A survey on measuring cognitive workload in human-computer interaction

T Kosch, J Karolus, J Zagermann, H Reiterer… - ACM Computing …, 2023 - dl.acm.org
The ever-increasing number of computing devices around us results in more and more
systems competing for our attention, making cognitive workload a crucial factor for the user …

[HTML][HTML] Artificial vision algorithms for socially assistive Robot applications: A review of the literature

VM Montaño-Serrano, JM Jacinto-Villegas… - Sensors, 2021 - mdpi.com
Today, computer vision algorithms are very important for different fields and applications,
such as closed-circuit television security, health status monitoring, and recognizing a …

Take an emotion walk: Perceiving emotions from gaits using hierarchical attention pooling and affective mapping

U Bhattacharya, C Roncal, T Mittal, R Chandra… - … on Computer Vision, 2020 - Springer
We present an autoencoder-based semi-supervised approach to classify perceived human
emotions from walking styles obtained from videos or motion-captured data and represented …

Assessing cognitive performance using physiological and facial features: Generalizing across contexts

K Sharma, E Niforatos, M Giannakos… - Proceedings of the ACM …, 2020 - dl.acm.org
Sensing and machine learning advances have enabled the unobtrusive measurement of
physiological responses and facial expressions so as to estimate one's cognitive …

Electroencephalogram-based cognitive load level classification using wavelet decomposition and support vector machine

F Khanam, ABMA Hossain, M Ahmad - Brain-Computer Interfaces, 2023 - Taylor & Francis
Cognitive load level identification is an interesting challenge in the field of brain-computer-
interface. The sole objective of this work is to classify different cognitive load levels from …

Examining the Impact of Uncontrolled Variables on Physiological Signals in User Studies for Information Processing Activities

K Ji, D Spina, D Hettiachchi, FD Salim… - Proceedings of the 46th …, 2023 - dl.acm.org
Physiological signals can potentially be applied as objective measures to understand the
behavior and engagement of users interacting with information access systems. However …

Assessing fatigue with multimodal wearable sensors and machine learning

A Jaiswal, MZ Zadeh, A Hebri, F Makedon - arXiv preprint arXiv …, 2022 - arxiv.org
Fatigue is a loss in cognitive or physical performance due to physiological factors such as
insufficient sleep, long work hours, stress, and physical exertion. It adversely affects the …

[HTML][HTML] Cogbeacon: A multi-modal dataset and data-collection platform for modeling cognitive fatigue

M Papakostas, A Rajavenkatanarayanan, F Makedon - Technologies, 2019 - mdpi.com
In this work, we present CogBeacon, a multi-modal dataset designed to target the effects of
cognitive fatigue in human performance. The dataset consists of 76 sessions collected from …

An intelligent action recognition system to assess cognitive behavior for executive function disorder

AR Babu, M Zakizadeh, JR Brady… - 2019 IEEE 15th …, 2019 - ieeexplore.ieee.org
This paper proposes a novel intelligent system to monitor and assess cognitive behavior
through physical tasks which are part of assessment and training for people with Executive …

A multi-modal system to assess cognition in children from their physical movements

A Ramesh Babu, MZ Zadeh, A Jaiswal… - Proceedings of the …, 2020 - dl.acm.org
In recent years, computer and game-based cognitive tests have become popular with the
advancement in mobile technology. However, these tests require very little body movements …