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Abstract

An example method and apparatus for measuring the breathing rate from the photoplethysmogram signal (PPG) uses auto-regressive modelling of the signal. The PPG signal is windowed in overlapping windows of typically 30 seconds' length, overlapping by 25 seconds, to obtain discrete sections of the signal and each section is low-pass filtered, downsampled and detrended and then AR modelled using an all-pole auto-regressive (AR) model. The AR model allows identification of the dominant frequencies in the signal and the pole corresponding to the breathing rate is identified by considering its magnitude and the breathing rate it represents. Each 30 second window gives a breathing rate estimate and use of successive windows displaced by 5 seconds results in a breathing rate estimate every 5 seconds. The time series of breathing rate estimates can be Kalman filtered to reject measurements which have a large change in magnitude or represent a large change in breathing rate. The measurements may also be fused with measurements from another sensor.

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