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IEEE EMBC 2022 Workshop and Challenge on Detection of Stress and Mental Health Using Wearable Sensors

  • Huiyuan Yang
  • , Han Yu
  • , Alicia Choto Segovia
  • , Maryam Khalid
  • , Thomas Vaessen
  • , Akane Sano

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

Mental health and well-being are one of the most challenging issues in modern so-ciety[1,2]. For example, moderate stress can help a person in many beneficial ways to confront a challenge [3]. On the other hand, excessive stress, a common phenomenon in our society, can cause overall negative health and well-being impact [4], such as increasing susceptibility to infection and illness[5-7], affecting a diverse range of physical, psychological, and behavioral conditions (i.e., anxiety, depression, sleep disorders, or decreasing job productivity)[8-11]. Furthermore, mental disorders such as depression and schizophrenia, if not monitored and treated timely, can lead to further degradation of the person’s mental health and well-being. The ability to measure stress levels or mental health could enable better self-management of one’s behavioral choices in ways that might be intervened timely.

Original languageEnglish
Title of host publicationHuman Activity and Behavior Analysis
Subtitle of host publicationAdvances in Computer Vision and Sensors: Volume 1
PublisherCRC Press/Balkema
Pages210-221
Number of pages12
Volume1
ISBN (Electronic)9781003815686
ISBN (Print)9781032443119
DOIs
Publication statusPublished - 1 Jan 2024

Keywords

  • NLA

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