An RFID Based Localization and Mental Stress Recognition System Using Wearable Sensors

Mhd. Raed, Semih Yön, Ali Güneş, Igor Kotenko, Elena Fedorchenko, Anna Polubaryeva

2023

Abstract

A vast increase in the percentage of elderly people over the past few decades has induced a serious concern among the research fraternity worldwide. Consequently, the large increase in the number of elderly needing assistance because of chronic diseases is expected to take place. Dementia, depression and mental stress are among the most disabling diseases with dangerous consequences such as wandering into hazardous or insecure areas. This wandering, particularly in urban areas can be life threatening. Recently, with the rapid emergence of disruptive technologies like Internet of Things (IoT), Radio Frequency Identification (RFID) and wireless bio sensors, it has become feasible to build systems that combine IoT and the cloud for monitoring the elderly suffering from dementia or depression. Furthermore, mental chronic diseases, such as stress and depression, are becoming a major concern for governments around the globe. The American Psychological Association (APA) categorizes stress, anxiety and depression as main factors for diverse mental health problems. The cost for treating work-related stress, anxiety and depression, is estimated to be around 617 billion euros per year in Europe alone. Wearable devices for monitoring chronic diseases such as mental stress and depression have been considered as game-changers to the way diseases are managed, by measuring vital signs like skin conductance and changes in the levels of biological stress, and sending warnings remotely to an online server. This paper proposes a work in progress Arduino based real-time stress recognition and localization system using wearable RFID and vital sign sensors for elderly suffering from Dementia and mental stress. The current work utilizes the heart rate variability and Electro Dermal Activity wearable sensors based on the Bitalino development system for measuring mental stress and anxiety in a smart home setting for elderly living alone by exposing a number of subjects to stress and anxiety stimulating horror videos. The system was tested successfully in the university lab.

Paper Citation

in Harvard Style

Raed M., Yön S., Güneş A., Kotenko I., Fedorchenko E. and Polubaryeva A. (2023). An RFID Based Localization and Mental Stress Recognition System Using Wearable Sensors. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 4: BIOSIGNALS; ISBN 978-989-758-631-6, SciTePress, pages 325-331. DOI: 10.5220/0011796000003414

in Bibtex Style

@conference{biosignals23,
author={Mhd. Raed and Semih Yön and Ali Güneş and Igor Kotenko and Elena Fedorchenko and Anna Polubaryeva},
title={An RFID Based Localization and Mental Stress Recognition System Using Wearable Sensors},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 4: BIOSIGNALS},
year={2023},
pages={325-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011796000003414},
isbn={978-989-758-631-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 4: BIOSIGNALS
TI - An RFID Based Localization and Mental Stress Recognition System Using Wearable Sensors
SN - 978-989-758-631-6
AU - Raed M.
AU - Yön S.
AU - Güneş A.
AU - Kotenko I.
AU - Fedorchenko E.
AU - Polubaryeva A.
PY - 2023
SP - 325
EP - 331
DO - 10.5220/0011796000003414
PB - SciTePress