WO2009136338A1

WO2009136338A1 - An adaptable probe having illumination and detection elements

Info

Publication number: WO2009136338A1
Application number: PCT/IB2009/051801
Authority: WO
Inventors: Bastiaan W. M. Moeskops; Golo Von Basum; Yan Liu; Kiran K. Thumma
Original assignee: Koninklijke Philips Electronics N.V.
Priority date: 2008-05-08
Filing date: 2009-05-04
Publication date: 2009-11-12

Abstract

A device for analyzing a material using illumination and optical sensing has an adaptable probe having an array of locations switchable for use as optical sources for the illumination or as optical receivers for the sensing, and a controller arranged to determine a pattern of locations of sources and receivers for the analyzing, and to switch the locations according to the pattern to adapt the probe. By adapting the probe, localized interference effects can be reduced or avoided, and measurements can be concentrated where a stronger signal can be obtained. This adaption can be repeated to adapt to dynamically changing spatial properties of the interfering effects.

Description

An adaptable probe having illumination and detection elements

FIELD OF THE INVENTION

This invention relates to devices for analysis of a material, and to corresponding systems and methods for manufacturing and operating the same.

BACKGROUND OF THE INVENTION

Obtaining values for biological or physical quantities in a living body in a noninvasive way has been thoroughly studied over the last few years. Obtaining accurately reproducible results by using sophisticated sensing and actuating devices for medical purposes may become difficult when sensors have to be repeatedly removed and replaced. Currently, many efforts have been put in developing instruments for noninvasive measurement of physiological parameters in a human or animal body, such as for example glucose measurements, based on optical methods. Although these methods have proven to have sufficient sensitivity for in-vitro and/or ex-vivo glucose quantification, devices based on such currently existing techniques have not been successfully brought to the market. The main reason for that is that the accuracy of recently developed devices is not sufficient to get an FDA (food and drug administration) approval.

Also instruments have been developed for minimally invasive measurement of physiological parameters in a human or animal body, such as for example glucose measurements, e.g. based on optical methods. These methods make use of a sensor implanted beneath the skin which is in contact with subcutaneous fluids. The sensor may include gels, particles, liquids which are biodegradable. Preferably, the biosensor that has to be implanted is small in size, and does not require a complicated or painful insertion below the skin.

Non-invasive measurement is the most desirable method for consumers. But the uncertainty and inaccuracy hampered the acceptance of non- invasive tests. There is a strong need in the non-invasive glucose-monitoring market to solve the inaccuracy or unreliability problems.

Many techniques have been investigated to non-invasively detect skin analyte(s) concentration by means of optical, electrical and/or optoelectronic methods, such as for example non-invasive glucose monitoring. Typically, in vivo measurements deal with a larger number of chemical, physical, and physiological interfering elements compared to in vitro measurements. These interfering elements induce ^reproducibility and inaccuracy of non- invasive measurements. Information on the presence of interfering elements, their effects, and variability range are often not known. Typically, data analysis of a system where a number of interfering elements is present is based on chemometric tools, e.g. multivariate analysis. However, for complex and variable systems such as e.g. human tissue, chemometric analysis becomes more complicated and may be prone to large errors. The accuracy and reproducibility of these measurements are generally poor due to the many interfering elements and ^reproducibility comparing with in vitro case. An example of an irreproducible factor is the placement of the measurement device on the skin. The morphology of the skin 1 is different at different locations (see Fig. 1), which leads to variations in the optical properties from site to site. Another irreproducible factor is the relative position of the sensing device to an implanted minimally invasive biosensor. US6411373 shows an example of a probe designed to launch and collect light from a tissue sample, such as human skin. It relates to optimization of patterns of fiber optics used for illumination and detection, and their shapes, and locations for use in the noninvasive global-estimation of analytes, such as blood glucose.

By systematically exploring patterns, shapes, and fiber locations, it teaches that it is possible to optimize the optical system design by maximizing desirable quantities in a system model, for example the signal-to-noise ratio (SNR).

