Tinoosh Mohsenin, CSEE
Sri Harsha Konuru, CSEE
In this research, we explore a variety of ultra low-power DSP techniques for wearable biomedical devices. A blend of feature engineering and machine learning algorithms are employed and evaluated within the context of real-time classification applications. The evaluation is based on two major criteria: 1. classification accuracy and 2. algorithmic complexity (computation, memory, latency). Currently, two case studies are being explored. The first case study is the detection of seizures for epileptic patients using multi-physiological signals in an ambulatory setting. The second case study is an assistive technology that enables a user to interactive with their surroundings using a tongue-driven interface.