Multi-tier method of developing localized calibration models for non ...

USO0RE41333E

(19) United States (12) Reissued Patent

(10) Patent Number:

Blank et al. (54)

(45) Date of Reissued Patent:

MULTI-TIER METHOD OF DEVELOPING

(56)

U_$_ PATENT DOCUMENTS

NON'INVASIVE BLOODANALYTE

5204532 A , ,

PREDICTION

5,553,616 A

Inventors: Thomas B- Blank’ Ch§nd1eLAZ (Us);

5,725,480 A

Stephen L-M0I1fre,G11berI,AZ (Us);

5,798,526 A

4/1993 Rosen 1111 161 . a e *

5,576,544 A

Timothy L. Ruchti, Gilbert, AZ (US); Suresh N. Thennadill, Gosforth (GB)

(73) Assignee: Sensys Medical, Inc., Chandler, AZ

(Us) (21) Appl.No.: 11/046,673 (22) Filed:

11/1996

250/341 ......... ..

116616161. ............. .. 128/925 116661111161 .... ..

3/1998 OOSta 6161. *

250/3411

..... .. 600/310

8/1998 Shenk 6161. ......... .. 250/33909

* cited by examiner

Primary ExamineriEr‘ic F Winakur (74) Attorney, Agent, or FirmiMichael A. Glenn; Glenn

Patent Group (57)

ABSTRACT

invasive blood analyte prediction minimizes prediction error

by limiting co-varying spectral interferents. Tissue samples are categorized based on subject demographic and instru mental skin measurements, including in vivo near-IR spec tral measurements. A multi-tier intelligent pattern classi?ca tion sequence organizes spectral data into clusters having a

Related US. Patent Documents

Reissue of:

(63)

9/1996

A method of multi-tier classi?cation and calibration in non

Jan. 27, 2005

(64) Patent No.:

May 11, 2010

References Cited

LOCALIZED CALIBRATION MODELS FOR

(75)

US RE41,333 E

6,512,937

Issued:

Jan. 28, 2003

Appl. No.: Filed:

09/825,687 Apr. 3, 2001

high degree of internal consistency in tissue properties. In each tier, categories are successively re?ned using subject demographics, spectral measurement information and other

Continuation-in-part of application No. 09/359,l9l, ?led on Jul. 22, 1999, now Pat. NO. 6,280,381.

device measurements suitable for developing tissue classi? cations.

(2006.01)

The multi-tier classi?cation approach to calibration utilizes multivariate statistical arguments and multi-tiered classi?ca tion using spectral features. Variables used in the multi

(52)

US. Cl. ....................... .. 600/322; 128/920; 600/310

tiered classi?cation can be skin surface hydration, skin sur

(58)

Field of Classi?cation Search ................ .. 600/310,

(51) Int. (31. A613 5/1455

600/322, 323, 330, 336,473; 128/920, 923, 128/924, 925, 356/402; 250/340, 341.1, 339.01, 702/19

face temperature, tissue volume hydration, and an assessment of relative optical thickness of the dermis by the near-IR fat band. All tissue parameters are evaluated using

the NIR spectrum signal along key Wavelength segments.

See application ?le for complete search history.

68 Claims, 9 Drawing Sheets

Measurement _n'_1

Prep rocessfng K Patient

/ 721

0

Clossi ficotion

Blood Ancllyte Concent rot ion

US. Patent

May 11,2010

Sheet 2 of9

US RE41,333 E

Algorithm Manager Management Level

f Adoption Rules Performance . Momtor

System State

Blood Analyte

Estimqte

Event

Coordinator

Coordinotion

Feature

Classification

Calibration

Lave‘

Extraction

System

Algorithm

41

Execution Level

M

easu remen

FIG. 2

t

P

.

rep races 5| ng

US. Patent

May 11,2010

Sheet 3 of9

53 _\

Measurement

:Q Feature

c’ossi?cquon

US RE41,333 E

54 1

Decision

CIOSS

Extmc?on p (Pre?ggtellon) 5> Engine F>Assignment FIG. 3

1.5"

ubsorbunce

‘1 0.5

12'00 14450 1sbo 1800 2660 2200 24'00 wavelength, nm

FIG. 4

US. Patent

May 11,2010

Sheet 4 of9

US RE41,333 E

61

combination region\ woter bond

2.5

\

2“ first overtone

water bond ]

1.5 cbsorbonce 1. 0 .5

1260

14b0

1660

1800 2600 22'00 2460

woveieng’ch, nm

FIG. 5

US. Patent

May 11,2010

Sheet 5 of9

US RE41,333 E

61

combination region \ water bond 2.5

\

2' first overtone

water bond] 1 5% obso rbonce 1-4

0 .5—

1260

14b0

1600 E00 20'00 2260 24630 wavelength, nm

FIG. 6

US. Patent

May 11,2010

Sheet 6 019

US RE41,333 E

1.7l 1.0 1.s~ 1.4 obsorbcnce

1.3‘

1.21

1.1_ 1‘ 0.91 O.8