SYSTEMS AND METHODS FOR COLLISION COMPUTING FOR DETECTION AND NONINVASIVE MEASUREMENT OF BLOOD GLUCOSE AND OTHER SUBSTANCES AND EVENTS

• US 20160139041A1
• Filed: 01/12/2016
• Published: 05/19/2016
• Est. Priority Date: 09/29/2014
• Status: Active Grant

• Current Assignee: Zyomed Holdings, Inc.
• Original Assignee: Zyomed Corp.
• Inventors: Gulati, Sandeep, Ruchti, Timothy L., Van Antwerp, William, Smith, John L.
• Granted Patent: US 9,459,202 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02433 for infrared radiation
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7235 Details of waveform analysis A61B5/349 takes precedence
• CPC Class Codes: A61B 5/7253 characterised by using transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G01N 21/3577 for analysing liquids, e.g. polluted water
• CPC Class Codes: G01N 21/359 using near infrared light
• CPC Class Codes: G01N 21/4795 spatially resolved investigating of object in scattering medium in vivo A61B
• CPC Class Codes: G01N 21/49 within a body or fluid
• CPC Class Codes: G01N 2201/0612 Laser diodes
• CPC Class Codes: G01N 2201/062 LED's
• CPC Class Codes: G01N 2201/067 : Electro-optic, magneto-optic, acousto-optic elements
• CPC Class Codes: G01N 2201/12 : Circuits of general importance; Signal processing
• CPC Class Codes: G01N 2201/129 : Using chemometrical methods
• CPC Class Codes: G01N 33/4833 : of solid biological material, e.g. tissue samples, cell cultures tissue in vivo A61B5/00; cell suspensions G01N33/48735
• CPC Class Codes: G01N 33/49 : Blood chemical methods for determining blood cell populations G01N33/5094; chemical analysis of blood groups or blood types G01N33/80
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 : for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A collision-computing system detects and amplifies the energy associated with a feature signal to determine occurrences or absence of events, such as ultrasonic and/or geophysical events, or to determine presence and/or concentrations of substances such as blood glucose, toxic chemicals, etc., in a noisy, high-clutter environment or sample. To this end, a conditioned feature, obtained by modulating a carrier kernel with a feature signal, is collided with a Zyoton—a waveform that without a collision can travel substantially unperturbed in a propagation medium over a specified distance. The conditioned feature and the Zyoton are particularly constructed to be co-dependent in terms of their respective dispersion velocities and the divergence of a waveform resulting from the collision. The collision operation can transfer at least a portion of the feature energy to the resulting waveform, and the transferred energy can be amplified in successive collisions for detecting/measuring events/substances.

Claims

1-48. -48. (canceled)

49. A method for measuring a property associated with an information signal, the method comprising:

colliding using a collision grid a first conditioned feature waveform that at least partially represents a property of the information signal with an original Zyoton, comprising a waveform that without a collision travels substantially unperturbed at a selected velocity in a substantially constant propagation medium at least over a length of a space-time grid, to obtain a first modified Zyoton, the first conditioned feature waveform and the original Zyoton being constructed to;

(i) be co-dependent, and (ii) transfer the property of the information signal to the first modified Zyoton through the collision.

52. The method of claim 49, further comprising:

deriving the first conditioned feature waveform by modulating a carrier kernel using a first feature derived from the information signal.

55. The method of claim 52, wherein modulating the carrier kernel comprises frequency modulation of the carrier kernel using the first feature.

56. The method of claim 52, wherein modulating the carrier kernel comprises:

generating an intermediate signal by modulating the first feature using a modulation signal; and

modulating the carrier kernel with the intermediate signal.

58. The method of claim 49, wherein constructing the original Zyoton and the first conditioned feature waveform to be co-dependent comprises determining whether an absolute difference between a scaled velocity of the original Zyoton and a velocity of the first conditioned feature does not exceed a threshold κ

_DV2.

59. The method of claim 58, further comprising:

adjusting at least one of;

(i) the velocity of the original Zyoton, and (ii) the velocity of the first conditioned feature waveform, such that the absolute difference between the scaled velocity of the original Zyoton and the velocity of the first conditioned feature is within the threshold κ

_DV2.

61. The method of claim 49, further comprising:

renormalizing the first modified Zyoton to obtain a first renormalized Zyoton.

62. The method of claim 61, wherein:

the property of the information signal comprises energy absorbed by at least one of an analyte and a confounder;

the first renormalized Zyoton comprises a set of analyte-information-representing components and a set of non-analyte-information-representing components; and

the set of analyte-information-representing components of the first renormalized Zyoton represents the energy absorbed by at least one of the analyte and the confounder.

63. The method of claim 61, further comprising:

colliding using the collision grid the first renormalized Zyoton with the original Zyoton to obtain a second modified Zyoton; and

renormalizing the second modified Zyoton to obtain a second renormalized Zyoton.

