Abstract
In this work, an algorithm was developed to measure respiration rate for an embedded device that can be used by a field robot for relief operations. With this algorithm, the rate measurement was calculated based on direct influences of respiratory-induced intensity variation (RIIV) on blood flow in cardiovascular pathways. For this, a photoplethysmogram (PPG) sensor was used to determine changes in heartbeat frequencies. The PPG sensor readings were filtered using an Information Filter and a fast Fourier transform (FFT) to determine the state of RIIV. With a relatively light initialization, the information filter can estimate unknown variables based on a series of measurements containing noise and other inaccuracies. Therefore, this filter is suitable for application in an embedded device. For faster calculation time in the implementation, the FFT analysis was calculated only for a major peak in frequency domain. Test and measurement of respiration rate was conducted based on the device algorithm and spirometer. Heartbeat measurements were also evaluated by comparing the heartbeat data of the PPG sensor and pulse-oximeter. Based on the test, the implemented algorithm can measure the respiration rate with approximately 80% accuracy compared with the spirometer.
Highlights
In recent years, rapid technological advances have led to significant developments in the field of robotics, especially for medical purposes [1]
A medical sensory system that can determine the physical state must be implemented in a robotic system, especially one that is related to vital health conditions, such as heartbeat and respiration rate
The respiration rate is a vital biosignal state that determines the physical state of the pulmonary system, which directly influences blood flow in cardiovascular pathways
Summary
Rapid technological advances have led to significant developments in the field of robotics, especially for medical purposes [1]. From the microscopic scale to a large robotic surgery system, these developments have brought significant progress in treatment and health-care system [2,3,4,5]. Robots need to be able to locate and preliminarily determine the physical state of an injured person so that a correct course of treatment can be quickly administered by the medical help. A medical sensory system that can determine the physical state must be implemented in a robotic system, especially one that is related to vital health conditions, such as heartbeat and respiration rate. The respiration rate is a vital biosignal state that determines the physical state of the pulmonary system, which directly influences blood flow in cardiovascular pathways. By measuring the changes in blood flow or heartbeat frequencies in the cardiovascular stream, the respiration rate
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