Book ChapterDOI
Evaluation of Algorithms for Automatic Classification of Heart Sound Signals
Ricardo Enrique Pérez-Guzmán,Rodolfo García-Bermúdez,Fernando Rojas-Ruiz,Ariel Céspedes-Pérez,Yudelkis Ojeda-Riquenes +4 more
- pp 536-545
Reads0
Chats0
TLDR
Results show that an adequate preprocessing of data and subsequent feature selection may improve the performance of machine learning and classification techniques.Abstract:
Auscultation is the primary tool for detection and diagnosis of cardiovascular diseases in hospitals and home visits. This fact has led in the recent years to the development of automatic methods for heart sound classification, thus allowing for detecting cardiovascular pathologies in an effective way. The aim of this paper is to review recent methods for automatic classification and to apply several signal processing techniques in order to evaluate them in the PhysioNet/CinC Challenge 2016 results. For this purpose, the records of the open database PysioNet/Computing are modified by segmentation or filtering methods and the results were tested using the challenge best ranked algorithms. Results show that an adequate preprocessing of data and subsequent feature selection may improve the performance of machine learning and classification techniques.read more
Citations
More filters
Journal ArticleDOI
A Novel Cardiac Auscultation Monitoring System Based on Wireless Sensing for Healthcare
TL;DR: A novel wireless sensing system to monitor and analyze cardiac condition is proposed, which sends the information to the caregiver as well as a medical practitioner with an application of the Internet of Things (IoT).
Journal ArticleDOI
Multi-centroid diastolic duration distribution based HSMM for heart sound segmentation
TL;DR: An extended logistic regression-HSMM algorithm using the proposed duration model is presented for the heart sound segmentation and the total variation filter is used to attenuate the effect of noises and emphasize the fundamental heart sounds.
Journal ArticleDOI
Heartbeat Monitoring and Alert System Using GSM Technology
TL;DR: This system proposes continuous, real time, remote, safe and accurate monitoring of the heartbeat rate, which is capable of providing an real time application in monitoring the heartbeat with improvements of an alarm and SMS alert.
Journal ArticleDOI
Active Filter Analysis on Designing Electronic Stethoscope
TL;DR: A lowcost tool for a diagnostic that analyzes the digitized heartbeat sound is given that can be used to detect heart anomalies and also keeps a patient's long-term record for future use.
Journal ArticleDOI
Evaluation of Perceptual and Multi Sub-Band Energy Features for Classification of Normal, Pathological and Noisy Phonocardiogram
TL;DR: After a comprehensive analysis of MFCC at a different number of coefficient values, it is observed that four MFCC coefficients are optimal and more discriminative than other conventional features, further compared with the proposed MSBE feature.
References
More filters
Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Journal ArticleDOI
An open access database for the evaluation of heart sound algorithms.
Chengyu Liu,David Springer,Qiao Li,Benjamin Moody,Ricardo Abad Juan,Ricardo Abad Juan,Francisco J. Chorro,Francisco Castells,José Millet Roig,Ikaro Silva,Alistair E. W. Johnson,Zeeshan Syed,Samuel Emil Schmidt,Chrysa D. Papadaniil,Leontios J. Hadjileontiadis,H. Naseri,Ali Moukadem,Alain Dieterlen,Christian Brandt,Hong Tang,Maryam Samieinasab,Mohammad Reza Samieinasab,Reza Sameni,Roger G. Mark,Gari D. Clifford,Gari D. Clifford +25 more
TL;DR: A public heart sound database, assembled for an international competition, the PhysioNet/Computing in Cardiology (CinC) Challenge 2016, which comprises nine different heart sound databases sourced from multiple research groups around the world is described.
Journal ArticleDOI
Logistic Regression-HSMM-Based Heart Sound Segmentation
TL;DR: This paper addresses the problem of the accurate segmentation of the first and second heart sound within noisy real-world PCG recordings using an HSMM, extended with the use of logistic regression for emission probability estimation, and implements a modified Viterbi algorithm for decoding the most likely sequence of states.
Journal ArticleDOI
Feature extraction and selection for objective gait analysis and fall risk assessment by accelerometry
TL;DR: This study gives a method to classify a population of hospitalized elderlies in two groups: at risk of falling or not at risk based on accelerometric data, a first step to design arisk of falling assessment system that could be used to provide the right treatment as soon as possible before the fall and its consequences.
Journal ArticleDOI
Automatic detection of voice impairments by means of short-term cepstral parameters and neural network based detectors
TL;DR: The Learning Vector quantization methodology demonstrated to be more reliable than the multilayer perceptron architecture yielding 96% frame accuracy under similar working conditions.