Real-time stress evaluation using wireless body sensor networks

Abstract

Stress is a physical, mental or emotional factor that causes bodily or mental tension. It is generally recognized as one of the major factors leading to a spectrum of health problems. Therefore, people with high risks of getting stressed should be continuously monitored in order to detect any stress signs before it causes health problems. Wireless body sensor networks(WBSNs) provide opportunities to monitor stress and can provide initial treatment. In this paper, we propose an energy-efficient stress detection and evaluation framework. A WBSN deployed on the patient's body collects stress-correlated physiological signals. First, the skin conductance (SC) is analyzed. Then, if any stress signs are detected, its level is calculated via a Fuzzy Inference System (FIS) using the following vital signs: Heart Rate (HR), Respiration Rate (RR) and Systolic Blood Pressure (ABPSys). The results show that the stress evaluation was coherent with the different experimental stages the monitored person has gone through.

A Sensor-Based Data Analytics for Patient Monitoring in Connected Healthcare Applications

“…Recently, the authors of [5], [8]- [10] open a new trend in connected healthcare by proposing several frameworks for a real-time patient monitoring and assessment. In [8], a framework for a stress detection and evaluation has been proposed.…”

“…Recently, the authors of [5], [8]- [10] open a new trend in connected healthcare by proposing several frameworks for a real-time patient monitoring and assessment. In [8], a framework for a stress detection and evaluation has been proposed. The framework works by detecting first stress signals according to skin conductance parameter, then the stress level is evaluated through fuzzy inference system based on patient vital signs, particularly heart rate, respiration rate, and average blood pressure.…”

“…Connected healthcare applications provide several challenges: First, reducing the energy consumption in the biosensors in order to save its limited power supply and ensure a long time patient monitoring [5]- [7]. Second, detecting emergency situations of the patient as fast as possible and quickly reported to the medical staff in order to take a suitable action [8]- [10]. Third, studying the progress of the patient behavior and predicting his future situation are important challenges in healthcare.…”

A Hadoop-Based Platform for Patient Classification and Disease Diagnosis in Healthcare Applications

“…Recently, the authors of [19][20][21][22] opened a new trend in sensing-based healthcare by proposing several frameworks for real-time patient monitoring and assessment. In [19], a framework for stress detection and evaluation is proposed.…”

“…Recently, the authors of [19][20][21][22] opened a new trend in sensing-based healthcare by proposing several frameworks for real-time patient monitoring and assessment. In [19], a framework for stress detection and evaluation is proposed. The framework works by detecting first stress signals according to skin conductance parameter, and then the stress level is evaluated through fuzzy inference system based on patient vital signs, particularly heart rate, respiration rate, and average blood pressure.…”