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Mental stress is a largely prevalent condition known to affect many people and could be a serious health concern. The quality of human life can be significantly improved if mental health is properly managed. Towards this, we propose a…

系统与控制 · 电气工程与系统科学 2022-06-23 Muhammad Majid , Aamir Arsalan , Syed Muhammad Anwar

In this paper, we present an experimental study for the classification of perceived human stress using non-invasive physiological signals. These include electroencephalography (EEG), galvanic skin response (GSR), and photoplethysmography…

信号处理 · 电气工程与系统科学 2019-05-17 Aamir Arsalan , Muhammad Majid , Syed Muhammad Anwar , Ulas Bagci

Objective: A person's affective state has known relationships to physiological processes which can be measured by wearable sensors. However, while there are general trends those relationships can be person-specific. This work proposes using…

应用统计 · 统计学 2020-02-12 Callum L. Stewart , Amos Folarin , Richard Dobson

Stress is various mental health disorders including depression and anxiety among college students. Early stress diagnosis and intervention may lower the risk of developing mental illnesses. We examined a machine learning-based method for…

人机交互 · 计算机科学 2023-09-21 Moein Razavi , Anthony McDonald , Ranjana Mehta , Farzan Sasangohar

Daily monitoring of stress is a critical component of maintaining optimal physical and mental health. Physiological signals and contextual information have recently emerged as promising indicators for detecting instances of heightened…

Stress, anxiety, and nervousness are all high-risk health states in everyday life. Previously, stress levels were determined by speaking with people and gaining insight into what they had experienced recently or in the past. Typically,…

信号处理 · 电气工程与系统科学 2022-04-08 Sadhana Tiwari , Sonali Agarwal

Healthcare professionals, particularly nurses, face elevated occupational stress, a concern amplified during the COVID-19 pandemic. While wearable sensors offer promising avenues for real-time stress monitoring, existing studies often lack…

机器学习 · 计算机科学 2025-07-11 Arpana Sinhal , Anay Sinhal , Amit Sinhal

With the development of wearable technologies, a new kind of healthcare data has become valuable as medical information. These data provide meaningful information regarding an individual's physiological and psychological states, such as…

机器学习 · 计算机科学 2023-03-09 Berrenur Saylam , Özlem Durmaz İncel

Cardiovascular activities are directly related to the response of a body in a stressed condition. Stress, based on its intensity, can be divided into two types i.e. Acute stress (short-term stress) and Chronic stress (long-term stress).…

机器学习 · 计算机科学 2022-10-31 Talha Iqbal , Adnan Elahi , Atif Shahzad , William Wijns

Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detection of stress of people in a social situation by combining two sensor systems that…

Stress has emerged as a critical global health issue, contributing to cardiovascular disorders, depression, and several other long-term illnesses. Consequently, accurate and reliable stress monitoring systems are of growing importance. In…

信号处理 · 电气工程与系统科学 2025-09-03 Md. Mohibbul Haque Chowdhury , Nafisa Anjum , Md. Rokonuzzaman Mim

Introduction. The stress response has both subjective, psychological and objectively measurable, biological components. Both of them can be expressed differently from person to person, complicating the development of a generic stress…

人工智能 · 计算机科学 2023-04-18 Gideon Vos , Kelly Trinh , Zoltan Sarnyai , Mostafa Rahimi Azghadi

Student mental health is an increasing concern in academic institutions, where stress can severely impact well-being and academic performance. Traditional assessment methods rely on subjective surveys and periodic evaluations, offering…

机器学习 · 计算机科学 2025-08-05 Md Sultanul Islam Ovi , Jamal Hossain , Md Raihan Alam Rahi , Fatema Akter

Physiological measurements involves observing variables that attribute to the normative functioning of human systems and subsystems directly or indirectly. The measurements can be used to detect affective states of a person with aims such…

机器学习 · 计算机科学 2022-10-31 Nibraas Khan , Nilanjan Sarkar

Stress detection and monitoring is an active area of research with important implications for the personal, professional, and social health of an individual. Current approaches for affective state classification use traditional machine…

机器学习 · 计算机科学 2021-07-14 Ramesh Kumar Sah , Hassan Ghasemzadeh

In today's world, stress is a big problem that affects people's health and happiness. More and more people are feeling stressed out, which can lead to lots of health issues like breathing problems, feeling overwhelmed, heart attack,…

机器学习 · 计算机科学 2024-12-11 Ashutosh Singh , Khushdeep Singh , Amit Kumar , Abhishek Shrivastava , Santosh Kumar

The stress detection problem is receiving great attention in related research communities. This is due to its essential part in behavioral studies for many serious health problems and physical illnesses. There are different methods and…

Increase in workload across many organisations and consequent increase in occupational stress is negatively affecting the health of the workforce. Measuring stress and other human psychological dynamics is difficult due to subjective nature…

人机交互 · 计算机科学 2015-10-15 Enrique Garcia-Ceja , Venet Osmani , Oscar Mayora

Stress research is a rapidly emerging area in thefield of electroencephalography (EEG) based signal processing.The use of EEG as an objective measure for cost effective andpersonalized stress management becomes important in…

信号处理 · 电气工程与系统科学 2019-07-19 Sanay Muhammad Umar Saeed , Syed Muhammad Anwar , Humaira Khalid , Muhammad Majid , Ulas Bagci

Since stress contributes to a broad range of mental and physical health problems, the objective assessment of stress is essential for behavioral and physiological studies. Although several studies have evaluated stress levels in controlled…

机器学习 · 计算机科学 2021-08-03 Ali Tazarv , Sina Labbaf , Stephanie M. Reich , Nikil Dutt , Amir M. Rahmani , Marco Levorato
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