Cummins, Nicholas

AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition

Ringeval, F., Schuller, B., Valstar, M., Cummins, N., Cowie, R., Tavabi, L., Schmitt, M., Alisamir, S., Amiriparian, S., Messner, E.-M., et al. (2019) · Proceedings of the 9th International on Audio/Visual Emotion Challenge and Workshop

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 409

Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19

Sun, S., Folarin, A. A., Ranjan, Y., Rashid, Z., Conde, P., Stewart, C., Cummins, N., Matcham, F., Dalla Costa, G., Simblett, S., et al. (2020) · Journal of Medical Internet Research

Human Mobility and Location-Based AnalysisCOVID-19 Digital Contact Tracing

Cited by 256

Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study

Zhang, Y., Folarin, A. A., Sun, S., Cummins, N., Ranjan, Y., Rashid, Z., Conde, P., Stewart, C., Laiou, P., Matcham, F., et al. (2021) · JMIR mHealth and uHealth

Mental Health Research TopicsDigital Mental Health Interventions

Cited by 68

Strength modelling for real-worldautomatic continuous affect recognition from audiovisual signals

Han, J., Zhang, Z., Cummins, N., Ringeval, F., & Schuller, B. (2017) · Image and Vision Computing

Emotion and Mood RecognitionSpeech and Audio Processing

Cited by 53

The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity

Siddi, S., Bailon, R., Giné-Vázquez, I., Matcham, F., Lamers, F., Kontaxis, S., Laporta, E., Garcia, E., Lombardini, F., Annas, P., et al. (2023) · Psychological Medicine

Heart Rate Variability and Autonomic ControlMental Health Research Topics

Cited by 31