Abstract
Physiological waveforms - such as electrocardiograms (ECG), electroencephalograms
(EEG), electromyograms (EMG) - are generated during the course of routine care. These
signals contain information that can be used to understand underlying conditions
of health. Effective processing and analysis of physiological data requires
specialized software. The WaveForm DataBase (WFDB) Toolbox for MATLAB and
Octave is a collection of over 30 functions and utilities that integrate PhysioNet's opensource applications and databases with the high-precision numerical computational and
graphics environment of MATLAB and Octave.
Background
Physiological waveforms - such as electrocardiograms (ECG), electroencephalograms
(EEG), electromyograms (EMG) - are generated during the course of routine care. These
signals contain information that can be used to understand underlying conditions of
health. For example, ECGs aid diagnosis of abnormal heart conditions, EEGs aid
detection of disorders such as epilepsy, and EMGs aid diagnosis of neuromuscular
diseases. Despite the potential utility of waveforms, their complexity and granularity
present challenges for retrospective analysis. Effective storage, processing and
analysis of physiological signals requires specialized software.
MLPClassifier supports multi-class classification by applying Softmax as the output
function. Further, the model supports multi-label classification in which a sample can
belong to more than one class. For each class, the raw output passes through the logistic
function.
Waveform Database Software Package
(WFDB) for MATLAB and Octave
A collection of functions for reading, writing,
and processing physiologic signals in the
formats used by PhysioNet