Visualization Engineering Platform for TCM Pulse Diagnosis - Pulse Diagnosis Based on Federated Learning to Diagnose Slippery and Choppy and Other Pulses Waveform Image Features to Assist in the Study of TCM Pathological Logic Analysis

Slippery Pulse Clinical Trial

Official title:

Visualization Engineering Platform for TCM Pulse Diagnosis - Pulse Diagnosis Based on Federated Learning to Diagnose Slippery and Choppy and Other Pulses Waveform Image Features to Assist in the Study of TCM Pathological Logic Analysis

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05630248
• Other study ID #: CMUH111-REC2-168
• Status: Recruiting
• Start date: December 2022
• Est. completion date: September 2024

Study information

• Verified date: December 2022
• Source: China Medical University Hospital
• Contact: Ching-Liang Hsieh, Ph.D
• Phone: +886-4-22053366
• Email: clhsieh[@]mail.cmuh.org.tw
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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. In this project, it is to classify pulse types by using specialized pulse measuring instruments. The measured pulse wave (Measured Pulse Wave, MPW) was segmented into arterial pulse wave curves (APWC) by the image suggestion method. The research object of this project is to collect and group patients diagnosed by traditional Chinese medicine practitioners, namely slippery pulse, choppy pulse group and normal pulse control group, with at least 80 cases for each group. The research purpose of this project is mainly to carry out the visualization engineering platform of TCM pulse diagnosis - based on the pulse diagnosis of federated learning to diagnose the pulse waveform image features such as slippery pulse and choppy pulse to provide auxiliary TCM pathological logic analysis research and back-end cross-federal learning of TCM pulse diagnosis Implementation of the node system. In other words, it is expected that the pulse wave characteristics measured by TCM physicians who cooperate with experts in the field can be collected from many TCM pulse diagnosis federated learning nodes, and analyzed by the Multiple-Expert Repertory Grid Elicitation (MERGE) method. Finally, the artificial intelligence model based on FL is trained to carry out TCM pathological logic analysis and related research. The results will be provided to TCM physicians as an important reference to assist clinical diagnosis.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 240
• Est. completion date: September 2024
• Est. primary completion date: September 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 20 Years to 90 Years

Eligibility

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.

Related Conditions & MeSH terms

• Disease
• Slippery Pulse

Intervention

Diagnostic Test:
• Recurrent Neural Network
it is to classify pulse types by using specialized pulse measuring instruments.

Locations

Country	Name	City	State
Taiwan	China Medical University Hospital	Taichung	North District

Sponsors (1)

Lead Sponsor	Collaborator
China Medical University Hospital

Country where clinical trial is conducted

Taiwan, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Slippery Pulse	The purpose of the study was to establish a scientific slippery pulse diagnosis system	30 minutes in duration