IP Library Granted Patent US 12,449,303
Granted Patent B2
US 12,449,303 · App. 18/472,759 · Granted Oct 21, 2025

Low-cost spectrometry system for end-user food analysis

Inventors: Damian Goldring (Tel Aviv, IL); Dror Sharon (Benei Atarot, IL)
Assignee: SCIO SOLUTIONS LTD
G01J3/0256G01J3/0208G01J3/26G01J3/2803G01J3/36G01N21/255G01J2003/1226
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Quick Facts
Patent No.
US 12,449,303
App. No.
18/472,759
Granted
Oct 21, 2025
Kind
B2
Abstract

A compact spectrometer is disclosed that is suitable for use in mobile devices such as cellular telephones. In preferred embodiments, the spectrometer comprises a filter, at least one Fourier transform focusing element, a micro-lens array, and a detector, but does not use any dispersive elements. Methods for using the spectrometer as an end-user device for performing on-site determinations of food quality, in particular, by comparison with an updatable database accessible by all users of the device, are also disclosed.

Claims (43)

1. A method of obtaining a spectrum of a sample without using dispersive optics, wherein said method comprises:

providing a sample;

causing light emanating from said sample to impinge on an optical filter, a center wavelength of which depends on an angle of incidence of the light impinging upon the optical filter;

passing the light to a first Fourier transform focusing element;

measuring an intensity of the light as a function of position in a predetermined plane P 1 ; and,

converting the intensity of the light as a function of the position in the plane P 1 to a spectrum.

2. The method of claim 1 , further comprising analyzing the spectrum using one or more models based on a database of spectral information.

3. The method of claim 2 , further comprising:

transmitting the spectrum to a remote processing unit;

using the remote processing unit to perform the analyzing; and,

transmitting the results of the analyzing to a user.

4. The method of claim 2 , wherein the transmitting is performed over a wireless network.

5. The method of claim 4 , wherein the performing the preliminary analysis of the spectrum further comprises at least one step chosen from the group consisting of

averaging a plurality of independent measurements,

compensating for optical aberrations, and

reducing detector noise using a noise reduction algorithm.

6. The method of claim 2 , further comprising performing a preliminary analysis of the spectrum obtained in converting the intensity of the light as a function of position in the focal plane of the first Fourier transform focusing element.

7. The method of claim 6 , wherein the performing the preliminary analysis of the spectrum is performed using a local processing unit.

8. The method of claim 6 , wherein the performing the preliminary analysis of the spectrum is performed remotely.

9. The method of claim 2 , wherein the analyzing comprises at least one step chosen from (a) comparing the spectrum with spectra in a spectral database; (b) comparing the spectrum with spectra in a spectral database by using Principal Components Analysis; (c) comparing the spectrum with spectra in a spectral database by using Partial Least Squares analysis; or (d) comparing the spectrum with spectra in a spectra database by using a neural network algorithm.

10. The method of claim 1 , wherein the sample comprises food.

11. A compact spectrometer for obtaining a spectrum of a sample without using dispersive optics, the compact spectrometer comprising a digital processor and a fixed memory, the fixed memory configured to store instructions that when executed by the digital processor cause the compact spectrometer to:

cause light emanating from a sample to impinge on an optical filter, a center wavelength of which depends on an angle of incidence of the light impinging upon the optical filter;

pass the light to a first Fourier transform focusing element;

measure an intensity of the light as a function of position in a predetermined plane P 1 ; and,

convert the intensity of the light as the function of position in the plane P 1 to a spectrum.

12. The compact spectrometer of claim 11 , wherein the compact spectrometer is incorporated into an oven or a refrigerator.

13. The compact spectrometer of claim 12 , wherein the oven is a microwave oven.

14. The compact spectrometer of claim 11 , further comprising a global positioning system (GPS) device configured to determine a location of the compact spectrometer.

15. The compact spectrometer of claim 11 , wherein the compact spectrometer is configured to analyze the spectrum obtained by a model based on a database of spectral information.

16. The compact spectrometer of claim 15 , wherein the spectrometer further:

transmits the spectrum to a remote processing unit;

uses the remote processing unit to perform the analyzing; and,

transmit results of the analyzing to a user.

17. The compact spectrometer of claim 16 , wherein the results are configured to be transmitted over a wireless network.

18. The compact spectrometer of claim 15 , wherein the processor is configured to perform a preliminary analysis of the spectrum obtained in converting the intensity of the light as a function of position in the focal plane of the first Fourier transform focusing element.

19. The compact spectrometer of claim 15 , wherein performing a preliminary analysis of the spectrum is performed using a local processing unit.

20. The compact spectrometer of claim 15 , wherein performing a preliminary analysis of the spectrum is performed remotely.

21. The compact spectrometer of claim 15 , wherein performing a preliminary analysis of the spectrum further comprises at least one step chosen from the group consisting of

averaging a plurality of independent measurements,

compensating for optical aberrations, and

reducing detector noise using a noise reduction algorithm.

22. The compact spectrometer of claim 15 , wherein the compact spectrometer is configured to analyze with at least one step chosen from (a) comparing the spectrum with spectra in a spectral database; (b) comparing the spectrum with spectra in a spectral database by using Principal Components Analysis; (c) comparing the spectrum with spectra in a spectral database by using Partial Least Squares analysis; or (d) comparing the spectrum with spectra in a spectra database by using a neural network algorithm.

Assignments (2)
CHANGE OF NAME Recorded Dec 30, 2024
From: VERIFOOD LTD
To: SCIO SOLUTIONS LTD
Reel/Frame 069795/0228 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 13, 2023
From: GOLDRING, DAMIAN; SHARON, DROR
To: VERIFOOD LTD
Reel/Frame 065546/0179 →
Continuity (9)
Continuation 17814983 · Jul 26, 2022
Continuation 17553318 · Dec 16, 2021
Continuation 16878807 · May 20, 2020
Continuation 16389723 · Apr 19, 2019
Continuation 15411922 · Jan 20, 2017
Continuation 15094927 · Apr 8, 2016
Continuation 14356144
Provisional Application 61555043 · Nov 3, 2011
Related Publication 20240142302A1 · May 2, 2024
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