Clinical trial NCT05522413: Pulse Momentum Research in Pulse Diagnosis
Official title: Quantitative Research on Pulse Momentum in Pulse Diagnosis of Traditional Chinese Medicine
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Suboptimal Health Status
Keywords: discrete wavelet transformation, Pulse diagnosis in TCM
Lead sponsor: Taipei Veterans General Hospital, Taiwan
Sponsor class: OTHER_GOV
Collaborators: name: National Yang Ming Chiao Tung University
First posted: 2022-08-31
Enrollment: 100
Sex: ALL
Minimum age (years): 20
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Participants have no chronic disease or those who have been diagnosed as Sub-optimal health status by a doctor.

Brief 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).

Detailed 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.

Eligibility criteria: 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

Primary outcomes:
measure: Pulse diagnosis data analysis
timeFrame: 1 day
Secondary outcomes:
measure: Suboptimal health status questionnaires
timeFrame: 1 day
Other outcomes:
Locations:
city: Taipei
country: Taiwan
facility: Taipei Veterans General Hospital
Study officials:
affiliation: Taipei Veterans General Hospital, Taiwan
name: Yen-Ying KUNG, doctor
role: STUDY_DIRECTOR
References: