[HTML][HTML] From smartphone data to clinically relevant predictions: A systematic review of digital phenotyping methods in depression
Background Smartphone-based digital phenotyping enables potentially clinically relevant
information to be collected as individuals go about their day. This could improve monitoring …
information to be collected as individuals go about their day. This could improve monitoring …
Uncovering social states in healthy and clinical populations using digital phenotyping and Hidden Markov Models
Brain related disorders are characterised by observable behavioural symptoms.
Smartphones can passively collect objective behavioural data, avoiding recall bias. Despite …
Smartphones can passively collect objective behavioural data, avoiding recall bias. Despite …
[HTML][HTML] Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic …
Background: Passive mobile sensing provides opportunities for measuring and monitoring
health status in the wild and outside of clinics. However, longitudinal, multimodal mobile …
health status in the wild and outside of clinics. However, longitudinal, multimodal mobile …
Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing
Objective: This study aimed to explore the associations between depression severity and
wearable-measured circadian rhythms, accounting for seasonal impacts and quantifying …
wearable-measured circadian rhythms, accounting for seasonal impacts and quantifying …
[PDF][PDF] This manuscript is a preprint and has not been peer-reviewed
Passive smartphone measures hold significant potential and are increasingly employed in
psychological and biomedical research to capture an individual's behavior. These measures …
psychological and biomedical research to capture an individual's behavior. These measures …