The effects of traveling in different transport modes on galvanic skin response (GSR) as a measure of stress: An observational study

Psychological Stress

“…[25] Modern humans may attempt to self-assess their own "stress-level"; third parties (sometimes clinicians) may also provide qualitative evaluations. Quantitative approaches such as Galvanic Skin Response [26] or other measurements giving results which may correlate with perceived psychological stress include testing for one or more of the several stress hormones, [27] for cardiovascular responses, [28] or for immune response. [29] There are some valid questionnaires to assess the stress level.…”

“…[89] Cycling and walking activities have lower stress scores when compared to all other activities. [26] A multitude of theories have been presented in attempts to explain why exercise effectively reduces stress. One theory, known as the time-out hypothesis, claims that exercise provides distraction from the stressor.…”

Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: A cross-sectional study using GPS from 122 individuals in three European cities

“…Intrapersonal variability describes the variability of mobility within an individual over specific time-frames, such as day-to-day, and interpersonal variability describes the variability between individuals across socioeconomic or built environment attributes ( Zhang et al, 2021 ). Quantifying day-to-day variability in mobility patterns enables it to be explored, compared and associated with other characteristics including, for example, health ( Barlacchi et al, 2017 ; Yang et al, 2021 ).…”

Preprocessing of PPG and EDA signals for detection of emotional and cognitive states via physiological signals

“…Every act of monitoring, as suggested above, could be successfully achieved through the use of sensors and systems for acquisition of physiological signals such as Electrodermal Activity (EDA), Photoplethysmography (PPG), Electrocardiography (ECG), etc. The easiest and most accurate physiological signals for out-of-the-lab monitoring prove to be the EDA (Yang, 2021) and PPG, which outperforms ECG in dynamic scenarios (Bradke, 2021). There are many databases with physiological signals adapted for emotional and cognitive states detection, for example, DEAP (Koelstra, 2012), CASE (Sharma, 2019) and CLAS (Markova, 2019).…”