{'fraction_non_alphanumeric': 0.03919597989949749, 'fraction_numerical': 0.021105527638190954, 'mean_word_length': 5.036363636363636, '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}}
Wavelet packet based algorithm for QRS region detection and R/S wave identification

This paper comprises the methodology followed to design and implement a wavelet packet based algorithm for QRS region detection and R/S wave identification. Validation is performed using electrocardiographic (ECG) records 100 to 109 of the MIT-BIH Arrhythmia database. The proposed algorithm reconstructs the ECG signal using two nodes from the wavelet packet decomposition. Sensitivity (Se) and positive predictivity (+P) are calculated and compared to other algorithms which use approaches based on derivative signals and digital filters (Hamilton & Tompkins) as well as wavelet-based QRS detection (Li et al.), obtaining the values Se = 99.87 % and +P = 99.85 %. Only 31 false negatives were found, from a total of 21,680 heartbeats, which shows the algorithms' contribution to region location improvement. Also, once the region is determined, a simple max/min threshold is used for R/S wave identification.