ArticleEvidence-based complementary and alternative medicine : eCAM2018
Pulse Wave Cycle Features Analysis of Different Blood Pressure Grades in the Elderly.
Article in Evidence-based complementary and alternative medicine : eCAM, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 24 citations in OpenAlex.
- 1DCNN-BiLSTM-transformer hypertension risk prediction model based on APW.Frontiers in microbiology · 2025Article
- A Study of Logistic Regression for Fatigue Classification Based on Data of Tongue and Pulse.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- The Research and Development Thinking on the Status of Artificial Intelligence in Traditional Chinese Medicine.Evidence-based complementary and alternative medicine : eCAM · 2022Review
- Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population.BMC medical informatics and decision making · 2021Article
- A New Approach of Fatigue Classification Based on Data of Tongue and Pulse With Machine Learning.Frontiers in physiology · 2021Article
- Fourier Series Analysis for Novel Spatiotemporal Pulse Waves: Normal, Taut, and Slippery Pulse Images.Evidence-based complementary and alternative medicine : eCAM · 2019Article
- A Study of Machine-Learning Classifiers for Hypertension Based on Radial Pulse Wave.BioMed research international · 2018Article
- Correlation Analysis of Data of Tongue and Pulse in Patients With Disease Fatigue and Sub-health Fatigue.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveThe same range of blood pressure values may reflect different vascular functions, especially in the elderly. Therefore, a single blood pressure value may not comprehensively reveal cardiovascular function. This study focused on identifying pulse wave features in the elderly that can be used to show functional differences when blood pressure values are in the same range.
methodsFirst, pulse data were preprocessed and pulse cycles were segmented. Second, time domain, higher-order statistics, and energy features of wavelet packet decomposition coefficients were extracted. Finally, useful pulse wave features were evaluated using a feature selection and classifier design.
resultsA total of 6,075 pulse wave cycles were grouped into 3 types according to different blood pressure levels and each group was divided into 2 categories according to a history of hypertension. The classification accuracy of feature selection in the 3 groups was 97.91%, 95.24%, and 92.28%, respectively.
conclusionSelected features could be appropriately used to analyze cardiovascular function in the elderly and can serve as the basis for research on a cardiovascular risk assessment model based on Traditional Chinese Medicine pulse diagnosis.
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Registered trials
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