High-resolution detection of sustained ventricular and supraventricular tachycardia through FPGA-based fuzzy processing of ECG signal.
The paper presents a field-programmable gate array (FPGA)-based fast processing system with 12-channel high-resolution (24 bits) front-end for ECG signal processing. The implemented high-resolution data conversion makes the system suitable for recording of late potentials of the QRS complex in patie...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 53; no. 10; pp. 1037 - 1048 |
|---|---|
| Autor principal: | |
| Formato: | equations & formulas pictorial research tables/charts tracings Journal Article |
| Publicado: |
Springer Nature
Oct2015
|
| 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=110401382&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110401382 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Oct2015 vid: 53 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 110401382 110401382 NLM26251028 110401382 10.1007/s11517-015-1364-x NLM26251028 110401382 ppf: 1037 ppct: 11 formats: fmt: @attributes: type: P tig: atl: High-resolution detection of sustained ventricular and supraventricular tachycardia through FPGA-based fuzzy processing of ECG signal. aug: au: Roy Chowdhury, Shubhajit affil: School of Computing and Electrical Engineering, Indian Insitute of Technology Mandi, Mandi 175005 India sug: subj: Signal Processing, Computer Assisted Tachycardia, Supraventricular Diagnosis Electrocardiography Methods Tachycardia, Ventricular Diagnosis Tachycardia, Ventricular Physiopathology Equipment Design Tachycardia, Supraventricular Physiopathology Logic Diagnosis, Differential Human ab: The paper presents a field-programmable gate array (FPGA)-based fast processing system with 12-channel high-resolution (24 bits) front-end for ECG signal processing. The implemented high-resolution data conversion makes the system suitable for recording of late potentials of the QRS complex in patients prone to sustained ventricular tachycardia. The system accepts ECG signals through 12 channels and then filtered to minimize baseline wander and power-line interference. The filter outputs are connected to 12 delta-sigma ADCs. The whole ADCs work synchronously at 8 kHz sampling frequency, and their output data are transferred to an FPGA that computes online on the digitized sample values in real time and ascertains whether the patient under study suffers from ventricular tachycardia or not. In order to ascertain the QRS complex accurately in the noisy ECG signal, fuzzy entropy of the sample values has been computed and provided as an input to inverse multiquadratic radial basis function neural network. Using the standard CSE ECG database, the algorithm performed highly effectively. The performance of the algorithm in respect of QRS detection with sensitivity of 99.83 % and accuracy of 99.7 % is achieved when tested using single-channel ECG with entropy criteria. The performance of the QRS detection system has been compared and found to be better than most of the QRS detection systems available in the literature. Using the system, 200 patients have been diagnosed with an accuracy of 99 %. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts tracings Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|