Blood glucose level prediction based on support vector regression using mobile platforms.

The correct treatment of diabetes is vital to a patient's health: Staying within defined blood glucose levels prevents dangerous short- and long-term effects on the body. Mobile devices informing patients about their future blood glucose levels could enable them to take counter-measures to prevent hypo or hyper periods. Previous work addressed this challenge by predicting the blood glucose levels using regression models.

Wearable Real-Time Skateboard Trick Visualization and Its Community Perception.

Motion visualization is an attractive way to provide support for a range of recreational and competitive sports. In skateboarding, sensor technology in particular can help visualization systems capture the motion of athletes to provide relevant information to athletes, judges, and spectators. This article describes the authors' proposed application of a 9D inertial-magnetic measurement unit (IMMU) based real-time trick classification and visualization system.

Wearable real-time ecg monitoring with emergency alert system for scuba diving.

Medical diagnosis is the first level for recognition and treatment of diseases. To realize fast diagnosis, we propose a concept of a basic framework for the underwater monitoring of a diver's ECG signal, including an alert system that warns the diver of predefined medical emergency situations. The framework contains QRS detection, heart rate calculation and an alert system.