Analysis of a low frequency MEMS capacitive accelerometer under the effect of biasing voltage for detection of Parkinsons tremor

The paper presents a comprehensive analysis of the design and simulation of a MEMS differential capacitive accelerometer optimized for the detection of tremor signals in Parkinson’s disease patients. The accelerometer design aims to address the sensing challenges at very low frequencies (< 10 Hz) associated with Parkinson’s tremors, specifically targeting the frequency range of 3.5–7.5 Hz. The design process considers various parameters to optimize the resonant frequency, mechanical stability, and sensitivity of the accelerometer. Finite element analysis (FEA) using COMSOL Multiphysics validates the design approach, demonstrating a resonant frequency of 3.5 Hz with a maximum displacement of 1.77 μm at an acceleration of 0.04 g at a biasing voltage of 10 V. This proposed design exhibits a noteworthy mechanical sensitivity of 44.25 μm and an electrical sensitivity of 1.428 nF/g, emphasizing its capacity to detect and respond to minute physical and electrical changes with high precision. Analytical models are developed to calculate the resonant frequency and effective spring constant, which further characterizes the accelerometer’s mechanical behavior. The proposed design achieves a comparable dynamic range, high sensitivity, linear response, and minimal cross sensitivity when compared with existing literature. The proposed MEMS differential capacitive accelerometer exhibits significant potential for precise measurement and quantification of tremor signals in individuals afflicted with Parkinson’s disease. By accurately capturing and analyzing these tremor signals, this accelerometer has the capacity to contribute significantly to the advancement of medical diagnosis and monitoring in the field of Parkinson’s disease.