An adaptive real-time beat detection method for continuous pressure signals.
A novel adaptive real-time beat detection method for pressure related signals is proposed by virtue of an enhanced mean shift (EMS) algorithm. This EMS method consists of three components: spectral estimates of the heart rate, enhanced mean shift algorithm and classification logic. The Welch power s...
| Publicado en: | Journal of Clinical Monitoring & Computing Vol. 30; no. 5; pp. 715 - 726 |
|---|---|
| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Oct2016
|
| 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=118091206&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 118091206 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13871307 OHC jtl: Journal of Clinical Monitoring & Computing issn: 13871307 maglogo: N pubinfo: dt: Oct2016 vid: 30 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 118091206 118091206 NLM26362452 10.1007/s10877-015-9770-z NLM26362452 118091206 ppf: 715 ppct: 11 formats: fmt: @attributes: type: P tig: atl: An adaptive real-time beat detection method for continuous pressure signals. aug: au: Liu, Xiaochang Wang, Gaofeng Liu, Jia affil: School of Electronic Information , Wuhan University , Wuhan 430072 China sug: subj: Blood Pressure Determination Methods Monitoring, Physiologic Methods Oximetry Methods Algorithms Heart Rate Decision Making Oxygen Signal Processing, Computer Assisted Statistics Diagnosis, Computer Assisted Methods Calibration Intracranial Pressure Blood Pressure Time Factors Models, Statistical Predictive Value of Tests Arterial Pressure ab: A novel adaptive real-time beat detection method for pressure related signals is proposed by virtue of an enhanced mean shift (EMS) algorithm. This EMS method consists of three components: spectral estimates of the heart rate, enhanced mean shift algorithm and classification logic. The Welch power spectral density method is employed to estimate the heart rate. An enhanced mean shift algorithm is then applied to improve the morphologic features of the blood pressure signals and detect the maxima of the blood pressure signals effectively. Finally, according to estimated heart rate, the classification logic is established to detect the locations of misdetections and over detections within the accepted heart rate limits. The parameters of the algorithm are adaptively tuned for ensuring its robustness in various heart rate conditions. The performance of the EMS method is validated with expert annotations of two standard databases and a non-invasive dataset. The results from this method show that the sensitivity (Se) and positive predictivity (+P) are significantly improved (i.e., Se > 99.45 %, +P > 98.28 %, and p value 0.0474) by comparison with the existing scheme from the previously published literature. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|