Automated Biosignal Quality Analysis of Electrocardiograms

Biosignals are signals that can be measured directly from biological organisms. Examples of biosignals include the electrocardiogram (ECG; electrical signal associated with the heart), electromyogram (EMG; electrical signal associated with muscles), electroencephalogram (EEG; electrical signal associated with the brain), phonocardiogram (PCG; heart sounds), photoplethysmogram (PPG; changes in blood volume measured optically), and body temperature. These biosignals provide valuable information regarding the status and function of the body and can be used in various applications. ECG is used to monitor heart rate during athlete training and to diagnose and monitor cardiovascular conditions, such as atrial fibrillation, myocardial ischemia, and myocardial infarction [1]-[3]. It is also being explored for use in the security field as a replacement or augmentation of current biometric systems [4]. EMG is used in movement and gait analysis, rehabilitation medicine, and as a control signal for prosthetic devices [5]-[7]. EEG is used for brain-computer interfaces [8] and to detect the onset of epileptic seizures [9]. Conventionally, biosignals are measured by highly trained personnel in a controlled environment with short recordings. This helps to minimize signal contaminants and ensure sufficient quality of the measurements before analysis or interpretation.