In the example of the signal-to-noise ratio, the signal is directly related to the photon pathlength in the subject's dermis and the noise is approximately inversely proportional to the intensity as a function of wavelength and detector to illumination fiber separation distance. This and other information is incorporated into a single program that uses a graphical user interface to allow for an interactive design and analysis of an arbitrary fiber layout. Designs are saved and used as input into a genetic algorithm that selects the best designs and attempts to improve upon them. The best pattern is then modified slightly (which usually leads to marginal incremental improvements) to yield a regular pattern throughout and to fit into the external geometry selected (in this case a hexagon or a rectangle).

Additionally, the number of fibers at a monochromator output slit and at the bundle termination at a detector optics stack can be determined, causing the optimization to become particularly constrained. Once this constraint is in place, it becomes significantly easier for the pattern of illumination and detection fibers to be investigated and optimized. To discover what pattern yields the best results, hundreds of initialization patterns were investigated. Each of these patterns is used as input to a genetic algorithm that keeps the best patterns and tries to improve upon them. After a certain amount of effort, the genetic algorithm is discontinued and the best results are examined. The basic pattern comprises alternating columns of illumination and detection fibers.

SUMMARY OF THE INVENTION

An object of the invention is to provide devices for analysis of a material, or corresponding systems or methods for manufacturing or operating the same. A first aspect of the invention provides:

A device for analyzing a material using illumination and optical sensing, the device having an adaptable probe having an array of locations for use as optical sources for the illumination or as optical receivers for the sensing, and a controller arranged to determine a pattern of locations of sources and receivers for the analyzing, and to configure the locations according to the pattern to adapt the probe. The locations are configurable, e.g. can function as switchable locations, which are switchable between a role as source location, receiving location, or neither. Alternatively, the switchable locations have a fixed role as either source or receiver location, but can be switched between an 'open' and 'closed' state. By adapting the probe, localized interference effects can be reduced or avoided, and/or measurements can be concentrated where a stronger signal can be obtained. This adaption can be repeated to adapt to dynamically changing spatial properties of the interfering effects or to the uncertainty of the position of a buried microsensor.

Another aspect of the invention provides a method of adapting a probe for analyzing a material using illumination and optical sensing, the probe having an array of locations configurable for use as optical sources for the illumination or as optical receivers for the sensing the method having the steps of determining a pattern of locations of sources and receivers for the analyzing, and adapting to configure the locations according to the pattern in order to adapt the probe. The locations can be configurable, e.g. can function as switchable locations, and the method can include switching a location between a role as source location, receiving location, or neither. Alternatively, the switchable locations have a fixed role as either source or receiver location, and the method includes switching between an 'open' and 'closed' state.

Another aspect provides a computer program for carrying out a corresponding method of adapting a probe. Another aspect is a computer readable medium with the computer program stored thereon.

Embodiments of the invention can have any other features added, some such additional features are set out in dependent claims and described in more detail below. Any of the additional features can be combined together and combined with any of the aspects. Other advantages will be apparent to those skilled in the art, especially over other prior art. Numerous variations and modifications can be made without departing from the claims of the present invention. Therefore, it should be clearly understood that the form of the present invention is illustrative only and is not intended to limit the scope of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 shows the photon density plot of a single (ID) fibre pair, Fig. 2 shows arbitrary configurations of the elements which might result from the optimization procedure, depending on spectral features and boundary conditions,

Fig. 3 is a schematic view of the adaptable probe according to an embodiment, having a matrix of source- and detector-elements, realized by standard NIR optical components,

Fig. 4 shows the absorption measurement of water, oxygenated blood and de- oxygenated blood,

Fig. 5 show the absorption spectrum of fat,

Fig. 6 shows graphs of experimental results showing measured diffuse reflectance spectra from a paper phantom with and without a hair attached (left). The hairs show distinct absorption features suitable to be used as a quality measure. The right figure shows in vivo spectra of scarred and non scarred skin,

Fig. 7 shows a schematic representation of the optimization algorithm, and Figs. 8 and 9 show a one-dimensional example of standard configuration (left), and optimized configuration (right) showing how a wider spacing of illuminator and receiver enable the light path to avoid surface interference. Fig. 10 shows a one-dimensional example of a configuration of illuminator and receiver for a microsensor.

DETAILED DESCRIPTION OF EMBODIMENTS

The present invention will be described with respect to particular embodiments and with reference to certain drawings but the invention is not limited thereto but only by the claims. Any reference signs in the claims shall not be construed as limiting the scope. The drawings described are only schematic and are non-limiting. In the drawings, the size of some of the elements may be exaggerated and not drawn on scale for illustrative purposes.

Where the term "comprising" is used in the present description and claims, it does not exclude other elements or steps. Where an indefinite or definite article is used when referring to a singular noun e.g. "a" or "an", "the", this includes a plural of that noun unless something else is specifically stated. Furthermore, the terms first, second and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a sequence, either temporally, spatially, in ranking or in any other manner. It is to be understood that the terms so used are interchangeable under appropriate circumstances and that the embodiments of the invention described herein are capable of operation in other sequences than described or illustrated herein.

Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to one of ordinary skill in the art from this disclosure, in one or more embodiments.

Similarly it should be appreciated that in the description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention. Furthermore, while some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention, and form different embodiments, as would be understood by those in the art. For example, in the following claims, any of the claimed embodiments can be used in any combination.

Furthermore, some of the embodiments are described herein as a method or combination of elements of a method that can be implemented by a processor of a computer system or by other means of carrying out the function. Thus, a processor with the necessary instructions for carrying out such a method or element of a method forms a means for carrying out the method or element of a method. Furthermore, an element described herein of an apparatus embodiment is an example of a means for carrying out the function performed by the element for the purpose of carrying out the invention. References to a signal can encompass any kind of signal in any medium, and so can encompass an electrical or optical or wireless signal or other signal for example. References to analyzing can encompass processing a signal in any way to derive or enhance information about the material.

References to a controller can encompass any means for controlling and so can encompass for example a personal computer, a microprocessor, analog circuitry, application specific integrated circuits, software for the same, and so on.

The present invention also includes a computer program product which provides the functionality of any of the methods according to the present invention when executed on a computing device. Such computer program product can be tangibly embodied in a carrier medium carrying machine -readable code for execution by a programmable processor. The present invention thus relates to a carrier medium carrying a computer program product that, when executed on computing means, provides instructions for executing any of the methods as described above. The term "carrier medium" refers to any medium that participates in providing instructions to a processor for execution. Such a medium may take many forms, including but not limited to, non-volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such as a storage device which is part of mass storage. Common forms of computer readable media include, a CD-ROM, a DVD, a flexible disk or floppy disk, a tape, a memory chip or cartridge or any other medium from which a computer can read. Various forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution. The computer program product can also be transmitted via a carrier wave in a network, such as a LAN, a WAN or the Internet. Transmission media can take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications. Transmission media include coaxial cables, copper wire and fibre optics, including the wires that comprise a bus within a computer. In the description provided herein, numerous specific details are set forth.

However, it is understood that embodiments of the invention may be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

