A survey on mobile crowdsensing systems: Challenges, solutions, and opportunities

A Capponi, C Fiandrino, B Kantarci… - … surveys & tutorials, 2019 - ieeexplore.ieee.org
Mobile crowdsensing (MCS) has gained significant attention in recent years and has
become an appealing paradigm for urban sensing. For data collection, MCS systems rely on …

Graph neural networks in IoT: A survey

G Dong, M Tang, Z Wang, J Gao, S Guo, L Cai… - ACM Transactions on …, 2023 - dl.acm.org
The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily
lives: healthcare, environment, transportation, manufacturing, supply chain, and so on. With …

Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms

S Hornstein, K Zantvoort, U Lueken, B Funk… - Frontiers in digital …, 2023 - frontiersin.org
Introduction Personalization is a much-discussed approach to improve adherence and
outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open …

[HTML][HTML] Passive sensing of health outcomes through smartphones: systematic review of current solutions and possible limitations

A Trifan, M Oliveira, JL Oliveira - JMIR mHealth and uHealth, 2019 - mhealth.jmir.org
Background: Technological advancements, together with the decrease in both price and
size of a large variety of sensors, has expanded the role and capabilities of regular mobile …

[HTML][HTML] Digital biomarkers of social anxiety severity: digital phenotyping using passive smartphone sensors

NC Jacobson, B Summers, S Wilhelm - Journal of medical Internet research, 2020 - jmir.org
Background Social anxiety disorder is a highly prevalent and burdensome condition.
Persons with social anxiety frequently avoid seeking physician support and rarely receive …

Digital biomarkers of anxiety disorder symptom changes: Personalized deep learning models using smartphone sensors accurately predict anxiety symptoms from …

NC Jacobson, S Bhattacharya - Behaviour Research and Therapy, 2022 - Elsevier
Smartphones are capable of passively capturing persons' social interactions, movement
patterns, physiological activation, and physical environment. Nevertheless, little research …

Digital phenotyping for mental health of college students: a clinical review

J Melcher, R Hays, J Torous - BMJ Ment Health, 2020 - mentalhealth.bmj.com
Experiencing continued growth in demand for mental health services among students,
colleges are seeking digital solutions to increase access to care as classes shift to remote …

[HTML][HTML] Digital phenotyping of mental health using multimodal sensing of multiple situations of interest: A systematic literature review

I Moura, A Teles, D Viana, J Marques… - Journal of Biomedical …, 2023 - Elsevier
Many studies have used Digital Phenotyping of Mental Health (DPMH) to complement
classic methods of mental health assessment and monitoring. This research area proposes …

Recurrent neural network for human activity recognition in embedded systems using ppg and accelerometer data

M Alessandrini, G Biagetti, P Crippa, L Falaschetti… - Electronics, 2021 - mdpi.com
Photoplethysmography (PPG) is a common and practical technique to detect human activity
and other physiological parameters and is commonly implemented in wearable devices …

ActiPPG: Using deep neural networks for activity recognition from wrist-worn photoplethysmography (PPG) sensors

M Boukhechba, L Cai, C Wu, LE Barnes - Smart Health, 2019 - Elsevier
Sensor-based activity recognition seeks to provide higher-level knowledge about human
activities from multiple sensors such as accelerometer and gyroscope. Thanks to growing …