TY - GEN
T1 - Machine learning algorithms for real time arrhythmias detection in portable cardiac devices
T2 - 17th Symposium of Image, Signal Processing, and Artificial Vision, STSIVA 2012
AU - Rua, Santiago
AU - Zuluaga, Santiago A.
AU - Redondo, Alfredo
AU - Orozco-Duque, Andres
AU - Restrepo, Jose V.
AU - Bustamante, John
PY - 2012
Y1 - 2012
N2 - This paper presents the development of two machine learning algorithms on a 32-bit ARM® Cortex® M4 microcontroller core from Freescale Semiconductors. A neural network (ANN) and a support vector machine (SVM) were implemented for real time detection of ventricular tachycardia (VT) and ventricular fibrillation (VF), and they were compared in terms of accuracy. In the feature extraction step a Fast Wavelet Transform (FWT) was used; which was analyzed using the time-frequency characteristics of energy in each sub-band frequency. For the training and validation algorithms, signals from MIT-BIH database with normal sinus rhythm, VF and VT in a time window of 2 seconds were used. Validation results achieve test accuracy of 99.46% by ANN and SVM in VT/VF detection.
AB - This paper presents the development of two machine learning algorithms on a 32-bit ARM® Cortex® M4 microcontroller core from Freescale Semiconductors. A neural network (ANN) and a support vector machine (SVM) were implemented for real time detection of ventricular tachycardia (VT) and ventricular fibrillation (VF), and they were compared in terms of accuracy. In the feature extraction step a Fast Wavelet Transform (FWT) was used; which was analyzed using the time-frequency characteristics of energy in each sub-band frequency. For the training and validation algorithms, signals from MIT-BIH database with normal sinus rhythm, VF and VT in a time window of 2 seconds were used. Validation results achieve test accuracy of 99.46% by ANN and SVM in VT/VF detection.
KW - Arrhythmias
KW - ECG signal
KW - Machine Learning
KW - Microcontroller
KW - Neural Network
KW - Support vector machine (SVM)
UR - http://www.scopus.com/inward/record.url?scp=84870677311&partnerID=8YFLogxK
U2 - 10.1109/STSIVA.2012.6340556
DO - 10.1109/STSIVA.2012.6340556
M3 - Ponencia publicada en las memorias del evento con ISBN
AN - SCOPUS:84870677311
SN - 9781467327619
T3 - STSIVA 2012 - 17th Symposium of Image, Signal Processing, and Artificial Vision
SP - 50
EP - 55
BT - STSIVA 2012 - 17th Symposium of Image, Signal Processing, and Artificial Vision
Y2 - 12 September 2012 through 14 September 2012
ER -