By way of introduction to the embodiments, the problem of interference sources in optical sensing such as non invasive blood glucose monitoring will be discussed briefly. The present invention is not limited to glucose measurement. For example, the measurement of glucose through near- infrared spectroscopy is based on a change in the concentration of glucose being indicated by a change in the absorption of light according to the absorption and scattering properties of glucose and/or the effect of glucose changes upon the anatomy and physiology of the sampled site. The measurement of glucose through spectroscopy can also be made by a change in the absorption of light according to the absorption and scattering properties of minimally invasive microsensors, or to the change in light emitted or reflected from such microsensors located below the skin. Such methods using microsensors may include, for example, - observing fluorescence (e.g. fluorescence resonance energy transfer) of a competitive binding assay encapsulated in microcapsules, for example based on competitive binding between the protein Concanavalin A and various saccharide molecules, specifically a glycodendrimer and glucose, the microcapsules can be polyelectrolyte microcapsules, detecting glucose using boronic acid-substituted violegens in fluorescent hydrogels in which a fluorescent anionic dye and a viologen are appended to boronic acid, which serve as glucose receptors, and are immobilised into a hydrogel, the fluorescence of the dye being modulated by the quenching efficiency of the viologen based receptor which is dependent upon the glucose concentration, other methods, e.g. to monitor oxygen or pH or other "smart tattoo" methods. However, in addition to the effect of glucose or the microsensors on the near- infrared light probing signal that is delivered to the skin, the probing signal is also reflected, diffusely reflected, transmitted, scattered, and absorbed in a complex manner related to the structure and composition of the tissue. When near- infrared light is delivered to the skin, a proportion of reflected light, or specular reflectance, is typically between 4-7% of the delivered light over the entire spectrum. Absorption by the various skin constituents accounts for the spectral extinction of the light within each layer. Scattering is the main process by which the beam may be returned to contribute to the diffuse reflectance of the skin. Scattering also has a strong influence on the light that is diffusely transmitted through a portion of the skin.

The scattering of light in tissues is in part due to discontinuities in the refractive indices on the microscopic level, such as the aqueous-lipid membrane interfaces between each tissue compartment or the collagen fibrils within the extracellular matrix. The spectral characteristics of diffuse remittance from tissue result from a complex interplay of the intrinsic absorption and scattering properties of the tissue, the distribution of the heterogeneous scattering components, and the geometry of the point(s) of irradiation relative to the point(s) of light detection. It is this geometry that can be improved by the adaptive bundle as will be described below.

The near-infrared absorption of light in tissue is primarily due to overtone and combination absorbances of C-H, N-H, and O-H functional groups. As skin is primarily composed of water, protein, and fat; these functional groups dominate the near-IR absorption in tissue. As the main constituent, water dominates the near- infrared absorbance above 1100 nm and is observed through pronounced absorbance bands at 1450, 1900, and 2600 nm. Protein in its various forms, in particular, collagen is a strong absorber of light that irradiates the dermis. Near-infrared light that penetrates to subcutaneous tissue is absorbed primarily by fat. In the absence of scattering, the absorbance of near- infrared light due to a particular analyte, A, can be approximated by Beer's Law. An approximation of the overall absorbance at a particular wavelength is the sum of the individual absorbance of each particular analyte given by Beer's Law. The concentration of a particular analyte, such as glucose, can be determined through a multivariate analysis of the absorbance over a multiplicity of wavelengths because it is unique for each analyte. However, in tissue compartments expected to contain glucose, the concentration of glucose is at least three orders of magnitude less than that of water. Given the known extinction coefficients of water and glucose, the signal targeted for detection by reported approaches to near-infrared measurement of glucose, i.e. the absorbance due to glucose in the tissue, is expected to be, at most, three orders of magnitude less than other interfering tissue constituents. Therefore, the near-infrared measurement of glucose requires a high level of sensitivity over a broad wavelength range. Multivariate analysis is often utilized to enhance sensitivity. In addition, the diverse scattering characteristics of the skin, e.g. multiple layers and heterogeneity, cause the light returning from an irradiated sample to vary in a highly nonlinear manner with respect to tissue analytes, in particular, glucose. Simple linear models, such as Beer's Law have been reported to be invalid for the dermis. Dynamic properties of the skin also add to the difficulties. Variations in the physiological state and fluid distribution of tissue profoundly affect the optical properties of tissue layers and compartments over a relatively short period of time. The optical properties of the microsensors, for example, may depend upon the location depth below the skin surface. For all these reasons therefore, the optical properties of the tissue sample are modified in a highly nonlinear and profound manner that introduces significant interference into non-invasive tissue measurements.

Currently a number of companies are developing instruments for non-invasive glucose measurements based on near-infrared diffuse reflectance spectroscopy. Although this method is proven to have sufficient sensitivity for in- vitro and/or ex-vivo glucose quantification, none of the currently existing companies was successful in bringing a noninvasive device to the market. The main reason is that the accuracy of recently developed devices is not sufficient to get FDA approval.

