Objectives: Digital sphygmomanometers have been used for more than 40 years in Western medicine for accurately measuring systolic and diastolic blood pressures, which are vital signs observed for the diagnosis of different diseases. Similarly, traditional Chinese medicine (TCM) has been using wrist pulse diagnosis for thousands of years. Some studies have combined digital wrist pulse signals and the diagnosis method of TCM to quantify pulse waves and identify diseases. However, the effectiveness of this approach is limited because of scattered methods and complex pathological features. Moreover, the literature on TCM does not provide quantitative data or objective indicators.
Methods: In this prospective study, we developed a diagnostic system that contains a modified sphygmomanometer. In addition, we designed a procedure for analyzing pulse waves with 156 features of harmonic modes and a decision tree method for diagnosing kidney insufficiency.
Results: In the decision tree method, at least three features of harmonic modes can achieve an accuracy of 0.86, a specificity of 0.91, and a Cohen's kappa coefficient of 0.72. By comparison, the random forest method can achieve an accuracy of 0.99, a specificity of 0.99, and a Cohen's kappa coefficient of 0.94 within 200 trees. The results of this study indicated that even in patients with kidney insufficiency and complex etiology, common features can be distinguished by identifying changes in pulse waveforms.
Conclusion: By using the modified sphygmomanometer to measure blood pressure, people can monitor their health status and take care of it in advance by simply measuring their blood pressure.
Keywords: Wrist-type sphygmomanometer; decision trees; harmonic modes; kidney insufficiency features; pulse diagnosis.
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