The main research objectives include: design of electronic components and subsystems of ES, including sensorics, signal processing, data communications, and energy supply problems.
Background. Sensor signal processing in ES has obtained extremely versatile features. Complicated algorithms and powerful computing resources are required. At the same time the tasks of ubiquitous computing require tiny devices fulfilling simple algorithms collectively. Well balanced HW/SW and analogue/digital partitioning and adequate digitizing of sensor signals will be an important issue in developing the future low-power processors. Implantable and wearable medical devices require processors with low power and energy consumption, as well as other battery powered exploitations. The efficiency of algorithms depends on the knowledge about the processing function and about signals to be processed, as well as on the art and skills to utilize this knowledge. Developing of function/application specific signal processors with reconfigurable architectures is unavoidable mainstream in this case .
Visions and goals. We will focus our research on mixed signal (analogue/digital) specific processors which will make a revolution in development of implantable and wearable biomedical technology where the energy supply problems have to be solved effectively, e.g. using human body heat and other energy harvesting methods. Another research objective will be BioMEMS, the next generation of biomedical devices requiring novel, function specific, and ultra low power signal processing methods and means with reduced complexity. Impedance spectroscopy will become an effective sensoric tool for getting the biological and physiological information from living matter. Reducing of digital complexity will depend mainly on the processing algorithms, whereas the methods and algorithms for joint time-frequency analysis will determine greatly the success of embedded signal processing.
The main research topics described are: (1) methods for signal and data acquisition; (2) signal processing methods and tools; (3) development of reconfigurable processor architectures; (4) impedance spectroscopy with applications in bio- and medical technology.