From the 1 of 3 linked papers with an AI index.
3 papers
cs.AR2026
Toward Energy-Efficient and Low-Power Arrhythmia Detection for Wearable Devices
Floriaan Bulten, Yawar Rasheed, Arlene John +2
The paper proposes using reduced data precision and approximate multipliers in a deep‑learning model to lower the power consumption of wearable arrhythmia detectors while keeping h…
cs.LG2026
EEG-FuseFormer: A Transformer-Driven Feature Fusion Framework for Seizure Onset Prediction
Vigneshwar Hariharan, Chithra Reghuvaran, Arlene John +4
Epilepsy is one of the most common neurological disorders globally, characterized by recurring seizures and significantly impacting the quality of life. Despite advancements in dia…
eess.SP2024
A Review on Multisensor Data Fusion for Wearable Health Monitoring
Arlene John, Barry Cardiff, Deepu John
The growing demand for accurate, continuous, and non-invasive health monitoring has propelled multi-sensor data fusion to the forefront of healthcare technology. This review aims t…