Near infrared spectroscopy of skin is a promising method to measure a person's glucose level non-invasively or minimally invasively. It is known from the art that the configuration of source and detector elements determines which volume of tissue is probed. For example, by increasing the separation distance between illumination and collection fibre, the measurement volume is placed deeper in the skin. This means that morphological disturbances could be avoided by using the proper source-probe configuration. Figure 1, Figure 1 shows a photon density plot with the illumination fibre on the right

(top), and the collection fibre on the left. By changing the separation distance the shape of the photon density changes. When this simple example is expanded to a 2D-matrix of illumination and collection fibres, the shape of the photon density can be changed considerably by applying different source-detector configurations. Many techniques are investigated to detect skin analyte(s) concentration non- invasively by means of optical, electrical and/or optoelectronic methods, e.g. non-invasive glucose monitoring. Typically, in vivo measurements deal with a larger number of chemical, physical, and physiological interferents in comparison to in vitro case. Information on the presence of interferents, their effects, and variability range are often not known. Typically, data analysis of a system where a number of interferents is present is based on chemometric tools, e.g. multivariate analysis. However, for such a complex and variable system as human tissue chemometric analysis becomes more complicated and is prone to large errors. The accuracy and reproducibility of these measurements are generally poor due to the many interferents comparing with in vitro case. One of the key interferents is skin morphology. Skin is a very heterogeneous medium. Current methods use a fixed probe- source configuration, which might be optimized for average features within the customer population. Although they may use multiple source-detector elements (as shown in WO 2005/004712), current methods can not adapt the probe-source configuration to the measurement site. This creates the need for elaborate measures to ensure the probe is placed on the same location every time to a high degree of accuracy.

Accordingly, at least some of the embodiments of the invention have a novel surface interface (e.g. skin-interface) to be used in, for example, non-invasive glucose monitoring. An adaptive matrix of source- and detector-elements configures itself for optimal performance, taking into account the variable interfering features such as tissue morphology. Based on factory defined boundary conditions and quality measures, the device activates the proper elements in the matrix to access the desired tissue regions. Additional features:

Embodiments can have any additional features as well as those features set out in the independent claims. Some additional features are as follows:

The array of locations can comprise one end of a bundle of optical fibers, the other end of the fibers being coupled to optical switches for coupling each of the fibers either to a light source or to a sensor.

The array of locations can comprise an array of sensors and optical sources, and electrical circuitry for switching selected ones of the sensors or optical sources on or off according to the pattern.

The controller can be arranged to make measurements to analyse the material, determine a quality of the measurements, and determine a revised pattern based on the quality of the measurements. The controller can be arranged to use spectral features due to morphology as quality measures, or to generate an image of the material, and to determine the quality measure from the image.

The controller can be arranged to use a genetic algorithm to determine a revised pattern. A reference to genetic algorithm is: David E. Goldberg, Genetic Algorithms in Search, Optimization & Machine Learning; Addison- Wesley Publishing Company, Inc.; 1989.

An optimization routine ensures the minimizing of unwanted features in the spectrum, and the maximizing of desired features in the diffuse reflectance spectrum. The result is an optimized shape of the photon density in tissue, such that more photons travel through desired regions, and less through interfering structures such as hairs, sweat glands etc. This leads to an increase in the accuracy and reproducibility of minimally invasive or non- invasive measurement of analytes in skin, when using diffuse reflectance spectroscopy. As described, these features can enable tailoring of the measurement volume to the measurement site and/or tailoring to the microsensors located below the skin and/or to the patient. They can create a higher tolerance for changes in positioning of the device. This can lead to reduced measurement errors due to variations in skin morphology, by microsensor placement or microsensor degradation by adjusting the shape and location of the measurement volume. In this way, unwanted features on skin (hair, scars, stratum corneum, etc) can be avoided and desired targets can be reached and concentrated on (such as blood vessels, fat layer, capillary bed, microsensors). This can generate more reliable and reproducible data.

