Contact-free measurement of respiratory rate using infrared and vibration sensors
buir.contributor.author | Çetin, A. Enis | |
buir.contributor.orcid | Çetin, A. Enis|0000-0002-3449-1958 | |
dc.citation.epage | 94 | en_US |
dc.citation.spage | 88 | en_US |
dc.citation.volumeNumber | 73 | en_US |
dc.contributor.author | Erden, F. | en_US |
dc.contributor.author | Alkar, A. Z. | en_US |
dc.contributor.author | Çetin, A. Enis | en_US |
dc.date.accessioned | 2016-02-08T11:02:10Z | |
dc.date.available | 2016-02-08T11:02:10Z | |
dc.date.issued | 2015 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description.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. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T11:02:10Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2015 | en |
dc.identifier.doi | 10.1016/j.infrared.2015.09.005 | en_US |
dc.identifier.issn | 1350-4495 | |
dc.identifier.uri | http://hdl.handle.net/11693/26607 | |
dc.language.iso | English | en_US |
dc.publisher | Elsevier BV | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.infrared.2015.09.005 | en_US |
dc.source.title | Infrared Physics and Technology | en_US |
dc.subject | Average magnitude difference function (AMDF) | en_US |
dc.subject | Empirical mode decomposition (EMD) | en_US |
dc.subject | Respiratory rate | en_US |
dc.subject | Vibration sensor | en_US |
dc.subject | Wavelet transform | en_US |
dc.subject | Functions | en_US |
dc.subject | Laptop computers | en_US |
dc.subject | Patient monitoring | en_US |
dc.subject | Pickups | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Ventilation exhausts | en_US |
dc.subject | Wavelet analysis | en_US |
dc.subject | Wavelet decomposition | en_US |
dc.subject | Wavelet transforms | en_US |
dc.subject | Average magnitude difference function | en_US |
dc.subject | Pir sensors | en_US |
dc.subject | Vibration sensors | en_US |
dc.subject | Signal detection | en_US |
dc.title | Contact-free measurement of respiratory rate using infrared and vibration sensors | en_US |
dc.type | Article | en_US |
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