Abstract
The vital sign monitoring through Impulse Radio Ultra-Wide Band (IR-UWB) radar provides continuous assessment of a patient’s respiration and heart rates in a non-invasive manner. In this paper, IR UWB radar is used for monitoring respiration and the human heart rate. The breathing and heart rate frequencies are extracted from the signal reflected from the human body. A Kalman filter is applied to reduce the measurement noise from the vital signal. An algorithm is presented to separate the heart rate signal from the breathing harmonics. An auto-correlation based technique is applied for detecting random body movements (RBM) during the measurement process. Experiments were performed in different scenarios in order to show the validity of the algorithm. The vital signs were estimated for the signal reflected from the chest, as well as from the back side of the body in different experiments. The results from both scenarios are compared for respiration and heartbeat estimation accuracy.
Highlights
The Ultra-Wide Band (UWB) regulations have been adopted to allow unlicensed operation in the range of 3.1 and 10.6 GHz [1]
A filter-based harmonic canceller algorithm is presented for the extraction of heart rate from the frequency transformed vital signal
We present an algorithm to find the heart rate based on the probability of occurrence our work, we present an algorithm findthe theheart heart rate based of occurrence ourInwork, we present an algorithm toto find basedon onthe theprobability probability of occurrence through certain iterations
Summary
The Ultra-Wide Band (UWB) regulations have been adopted to allow unlicensed operation in the range of 3.1 and 10.6 GHz [1]. A filter-based harmonic canceller algorithm is presented for the extraction of heart rate from the frequency transformed vital signal. It doesn’t provide any detail about dealing with the random body motions during the measurement process. In [52,53] the body state of the humans is monitored using IR-UWB radar but a strategy to overcome the effect of motion on vital sign measurements was missing in these references. The previous work regarding vital sign measurements through IR UWB has certain limitations i.e., the effect of random body motion on the vital signs has not been studied quantitatively and an algorithm for heart rate detection in the presence of strong breathing harmonics located close to the heart rate was missing.
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