{'fraction_non_alphanumeric': 0.015584415584415584, 'fraction_numerical': 0.006926406926406926, 'mean_word_length': 5.4222222222222225, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Enhancing the Precision of ECG Baseline Correction: Selective Filtering and Removal of Residual Error

Reemergence of the problem of baseline correction is related to recent advancements in the electrocardiographic (ECG) analysis of beat-to-beat repolarization changes which play an important role in risk assessment and the prediction of sudden cardiac death. These alterations often have an amplitude of a few microvolts and duration of several milliseconds and their detection requires special accuracy of baseline estimation. Using detailed analysis of various types of residual errors we designed a two-step procedure for selective filtering of ECG and removal of residual error with minimal distortion of cardiac complexes and tested this approach on 100 simulated and 210 real ECG signals. Application of this procedure provided a twofold reduction in the error of baseline estimation and T-wave amplitude measurements compared to high-pass filtering. Selective application of this approach to the segments with low baseline drift allowed analysis of low-amplitude, beat-to-beat changes in repolarization during more than 70% of the recording time.