Ubiquitous physiological monitoring will be a key driving force in the upcoming wireless health revolution. Cardiac and brain signals in the form of ECG and EEG are two critical health indicators that directly benefit from long -term monitoring. Despite advancements in wireless technology and electronics miniaturization, however, the use of wireless home ECG/EEG monitoring is still limited by the inconvenience and discomfort of wet, contact electrodes. This research focuses on the development of non-contact electrodes, which do not require direct electrical skin contact as a patient-friendly alternative and begins with a review of the field. Early attempts at building non-contact sensors using off-the-shelf commercial components demonstrated the feasibility of building low-cost, wireless, wearable ECG and EEG monitoring systems. As part of this early work, it was discovered that the interface noise from the insulating medium between body and sensor was often dominant, contributing significant new knowledge in this field. Further research revealed that discrete amplifiers contained many limitations, especially regarding frequency response and noise that were difficult to surmount. Previous implementations known in the literature required extensive manual tuning and calibration in order to boost the input impedance of discrete amplifiers, an imperfect and tedious process. To overcome the challenges with using discrete components, a fully custom analog sensor front- end was developed, achieving input impedances and frequency responses far exceeding than what was previously possible, all completely without the need for manual adjustment. Validation of this sensor in ECG applications show that it easily meets medical grade frequency response specifications and attains closer signal correlation to adhesive wet electrodes. Neural applications of this sensor were also explored and validated within an EEG (stead state visual evoked potential) brain-computer interface and benchmarked against dry and wet sensors. Successful real-time control of a computer, to a degree never before demonstrated with non-contact sensors, was achieved with the electrodes placed on top of hair, completely without gels or skin preparation. Additional sensor applications including EOG eye tracking and low- power integrated, focal-plane video compression are also discussed

Traditional approaches for neurological rehabilitation of patients affected with movement disorders, such as Parkinson's disease (PD), dystonia, and essential tremor (ET) consist mainly of oral medication, physical therapy, and botulinum toxin injections. Recently, the more invasive method of deep brain stimulation (DBS) showed significant improvement of the physical symptoms associated with these disorders. In the past several years, the adoption of feedback control theory helped DBS protocols to take into account the progressive and dynamic nature of these neurological movement disorders that had largely been ignored so far. As a result, a more efficient and effective management of PD cardinal symptoms has emerged. In this paper, we review closed-loop systems for rehabilitation of movement disorders, focusing on PD, for which several invasive and noninvasive methods have been developed during the last decade, reducing the complications and side effects associated with traditional rehabilitation approaches and paving the way for tailored individual therapeutics. We then present a novel, transformative, noninvasive closed-loop framework based on force neurofeedback and discuss several future developments of closed-loop systems that might bring us closer to individualized solutions for neurological rehabilitation of movement disorders.