the Study:

  • To investigate the efficacy of HRV-derived features as reliable stress markers.
  • To develop and compare machine learning models for accurate stress level classification.
  • To explore the potential of using wearable device data for non-invasive stress detection.

Main Methods:

  • Extracted HRV features from ECG data of automobile drivers.
  • Developed and evaluated machine learning models including KNN, SVM, MLP, RF, and GB.
  • Validated models for stress classification accuracy.
  • Focused on key HRV metrics like AVNN, SDNN, and RMSSD.

Main Results:

  • HRV features demonstrated strong potential as stress indicators.
  • The best-performing machine learning model achieved an 80% recall rate in stress detection.
  • Specific HRV metrics (AVNN, SDNN, RMSSD) were identified as crucial for stress detection.

Conclusions:

  • HRV analysis, combined with machine learning, offers a viable method for non-invasive stress detection.
  • The developed models can be adapted for stress monitoring in diverse applications.
  • This approach supports applications in physical rehabilitation, anxiety management, and mental wellbeing.