Tremor Class Scaling for Parkinson Disease Patients Using an Array X-Band Microwave Doppler-Based Upper Limb Movement Quantizer

Abstract

Consensus criteria for tremor classification in Parkinson’s disease (PD) patients are clinically important for automatically evaluating the PD rating scale. Wearable sensing tools with direct contact measurements can obtain physiological signals to monitor tremor symptoms. Then, machine learning algorithms (MLAs) can train the frequency-based parameters and motion features to accurately measure PD-related tremors. Noncontact measurement with customized computer information devices can also digitalize the digitized handwritten patterns with the bespoke movements that a hand makes for identifying tremor classes. However, wearable sensors need a set of multiple electrodes to be placed on a patient’s body to acquire biosignals, and the setup does not allow continuous measurement and limits the patient’s motion range. The handwritten patterns of noncontact-based methods need frequency-domain and linearization transformations. In addition, feature extraction methods and MLAs are limited in complex computations and adaptive applications. Hence, in this work, a noncontact measurement with an array X-band microwave (10 GHz) Doppler-based linear quantizer is designed to continuously measure upper limb movements for tremor class scaling. To overcome the complex computations, time-domain parametric features, including zero crossing (ZC), Willison amplitude (WAMP), and waveform length (WL) indexes, are used to extract the physical changes in the oscillation frequencies, amplitudes, and directions of tremor signals for scaling upper limb tremor (ULT) levels. In the experiments involving 10 subjects, the proposed noncontact bioradar sensor could quantify asymmetrical and irregular oscillations with a positive correlation (mean R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> > 0.85) between the three indexes (ZC, WAMP, WL) and various oscillation frequencies. The linear relationship quantizer could predict the ULT levels from 0 Hz to 8 Hz for PD patients (typical tremor frequency: 4–6 Hz). It could also map the three indexes into colored visual representation for computerized visual analysis.