Contact-free measurement of respiratory rate using infrared and vibration sensors

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Date

2015

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier Science Bv

Research Projects

Organizational Units

Organizational Unit
Department of Electrical & Electronics Engineering
Department of Electrical and Electronics Engineering (EE) offers solid graduate education and research program. Our Department is known for its student-centered and practice-oriented education. We are devoted to provide an exceptional educational experience to our students and prepare them for the highest personal and professional accomplishments. The advanced teaching and research laboratories are designed to educate the future workforce and meet the challenges of current technologies. The faculty's research activities are high voltage, electrical machinery, power systems, signal and image processing and photonics. Our students have exciting opportunities to participate in our department's research projects as well as in various activities sponsored by TUBİTAK, and other professional societies. European Remote Radio Laboratory project, which provides internet-access to our laboratories, has been accomplished under the leadership of our department with contributions from several European institutions.

Journal Issue

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, PIR sensors pick up the thoracic movements. Sensor signals are sampled using a microprocessor board and analyzed on a laptop computer. Sensor signals are processed using wavelet analysis and empirical mode decomposition (EMD). Since breathing is almost periodic, a new multi-modal average magnitude difference function (AMDF) is used to detect the periodicity and the period in the processed signals. By fusing the data of two different types of sensors we achieve a more robust and reliable contact-free human breathing activity detection system compared to systems using only one specific type of sensors. (C) 2015 Elsevier B.V. All rights reserved.

Description

Erden, Fatih/0000-0002-1708-3063; Alkar, Ali Ziya/0000-0002-5880-2423

Keywords

Average magnitude difference function (AMDF), Empirical mode decomposition (EMD), PIR sensor, Respiratory rate, Vibration sensor, Wavelet transform

Turkish CoHE Thesis Center URL

Citation

20

WoS Q

Q2

Scopus Q

Q2

Source

Volume

73

Issue

Start Page

88

End Page

94

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