title: Heart beat detection using a multimodal data coupling method.
abstract: The most straightforward method for heart beat estimation is R-peak detection based on an electrocardiogram (ECG) signal. Current R-peak detection methods do not work properly when the ECG signal is contaminated or missing, which leads to the incorrect estimation of the heart rate. This raises the need for reliable algorithms which can locate heart beats in continuous long-term multimodal data, allowing robust analysis.In this paper, three peak detectors are evaluated for heart beat detection using various cardiovascular signals. One of the peak detectors is a new general peak detector (GPD) algorithm which is applicable on ECG and other pulsatile signals to compensate for the limitation of QRS detection. This peak detector algorithm is adaptive and independently finds amplitude characteristics for every recording, while not tuned for ECG or other pulsatile signals. Three strategies, which are different disciplines of detectors, are then proposed while the fusion method remains the same in all strategies. In the first strategy, the ECG and the lowest-indexed signal of general blood pressure (BP), arterial blood pressure (ART) and pulmonary arterial pressure (PAP) are processed through gqrs and wabp (from the PhysioNet library), respectively. In the second strategy, all beats in different signals are detected by GPD. In the third strategy, ECG and other signals are processed by gqrs and GPD, respectively. In all three strategies two criteria are used in order to fuse the detections. The first criterion is based on the number of candidate detections in a specific time period, based on which signals of interest are selected. The second fusion criterion is based on the regularity of the derived intervals between subsequent candidate detections. If the number of detections in ECG and one of BP, ART and PAP signals have reasonable physiological range, a new signal is generated in which they are coupled with each other. Heart beats can more easily be detected in noisy parts of these signals using the new coupled waveform. For instance, if ECG and BP are coupled, BP pulses make the real heart beats in noisy parts of ECG detectable and ECG R-peaks make the weak BP pulses detectable in the new waveform. The proposed peak detector is developed using the MIT/BIH arrhythmia database. Furthermore, heart beat detection strategies were evaluated using the train and test datasets of PhysioNet/CinC Challenge (2014), and the overall results of the strategies are compared.
authors.affiliation: CardioVascular Research Group (CVRG), Department of Mechanical Engineering at K.N.Toosi University of Technology, Tehran, Iran.
authors.forename: M Javad
authors.initials: MJ
authors.lastname: Mollakazemi
authors.forename: S Abbas
authors.initials: SA
authors.lastname: Atyabi
authors.forename: Ali
authors.initials: A
authors.lastname: Ghaffari
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis / Q000503:physiopathology; D001794:Blood Pressure / Q000502:physiology; D001795:Blood Pressure Determination / Q000379:methods*; D016208:Databases, Factual; D004562:Electrocardiography / Q000379:methods*; D006321:Heart / Q000502:physiology*; D006339:Heart Rate; D006801:Humans; D008991:Monitoring, Physiologic / Q000379:methods; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted