Fabrication of a portable device for stress monitoring using wearable sensors and soft computing algorithms

@article{Golgouneh2019FabricationOA,
  title={Fabrication of a portable device for stress monitoring using wearable sensors and soft computing algorithms},
  author={Alireza Golgouneh and Bahram Tarvirdizadeh},
  journal={Neural Computing and Applications},
  year={2019},
  volume={32},
  pages={7515-7537}
}
Stress is an issue that everyone experiences in today’s modern life. Prolonged exposure to stress can cause many mental and physical diseases. Accordingly, the stress management issue has become popular, and the need for personal healthcare devices has increased in recent years. Therefore, the aim of this research is to design and manufacture a portable stress monitoring system, based on photoplethysmography (PPG) and galvanic skin response (GSR) physiological signals, acquired by wearable… Expand
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References

SHOWING 1-10 OF 71 REFERENCES
Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables
  • Jing Zhai, A. Barreto
  • Computer Science, Medicine
  • 2006 International Conference of the IEEE Engineering in Medicine and Biology Society
  • 2006
TLDR
Results indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in emotional state of experimental subjects when stress stimuli are applied to the interaction environment. Expand
Wearable Physiological Sensors Reflect Mental Stress State in Office-Like Situations
TLDR
Electrocardiogram, respiration, skin conductance and surface electromyogram of the upper trapezius muscle were measured with a wearable system during three distinctive stress tests to identify physiological signals and features suitable for detecting mental stress in office-like situations. Expand
Portable System for Real-Time Detection of Stress Level
TLDR
A portable system for real-time detection of stress based on multiple biosignals such as electroencephalography, electrocardiography, electromyography, and galvanic skin response that can be used to prevent stress episodes in many situations of everyday life such as work, school, and home is proposed. Expand
A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals
TLDR
This work proposes a neural network driven based solution to learning driving-induced stress patterns and correlating it with statistical, structural and time-frequency changes observed in the recorded biosignals, concluded that Layer Recurrent Neural Networks are most optimal for stress level detection. Expand
Towards Measuring Stress with Smartphones and Wearable Devices During Workday and Sleep
TLDR
This work uses information from audio, physical activity, and communication data collected during workday and heart rate variability data collected at night during sleep to build multinomial logistic regression models and presents a solution for assessing the stress experience of people, using features derived from smartphones and wearable chest belts. Expand
Towards an automatic early stress recognition system for office environments based on multimodal measurements: A review
TLDR
This work reviews and brings together the recent works carried out in the automatic stress detection looking over the measurements executed along the three main modalities, namely, psychological, physiological and behaviouralmodalities, in order to give hints about the most appropriate techniques to be used and thereby, to facilitate the development of such a holistic system. Expand
EEG analysis for understanding stress based on affective model basis function
TLDR
Results have shown the potential of using the basic emotion basis function to visualize the stress perception as an alternative tool for engineers and psychologist. Expand
Stress and EEG
Many people suffer from stress in their everyday life. While there is a close relationship between stress and mental health, psychological stress (and associated emotions such as anger, anxiety, andExpand
Detection of variations in cognitive workload using multi-modality physiological sensors and a large margin unbiased regression machine
TLDR
A study on detecting changes in workload using multi-modality physiological sensors and a novel feature extraction and classification algorithm and shows that EEG can provide significantly better prediction of the cognitive workload variation than ECG, with 87.5% in accuracy rate. Expand
Smart technologies for long-term stress monitoring at work
TLDR
The main results of the evaluation are that the results of long-term measurements of stress reveal people information about their behavioral patterns that they perceive as meaningful and useful, and trigger their ideas about behavioral changes necessary to achieve a better stress balance. Expand
...
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3
4
5
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