Remote monitoring of cardiorespiratory signals from a hovering unmanned aerial vehicle.
Background: Remote physiological measurement might be very useful for biomedical diagnostics and monitoring. This study presents an efficient method for remotely measuring heart rate and respiratory rate from video captured by a hovering unmanned aerial vehicle (UVA). The proposed method estimates h...
| Publicado en: | BioMedical Engineering OnLine Vol. 16; pp. 1 - 21 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts tracings Journal Article |
| Publicado: |
BioMed Central
8/8/2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=124552223&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 124552223 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1475925X 1CGX jtl: BioMedical Engineering OnLine issn: 1475925X maglogo: N pubinfo: dt: 8/8/2017 vid: 16 pid: 24147 pub: BioMed Central artinfo: ui: 124552223 124552223 NLM28789685 124552223 10.1186/s12938-017-0395-y NLM28789685 124552223 ppf: 1 ppct: 20 formats: tig: atl: Remote monitoring of cardiorespiratory signals from a hovering unmanned aerial vehicle. aug: au: Al-Naji, Ali Perera, Asanka G. Chahl, Javaan affil: School of Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia sug: subj: Telemetry Equipment and Supplies Heart Rate Monitoring, Physiologic Equipment and Supplies Respiration Adolescence Child Female Child, Preschool Adult Signal Processing, Computer Assisted Young Adult Male Human Adolescent: 13-18 years Child: 6-12 years Child, Preschool: 2-5 years Adult: 19-44 years Female Male ab: Background: Remote physiological measurement might be very useful for biomedical diagnostics and monitoring. This study presents an efficient method for remotely measuring heart rate and respiratory rate from video captured by a hovering unmanned aerial vehicle (UVA). The proposed method estimates heart rate and respiratory rate based on the acquired signals obtained from video-photoplethysmography that are synchronous with cardiorespiratory activity.Methods: Since the PPG signal is highly affected by the noise variations (illumination variations, subject's motions and camera movement), we have used advanced signal processing techniques, including complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and canonical correlation analysis (CCA) to remove noise under these assumptions.Results: To evaluate the performance and effectiveness of the proposed method, a set of experiments were performed on 15 healthy volunteers in a front-facing position involving motion resulting from both the subject and the UAV under different scenarios and different lighting conditions.Conclusion: The experimental results demonstrated that the proposed system with and without the magnification process achieves robust and accurate readings and have significant correlations compared to a standard pulse oximeter and Piezo respiratory belt. Also, the squared correlation coefficient, root mean square error, and mean error rate yielded by the proposed method with and without the magnification process were significantly better than the state-of-the-art methodologies, including independent component analysis (ICA) and principal component analysis (PCA). pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts tracings Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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