A review of emotion recognition methods based on data acquired via smartphone sensors

A Kołakowska, W Szwoch, M Szwoch - Sensors, 2020 - mdpi.com
In recent years, emotion recognition algorithms have achieved high efficiency, allowing the
development of various affective and affect-aware applications. This advancement has taken …

Methodological standards in accessibility research on motor impairments: A survey

Z Sarsenbayeva, N Van Berkel, E Velloso… - ACM Computing …, 2022 - dl.acm.org
The design and evaluation of accessibility technology is a core component of the computer
science landscape, aiming to ensure that digital innovations are accessible to all. One of the …

Does smartphone use drive our emotions or vice versa? A causal analysis

Z Sarsenbayeva, G Marini, N van Berkel… - Proceedings of the …, 2020 - dl.acm.org
In this paper, we demonstrate the existence of a bidirectional causal relationship between
smartphone application use and user emotions. In a two-week long in-the-wild study with 30 …

Light and dark mode: a comparison between android and iOS app UI modes and interviews with app designers and developers

S Andrew, C Bishop, GW Tigwell - … of the ACM on Interactive, Mobile …, 2024 - dl.acm.org
Mobile app light and dark modes offer improved usability within different contexts (eg, dark
mode for easier night reading). Yet, little research has investigated the prevalence of light …

On stress: Combining human factors and biosignals to inform the placement and design of a skin-like stress sensor

Y Khan, ML Mauriello, P Nowruzi, A Motani… - Proceedings of the …, 2024 - dl.acm.org
With advances in electronic-skin and wearable technologies, it is possible to continuously
measure stress markers from the skin and sweat to monitor and improve wellbeing and …

[HTML][HTML] The ERMES chatbot: A conversational communication tool for improved emergency management and disaster risk reduction

A Urbanelli, A Frisiello, L Bruno, C Rossi - International Journal of Disaster …, 2024 - Elsevier
The increased occurrence and severity of worldwide disasters, exacerbated by the impact of
climate change, pose significant challenges to emergency management, calling for novel …

[HTML][HTML] Predicting the next-day perceived and physiological stress of pregnant women by using machine learning and explainability: algorithm development and …

A Ng, B Wei, J Jain, EA Ward, SD Tandon… - JMIR mHealth and …, 2022 - mhealth.jmir.org
Background Cognitive behavioral therapy–based interventions are effective in reducing
prenatal stress, which can have severe adverse health effects on mothers and newborns if …

Keep calm and do not carry-forward: Toward sensor-data driven AI agent to enhance human learning

K Sharma, S Lee-Cultura, M Giannakos - Frontiers in Artificial …, 2022 - frontiersin.org
The integration of Multimodal Data (MMD) and embodied learning systems (such as Motion
Based Educational Games, MBEG), can help learning researchers to better understand the …

Reading between the heat: Co-teaching body thermal signatures for non-intrusive stress detection

Y **ao, H Sharma, Z Zhang, D Bergen-Cico… - Proceedings of the …, 2024 - dl.acm.org
Stress impacts our physical and mental health as well as our social life. A passive and
contactless indoor stress monitoring system can unlock numerous important applications …

Affective state prediction based on semi-supervised learning from smartphone touch data

R Wampfler, S Klingler, B Solenthaler… - Proceedings of the …, 2020 - dl.acm.org
Gaining awareness of the user's affective states enables smartphones to support enriched
interactions that are sensitive to the user's context. To accomplish this on smartphones, we …