Towards Ambulatory Mental Stress Measurement from Physiological Parameters

Wijsman, Jacqueline; Vullers, Ruud; Polito, Salvatore; Agell, Carlos; Penders, Julien; Hermens, Hermie

doi:10.1109/acii.2013.99

Cited by 14 publications

(7 citation statements)

References 10 publications

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“…For the validation of results, it is necessary to measure physiological parameters for an extended time in real-time conditions which can be a real challenge. The recorded signals can be influenced by various context facts like a poster, temperature, and physical activity, and various types of artifacts like motion artifacts [8].…”

Section: Real-time Stress Monitoringmentioning

confidence: 99%

“…For real-time monitoring of stress, various wearable commercial devices are available in the market. Some researchers have used these devices for data collection and continuous monitoring of stress levels of users while some have developed their own wearable devices [8], [9], [11], [12], [14] made from low-cost sensors for ambulatory monitoring of stress. These devices must measure the signals with minimal error and noise for achieving better accuracy of the algorithm.…”

Section: Real-time Stress Monitoringmentioning

confidence: 99%

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A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques

2021

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Stress is an escalated psycho-physiological state of the human body emerging in response to a challenging event or a demanding condition. Environmental factors that trigger stress are called stressors. In case of prolonged exposure to multiple stressors impacting simultaneously, a person's mental and physical health can be adversely affected which can further lead to chronic health issues. To prevent stress-related issues, it is necessary to detect them in the nascent stages which are possible only by continuous monitoring of stress. Wearable devices promise real-time and continuous data collection, which helps in personal stress monitoring. In this paper, a comprehensive review has been presented, which focuses on stress detection using wearable sensors and applied machine learning techniques. This paper investigates the stress detection approaches adopted in accordance with the sensory devices such as wearable sensors, Electrocardiogram (ECG), Electroencephalography (EEG), and Photoplethysmography (PPG), and also depending on various environments like during driving, studying, and working. The stressors, techniques, results, advantages, limitations, and issues for each study are highlighted and expected to provide a path for future research studies. Also, a multimodal stress detection system using a wearable sensor-based deep learning technique has been proposed at the end.

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Section: Real-time Stress Monitoringmentioning

confidence: 99%

Section: Real-time Stress Monitoringmentioning

confidence: 99%

A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques

2021

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“…Though accurate monitoring of heart rate variability (HRV) has not yet been achieved in motion state, once it is achieved, it will open a variety of applications including like music recommendation based on user affective state, stress monitoring and cardiac insufficiency detection (Wijsman, 2013); (Shin, 2014); (Venema, 2015). In comparison with chest-strap-type wearable electrocardiography (ECG) monitors, wristband-type PPG heart rate sensors can be comfortably worn without placing a burden on the user, which gives them a user-friendly advantage.…”

Section: Introductionmentioning

confidence: 99%

Wearable Motion Tolerant PPG Sensor for Instant Heart Rate in Daily Activity

Ishikawa

Hyodo

Miyashita³

et al. 2017

Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies

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A wristband-type PPG heart rate sensor capable of overcoming motion artifacts in daily activity and detecting heart rate variability has been developed together with a motion artifact cancellation framework. In this work, a motion artifact model in daily life was derived and motion artifacts caused by activity of arm, finger, and wrist were cancelled significantly. Highly reliable instant heart rate detection with high noiseresistance was achieved from noise-reduced pulse signals based on peak-detection and autocorrelation methods. The wristband-type PPG heart rate sensor with our motion artifact cancellation framework was compared with ECG instant heart rate measurement in both laboratory and office environments. In a laboratory environment, mean reliability (percentage of time within 10% error relative to ECG instant heart rate) was 86.5% and the one-day pulse-accuracy achievement rate based on time use data of body motions in daily life was 88.1% or approximately 21 hours. Our device and motion artifact cancellation framework enable continuous heart rate variability monitoring in daily life and could be applied to heart rate variability analysis and emotion recognition.

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“…Students do not know what to expect from the scenario before taking part in the training, and have to give agreement not to disclose the scenario to any other participants. Physiological variables (heart rate (HR), HR variability (HRV) and skin conductance (SC)) are continuously measured with an ECG-necklace and a wristband [129,168]. This equipment is especially designed for measuring stress variables by Holst Centre/imec (Eindhoven, The Netherlands).…”

Section: Study Protocolmentioning

confidence: 99%

“…The system consists of up to six low-power wearable sensor nodes that are synchronized in time and that can measure various physiological parameters. For details, see [129,168].…”

Section: Measurement Equipmentmentioning

confidence: 99%

Sensing stress : stress detection from physiological variables in controlled and uncontrolled conditions

Wijsman¹

Self Cite

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Samenvatting Acknowledgements 1. The engineering approach sees stress as being caused by the environment. The amount of work load and demand are objectively measurable factors that cause stress. 2. The physiological approach sees stress as the physiological response to certain stimuli. This is a general and non-specific response to any stressor. 3. The psychological approach focuses on the interaction between a person and his environment when studying stress. The engineering approach and the physiological approach form the earlier approaches to defining and measuring stress. These approaches have suffered from much criticism, though. A major point of critique towards the engineering approach was its emphasis on environmental factors. These factors do not always have the same effect on, for example, performance or comfort. For the physiological approach, it is mainly the non-specificity that was criticized. It was proven that the stress response is not identical among various stressors, but varies for different types of stressors. Moreover, both approaches ignore individual differences. Current stress research is mainly based on the psychological approach, which focuses on the relations between a person and his environment and the cognitive and emotional processes that are involved in these relations. There are two interaction theories that evolved from the psychological approach that explain the interaction between a person and his environment [33]. One interaction theory is the person-environment fit: if a person and his environment (e.g. work) do not fit, this situation can lead to stress. Another interaction theory is the demand-control model: if the environment is highly demanding and the person working in the environment has low control this can also lead to stress. A distinction can be made between short-term and chronic (long-term) stress. Short-term stress follows from incidental stressful conditions such as a short period of high demand to finish a crucial report. Chronic stress is caused by a long-term imbalance between person and environment and/or demand and control. 1.2 Effects of Chronic Stress Chronic stress induces negative psychological and social effects, as well as physiological effects. For example, stress causes adrenaline and cortisol levels to rise. Chronically elevated levels of these hormones negatively influence cardiovascular health because of their effects on blood pressure and cholesterol levels. The hormone imbalance also suppresses the immune system. 1.3.2 Biochemical Measures The main biochemical measures for stress are the levels of the hormones adrenaline and cortisol in various body fluids: blood, saliva, urine. Stress increases secretion How Mental Stress Influences Physiological Variables: a Selective Review Mental stress is a growing problem in society. To prevent stress-related health problems, it is crucial to assess mental stress levels and to take action when stress becomes too high and/or chronic. Noninvasively measurable physiological parameters are useful to measure st...

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Towards Ambulatory Mental Stress Measurement from Physiological Parameters

Cited by 14 publications

References 10 publications

A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques

A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques

Wearable Motion Tolerant PPG Sensor for Instant Heart Rate in Daily Activity

Sensing stress : stress detection from physiological variables in controlled and uncontrolled conditions

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