Multichannel ECG Filtering: Source Consistency Filtering, Eigenfiltering and Traditional Methods

Noise reduction is a fundamental aspect of stress electrocardiogram
$(ECG)$
recording. In this setting, muscular noise represents the main antagonist to signal quality. A possible solution to muscle noise in stress
$ECG$
is to exploit the information redundancy in 12 - lead recordings to reduce noise while preserving the
$ECG$
signal. Source Consistency Filtering
$(SCF)$
is a spatial redundancy filter that follows this principle. In this paper, we compare the muscle noise rejection performance of conventional
$25Hz$
and
$40Hz$
low-pass filters (LPFs), the SC
$F$
‘ and a method based on singular value decomposition
$(SVD)$
which exploits both the spatial and temporal correlation in the
$ECG$
signal. Our results indicate that the
$SCF$
can afford a
$QRS$
complex distortion lower than that of a 40
$Hz$
lowpass filter while still maintaining a high noise rejection. The
$QRS$
detection accuracy on the filtered
$ECG$
was comparable for all methods except for the
$SVD$
filter, which allowed a superior detection performance score in all the records.