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Deep Learning for IoT-Healthcare Based on Physiological Signals
Published in Jacques Bou Abdo, Jacques Demerjian, Abdallah Makhoul, 5G Impact on Biomedical Engineering, 2022
Joseph Azar, Raphaël Couturier
The blood vessels in the skin and sweat glands are linked to the sympathetic nervous system. Sweat secretion proportionally increases the skin's conductance, so its conductivity measures electrodermal activity (EDA). Sweat secretion from the skin is tracked with lightweight and mobile sensors, making data acquisition very simple. Increased sweating contributes to greater conductivity of the skin. When exposed to emotional stimuli, one sweats, especially on the forehead, hands, and feet. Skin behavior is subconsciously regulated, much like pupil dilation, thereby providing tremendous insights into an individual's unbiased emotional arousal.
Instructional Technologies in Aviation Training: Today and Beyond
Published in Suzanne K. Kearns, Timothy J. Mavin, Steven Hodge, Competency-Based Education in Aviation, 2017
Suzanne K. Kearns, Timothy J. Mavin, Steven Hodge
The possibilities for use of wearable technology in aviation are as broad as one’s imagination. For example, early devices that track eye movements and measure electrodermal activity (EDA) have the ability to sense different types of stress. That is, they can distinguish work-related social or time-related stress from stress associated with cognitive load, which occurs when a learner is becoming overwhelmed by information (Setz et al. 2010). This suggests that devices in the future may help instructors determine when a learner has achieved competence: the learner who has achieved such competence may no longer exhibit cognitive load stress in challenging scenario-based training.
The Multi-Aspect Measurement Approach: Rationale, Technologies, Tools, and Challenges for Systems Design
Published in Pamela Savage-Knepshield, John Martin, John Lockett, Laurel Allender, Designing Soldier Systems, 2018
Kelvin S. Oie, Stephen Gordon, Kaleb McDowell
Electrodermal activity Electrodermal activity (EDA), also commonly known as galvanic skin response, is the result of increased sweat production and is often measured on the palmar surface of the hands or plantar surface of the feet in response to increased arousal (Ikehara and Crosby 2005, Mandryk, Inkpen, and Calvert 2006, Reeves, Schmorrow, and Stanney 2007), emotional stress (Perala and Sterling 2007, Wagner, Kim, and Andre 2005), and cognitive load (Allanson and Fairclough 2004). EDA recordings have been linked to levels of attention, vigilance (Andreassi 2000), and stimulus significance (Wingard and Maltzman 1980).
Certified Flight Instructors’ Performance – Review of the Literature and Exploration of Future Steps
Published in The International Journal of Aerospace Psychology, 2020
Christophe Lazure, Laurence Dumont, Sofia El Mouderrib, Jean-François Delisle, Sylvain Sénécal, Pierre-Majorique Léger
There are currently many ways to measure a person’s stress level. There are four types of stress indices, namely subjective, behavioral, psychophysiological, and biochemical (Stokes & Kite, 1994). Subjective measures require a scale, in which a person writes down how he feels and believes he is doing. Behavioral measures may require a range of computerized test batteries, specialized performance tests and flight simulator training. Psychophysiological indices can be measured via the heart rate, skin conductance, respiratory rate, muscle tension, etc. Biochemical indices are objective measures of neurotransmitters, hormones or their metabolites, like serotonin, epinephrine, norepinephrine, dopamine, or most commonly cortisol. Electrodermal activity (EDA) measures the skin conductance and has been proven to effectively measure the stress level of a person (Riedl & Léger, 2016).
Mental workload variations during different cognitive office tasks with social media interruptions
Published in Ergonomics, 2023
Elmira Zahmat Doost, Wei Zhang
ECG technology uses multiple sensors to measure the electrical activity of the heart. Cardiac activity can be analysed in the time or frequency domain. This work selected two metrics from the time domain (HR and SDNN) and one from the frequency domain (LF/HF). Heart rate (HR) is a time-domain measurement that is usually reported and is measured as the number of beats over a period of time, most often recorded per minute (Charles and Nixon 2019). SDNN is a standard deviation of RR interval (time duration between two successive R peaks) within the specified time. The ratio of LF (low frequency) and HF (high frequency) (LF/HF) is a frequency-domain method, and it is known as a measurement for Sympathovagal balance. LF was bandpass filtered within the range of 0.04–0.15 Hz and HF filtered within 0.15–0.4 Hz. Moreover, Electrodermal activity (EDA) measures the changes in electrical activity in the eccrine sweat glands controlled by the sympathetic nervous system (Charles and Nixon 2019). The EDA signals were bandpass filtered with the range of 0.05–500 Hz. The physiological indexes were selected based on the previous review (Charles and Nixon 2019; Ding et al. 2020). First, physiological signals were pre-processed through ErgoLAB®. Then, data was cleaned with wavelet denoising and root-mean-square (RMS) filtering. Baseline mean values were subtracted from each respective task data to perform baseline correction. The required recordings of physiological signals were the first 2-min segments for each task (six 2-min segments per participant). These were distinguished by screen recording made by ErgoLAB®.