[HTML][HTML] Correlations between objective behavioral features collected from mobile and wearable devices and depressive mood symptoms in patients with affective …
Background: Several studies have recently reported on the correlation between objective
behavioral features collected via mobile and wearable devices and depressive mood …
behavioral features collected via mobile and wearable devices and depressive mood …
[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 …
Predicting symptoms of depression and anxiety using smartphone and wearable data
Background: Depression and anxiety are leading causes of disability worldwide but often
remain undetected and untreated. Smartphone and wearable devices may offer a unique …
remain undetected and untreated. Smartphone and wearable devices may offer a unique …
Tracking depression dynamics in college students using mobile phone and wearable sensing
There are rising rates of depression on college campuses. Mental health services on our
campuses are working at full stretch. In response researchers have proposed using mobile …
campuses are working at full stretch. In response researchers have proposed using mobile …
Algorithms that remember: model inversion attacks and data protection law
Many individuals are concerned about the governance of machine learning systems and the
prevention of algorithmic harms. The EU's recent General Data Protection Regulation …
prevention of algorithmic harms. The EU's recent General Data Protection Regulation …
Deepmood: Forecasting depressed mood based on self-reported histories via recurrent neural networks
Depression is a prevailing issue and is an increasing problem in many people's lives.
Without observable diagnostic criteria, the signs of depression may go unnoticed, resulting …
Without observable diagnostic criteria, the signs of depression may go unnoticed, resulting …
GLOBEM dataset: multi-year datasets for longitudinal human behavior modeling generalization
Recent research has demonstrated the capability of behavior signals captured by
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
[HTML][HTML] Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis
Depression is a prevalent mental disorder. Current clinical and self-reported assessment
methods of depression are laborious and incur recall bias. Their sporadic nature often …
methods of depression are laborious and incur recall bias. Their sporadic nature often …
Leveraging collaborative-filtering for personalized behavior modeling: a case study of depression detection among college students
The prevalence of mobile phones and wearable devices enables the passive capturing and
modeling of human behavior at an unprecedented resolution and scale. Past research has …
modeling of human behavior at an unprecedented resolution and scale. Past research has …
Leveraging routine behavior and contextually-filtered features for depression detection among college students
The rate of depression in college students is rising, which is known to increase suicide risk,
lower academic performance and double the likelihood of dropping out of school. Existing …
lower academic performance and double the likelihood of dropping out of school. Existing …