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Respiratory Rate and Flow Waveform Estimation from Triaxial Accelerometer Data

Respiratory Rate and Flow Waveform Estimation from Triaxial Accelerometer Data,10.1109/BSN.2010.50,A. Bates,M. J. Ling,J. Mann,D. K. Arvind

Respiratory Rate and Flow Waveform Estimation from Triaxial Accelerometer Data   (Citations: 2)
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There is a strong medical need for continuous, unobstrusive respiratory monitoring, and many shortcomings to existing methods. Previous work shows that MEMS accelerometers worn on the torso can measure inclination changes due to breathing, from which a respiratory rate can be obtained. There has been limited validation of these methods. The problem of practical continuous monitoring, in which patient movement disrupts the measurements and the axis of interest changes, has also not been addressed. We demonstrate a method based on tri-axial accelerometer data from a wireless sensor device, which tracks the axis of rotation and obtains angular rates of breathing motion. The resulting rates are validated against gyroscope measurements and show high correlation to flow rate measurements using a nasal cannula. We use a movement detection method to classify periods in which the patient is static and breathing signals can be observed accurately. Within these periods we obtain a close match to cannula measurements, for both the flow rate waveform and derived respiratory rates, over multi-hour datasets obtained from wireless sensor devices on hospital patients. We discuss future directions for improvement and potential methods for estimating absolute airflow rate and tidal volume.
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    • ...Previous work by Bates et al has demonstrated an algorithm for obtaining a respiration signal of the patient at rest from triaxial accelerometer data [12]...
    • ...As previously described [12], Orient is a general purpose wireless IMU device consisting of a Freescale MMA7260QT tri-axial accelerometer, three Analog Devices ADXRS300 rate gyroscopes, and two Honeywell HMC1052 dual-axis magnetometers, combined with a Microchip dsPIC30F3014 and a 433MHz radio...
    • ...Our approach to respiratory monitoring with tri-axial accelerometer is based on our previous work [12]...

    J. Mannet al. Simultaneous Activity and Respiratory Monitoring Using an Acceleromete...

    • ...These chest wall rotations are detected by reference to gravity rather than by direct measurement of accelerations due to breathing [1]‐[4]...
    • ...In preliminary trials on hospital patients, it has been shown that with appropriate processing, this method can produce results that match closely with measurements of nasal cannula pressure and that periods of disturbance during patient measurement can be identified and removed [1]...
    • ...The most recent study in this area, by some of the authors of the present paper, proposes an algorithm to recover chest wall rotational rates from tri-axial accelerometer data [1]...
    • ...After capture the accelerometer data was processed using the method proposed in [1], which tracks the axis of breathinginduced rotation and extracts a rotational rate signal from the data...
    • ...Since in previous work the rotational rate had appeared to be a proxy for the respiratory airflow [1], we initially expected the audible inbreath periods to consistently have rotational rates in the direction associated with inhalation, here defined as being positive...
    • ...A dual threshold state-based breath detection method was given in [1] to accompany the rotational rate algorithm...

    Andrew Bateset al. Accelerometer-Based Respiratory Measurement During Speech

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