The DSP Laboratory has developed and implemented algorithms for the processing of signals in diverse contexts. Several of our projects have involved processing signals from biomedical transducers, such as Blood Volume Pulse photoplethysmographs, and Electroencephalogram (EEG) and Electromyogram (EMG) electrodes.
We have applied processing to the signals from these transducers towards the development of alternate human-computer interfaces for the benefit of users with severe motor disabilities. Recently, we have worked in integra ting an infrared video eye gaze tracking system with the EMG-driven interface.
The DSP Lab has carried out research in the area of Deconvolution of the Doppler-Azimuth Radar Spectrum, by which the spatio-temporal data obtained from a multi-element radar array is enhanced to obtain a more defined characterization of objects of interest, while minimizing the effects of unwanted components.
The DSP Lab has also been involved in applied research for the local manufacturing industry. We have developed a self-tuning motion control system for a local Computerized Numerical Control (CNC) company. In this project, a DSP chip executes an algorithm to obtain a dynamic model of a CNC machine (such as a lathe or milling machine). It is then possible to implement a real-time inverse controller to compensate for the dynamic characteristics of the plant, yielding improved performance.