2015
DOI: 10.1016/j.infrared.2015.09.005
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Contact-free measurement of respiratory rate using infrared and vibration sensors

Abstract: Respiratory rate is an essential parameter in many practical applications such as apnea detection, patient monitoring, and elderly people monitoring. In this paper, we describe a novel method and a contact-free multi-modal system which is capable of detecting human breathing activity. The multimodal system, which uses both differential pyro-electric infrared (PIR) and vibration sensors, can also estimate the respiratory rate. Vibration sensors pick up small vibrations due to the breathing activity. Similarly, … Show more

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Cited by 18 publications
(16 citation statements)
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“…We compared the error to that of produced by autocorrelation function (ACF) maximization, Fourier transform (FT), local extrema detection (LED), and the average magnitude difference function (AMDF) method [16]. Results are presented in Table I.…”
Section: Experiments and Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…We compared the error to that of produced by autocorrelation function (ACF) maximization, Fourier transform (FT), local extrema detection (LED), and the average magnitude difference function (AMDF) method [16]. Results are presented in Table I.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…In this letter, we present a noninvasive pyro-electric infrared (PIR) sensor array-based system. It is similar to the one previously developed in [16] with the difference that accelerometer is now replaced with an extra PIR sensor. Data received from the sensors are processed using the TDA method to estimate the RR.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, when the number of signal sampling points exceeds 3600 points in a fixed fire state (a sampling frequency of 6 times per second and a signal duration of 600 seconds), the program will force the execution cycle extraction. The peak amplitude of AMDF will decrease with the increase of the lag time [11]. Therefore, this paper divides the AMDF value by the number of overlapping points to suppress this downward trend, and reciprocates the non-zero amplitude to convert the valley point to the peak value.…”
Section: Signal Period Detection Methods Based On Amdfmentioning
confidence: 99%
“…Among all period detection techniques, those based on AMDF and ACF are more widely used than other methods. AMDF has the advantages of low computation complexity and high precision, but with the increase of delay, the decrease of frame overlap for its calculating will lead to the phenomenon of a falling trend [10,11]. In addition, the traditional AMDF will appear to mistake showing the location of the lowest notch besides zero point rather than showing the real period.…”
Section: Introductionmentioning
confidence: 99%