An Ultra-Low Power Reconfigurable Biomedical AI Processor With Adaptive Learning for Versatile Wearable Intelligent Health Monitoring.

Wearable intelligent health monitoring devices with on-device biomedical AI processor can be used to detect the abnormity in users' biomedical signals (e.g., ECG arrythmia classification, EEG-based seizure detection).

A High Accuracy & Ultra-Low Power ECG-Derived Respiration Estimation Processor for Wearable Respiration Monitoring Sensor.

The respiratory rate is widely used for evaluating a person's health condition. Compared to other invasive and expensive methods, the ECG-derived respiration estimation is a more comfortable and affordable method to obtain the respiration rate. However, the existing ECG-derived respiration estimation methods suffer from low accuracy or high computational complexity.

4D patient dose reconstruction using online measured EPID cine images for lung SBRT treatment validation.

Purpose: This study aims to develop an EPID-guided 4D patient dose reconstruction framework and to investigate its feasibility for lung SBRT treatment validation.

Methods: Both the beam apertures and tumor movements were detected based on the continuously acquired EPID images during the treatment. Instead of directly using the transit photon fluence measured by the EPID, this method reconstructed the entrance fluence with the measured beam apertures and the delivered MUs.