Stephen is heading up the system-level design of the demonstrator with a number of other members of EEDSP. The aim of the system is to advance the methods currently used in ambulatory monitoring of biomedical signals. Currently, sensors detect signals, such as EEG, ECG, activity levels, etc and save them to a hard disk or flash memory. This leads to large, power hungry devices, latency in treatment and excessive time spent analysing data by medical staff. The aims of this demonstrator are to enhance the devices by using efficient algorithms to increase battery life, reduce size and improve the features and information provided to the medical staff in order to reduce analysis time and workload.
In order for this to be realised, algorithms and constraints tested in simulation are implemented on a real-time DSP processor to be evaluated. Benchmark power and time measurements have been taken for a basic system and improvements are sought through the alteration of algorithms, signal properties and information flow. This is the point where research from around the group is integrated together to create a prototype smart, physiological signal analysis tool. A system has been designed incorporating an Analog Devices Blackfin DSP processor, Analog Devices Sigma-Delta ADC at the front end, SDRAM and Bluetooth communication. This system has the power and scope to test various implementations of EEDSP algorithms.