Electrocardiography is a simple clinically useful non-invasive technique to evaluate the activity of the heart. The heart rate is very variable parameter and sometimes reaches very high values. In these cases, the frequency band of the electrocardiographic (ECG) signal overlaps the band of the surface electromyographic (sEMG) signal, which it represents an interfering signal. The aim of the present study is to show how the Segmented Beat Modulation Method (SBMM) can be used to clean the ECG signal from muscular noise. To this aim, a real ECG signal (characterized by a fast heart rate and corrupted by muscular noise) was acquired from a violinist while he was playing. Results indicate that the ECG and the sEMG signal can be separated without losing morphological features and spectral components of both signals. Thus SBMM is a promising tool for cleaning the ECG signal from muscular noise.
Cleaning the electrocardiographic signal from muscular noise / Burattini, Laura; Agostinelli, Angela; Maranesi, Elvira; Sbrollini, Agnese; Fioretti, Sandro; DI NARDO, Francesco. - ELETTRONICO. - (2015), pp. 57-61. (Intervento presentato al convegno 12th International Workshop on Intelligent Solutions in Embedded Systems, WISES 2015 tenutosi a Universita Politecnica delle Marche, ita nel 2015).
Cleaning the electrocardiographic signal from muscular noise
BURATTINI, LAURA
;AGOSTINELLI, ANGELA;MARANESI, ELVIRA;SBROLLINI, AGNESE;FIORETTI, Sandro;DI NARDO, Francesco
2015-01-01
Abstract
Electrocardiography is a simple clinically useful non-invasive technique to evaluate the activity of the heart. The heart rate is very variable parameter and sometimes reaches very high values. In these cases, the frequency band of the electrocardiographic (ECG) signal overlaps the band of the surface electromyographic (sEMG) signal, which it represents an interfering signal. The aim of the present study is to show how the Segmented Beat Modulation Method (SBMM) can be used to clean the ECG signal from muscular noise. To this aim, a real ECG signal (characterized by a fast heart rate and corrupted by muscular noise) was acquired from a violinist while he was playing. Results indicate that the ECG and the sEMG signal can be separated without losing morphological features and spectral components of both signals. Thus SBMM is a promising tool for cleaning the ECG signal from muscular noise.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.