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Visualization Engineering Platform for Pulse Diagnosis of Traditional Chinese Medicine-The Research of Similar Moiré Feature Analyzing Approach Based on Recurrent Neural Network to Process the Measured Slip Pulse Wave-Images With Chun, Guan and Chy

Visualization Engineering Platform for Pulse Diagnosis of Traditional Chinese Medicine-The Research of Similar Moiré Feature Analyzing Approach Based on Recurrent Neural Network to Process the Measured Slip Pulse Wave-Images With Chun, Guan and Chy

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04661605
Enrollment
80
Registered
2020-12-10
Start date
2020-12-31
Completion date
2021-12-31
Last updated
2020-12-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Slippery Pulse

Keywords

Artificial intelligence, Recurrent Neural Network, Wrist artery pulse diagnosis instrument, TCM pulse diagnosis, Feature extraction

Brief summary

The diagnoses processes of Traditional Chinese Medicine (TCM) focus on the following four main types of diagnoses methods consisting of inspection, olfaction, inquiry, and palpation. The most important one is palpation also called pulse diagnosis which is to measure wrist artery pulse by TCM doctor's fingers to detect patient's health state. The pulse diagnosis has three parts, namely 'Chun', 'Guan' and 'Chy', with the location. Wrist measurements correspond to different parts of the body's organs. However, the pulse information is analyzed by TCM doctor's pulse diagnoses process, which is picked only a single waveform from a long-term pulse measured process and often discarded the other waveforms contained in the same information, e.g. Slip Pulse waveform. The research object of this project is to divide the TCM diagnosis patients into two groups, one is the Slip pulse group and the other is a Flat Pulse group, in which the cases are collected at least 50 cases for the first gruop and 30 cases for the second group, individually. The purpose of this project will integrate the TCM doctor's experiences and standardize them in order to construct an effective Slip pulse diagnosis system based on visualization engineering platform. It could refine Slip pulse diagnoses processes and reduce their diagnoses loading by using the proposed approach during this project. Therefore, we will propose a similar Moiré feature analyzing approach based on Recurrent Neural Network to process the measured Slip Pulse wave-images with 'Chun', 'Guan' and 'Chy' in order to prepare this visualization engineering platform. We will measure the waveform images of the three parts of the wrist as 'Chun', 'Guan' and 'Chy' with the moiré feature technology proposed in this project. It mainly extracts the moiré features such as pulse image from numerous measurement 'Chun', 'Guan' and 'Chy' signals, and further analyzes and summarizes them with AI technology. We could extract the pulse characteristics of Slip pulse automatically from the many measurement signals and enhance the automatic judging ability of the current pulse instrument to the Slip pulse waveform. Provide important pulse information to the TCM doctors as an important reference for precision clinical diagnoses.

Interventions

We will propose a similar Moiré feature analyzing approach based on Recurrent Neural Network to process the measured Slip Pulse wave-images with 'Chun', 'Guan' and 'Chy' in order to prepare this visualization engineering platform.

Sponsors

China Medical University Hospital
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
20 Years to 90 Years
Healthy volunteers
Yes

Inclusion criteria

1. Already sign test consent permit. 2. More than 20-year-old.

Exclusion criteria

1\. There is a wound or inflammation at the wrist skin measurement.

Design outcomes

Primary

MeasureTime frameDescription
Slippery Pulse30 minutes in durationThe purpose of this project will integrate the TCM doctor's experiences and standardize them in order to construct an effective Slippery Pulse diagnosis system.

Countries

Taiwan

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026