Figure 2 embodiment Some features of embodiments which will be discussed are as follows:

A controllable 2D-matrix of source- and detector-elements is provided. A configuration mode is provided in which multiple source-detector combinations are activated, and each resulting spectrum is analyzed for desired and undesired features. A selection of a source-detector-confϊguration for measurement is made, based on optimizing of spectral features. An optimization routine is used to identify the optimal pattern of source- and detector-elements. Spectral features due to morphology (e.g. fat absorption, water absorption, melanin absorption), or the optical properties of one or more microsensors located beneath the skin or an imaging modality can serve as the quality measure for example. Finally the spectroscopic measurement is performed using the selected configuration. The multiple source and detector elements can be placed in an array. This array of source- and detector-elements can be produced in various ways. Two possible embodiments will be discussed.

Fibre-based embodiment

In this embodiment as shown in figure 2, the source and detector elements are formed by at least three optical fibres. Fibre switchers are used to connect the fibres either to a broadband lightsource, a spectrometer, or to put them in an inactive state. In this way each element can be switched between acting as a lightsource, a detector, and being inactive.

The fiber switch part can be implemented using established technologies such as MEMs based mirrors. A controller controls the various parts of the device, and may follow the sequence shown in figure 7 for example. The controller can be implemented using software in conventional languages, executed by conventional processing hardware such as a PC, or embedded microprocessor or ASIC for example. Diode based embodiment This embodiment uses a matrix of at least three LEDS or OLEDS as the source-elements. Photodiodes are used as detector elements. The difference with the previous embodiment is that the light source and detectors are included in the matrix itself. This allows for a compact, sheet-like, device.

Optimization of the pattern There are at least three methods to optimize the pattern of the source- and detector-elements. The first is to use spectral features resulting from morphology or from the optical properties of microsensors as quality measures. The second is to use spectral features resulting from the optical properties of microsensors as a quality measure. The third method is to use the output from an imaging modality as a quality measure. Spectroscopic measurement methods obtain a signal from the sample as a function of radiation wavelength, a spectrum. A spectral quality measure is a feature in the observed spectrum that is an indicator of the quality of the current configuration of the source and receiver locations. An optimization routine can try to maximize, or minimize such a quality measure. As an example we assume that the objective is to measure the concentration of an analyte (e.g. glucose) in the dermis. Contributions to the observed spectrum from sources outside the dermis, such as hairs and fat can then be seen as unwanted. If these sources have a recognizable spectral signature, this signature can serve as a quality measure. In this case, the command to the optimization routine could be: minimize the signal from hair and fat. To avoid the optimization routine giving unrealistic solutions, boundary conditions can be introduced. For example, the maximum distance between source and closest receiver is 5 mm. Another example: the minimum amount or activated receivers is 1.

As a further example we assume that the objective is to measure the concentration of an analyte (e.g. glucose) in the tissue by minimally invasive methods. The contributions to the observed spectrum from microsensors located below the skin are those that are wanted. If these sources have a recognizable spectral signature, this signature can serve as a quality measure. In this case, the command to the optimization routine could be: maximise the signal from microsensors. To avoid the optimization routine giving unrealistic solutions, boundary conditions can be introduced. For example, the maximum distance between source and closest receiver is 5 mm. Another example: the minimum amount or activated receivers is 1.

An imaging modality is a technology that images the skin. Such a technology typically provides information in the form of intensity vs. position (a picture). Examples are: Optical Coherence Tomography, Orthogonal Polarized Spectral Imaging, and Ultrasound, among others. Such an imaging modality could locate e.g. a hair, which could be an unwanted element. The location of the hair is then send to the controller. The controller then configures the locations (sources/receivers/off) such that the contribution of this hair to the total spectral signal is minimized. Using spectral features due to morphology as quality measures

Structures or analytes with distinct spectral features can serve as quality measures. Figures 4, 5 and 6 show absorption spectra of some of the analytes that can serve as quality measures. Fig 4 shows the absorption measurement of water, oxygenated blood and de-oxygenated blood. Fig 5 shows the absorption spectrum of fat, and Fig 6 shows graphs of experimental results showing measured diffuse reflectance spectra from a paper phantom with and without a hair attached (left). The hairs show distinct absorption features suitable to be used as a quality measure. The right figure shows in vivo spectra of scarred and non scarred skin,

When using spectral features as a quality measures there is need to optimize the spectrum. One approach is to try a number of predefined configurations and see which performs best.

Figure 7 shows how the algorithm determines the optimum fibre configuration. At first the pattern is changed. The spectrum is measured. An assessment of how optimal it is, is made. If less optimal than a threshold, the pattern is changed and spectrum measurement repeated. Once sufficiently optimal, a measurement is taken.

In some embodiments the assessment and changing of the pattern can involve a sophisticated 'learning' optimization routine. A method that is well suited to this type of optimization task is the use of a genetic algorithm. A genetic algorithm (GA) is a technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms (also known as evolutionary computation) that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover (also called recombination).

Genetic algorithms are implemented as a computer simulation in which a population of abstract representations (called chromosomes or the genotype or the genome) of candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem evolves toward better solutions. Traditionally, solutions are represented in binary as strings of Os and Is, but other encodings are also possible. The evolution usually starts from a population of randomly generated individuals and happens in generations. In each generation, the fitness of every individual in the population is evaluated, multiple individuals are stochastically selected from the current population (based on their fitness), and modified (recombined and possibly randomly mutated) to form a new population. The new population is then used in the next iteration of the algorithm. Commonly, the algorithm terminates when either a maximum number of generations has been produced, or a satisfactory fitness level has been reached for the population. If the algorithm has terminated due to a maximum number of generations, a satisfactory solution may or may not have been reached. Genetic algorithms find application in biogenetics, computer science, engineering, economics, chemistry, manufacturing, mathematics, physics and other fields. A typical genetic algorithm requires two things to be defined:

1. a genetic representation of the solution domain,

2. a fitness function to evaluate the solution domain. During the configuration step, a number of 'test'-configurations are evaluated.

This algorithm could consist of a predefined set up configurations. It could also allow for 'organic' growth towards an optimum configuration, e.g. by the use of a genetic algorithm. The quality measure during this evaluation is predefined. In the example illustrated in Figures 8 and 9 it is desired to maximize the signal acquired from the capillary bed, and minimize the signal from hairs which are both characterized by distinct spectral features. Figure 8 shows how a non-optimized configuration places the measurement volume (dark=emission fibre, grey = collection fibre, white= inactive). In this case the depth of the capillary bed is not reached, and the measurement volume contains two hairs. This will significantly degrade the signal quality. By contrast, in figure 9 an improved pattern of locations provides greater spacing which produces a stronger signal. This is obtained by minimizing the unwanted spectral signature of hair, and maximizing the desired signal of the capillary bed. In this case the adaptation of the locations in the probe has found a configuration that allows the photon density to reach the capillary bed, while avoiding the hairs. Once this near-optimum configuration is selected the diffuse reflectance spectrum is measured. Using light from microsensors as a quality measure

When using microsensors that may include chips, gels, liquids, particles etc. a quality measure can be the optical properties of such sensors. The spectral properties of light returned from such microsensors may be used to identify the location of invisible microsensors, and also to optimise the pattern and/or position of the source- and detector- elements. Methods given above to optimise spectral characteristics can be used in this embodiment as well, however with the difference that the optimisation in general will be to maximise signals from the microsensors. Optionally the optimisation may also involve minimisation of interference effects as described for the previous embodiment. The fluorescent emissions from microsensors such as "smart tattoos" located below the skin is an example of the optical properties of microsensors that may be used as a quality measure.

Figure 10 it is desired to maximize the signal acquired from the microsensor. Preferably it is also desired, as the same time, to minimize the signal from hairs which are possibly both characterized by distinct spectral features. In figure 10 a pattern of locations provides a strong signal. This is obtained by maximizing the desired signal from the microsensor. In this case the adaptation of the locations in the probe has found a configuration that allows the photon density to reach the microsensor, preferably while avoiding the hairs. Once this near-optimum configuration is selected the diffuse reflectance spectrum is measured.

