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An affect detection technique using mobile commodity sensors in the wild

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A wearable system for mood assessment considering smartphone features and data from mobile ECGs

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Improving prediction of real-time loneliness and companionship type using geosocial features of personal smartphone data

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Understanding, Discovering, and Mitigating Habitual Smartphone Use in Young Adults

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Predictive modeling in e-mental health: A common language framework

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Personalized mood prediction from patterns of behavior collected with smartphones

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Real World User Model: Evolution of User Modeling Triggered by Advances in Wearable and Ubiquitous Computing

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One More Bite? Inferring Food Consumption Level of College Students Using Smartphone Sensing and Self-Reports

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Linking physical and social environments with mental health in old age: a multisensor approach for continuous real-life ecological and emotional assessment

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Real-time Smartphone Activity Classification Using Inertial Sensors—Recognition of Scrolling, Typing, and Watching Videos While Sitting or Walking

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Passive Sensor Data Based Future Mood, Health, and Stress Prediction: User Adaptation Using Deep Learning

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Aristotle Said “Happiness is a State of Activity” — Predicting Mood Through Body Sensing with Smartwatches

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PrivacyStreams: Enabling Transparency in Personal Data Processing for Mobile Apps

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Evaluating effectiveness of smartphone typing as an indicator of user emotion

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Knowledge Engineering Framework for IoT Robotics Applied to Smart Healthcare and Emotional Well-Being

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Through a Gender Lens: An Empirical Study of Emoji Usage over Large-Scale Android Users.Preprint

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K-EmoPhone: A Mobile and Wearable Dataset with In-Situ Emotion, Stress, and Attention Labels

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Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data

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Smart-U: Smart Utensils Know what You Eat

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Unobtrusive Stress Assessment Using Smartphones

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Affective State Prediction Based on Semi-Supervised Learning from Smartphone Touch Data

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Survey on Emotion Sensing Using Mobile Devices

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Smartphone Sensing for the Well-Being of Young Adults: A Review

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Intelligent Notification Systems: A Survey of the State of the Art and Research ChallengesPreprint

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Predicting Brain Functional Connectivity Using Mobile Sensing

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Investigating interruptibility at activity breakpoints using smartphone activity recognition API

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Adversary Models for Mobile Device Authentication

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SPIDERS + : A light-weight, wireless, and low-cost glasses-based wearable platform for emotion sensing and bio-signal acquisition

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iAware: A Real-Time Emotional Biofeedback System Based on Physiological Signals

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How to use smartphones for less obtrusive ambulatory mood assessment and mood recognition

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Smartphone accelerometer data used for detecting human emotions

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Using Smartphone Survey Data and Machine Learning to Identify Situational and Contextual Risk Factors for HIV Risk Behavior Among Men Who Have Sex with Men Who Are Not on PrEP

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A Review of the Role of Sensors in Mobile Context-Aware Recommendation Systems

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The Mobile Territorial Lab: a multilayered and dynamic view on parents’ daily lives

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Network Diversity and Affect Dynamics: The Role of Personality Traits

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Naturalistic Recognition of Activities and Mood Using Wearable Electronics

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Daily estimates of clinical severity of symptoms in bipolar disorder from smartphone-based self-assessments

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Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment

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Complex Daily Activities, Country-Level Diversity, and Smartphone Sensing: A Study in Denmark, Italy, Mongolia, Paraguay, and UK

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myStress: Unobtrusive Smartphone-based Stress Detection

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SPIDERS: Low-Cost Wireless Glasses for Continuous In-Situ Bio-Signal Acquisition and Emotion Recognition

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Applied Affective Computing

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Designing for Tangible Affective Interaction

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A Deep Learning Approach for Mood Recognition from Wearable Data

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Designing an Experience Sampling Method for Smartphone Based Emotion Detection

Ghosh, S., Ganguly, N., Mitra, B., & De, P. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2019.2905561 · Cited by 22

Enhancing intelligence in multimodal emotion assessments

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FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning

Shin, J., Yoon, H. S., Lee, S., Park, S., Liu, Y., Choi, J. D., & Lee, S.-J. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.734 · Cited by 33

Leveraging Smart Devices for Automatic Mood-Transferring in Real-Time Oil Painting

Dutta, T., & Gupta, H. P. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2613978 · Cited by 21

Investigating the Impact of Adding Plan Reminders on Implementation Intentions to Support Behaviour Change