64. The method of claim 63, further comprising:

iterating the colliding and renormalizing steps (Z−

2) times, N>

2, each iteration being based on a renormalized Zyoton from an immediately preceding iteration, and producing a new renormalized Zyoton, until a final renormalized Zyoton is produced after (N−

2) iterations.

65. The method of claim 63, wherein:

the at least partially represented property of the information signal comprises energy absorbed by at least one of an analyte and a confounder in a wavelength range associated with a first feature corresponding to the first conditioned feature waveform;

the final renormalized Zyoton comprises a set of analyte-information-representing components and a set of non-analyte-information-representing components; and

the set of analyte-information-representing components of the final renormalized Zyoton represents the energy absorbed by at least one of an analyte and a confounder in the wavelength range associated with the first feature.

66. The method of claim 65, further comprising:

colliding using the collision grid a second conditioned feature waveform that at least partially represents the property of the information signal with the original Zyoton, to obtain a new first modified Zyoton, the second conditioned feature waveform and the original Zyoton being constructed to;

(i) be co-dependent, and (ii) transfer the property of the information signal to the new first modified Zyoton through the collision;

renormalizing the new first modified Zyoton to obtain a new first renormalized Zyoton; and

iterating the colliding and renormalizing steps (N−

2) times, N>

2, each iteration being based on a new renormalized Zyoton from an immediately preceding iteration, and producing another new renormalized Zyoton, until a new final renormalized Zyoton is produced after (N−

2) iterations, wherein;

the new final renormalized Zyoton comprises a set of analyte-information-representing components and a set of non-analyte-information-representing components; and

the set of analyte-information-representing components of the new final renormalized Zyoton represents the energy absorbed by at least one of an analyte and a confounder in a wavelength range associated with a second feature corresponding to the second conditioned feature waveform.

83. The method of claim 49, wherein:

the collision grid comprises a frequency-domain grid; and

colliding comprises a first bracketed conditional interaction, in frequency domain, between a first component of the original Zyoton and a first bracket of components of the first conditional feature waveform.

84. The method of claim 83, wherein the first bracketed conditional interaction comprises, for each component of the first conditional feature waveform in the first bracket:

testing if frequencies of the component of the first conditioned feature waveform and the first component of the original Zyoton satisfy a first epsilon test;

if the first epsilon test succeeds, generating a component of the first modified Zyoton, and setting an amplitude of the generated component of the first modified Zyoton as a product of amplitudes of the component of the first conditioned feature waveform and the first component of the original Zyoton;

if the frequencies of the component of the first conditioned feature waveform and the first component of the original Zyoton satisfy a second epsilon test, setting a frequency of the generated component of the first modified Zyoton to a frequency of the first component of the original Zyoton; and

otherwise setting the frequency of the generated component of the first modified Zyoton to a sum of frequencies of the component of the first conditioned feature waveform and the first component of the original Zyoton.

87. The method of claim 83, wherein colliding further comprises a second bracketed conditional interaction, in frequency domain, between a second component of the original Zyoton and a second bracket of components of the first conditional feature waveform.

88. The method of claim 87, wherein the first bracketed conditional interaction produces a first component of the modified Zyoton and the second bracketed conditional interaction produces a second component of the modified Zyoton, the method further comprising:

determining if the first and second modified Zyoton components are to be merged by testing if frequencies of the first and second modified Zyoton components satisfy a third epsilon test.

90. The method of claim 88, further comprising:

merging the first and second modified Zyoton components into the first modified Zyoton component by resetting an amplitude of the first modified Zyoton component to a sum of amplitudes of the first and second modified Zyoton components; and

removing the second modified Zyoton component.

98. The method of claim 49, wherein the original Zyoton is synthesized from at least one of a plurality of waveform families comprising:

solitons;

autosolitons;

similaritons;

custom solitons generated using a sine-Gordon-based equation;

self-compressing similaritons;

vortex-solitons;

multi-color solitons;

parabolic-similaritons;

Ricci solitons;

wavelets;

curvelets;

ridgelets;

bions;

elliptic waves comprising at least one of Jacobi elliptic functions and Weierstrass elliptic functions; and

nonautonomous similinear wave equation.

99. The method of claim 49, wherein the original Zyoton is synthesized from at least one of a plurality of waveform generators comprising:

meromorphic functions;

Gamma functions;

Riemann Zeta functions;

regular instantons;

Frobenius manifolds;

harmonic oscillators;

Hermite polynomials;

polynomial sequences;

asymptotic Hankel functions;

Bessel functions;

fractals;

Neumann functions (spherical);

poweroid coupled with sinusoidal functions;

spatial random fields;

cyclostationary series;

random number generators;

spherical harmonics;

chaotic attractors;

exponential attractors;

multipoint Krylov-subspace projectors;

Lyapunov functions;

inertial manifolds of Navier-Stokes equation;

evolution equation for polynomial nonlinear reaction-diffusion equation;

evolution equation for Kuramoto-Savashinsky equation;

evolution equation of exponential attractors;

Fourier series; and

Ramanujan theta functions.

