Approximately 20% of people diagnosed with epilepsy cannot be treated effectively. Consequently, there exists a significant need for alternative types of treatment. To aid in the effort of solving ...this problem, the authors have developed a prototype system that will monitor neuron activity to detect a seizure and terminate seizures in their initial stages. The system consists of 3 blocks: a data acquisition system, a seizure detection unit, and a stimulation device. The data acquisition system includes a detector implanted in the brain. This detector collects raw electrical waveforms that are filtered for the presence of neural action potentials by special signal processing equipment. The quantity and frequency of these neural action potentials is sent to the seizure detection unit, which employs a specially designed algorithm to detect pre-seizure activity in single neuron firing patterns. If the presence of pre-seizure activity is discovered, the seizure detection unit sends a signal to the stimulation device, which emits an electrical signal into the brainstem, thereby preventing a full seizure. This prototype is tested in rats treated with pentylenetetrazol (PZT) a known seizure inducing drug.
Approximately 20% of people diagnosed with epilepsy cannot be treated effectively. Consequently, there exists a significant need for alternative types of treatment. To aid in the effort of solving ...this problem, we developed a prototype system to detect changes in neural activity prior to the onset of a seizure. This system can be used as warning device or as part of a large system to terminate seizures in their initial stages via drug administration or nerve stimulation. The detection algorithm used data collected from intracranial electrodes. The waveforms were filtered and amplified to identify single neuron action potentials. The time of occurrence of each action potential for each neuron was then passed to a preprocessor algorithm that summed the data into 50 ms time bins. Sliding windows consisting of 128 bins for each neuron were cross-correlated. The results were summed and the variance of the cross-correlation was used as a measure of global neuron correlation. The algorithm was implemented in a PC board and tested in rats treated with pentylenetetrazol (PTZ) a known seizure inducing drug. The system was 100% effective at detecting seizures approximately 4.6 seconds before seizure onset and had a false positive rate of 0.3%.
