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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05522413
Other study ID # 2022-06-014AC
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date August 10, 2022
Est. completion date July 10, 2023

Study information

Verified date August 2022
Source Taipei Veterans General Hospital, Taiwan
Contact Yen-Ying KUNG, doctor
Phone 886-2-28757453
Email yykung@vghtpe.gov.tw
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Traditional Chinese medicine has a long history of disease diagnosis applications by pulse diagnosis. The pulse "position", "number", "shape", and "momentum" can be used as four guidelines for pulse classification. However, the finger feeling is difficult to be expressed in a quantitative approach for clinical teaching and illness-state recognition. The pressure sensor was applied to measure wrist pulse waveforms for analysis. In this research project, the "discrete wavelet transformation (DWT)" is used to decompose the time-domain pulse into several sets of signals, which are allocated at different frequency bands. The high-frequency signal over the range of 12-50 Hz is then acquired to calculate the spectral energy ratio (SER) for quantization of the pulse momentum to the persons under the suboptimal health status (SHS).


Description:

Traditional Chinese medicine has a long history of disease diagnosis applications by pulse diagnosis. Ancient physicians classified the pulse types on the basis of pulse manifestation attributes and finger-feeling features. The pulse "position", "number", "shape", and "momentum" can be used as four guidelines for pulse classification. However, the finger feeling is difficult to be expressed in a quantitative approach for clinical teaching and illness-state recognition. The modernization of pulse diagnosis in Taiwan began in the 1970s. The pressure sensor was applied to measure wrist pulse waveforms for analysis. Nowadays, the pulse "position", "number", and "shape" have been quantitatively analyzed and classified by using time-domain pulse signals and their corresponding frequency spectrums. However, since it is lack of effective high-frequency pulse acquisition method and quantitative approach, the quantitative research on "pulse momentum" for judgement of pathological status is still being investigated. In this research project, the "discrete wavelet transformation (DWT)" is used to decompose the time-domain pulse into several sets of signals, which are allocated at different frequency bands. The high-frequency signal over the range of 12-50 Hz is then acquired to calculate the spectral energy ratio (SER) for quantization of the pulse momentum. In addition, the approximate entropy (ApEn) of the high-frequency signal is computed and defined as a new quantitative factor of pulse momentum. It will be further tried to relate the scores of clinical questionnaires. The analysis method proposed in this project has been preliminarily applied to analyze the pulse waveforms of the persons under the suboptimal health status (SHS) to demonstrate the effectiveness. In the future, more measured pulses of the subject under test will be collected and analyzed to examine the robustness of the proposed method. It is also planned to figure out the relationship between the quantitative factors, such as SER and ApEn, and the high- and low-frequency parameters of the heart rate variability (HRV). It can be further linked to the activation of sympathetic and parasympathetic nerves, and potentially build up an objective bridge of clinical diagnosis to connect the traditional Chinese medicine and modern western medicine.


Recruitment information / eligibility

Status Recruiting
Enrollment 100
Est. completion date July 10, 2023
Est. primary completion date July 10, 2023
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 20 Years to 70 Years
Eligibility Inclusion Criteria: - A+B+C or A+B+D that meet the following description, and those who have no clear diagnosis of chronic diseases by western medicine, can be included: (A) Sub-Health Questionnaire (SHSQ-25) ?35 points (B) Resting blood pressure 120-139/80-89 mmHg measured more than 3 times a week (C) The PSQI score of the sleep questionnaire on the first test is greater than 5 points (D) Body mass index (BMI): 24~29 Kg/m2 Exclusion Criteria: - Considerations for selection/exclusion criteria include: 1. Those with a clear diagnosis of chronic diseases in Western medicine, such as hypertension, diabetes, chronic hepatitis, chronic kidney disease, chronic hyperlipidemia, coronary heart disease, etc., which fall within the scope of chronic diseases under the National Health Insurance 2. Have a definite diagnosis of mental illness by Western medicine 3. Cancer patients 4. Pregnancy 5. Those with obvious inflammatory infection at the time of receipt of the case

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
Taiwan Taipei Veterans General Hospital Taipei

Sponsors (2)

Lead Sponsor Collaborator
Taipei Veterans General Hospital, Taiwan National Yang Ming University

Country where clinical trial is conducted

Taiwan, 

Outcome

Type Measure Description Time frame Safety issue
Primary Pulse diagnosis data analysis Palpation of the 6 pulse positions (right cun, right guan, right chi, left cun, left guan, left chi) measured by the pulse diagnostic instrument are read into the processing program, and then the time domain signal of each pulse position is analyzed in sequence . 1 day
Secondary Suboptimal health status questionnaires 25 items of Suboptimal symptoms 1 day
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