The design of a novel feedback sensor system with wireless implantable polymer MEMS sensors for detecting and wirelessly transmitting physiological data that can be used for the diagnosis and treatment of various neurological disorders, such as Parkinson's disease, epilepsy, head injury, stroke, hydrocephalus, changes in pressure, patient movements, and tremors is presented in this paper. The sensor system includes MEMS gyroscopes, accelerometers, and
pressure sensors. This feedback sensor system focuses on the development and integration of implantable systems with various wireless sensors for medical applications, particularly for the Parkinson's disease. It is easy to integrate and modify the sensor network feed back system for other neurological disorders mentioned above. The monitoring and control of tremor in Parkinson's disease can be simulated on a skeleton via wireless telemetry system communicating with electroactive polymer actuator, and microsensors attached to the skeleton hand and legs. Upon sensing any abnormal motor activity which represent the characteristic rhythmic motion of a typical Parkinson's (PD) patient, these sensors will generate necessary control pulses which will be transmitted to a hat sensor system on the skeleton head. Tiny inductively coupled antennas attached to the hat sensor system can receive these control pulses,
demodulate and deliver it to actuate the parts of the skeleton to control the abnormal motor activity. This feedback sensor system can further monitor and control depending on the amplitude of the abnormal motor activity. This microsystem offers cost effective means of monitoring and controlling of neurological disorders in real PD patients. Also, this network system offers a remote monitoring of the patients conditions without visiting doctors office or hospitals. The data can be monitored using PDA and can be accessed using internet (or cell phone). Cellular phone technology will allow a health care worker to be automatically notified if monitoring indicates an emergency situation. The main advantage of such system is that it can effectively monitor large number of patients at the same time, which
helps to compensate the present shortage of health care workers.