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Slippery PulseNCT04661605

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

An observational study of Slippery Pulse, run by China Medical University Hospital at 1 site in Taiwan.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Official record
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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. Read more about this study

Who is it for?
Ages 20 to 90 yearsHealthy volunteers can take part
Conditions the study is for
Slippery Pulse
What is being tested?
Recurrent Neural Network
How many people
80 participants
Where
1 siteTaiwan
Study dates
Dec 2020to Dec 2021
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 20 to 90 years
  • All sexes
  • Healthy volunteers accepted
  • Adult, Older adult

Study population: Outpatient.

Who may be able to join

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

Who cannot join

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

Trial locations and contacts

1 site in 1 country.

Taiwan1 site, 1 recruiting
  • China Medical University Hospital

    Taichung, North District, 40447

    Ching-Liang Hsieh, Ph.D, +886-4-22053366 ext. 3127, clhsieh@mail.cmuh.org.tw

    Recruiting

Other trials in Taiwan

About this study

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.

Conditions
Slippery Pulse
Being tested
Recurrent Neural Network
Keywords
Artificial intelligence, Recurrent Neural Network, Wrist artery pulse diagnosis instrument, TCM pulse diagnosis, Feature extraction

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Recurrent Neural NetworkDiagnostic test

    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.

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Slippery Pulse

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

    Measured: 30 minutes in duration

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted10 Dec 2020
  2. Study startDec 2020 (estimated)
  3. Primary completionDec 2021 (estimated)
  4. Study completionDec 2021 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Other
Time perspective
Prospective
Enrolment
80 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT04661605
Sponsor's protocol ID
CMUH109-REC2-159
Status last verified
Dec 2020
First submitted
4 Dec 2020
Last updated
10 Dec 2020
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No

Questions about this trial

What is this clinical trial studying?

An observational study of Slippery Pulse, run by China Medical University Hospital at 1 site in Taiwan.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: status not confirmed, as of the sponsor's last update on 10 Dec 2020. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

Results are not available in the source record.

How can a doctor refer a patient or contact the research team?

Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Slippery Pulse (time frame: 30 minutes in duration). It is what the study was designed to measure, not a finding.

Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Dec 2020.

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