A New Scheme for Determination of Respiration Rate in Human Being using MEMS Based Capacitive Pressure Sensor: Simulation Study

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic

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VOLUME 7 , ISSUE 5 (December 2014) > List of articles

Special issue ICST 2014

A New Scheme for Determination of Respiration Rate in Human Being using MEMS Based Capacitive Pressure Sensor: Simulation Study

Madhurima Chattopadhyay / Deborshi Chakraborty

Keywords : MEMS capacitive nasal sensor, diaphragm deflection, respiration rate (RR), oscillator, sensitivity, Finite Element Analysis, Boundary Element Analysis

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 5, Pages 1-5, DOI: https://doi.org/10.21307/ijssis-2019-083

License : (CC BY-NC-ND 4.0)

Published Online: 15-February-2020

ARTICLE

ABSTRACT

In this paper, a MEMS based capacitive nasal sensor system for measuring Respiration Rate (RR) of human being is developed. At first two identical diaphragm based MEMS capacitive nasal sensors are designed and virtually fabricated. A proposed schematic of the system consists of signal conditioning circuitry alongwith the sensors is described here. In order to measure the respiration rate the sensors are mounted below Right Nostril (RN) and Left Nostril (LN), in such a way that the nasal airflow during inspiration and expiration impinge on the sensor diaphragms. Due to nasal airflow, the designed square diaphragm of the sensor is being deflected and thus induces a corresponding change in the original capacitance value. This change in capacitance value is to be detected by a correlateddouble-sampling (CDS) capacitance-to-voltage converter is designed for a precision interface with a MEMS capacitive pressure sensor, followed by an amplifier and a  differential cyclic ADC to digitize the pressure information. The designed MEMS based capacitive nasal sensors is capable of identifying normal RR (18.5±1.5 bpm) of human being. The design of sensors and its characteristics analysis are performed in a FEA/BEA based virtual simulation platform.

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