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Found 7 papers, 0 papers with code
Transfer Learning to Detect COVID-19 Coughs with Incremental Addition of Patient Coughs to Healthy People's Cough Detection Models
Millions of people have died worldwide from COVID-19.
Discovering COVID-19 Coughing and Breathing Patterns from Unlabeled Data Using Contrastive Learning with Varying Pre-Training Domains
Rapid discovery of new diseases, such as COVID-19 can enable a timely epidemic response, preventing the large-scale spread and protecting public health.
Predicting dominant hand from spatiotemporal context varying physiological data
Health metrics from wrist-worn devices demand an automatic dominant hand prediction to keep an accurate operation.
Automatic Anomalies Detection in Hydraulic Devices
Nowadays, the applications of hydraulic systems are present in a wide variety of devices in both industrial and everyday environments.
Opportunistic Multi-Modal User Authentication for Health-Tracking IoT Wearables
While most of these external authentication techniques suffer from multiple limitations, including recall burden, human errors, or biases, researchers have started using various physiological and behavioral data, such as gait and heart rate, collected by the wearables to authenticate a wearable user implicitly with a limited accuracy due to sensing and computing constraints of wearables.
Context-Dependent Implicit Authentication for Wearable Device User
As market wearables are becoming popular with a range of services, including making financial transactions, accessing cars, etc.
Continuous Authentication of Wearable Device Users from Heart Rate, Gait, and Breathing Data
In this work, we present a context-dependent soft-biometric-based authentication system for wearables devices using heart rate, gait, and breathing audio signals.
