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相关概念视频

Physiological Foundation of Stress01:24

Physiological Foundation of Stress

576
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...
576
Exercise Stress Test01:26

Exercise Stress Test

1.2K
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
1.2K
Applications of Stress01:04

Applications of Stress

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Consider a structure made of a boom and a rod designed to support a load. These two components are connected by a pin and stabilized by brackets and pins. The boom and the rod are detached from their supports to assess the different stresses imposed on this structure, and a free-body diagram is drawn. Then, all the forces applied, including the load acting on the structure, are identified. The reaction forces exerted on both the boom and the rod are computed using the equilibrium equations.
The...
643
Introduction to Stress and Lifestyle01:27

Introduction to Stress and Lifestyle

513
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...
513
Psychological Responses to Stress01:20

Psychological Responses to Stress

483
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...
483
Components of Stress01:23

Components of Stress

503
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...
503

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Evaluation of Commercial-Off-The-Shelf Wrist Wearables to Estimate Stress on Students
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测试结果的预测建模使用压力意识学习从可穿戴生物信号.

Sham Lalwani1, Saideh Ferdowsi1

  • 1School of Mathematics, Statistics and Actuarial Science, University of Essex, Colchester CO4 3SQ, UK.

Sensors (Basel, Switzerland)
|September 27, 2025
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概括
此摘要是机器生成的。

穿戴式传感器和机器学习可以通过分析与压力相关的生理信号来预测学业绩. 这项技术提供了实时监控的潜力,以支持学生的福祉和成功.

关键词:
学术表现预测学术表现预测机器学习是机器学习.生理信号 生理信号压力检测 压力检测可以穿戴的传感器.

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科学领域:

  • 教育技术的教育技术
  • 生物医学工程 生物医学工程
  • 数据科学数据科学数据科学

背景情况:

  • 学业表现受到包括压力在内的各种因素的影响.
  • 评估学业成绩和压力的传统方法缺乏实时洞察力.
  • 可穿戴技术提供了一种非侵入性的方法来收集连续的生理数据.

研究的目的:

  • 研究使用可穿戴技术和机器学习来预测学业成绩的可行性.
  • 检查生理压力指标与学业成绩之间的相关性.
  • 基于生理信号,开发学生学业成功的预测模型.

主要方法:

  • 在检查期间使用可穿戴设备收集了六个生理信号 (皮肤导电,心率,皮肤温度,皮肤活动,血液体积脉冲,心跳间隔,加速度计).
  • 开发了一个数据预处理和功能工程管道用于生理数据.
  • 训练并评估了五种机器学习模型 (随机森林,SVM,XGBoost,CatBoost,GBM) 使用SMOTE,超参数调整和维度减少等技术.

主要成果:

  • 通过可穿戴设备收集的生理信号可以有效地预测学业成绩.
  • 在测量压力水平和学业成果之间发现了显著的相关性.
  • 开发的机器学习模型展示了基于生理数据预测考试结果的能力.

结论:

  • 可穿戴技术与机器学习相结合,为预测学业成绩提供了一种可行的方法.
  • 生理压力监测可以提供对影响学生成功的因素有价值的见解.
  • 这种方法有望开发实时监控系统,以提高学生的福祉和学业成绩.