104. The method of claim 49, wherein the original Zyoton is synthesized, at least in part, from at least one of:

(i) a waveform family and (ii) a waveform generator, the method further comprising;

at least one of transforming and reducing a function to at least one of the waveform family and the waveform generator.

50-51. -51. (canceled)

53-54. -54. (canceled)

57. (canceled)

60. (canceled)

67-82. -82. (canceled)

85-86. -86. (canceled)

89. (canceled)

91-97. -97. (canceled)

100-103. -103. (canceled)

105. (canceled)

106. A system for measuring a property associated with an information signal, the system comprising:

a first processor; and

a first memory in electrical communication with the first processor, the first memory comprising instructions which, when executed by a processing unit comprising at least one of the first processor and a second processor, and in electronic communication with a memory module comprising at least one of the first memory and a second memory, program the processing unit to;

collide using a collision grid a first conditioned feature waveform that at least partially represents a property of the information signal with an original Zyoton, comprising a waveform that without a collision travels substantially unperturbed at a selected velocity in a substantially constant propagation medium at least over a length of a space-time grid, to obtain a first modified Zyoton, the first conditioned feature waveform and the original Zyoton being constructed to;

(i) be co-dependent, and (ii) transfer the property of the information signal to the first modified Zyoton through the collision.

107-214. -214. (canceled)

215. A method of quantitating an analyte, the method comprising:

receiving from an uncharacterized sample an energy change value to be mapped, the energy change value corresponding to an uncharacterized sample;

mapping the energy change value to be mapped to a quantity of an analyte in the uncharacterized sample, via an individual projector curve associating;

(i) energy change values obtained from a synthetic reference system to analyte quantities of the reference system, and (ii) energy change values obtained from a non-synthetic reference system to the analyte quantities of the reference system.

216. The method of claim 215, further comprising:

computing a representative absorption gradient (AG) using a first set of energy change values corresponding to a first feature pair, each energy change value in the first set corresponding to a respective path of radiation through a medium to be analyzed;

selecting the individual projector curve from a plurality of projector curves using the representative gradient value associated with the first feature pair; and

determining a quantity of an analyte using the selected individual projector curve, the energy change value to be mapped being a representative energy change value associated with the first feature pair.

217. The method of claim 216, wherein the representative gradient value comprises a normalized AG (NAG), the method further comprising:

weighing the representative gradient associated with the first feature pair by a weight associated with the first feature pair, to obtain the NAG.

218. The method of claim 216, wherein computing the representative energy change value comprises weighting one energy change value from the first set of energy change values by a weight associated with the first feature pair.

219. The method of claim 216, wherein a plurality of feature pairs comprises the first feature pair, the method further comprising:

generating a set of acceptable feature pairs from the plurality of feature pairs;

for each feature pair in the set of acceptable feature pairs computing a respective absorption gradient (AG) using a respective set of energy change values corresponding to the feature pair;

computing the representative AG value as an average of the respective AGs associated with each of the acceptable feature pairs.

220. The method of claim 219, wherein generating the set of acceptable feature pairs comprises testing for each feature pair in the plurality of feature pairs monotonicity of the corresponding set of energy change values across a plurality of illumination states.

221. The method of claim 219, wherein computing the AG for each acceptable feature pair comprises:

determining a slope of a regression of the corresponding set of energy change values with respect to the illumination states, the illumination states being ordered such that successive illumination states represent monotonically changing distance between the source and at least one detector.

223. The method of claim 219, wherein computing the representative energy change value comprises:

for each acceptable feature pair, selecting one energy change value from the respective set of energy change values;

weighting for each acceptable feature pair, the selected energy change value by a weight associated with the acceptable feature pair; and

setting an average of the weighted energy change values as the representative energy change value.

222. (canceled)

224-225. -225. (canceled)

226. A system of quantitating an analyte, the system comprising:

a first processor; and

a first memory in electrical communication with the first processor, the first memory comprising instructions which, when executed by a processing unit comprising at least one of the first processor and a second processor, and in electronic communication with a memory module comprising at least one of the first memory and a second memory, program the processing unit to;

receive an energy change value to be mapped, the energy change value corresponding to an uncharacterized sample; and

map the energy change value to be mapped to a quantity of an analyte in the uncharacterized sample, via an individual projector curve associating;

(i) energy change values obtained from a synthetic reference system to analyte quantities of the reference system, and (ii) energy change values obtained from a non-synthetic reference system to the analyte quantities of the reference system.

227-262. -262. (canceled)