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Found 9 papers, 1 papers with code
Incremental Semi-supervised Federated Learning for Health Inference via Mobile Sensing
We evaluate FedMobile using a real-world mobile sensing dataset for influenza-like symptom recognition.
Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline
To address this concern, in Study 1, we collected linguistic data from N=35 high socially anxious participants in a variety of social contexts, finding that digital linguistic biomarkers significantly differ between evaluative vs. non-evaluative social contexts and between individuals having different trait psychological symptoms, suggesting the likely importance of personalized approaches to detect state anxiety.
Graph Neural Networks in IoT: A Survey
The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily lives: healthcare, home, transportation, manufacturing, supply chain, and so on.
Using Ballistocardiography for Sleep Stage Classification
A practical way of detecting sleep stages has become more necessary as we begin to learn about the vast effects that sleep has on people's lives.
From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques
Mobile Sensing Apps have been widely used as a practical approach to collect behavioral and health-related information from individuals and provide timely intervention to promote health and well-beings, such as mental health and chronic cares.
Sparse Longitudinal Representations of Electronic Health Record Data for the Early Detection of Chronic Kidney Disease in Diabetic Patients
Chronic kidney disease (CKD) is a gradual loss of renal function over time, and it increases the risk of mortality, decreased quality of life, as well as serious complications.
Offline Contextual Multi-armed Bandits for Mobile Health Interventions: A Case Study on Emotion Regulation
Our experimentation shows that the proposed doubly robust offline learning algorithms performed significantly better than baseline approaches, suggesting that this type of recommender algorithm could improve emotion regulation.
Enabling Smartphone-based Estimation of Heart Rate
The promising results provide preliminary evidence of the feasibility of combining smartphone sensor data with wearable sensor data for continuous heart rate monitoring.
Cluster-based Approach to Improve Affect Recognition from Passively Sensed Data
Negative affect is a proxy for mental health in adults.
