Detection Clinical Trial
Official title:
To Develop Pulse Diagnosis of Traditional Chinese Medicine by Deep Learning.
Taking pulse as a disease diagnosis process has a long history in traditional Chinese medicine (TCM). Ancient physicians used the common attributes of pulse conditions and finger-feeling characteristics as a basis for pulse classification, which " position, rate, shape and tendency " is the principle for pulse differentiation. However, it is not easy to express feelings of hands in a scientific way and not easy for clinical teaching and practice. To develope a new direction of pulse diagnosis in TCM by deep learning and integrative time-frequency domain analysis maybe can be solved the problem.
Status | Recruiting |
Enrollment | 100 |
Est. completion date | January 5, 2022 |
Est. primary completion date | May 5, 2021 |
Accepts healthy volunteers | |
Gender | All |
Age group | 20 Years to 70 Years |
Eligibility | Inclusion Criteria: People who do not have a clear diagnosis of chronic diseases by Western medicine Exclusion Criteria: 1. Western medicine confirms the diagnosis of chronic diseases, such as high blood pressure, diabetes, chronic hepatitis, chronic kidney disease, chronic hyperlipidemia, coronary heart disease, etc. 2. There is a clear diagnosis of mental illness by Western medicine 3. Cancer patients |
Country | Name | City | State |
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Taiwan | Center for Traditional Medicine, Taipei Veterans General Hospital | Taipei |
Lead Sponsor | Collaborator |
---|---|
Taipei Veterans General Hospital, Taiwan |
Taiwan,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | "Skylark" Pulse Analysis System | That is, after measuring the pulse waves at different positions and depths of the bilateral radial arteries, by using the pulse diagnostic instrument, to initial signal processing and to get a single pulse. Then Fourier transformation is performed to obtain the magnitude and phase parameters of the 12 harmonics (24 variables in total), and then extract 7 time-domain characteristic parameters of a single pulse. The next step to perform Fourier transformation again using the 6-second pulse waves to obtain high and low frequency spectrum by using above parameters. The feature parameters obtained by the above two analysis methods are simultaneously sent to the deep learning-convolution neuron network (CNN) training. | 6 second |
Status | Clinical Trial | Phase | |
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Recruiting |
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