DATA PROCESSING METHOD BASED ON WAVELET TRANSFORM AND ITS APPLICATION IN CLASSIFICATION OF HERBAL MEDICINES

• US 20080109174A1
• Filed: 11/07/2006
• Published: 05/08/2008
• Est. Priority Date: 11/07/2006
• Status: Active Grant

• Current Assignee: Hong Kong Polytechnic University
• Original Assignee: Hong Kong Polytechnic University
• Inventors: CHAU, Foo-Tim
• Granted Patent: US 7,496,453 B2
• Time in Patent Office: Days
• US Class Current: 702/27
• CPC Class Codes: G16C 20/20 Identification of molecular entities, parts thereof or of chemical compositions
• CPC Class Codes: G16C 20/70 Machine learning, data mining or chemometrics
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage

Abstract

An efficient, effective and reliable method for authentication of herbal medicines (HMs) based on a novel wavelet-enhanced automated three-dimensional chromatograms classification system. The method takes advantage of the character of 3D chromatograms which appear as functional curves and the preprocessing power of wavelet transform (WT) to minimize the interferences from noises and baseline drifting of the raw data, and at the same time significantly reduces the data sizes. This compressed data retain the essential features of the original raw data, whereby leading to efficient and reliable method for identifying or authenticating herbal medicines or other chemical mixtures of great complexity.

Claims

1. A method of identifying or authenticating a substance containing a plurality of chemical ingredients, the method comprising:

(a) obtaining a data set from a sample of a substance with using a measuring instrument;

(b) transforming said data set using a wavelet with a vanishing moment to obtain a set of coefficients at a decomposition scale; and

(c) optionally classifying said set of coefficients with a classification method to generate a classification result;

wherein said data set is a 3D chromatogram, and said substance is an herbal medicine or an agricultural plant.

2. The method of claim 1, wherein steps (a) to (c) are performed on at least two substances whose identity is known or unknown.

3. The method of claim 1, wherein said data set is a smooth data set.

5. The method of claim 1, wherein said substance contains a plurality of chemical compounds.

7. The method of claim 1, wherein said wavelet is Symlet4.

8. The method of claim 7, wherein said vanishing moment is 4.

9. The method of claim 8, wherein said set of coefficients is at a decomposition scale of 5 or 6.

10. The method of claim 9, wherein said classification method is a Principal Component Analysis (PCA) method.

11. The method of claim 3, wherein said smooth data set is obtained from an instrument of CE-DAD, HPLC-IR, HPLC-DAD or GC-IR.

12. The method of claim 2, wherein at least one of said substances is of known identity and at least one of said substances is of unknown identity.

13. The method claim 12, further comprising comparing said classification result of said substance of known identity and of said substance of unknown identity.

4. (canceled)

6. (canceled)

14. A device for identifying or authenticating a substance containing a plurality of chemical ingredients, comprising:

(a) a data interface to connect with a measuring instrument and to receive a data set from said measuring instruments; and

(b) a data compression module capable of performing a wavelet transform on said data set to produce a set of coefficients at a given decomposition scale, said module allowing selection of a wavelet, a vanishing moment, and a decomposition scale for performing said wavelet transform;

wherein said data set is a 3D chromatogram, and said substance is an herbal medicine or an agricultural plant.

15. The device of claim 14, further comprising a data classification module for performing classification on said set of coefficients and outputting a classification result.

16. The device of claim 15, wherein said data compression module is implemented in hardware, software or combination of hardware and software.

17. The device of claim 16, wherein said data classification module is implemented in hardware, software or combination of hardware and software.

18. The device of claim 17, wherein said device is a personal computer,

said data interface is a serial port, parallel port, firewire port, USB port, WiFi connection, Bluetooth connection or infrared connection, and

said data compression module and data classification module are implemented in software.

19. The device of claim 15, wherein said classification result is visually presented on a screen or as a printout on paper.