Current trends and opportunities in the methodology of electrodermal activity measurement

C Tronstad, M Amini, DR Bach… - Physiological …, 2022 - iopscience.iop.org
Electrodermal activity (EDA) has been measured in the laboratory since the late 1800s.
Although the influence of sudomotor nerve activity and the sympathetic nervous system on …

[HTML][HTML] FLIRT: A feature generation toolkit for wearable data

S Föll, M Maritsch, F Spinola, V Mishra, F Barata… - Computer Methods and …, 2021 - Elsevier
Abstract Background and Objective: Researchers use wearable sensing data and machine
learning (ML) models to predict various health and behavioral outcomes. However, sensor …

Reading the room: Automated, momentary assessment of student engagement in the classroom: Are we there yet?

B DiSalvo, D Bandaru, Q Wang, H Li… - Proceedings of the ACM on …, 2022 - dl.acm.org
When in front of a classroom, a skilled teacher can read the room, identifying when students
are engaged, frustrated, distracted, etc. In recent years we have seen significant changes in …

[HTML][HTML] Corrnet: Fine-grained emotion recognition for video watching using wearable physiological sensors

T Zhang, A El Ali, C Wang, A Hanjalic, P Cesar - Sensors, 2020 - mdpi.com
Recognizing user emotions while they watch short-form videos anytime and anywhere is
essential for facilitating video content customization and personalization. However, most …

[HTML][HTML] Understanding occupants' behaviour, engagement, emotion, and comfort indoors with heterogeneous sensors and wearables

N Gao, M Marschall, J Burry, S Watkins, FD Salim - Scientific Data, 2022 - nature.com
We conducted a field study at a K-12 private school in the suburbs of Melbourne, Australia.
The data capture contained two elements: First, a 5-month longitudinal field study In-Gauge …

The role of model personalization for sleep stage and sleep quality recognition using wearables

S Gashi, L Alecci, E Di Lascio… - IEEE Pervasive …, 2022 - ieeexplore.ieee.org
Personal informatics systems can help people promote their health and well-being. Recent
studies have shown that such systems can be used to infer relevant health indicators such …

[HTML][HTML] A multidevice and multimodal dataset for human energy expenditure estimation using wearable devices

S Gashi, C Min, A Montanari, S Santini, F Kawsar - Scientific Data, 2022 - nature.com
We present a multi-device and multi-modal dataset, called WEEE, collected from 17
participants while they were performing different physical activities. WEEE contains:(1) …

[HTML][HTML] The connection between stress, density, and speed in crowds

M Beermann, A Sieben - Scientific Reports, 2023 - nature.com
Moving around in crowds is part of our daily lives, and we are used to the associated
restriction of mobility. Nevertheless, little is known about how individuals experience these …

Fetal movement detection by wearable accelerometer duo based on machine learning

J Xu, C Zhao, B Ding, X Gu, W Zeng, L Qiu… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Objective: Fetal movement counting is one of the most important indices reflecting the health
of the fetus. In the hospital, ultrasound method serves as gold standard but could only be …

Lateralization Effects in Electrodermal Activity Data Collected Using Wearable Devices

L Alchieri, N Abdalazim, L Alecci, S Gashi… - Proceedings of the …, 2024 - dl.acm.org
Electrodermal activity (EDA) is a physiological signal that can be used to infer humans'
affective states and stress levels. EDA can nowadays be monitored using unobtrusive …