Introduction to the special issue on IEEE NEWCAS 2017

A contactless detector is presented for evaluating hand tremors caused by exercise-induced fatigue and early Parkinson’s disease. The device consists of a spiral coil, a microcontroller, and an inductive sensor circuitry. Theory shows that the resonant frequency of the circuitry increases when the distance between the hand and the spiral coil decreases, thus small variations of distance from tremor can be detected from the changes of resonant frequencies. A mechanical hand was built for experiments to simulate human hand tremors with repeatability at a fixed frequency. The magnitudes and frequencies of the tremors in the mechanical hand were quantitatively identified using the inductive sensor. Hence, feasibility and accuracy of the contactless hand tremor detector were determined. A triaxial accelerometer was used for comparison. By comparing spectral distributions and magnitudes of the tremors, the inductive sensor performed better than the accelerometer. The detector was applied to evaluate actual hand tremors of three subjects who had undergone exercise to induce tremors. The tremor waveform amplitudes of the subjects were quantitatively analyzed by the standard deviations method. The increased signal energies of exercise-induced tremor within 8–12 Hz were confirmed. Then, a subject with early Parkinson’s disease was evaluated by the proposed hand tremor detector. The tremor magnitudes and frequencies of the patient hand were quantitatively identified within in 4–7 Hz. Therefore, the new contactless hand tremor detector can be developed as a clinical instrument for monitoring the fatigue symptoms of post-exercise and diagnosing the early Parkinson’s disease.