Design and analysis of proof mass based micro sensor for early detection of Parkinson’s disease

  • Authors

    • G.R.K Prasad
    • Syed Shameem
    • N. Srinivasulu
    • C. Renukavalli
    • B. Manasa
    • P. S. Srinivas Babu
    2017-12-31
    https://doi.org/10.14419/ijet.v7i1.5.9137
  • MEMS, Parkinson’s Disease, frequency, tremor, Eigen Frequency, Amplifier.

  • Abstract

    Micro Electro Mechanical System (MEMS) is the promising technology in bio-medical engineering which reduces the cost, sensitivity and accuracy of the devices. A Novel structure is proposed using MEMS technology in this paper. The structure comprises of a proof mass which is movable and four arms or limbs with a torus of 900 revolution angle. The four edges of the torus are fixed. A fixed plate is kept on the top of the proof mass to measure the capacitance and output voltage of the proposed MEMS sensor. The sensor is designed for a value of 0.4g to 0.8g. The simulated values are correlated with the theoretical values. The proposed design accurately measures tremor frequency which is in the range of 4Hz to 7Hz. The proof mass in the structure moves up and down when the device is attached to finger tip of the patient because the resting tremor or pill rolling tremor is the preliminary and basic detection symptom of Parkinson’s disease. When the structure is connected to fingertip, variation in Eigen Frequency, output voltage and capacitance is measured. An amplifier is designed with a gain of 103dB and verified with the voltage so obtained from the output of the proposed sensor is 100 milli volts. There is a variation of 5% change in capacitance from theoretical to simulated values. Similarly, 8% variation in voltage. The displacement sensitivity is increased by 10%. The design is simulated using FEM tool COMSOL Multiphysics.

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  • How to Cite

    Prasad, G., Shameem, S., Srinivasulu, N., Renukavalli, C., Manasa, B., & Srinivas Babu, P. S. (2017). Design and analysis of proof mass based micro sensor for early detection of Parkinson’s disease. International Journal of Engineering & Technology, 7(1.5), 146-151. https://doi.org/10.14419/ijet.v7i1.5.9137

    Received date: 2018-01-11

    Accepted date: 2018-01-11

    Published date: 2017-12-31