Abstract
The aim of this work is to present a method for accurately estimating heart and respiration rates under different actual conditions based on a mattress which was integrated with an optical fiber sensor. During the estimation, a ballistocardiogram (BCG) signal, which was obtained from the optical fiber sensor, was used for extracting the heart rate and the respiration rate. However, due to the detrimental effects of the differential detector, self-interference, and variation of installation status of the sensor, the ballistocardiogram (BCG) signal was difficult to detect. In order to resolve the potential concerns of individual differences and body interferences, adaptive regulations and statistical classifications spectrum analysis were used in this paper. Experiments were carried out to quantify heart and respiration rates of healthy volunteers under different breathing and posture conditions. From the experimental results, it could be concluded that (1) the heart rates of 40–150 beats per minute (bpm) and respiration rates of 10–20 breaths per minute (bpm) were measured for individual differences; (2) for the same individuals under four different posture contacts, the mean errors of heart rates were separately 1.60 ± 0.98 bpm, 1.94 ± 0.83 bpm, 1.24 ± 0.59 bpm, and 1.06 ± 0.62 bpm, in contrast, the mean errors of the polar beat device were 1.09 ± 0.96 bpm, 1.44 ± 0.99 bpm, and 1.78 ± 0.94 bpm. Furthermore, the experimental results were validated by conventional counterparts which used skin-contacting electrodes as their measurements. It was reported that the heart rate was 0.26 ± 2.80 bpm in 95% confidence intervals (± 1.96SD) in comparison with Philips sure-signs VM6 medical monitor, and the respiration rate was 0.41 ± 1.49 bpm in 95% confidence intervals (± 1.96SD) in comparison with ECG-derived respiratory (EDR) measurements for respiration rates. It was indicated that the developed system using adaptive regulations and statistical classifications spectrum analysis performed better and could easily be used under complex environments.
Highlights
In order to address the potential concerns of chronic diseases and sub-health status, the development of remote, intimate, and immediate medical treatments with extensive mobile network coverage is really significant
The results showed that the mean error in the range of a 40 to 145 heart rate within (±1.96 SD) was −0.26 ± 2.80 bpm, tests of the respiration rates were recorded by 167 groups of data measured at different intensities
A method of accurately estimating heart and respiration rates was designed under different actual conditions by the integration of an optical fiber sensor into a mattress
Summary
In order to address the potential concerns of chronic diseases and sub-health status, the development of remote, intimate, and immediate medical treatments with extensive mobile network coverage is really significant. With the coming of aged societies, the urgent need of remote, miniaturized, and portable healthcare equipment is imperative for health monitoring, adjuvant treatments, and rehabilitation exercises to every user [1,2,3]. The heart rate, which is represented by the number of contractions of the heart per minute, is closely correlated with various heart diseases, such as sinus tachycardia, heart arrhythmia, and premature ventricular contraction. As for the respiration rate, which is a parameter referring to the number of breaths per minute, it can be used as an indicator for various abnormal physical conditions such as asthma, anxiety, pneumonia, and drug abuse
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