Automatic detection of ECG lead-wire interchange for conventional and Mason-Likar lead systems

Misconnection of ECG lead-wires can generate abnormal ECG and erroneous diagnosis. Existing methods for detecting lead-wire interchange were designed for ECG devices using conventional lead system. In this work we developed an automatic ECG cable interchange detection algorithm and compared the algorithm performance between conventional and Mason-Likar (ML) electrode placements. The algorithm was developed based on a decision tree classifier which uses beat morphology measurements that were obtained using Philips DXL ECG algorithm. The algorithm was evaluated for detecting limb cable interchanges on an independent database which included both conventional and ML ECG recordings for each subject (total 423 subjects). There was no statistically significant difference in terms of overall sensitivity and specificity. This morphology-based cable interchange detection algorithm showed similarly high performance for maintaining a low false positive rate for both lead systems. Therefore, in practice, the same algorithm may be used with either electrode placement without a need for a special configuration.