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Exploring and Comparing Machine Learning Approaches for Predicting Mood Over Time

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Forbidden knowledge in machine learning reflections on the limits of research and publication

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Emotions on the Go

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mFingerprint: Privacy-Preserving User Modeling with Multimodal Mobile Device Footprints

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Wearable and ambient sensing for well-being and emotional awareness in the smart workplace

Hänsel, K. (2016) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2968219.2971360 · Cited by 20

Designing Effective Movement Digital Biomarkers for Unobtrusive Emotional State Mobile Monitoring

Mehrotra, A., & Musolesi, M. (2017) · doi:10.1145/3089341.3089342 · Cited by 19

iGuard: A Real-Time Anti-Theft System for Smartphones

Jin, M., He, Y., Fang, D., Chen, X., Meng, X., & Xing, T. (2018) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2018.2798618 · Cited by 20

Emotion Forecasting: A Transformer-Based Approach

Paz-Arbaizar, L., López‐Castromán, J., Artés-Rodrı́guez, A., Olmos, P. M., & Ramírez, D. (2025) · Journal of Medical Internet Research · doi:10.2196/63962 · Cited by 20

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A Mixed-Method Exploration into the Mobile Phone Rabbit Hole

Terzimehić, N., Bemmann, F., Halsner, M., & Mayer, S. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3604241 · Cited by 25

Detecting change in depressive symptoms from daily wellbeing questions, personality, and activity

Demasi, Aguilera, A., & Recht (2016) · Wireless Health · doi:10.1109/wh.2016.7764552 · Cited by 21

What to Put on the User

Hänsel, K., Poguntke, R., Haddadi, H., Alomainy, A., & Schmidt, A. (2018) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173719 · Cited by 19

The influence of concurrent mobile notifications on individual responses

Turner, L. D., Allen, S. M., & Whitaker, R. M. (2019) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2019.07.011 · Cited by 22

Towards Deep Learning Models for Psychological State Prediction using Smartphone Data: Challenges and OpportunitiesPreprint

Mikelsons, G., Smith, M. D., Mehrotra, A., & Musolesi, M. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1711.06350 · Cited by 27

Comparing self reported and physiological sleep quality from consumer devices to depression and neurocognitive performance

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Sensing Eating Events in Context: A Smartphone-Only Approach

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Helping mobile apps bootstrap with fewer users

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Can We Assess Mental Health Through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation

Tsakalidis, A., Liakata, M., Damoulas, T., & Cristea, A. I. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-10997-4_25 · Cited by 19

The Case for Operating System Management of User Attention

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Opportunistic and Context-Aware Affect Sensing on Smartphones

Rana, R. K., Hume, M., Reilly, J., Jurdak, R., & Soar, J. (2016) · IEEE Pervasive Computing · doi:10.1109/mprv.2016.36 · Cited by 19

Smartphone-Based Platform for Affect Monitoring through Flexibly Managed Experience Sampling Methods

Bailón, C., Damas, M., Pomares, H., Sanabria, D., Perakakis, P., Goicoechea, C., & Baños, O. (2019) · Sensors · doi:10.3390/s19153430 · Cited by 19

A Survey on Mobile Social Signal Processing

Palaghias, N., Hoseinitabatabaei, S. A., Nati, M., Gluhak, A., & Moessner, K. (2016) · ACM Computing Surveys · doi:10.1145/2893487 · Cited by 19

Loneliness Recognition Based on Mobile Phone Data

Li, Z., Shi, D., Wang, F., & Liu, F. (2016) · International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE) · doi:10.2991/isaeece-16.2016.34 · Cited by 16

Evidence to support common application switching behaviour on smartphones

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How Do You Feel Online

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Predicting Subjective Well-Being by Smartphone Usage Behaviors

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Towards Unobtrusive Mental Well-Being Monitoring for Independent-Living Elderly

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Automatic Tracking of Behavior With Smartphones: Potential for Behavior Change Interventions

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Finding critical features for predicting quality of life in tablet-based serious games for dementia

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Exploiting the Use of Ensemble Classifiers to Enhance the Precision of User's Emotion Classification

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‘Smartphine': Supporting students' well-being according to their calendar and mood

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Toward a proposed framework for mood recognition using LSTM Recurrent Neuron Network

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Design Implications for One-Way Text Messaging Services that Support Psychological Wellbeing

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Cluster-based approach to improve affect recognition from passively sensed data

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