Ignite Creation Date:
2024-05-06 @ 6:03 PM
Last Modification Date:
2024-10-26 @ 2:40 PM
Study NCT ID:
NCT05522413
Status:
UNKNOWN
Last Update Posted:
2022-08-31
First Post:
2022-08-28
Brief Title:
Pulse Momentum Research in Pulse Diagnosis
Sponsor:
Taipei Veterans General Hospital Taiwan
Organization:
Taipei Veterans General Hospital Taiwan
Study Overview
Official Title:
Quantitative Research on Pulse Momentum in Pulse Diagnosis of Traditional Chinese Medicine
Status:
UNKNOWN
Status Verified Date:
2022-08
Last Known Status:
RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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
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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None