Using an imaging modality as a quality measure

A different approach is to use an imaging modality as a quality measure. A technique such as Optical Coherence Tomography, Orthogonal Polarized Spectral Imaging, or Ultrasound could be used to locate desired and unwanted features. Using back-calculation, the appropriate elements of the source-detector array can then be addressed.

Many applications of the embodiments can be envisaged. An opto -mechanical probe skin interface, as proposed here, is needed by most techniques that sense analytes within the skin. The embodiments can be applied for minimally invasive or non-invasive glucose detection by means of NIR diffuse back-reflectance spectroscopy. Further applications include measurements of skin properties (e.g. skin cancer, skin aging, etc.) by means of light.

Other variations can be envisaged within the scope of the claims.

Claims

CLAIMS:

1. A device for analyzing a material using illumination and optical sensing, the device having an adaptable probe having an array of locations for use as optical sources for the illumination or as optical receivers for the sensing, and a controller arranged to determine a pattern of locations of sources and receivers for the analyzing, and to configure the locations according to the pattern to adapt the probe.

2. The device of claim 1, wherein the locations function as switchable locations, which are switchable between a role as source location, receiving location, or neither.

3. The device of claim 1, wherein the locations are switchable and have a fixed role as either source or receiver location, but can be switched between an 'open' and 'closed' state.

4. The device of any previous claim, the array of locations comprising one end of a bundle of optical fibers, the other end of the fibers being coupled to optical switches for coupling each of the fibers either to a light source or to a sensor.

5. The device of claim 3 or 4, the array of locations comprising an array of sensors and optical sources, and electrical circuitry for switching selected ones of the sensors or optical sources on or off according to the pattern.

6. The device of any preceding claim, having a controller arranged to make measurements to analyse the material, determine a quality of the measurements, and determine a revised pattern based on the quality of the measurements.

7. The device of claim 6, the controller being arranged to use spectral features due to morphology as quality measures.

8. The device of claim 6 or 7, the controller being arranged to generate an image of the material, and to determine the quality measure from the image.

9. The device of any preceding claim, the controller being arranged to use a genetic algorithm to determine a revised pattern.

10. A method of adapting a probe for analyzing a material using illumination and optical sensing, the probe having an array of locations for use as optical sources for the illumination or as optical receivers for the sensing the method having the steps of determining a pattern of locations of sources and receivers for the analyzing, and adapting to configure the locations according to the pattern to adapt the probe.

11. A method as set out in claim 8 and having the steps of making measurements to analyze the material, determining a quality of the measurements, and determining a revised pattern based on the quality of the measurements.

12. The method of claim 10 or 11, and having the step of using signals or spectral features due to morphology or microsensors or "smart tattoos" as quality measures.

13. The method of any of claims 10 to 12, for analyzing blood in a human or animal body and having the step of using near infra red spectrometry to determine a concentration of a constituent of the blood.

14. A controller for use with a device for analyzing a material using illumination and optical sensing, the device having an adaptable probe having an array of locations configurable for use as optical sources for the illumination or as optical receivers for the sensing, the controller being arranged to determine a pattern of locations of sources and receivers for the analyzing, and to configure the locations according to the pattern to adapt the probe.

15. The controller of claim 14 being arranged to make measurements to analyse the material, determine a quality of the measurements, and determine a revised pattern based on the quality of the measurements.

16. The controller device of claim 15, the controller being arranged to use spectral features due to morphology as quality measures and/or to generate an image of the material, and to determine the quality measure from the image and/or to use a genetic algorithm to determine a revised pattern.

17. A computer program product for performing, when executed on a computing means, a method of controlling the device of any of claims 1 to 9 to determine a pattern of locations of sources and receivers for the analyzing, and to configure the locations according to the pattern to adapt the probe.

18. A computer readable medium with the computer program product of claim 17, stored thereon.