{'fraction_non_alphanumeric': 0.01652089407191448, 'fraction_numerical': 0.0, 'mean_word_length': 5.602564102564102, '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}}
Virtual instrumentation in medical investigations and diagnosis support

The improvement in medical care, which we have observed in the last few decades, has been influenced by the introduction of new technologies and methods for monitoring the patient. Medical researchers working have been faced with large amount of different types of data (alphanumeric, signals, images), that are sometimes difficult to analyze using traditional methods. In order to extract maximum information from the collected data, introduction of sophisticated mathematical methods to medical sciences has been necessary. The aim of this article is to explain how virtual instrumentation concept may facilitate creation of tools, which may be useful both in medical investigations and diagnosis support. As the example we present the analysis of the fetal heart rate signal in time, frequency and joined time-frequency domain. The possibility of classification of such obtained results with statistical and artificial intelligence methods is described.