Summary
Objectives
: This article deals with recognition of sleep apnea, using solely information available
from multilead ECGs.
Methods
: Characteristic variations in heart rhythm and amplitude of the ECG are compared
with respect to their diagnostic accuracy by means of an ROC analysis that is performed
on a local similarity index. In 38 8-lead ECGs, each minute is classified with respect
to occurrence of apnea events and the result is validated against expert annotations
derived from synchronized polysomnographic recordings. Moreover, the results are compared
to those obtained from the well known Physionet apnea-ECG database.
Results
: Whereas the effect of amplitude modulation yields consistent results on both data
sets (ROC-area 89.0% vs. 88.3%), a remarkable loss in performance is observed for
the frequently applied heart rhythm (89.8% vs. 77.9%). Examples illustrating the reasons
for this difference are given and discussed. With respect to aggregation of multi-lead
information, two methods (PCA vs. averaging) are compared. The results indicate that
averaging performs better (89.3%) than the adaptively estimated PCA (87.2) even when
applied to a reduced set of leads.
Conclusions
: It is concluded that sleep apnea recognition from heart rhythm should always be
complemented by analysis of the amplitude variations of the ECG.
Keywords
Amplitude modulation - apnea detection - heart rate - multi-lead ECG - respiratory
movements