Non-Contact Breathing Monitoring Using Sleep Breathing Detection Algorithm (SBDA) Based on UWB Radar Sensors

Abstract

Ultra-wideband radar application for sleep breathing monitoring is hampered by the difficulty of obtaining breathing signals for non-stationary subjects. This occurs due to imprecise signal clutter removal and poor body movement removal algorithms for extracting accurate breathing signals. Therefore, this paper proposed a Sleep Breathing Detection Algorithm (SBDA) to address this challenge. First, SBDA introduces the combination of variance feature with Discrete Wavelet Transform (DWT) to tackle the issue of clutter signals. This method used Daubechies wavelets with five levels of decomposition to satisfy the signal-to-noise ratio in the signal. Second, SBDA implements a curve fit based sinusoidal pattern algorithm for detecting periodic motion. The measurement was taken by comparing the R-square value to differentiate between chest and body movements. Last but not least, SBDA applied the Ensemble Empirical Mode Decomposition (EEMD) method for extracting breathing signals before transforming the signal to the frequency domain using Fast Fourier Transform (FFT) to obtain breathing rate. The analysis was conducted on 15 subjects with normal and abnormal ratings for sleep monitoring. All results were compared with two existing methods obtained from previous literature with Polysomnography (PSG) devices. The result found that SBDA effectively monitors breathing using IR-UWB as it has the lowest average percentage error with only 6.12% compared to the other two existing methods from past research implemented in this dataset.

Systematic Literature Review Regarding Heart Rate and Respiratory Rate Measurement by Means of Radar Technology

“…In 74 studies, both the heart rate and the respiratory rate were measured [2,5,10,12,. In 14 studies, only the respiratory rate was considered [3,11,13,[84][85][86][87][88][89][90][91][92][93][94], and in 26 studies, only the heart rate . Table 2 shows the number of acquisitions of the vital parameters considered in the experiments in relation to the radar type.…”

“…The number of test persons in the studies ranged from one test person [10,12,24,42,43,49,60,[85][86][87]108] to 212 test persons [98,99]. Five of the experiments were conducted with children and babies [17,45,84,88,89], eleven with miscellaneous patient groups [5,17,21,39,41,51,88,89,91,93,112] and one with animals [38], while seven experiments additionally measured a model [37,42,44,60,85,97] and two exclusively measured a model [90,92]. In 74 studies [2,3,[10][11][12][13]16,17,20,[22]…”

“…The test persons' positions relative to the radar were as follows: lying in 36 studies [2,3,5,13,17,23,28,29,[31][32][33][34]44,45,50,51,53,55,58,62,77,82,84,88,91,93,94,99,[104][105][106][107]110,112,114,120]; sitting in 60 studies [3,10,11,14-17,19,20,22,24,25,31,36,40,42,46-49,52-54,56,58-61,63,65,66,68-76, 78-80,83,85,86,88,89,96,97,100-103,109-111,113,117,118]; standing in 14 studies [3,21,26,27,39,57,72,76,81,87,110,113,…”

Advances in Non-Invasive Neuromodulation: Designing Closed-Loop Devices for Respiratory-Controlled Transcutaneous Vagus Nerve Stimulation

“…Conversely, methods for processing respiratory signals are commonly observed in respiratory performance tests and polysomnography examinations. Some studies have proposed algorithms that utilize tools like discrete wavelet transform (DWT) and FFT for sleep respiration detection [ 18 ]. The accurate detection of the end of inspiration and the start of expiration has been investigated by other researchers as well [ 14 , 19 ].…”

Non-Contact VITAL Signs Monitoring of a Patient Lying on Surgical Bed Using Beamforming FMCW Radar

“…Thanks to the demand for sensing remotely, the radar sensor has received attention and started entering the industry market. In the healthcare industry, using the technologies based on monitoring vital signs and movements, radar sensors have been applied to fall detection [ 10 , 11 , 12 ], vital sign monitoring, and sleep monitoring [ 13 , 14 , 15 , 16 , 17 ]. As well, beamforming imaging radar is applied to cancer diagnoses [ 18 , 19 , 20 ].…”