Development Of An EEG Recording System Available For Freely Moving Animals

Electromyography is the result of the muscle electricity both spatial and temporal,which is related with the neural control signals as well as the physiological characteristicsof muscle. These days, the study of EMG signals has been widely used in many fieldssuch as rehabilitation engineering, clinical diagnosis, kinesiology and athletics medicine.The works in this thesis have been supported by National Natural Science Foundationof China. After the introduction of the mechanism of EMG signals and the strategies toavoid noise, an optimization of the EMG signal acquisition system used for freely movinganimal is developed to meet the needs during the animal experiments. The works includesolutions of the selection of the electrode, the way of the electrode implantation, design ofthe amplifying circuit, the filtering circuit as well as the software used for the datamanagement.In this thesis, a portable data acquisition system with high precision which is suitablefor animal experiment has been developed. The system contains two parts, i.e. thehardware and the software. In the hardware design part, in order to pick up the EMGsignals, a wire electrode was selected as the recording electrode; a dual-channelinstrumentation amplifier AD8222was used to form a pre-amplifier board which islocated on the head of a rat; a typical filtering and amplifying circuit were chosen and aUSB-4716data acquisition card was brought. In the software part, two parts of work havebeen done: an algorithm for detecting the onset and offset of muscle contraction using thegeneralized likelihood ratio test (GLRT) and the programs to achieve the acquisition,filtering and data management using programming tools such as LABVIEW andMATLAB, and the programs can also achieve the mission of data acquisition and deliveryby using the data acquisition card. Finally, the thesis introduces the surgery of the implantation of the recording electrodes and the method to carry an animal experiment.The result shows that the recording system works effectively, and results that themaximum error of the onset detection is4.9%and the maximum error of the offsetdetection is4.4%shows that the algorithm for onset and offset detection of musclecontraction is practicable and effective.