BACKGROUND: Recording and displaying outputs from electronic pacemakers with electrocardiogram (ECG) recorders typically used in clinical practice have presented a number of technical limitations. We have recently reported on a new high-bandwidth ECG system and have shown that it is capable of reproducing accurate pulse amplitudes and durations from the body surface. In the present work, we have used our data to calculate a transform function between the programmed pacemaker output voltage and the amplitude on the body surface. METHODS: We recorded 3 high-bandwidth (75,000 samples per second) ECGs from each of 100 pacemaker patients at 3 different programmed outputs. Each pacemaker pulse was isolated using the criterion standard annotations, and the pulses were transformed from the 8 independent leads to an XYZ vector using the Dower transform. The magnitude of the vector was calculated. Linear regression techniques were used to learn a transfer function over the records of the first 50 patients. These results were tested against the second 50 patients. RESULTS: The measured pacemaker pulse vector magnitude has a linear relationship to the programmed pacemaker amplitude on a per-patient basis for most of the patients in the training database. The linear transform models were tested against the testing set with an R(2) metric of 0.38 for the atrial pulses and 0.54 for the right ventricular pulses. CONCLUSION: Understanding the relationship between the generated pacemaker pulses and the measurements at the body surface will help drive specifications for pacemaker pulse detection among the various device manufactures.
BACKGROUND: Recording and displaying outputs from electronic pacemakers with electrocardiogram (ECG) recorders typically used in clinical practice have presented a number of technical limitations. We have recently reported on a new high-bandwidth ECG system and have shown that it is capable of reproducing accurate pulse amplitudes and durations from the body surface. In the present work, we have used our data to calculate a transform function between the programmed pacemaker output voltage and the amplitude on the body surface. METHODS: We recorded 3 high-bandwidth (75,000 samples per second) ECGs from each of 100 pacemaker patients at 3 different programmed outputs. Each pacemaker pulse was isolated using the criterion standard annotations, and the pulses were transformed from the 8 independent leads to an XYZ vector using the Dower transform. The magnitude of the vector was calculated. Linear regression techniques were used to learn a transfer function over the records of the first 50 patients. These results were tested against the second 50 patients. RESULTS: The measured pacemaker pulse vector magnitude has a linear relationship to the programmed pacemaker amplitude on a per-patient basis for most of the patients in the training database. The linear transform models were tested against the testing set with an R(2) metric of 0.38 for the atrial pulses and 0.54 for the right ventricular pulses. CONCLUSION: Understanding the relationship between the generated pacemaker pulses and the measurements at the body surface will help drive specifications for pacemaker pulse detection among the various device manufactures.
Authors: Derek S Chew; Sharita Manga; Andrew Roberts; Glen L Sumner; Katherine M Kavanagh; Andrew G Howarth; Carmen Lydell; James A White; Karen Cowan; Gordon Rowlandson; Joel Xue; Derek V Exner Journal: CJC Open Date: 2021-05-27