Novel Multiscale Frequency Approach to Identify the Pivot Point of the Rotor1

Arunachalam, Shivaram P.; Annoni, Elizabeth M.; Mulpuru, Siva K.; Friedman, Paul A.; Tolkacheva, Elena G.

doi:10.1115/1.4033148

Cited by 14 publications

(13 citation statements)

References 4 publications

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“…A novel multiscale frequency technique was proposed for analyzing biomedical signals and successfully applied for rotor identification [9][10][11], AF and NSR discrimination [12] etc. To summarize briefly, eight Log-Gabor filters were designed and used with a relative filter bandwidth B of 2√2, one octave apart and the center frequencies for the log-Gabor filters were chosen to accommodate the frequency range of PCG signals from humans.…”

Section: Multiscale Frequency Techniquementioning

confidence: 99%

“…In this work the authors explore the previously proposed multiscale frequency (MSF) [8][9] approach that takes into account the contribution from various frequencies in PCG to yield valuable information regarding the instantaneous frequency state of the PCG. An initial feasibility study is performed using normal PCG data from Peter Bentley Heart Sounds Database.…”

Section: Introductionmentioning

confidence: 99%

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Profiling Multiscale Frequency State of Normal Phonocardiogram: Feasibility Study

Sundaram

Anjani

Balasubramani³

et al. 2019

2019 Design of Medical Devices Conference

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Phonocardiogram (PCG) signals contain very important information regarding the heart condition. Recently, several automatic detection algorithms have been explored to profile the characteristics of heart sounds to aid in disease diagnosis. However, many of these methods has been demonstrated only on clean signals with limited test data and variety of PCG signals that can accurately provide information of diagnostic importance with higher sensitivity and specificity. In this work, we propose to characterize the multiscale frequency state of the normal PCG signals that can aid in accurate profiling of PCG to discriminate from pathological conditions.

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Section: Multiscale Frequency Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Profiling Multiscale Frequency State of Normal Phonocardiogram: Feasibility Study

Sundaram

Anjani

Balasubramani³

et al. 2019

2019 Design of Medical Devices Conference

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“…Previously, the MSF approach was successfully applied to locate the pivot points of the rotors in animal hearts. [5].…”

Section: Multiscale Frequency Techniquementioning

confidence: 99%

Robust Discrimination of Normal Sinus Rhythm and Atrial Fibrillation on ECG Using a Multiscale Frequency Technique

Arunachalam

Annoni

Kapa

et al. 2017

2017 Design of Medical Devices Conference

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Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia affecting approximately 3 million Americans, and is a prognostic marker for stroke, heart failure and even death [1]. 12-lead electrocardiogram (ECG) is used to monitor normal sinus rhythm (NSR) and also detect AF. Although the persistent form of AF can be detected relatively easy, detecting paroxysmal AF is often a challenge since requiring continuous monitoring, which becomes expensive and cumbersome to collect lot of ECG data [1]. Several researchers have attempted to develop new methods to discriminate NSR and AF which are based on R-R interval analysis, linear methods, filtering, spectral analysis, statistical approaches such as entropy etc. which faces limitation of successfully detecting AF of all types with high sensitivity and specificity using short time ECG data [1][2][3]. The major issues with these approaches is that they often distort the ECG by several pre-processing steps with filters, do not provide reliable discrimination using short ECG time series data and many of them lack real-time capability that makes it difficult to trust the data for diagnosis and treatment. Both clinical and scientific communities recognize these difficulties and the necessity to develop novel methods that can enable accurate monitoring and detection of AF [2]. In addition, robust detection and classification algorithms are essential for delivering appropriate therapy for implantable cardioverter defibrillators (ICD) to provide lifesaving timely actionIn this work, the authors propose and demonstrate the application of a multiscale frequency (MSF) approach [4] for accurate detection and discrimination between AF and NSR ECG traces taken from publically available Physionet database. The MSF approach takes into account the contribution from various frequencies in ECG and thus yield valuable information regarding the chaotic nature of AF. Therefore, we demonstrate that MSF can capture the complexity of AF which is associated with higher MSF value compared with NSR thus enabling robust discrimination e AF manifests itself with numerous chaotic frequencies within the body surface ECG,. We validate the feasibility of this technique to discriminate NSR from AF. Methods Multiscale frequency techniqueHilbert transform operation on real-valued signal in combination with band-pass quadrature filters can yield MSF information by weighting the various frequency components [4]. In this work eight Log-Gabor filters were designed and used with a relative filter bandwidth B of 2√2, and one octave apart. The center frequencies for the log-Gabor filters were chosen to span a physiological range for human heart rate. A wide range of local MSF estimate can be obtained by weighted summation over the eight different filter pairs using the following equation, where is the output of the i th log-Gabor filter and is the center frequency of the first log-Gabor filter [4]. Figure 1 shows the frequency response of the 8 Log-Gabor filters with varying bandwidths used in this w...

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“…The relevant methods available in the literature for locating rotors involve deterministic, noniterative solutions using time-domain and frequency-domain characteristics [54][55][56][57][58]. The developed method uses a Bayesian filtering approach to search for the rotors by iteratively guiding an MPDC toward the center of a rotor.…”

Section: Computer-aided Technologies -Applications In Engineering Andmentioning

confidence: 99%

“…Several methods were introduced to help map rotors using engineering techniques in both time and frequency domain [54][55][56][57][58]. Some of these methods are specifically designed to use conventional MPDCs such as a Lasso catheter, aiming to outperform the limitations of the current EP systems available for identifying rotors.…”

Section: Computer-aided Technologies For Atrial Fibrillationmentioning

confidence: 99%

Computer-Aided Clinical Decision Support Systems for Atrial Fibrillation

Ganesan¹,

Sterling²,

Ladavich³

et al. 2016

Computer-Aided Technologies - Applications in Engineering and Medicine

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Clinical decision support systems (clinical DSSs) are widely used today for various clinical applications such as diagnosis, treatment, and recovery. Clinical DSS aims to enhance the end-to-end therapy management for the doctors, and also helps to provide improved experience for patients during each phase of the therapy. The goal of this chapter is to provide an insight into the clinical DSS associated with the highly prevalent heart rhythm disorder, atrial fibrillation (AF). The use of clinical DSS in AF management is ubiquitous, starting from detection of AF through sophisticated electrophysiology treatment procedures, all the way to monitoring the patient's health during follow-ups. Most of the software associated with AF DSS are developed based on signal processing, image processing, and artificial intelligence techniques. The chapter begins with a brief description of DSS in general and then introduces DSS that are used for various clinical applications. The chapter continues with a background on AF and some relevant mechanisms. Finally, a couple of clinical DSS used today in regard with AF are discussed, along with some proposed methods for potential implementation of clinical DSS for detection of AF, prediction of an AF treatment outcome, and localization of AF targets during a treatment procedure.

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Novel Multiscale Frequency Approach to Identify the Pivot Point of the Rotor1

Cited by 14 publications

References 4 publications

Profiling Multiscale Frequency State of Normal Phonocardiogram: Feasibility Study

Profiling Multiscale Frequency State of Normal Phonocardiogram: Feasibility Study

Robust Discrimination of Normal Sinus Rhythm and Atrial Fibrillation on ECG Using a Multiscale Frequency Technique

Computer-Aided Clinical Decision Support Systems for Atrial Fibrillation

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