DE29519697U1 - Diagnostic facility - Google Patents

Description

Dr. Reinhard Möller Graz (Austria)

Diagnostic facility

The invention relates to a new device for diagnosing the state of health of human individuals, in particular for detecting pathological changes or diseases and/or for classifying metabolic disorders, with at least one device (200) for collecting, determining and/or measuring body-specific characteristics and at least one device (300) for recording, storing, processing and editing them as well as for making diagnoses.

The present invention is based on the observation that there are very specific connections, which occur with an astonishingly high probability of success for medical conditions, between authentically determined characteristic data on physiological characteristics at precisely defined points on the human body, which do not reveal any prior connections, and the state of health or certain diseases.

Although it is to be assumed that such non-obvious connections, which can ultimately be used for accurate diagnoses, exist for a large number of illnesses and chronic diseases, the concrete observations and series of experiments in this sector to date are sufficient to use these surprising connections, at least for the detection of chronic metabolic diseases, such as coronary heart disease, gout in its various forms, and diabetes I and II, for a completely new type of diagnosis, whereby modern computer technology represents a significant aid in view of the large amount of data that has to be processed and linked together according to various criteria.

Such a new diagnostic technique based on the above-mentioned observations and findings is particularly advantageous if the physiological data to be determined, for example, at a number of specified body locations can be collected using an examination device that uses a non-invasive measuring method.

In particular, it was unexpectedly found that the body topographical distribution of the thickness of the subcutaneous fat layer of a person is closely related to their state of health. It was found - of course, differing according to age, gender, and body type - that the thickness of the subcutaneous fat layer in people suffering from a chronic metabolic disease at certain parts of their body differs significantly and statistically from the thickness of the fat layer at the same part of the body in healthy people or people suffering from another disease.

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Now, modern equipment technology in connection with the determination of the subcutaneous fat layer thickness has the great advantage that it is non-invasive and therefore not only problem-free for the test subject, but also provides a quick and precise method for the rapid and, if necessary, even online creation of a diagnosis using the described findings.

For measuring the fat layer thickness, reference is made to the expensive technique of computer tomography based on NMR technology, which records the subcutaneous fat layer thickness along a number of measuring horizons in humans, which ultimately enables the creation of an accurate image of the entire subcutaneous fat layer topography of a subject.

A much less complex device for determining the thickness of the subcutaneous fat layer is described in EP 516.251 as a lipometer. It is a real handheld device that is able to determine the thickness of the fat layer based on the reflection and scattering of optical signals by the subcutaneous fat tissue.

The device of the type mentioned at the outset, which forms the subject of the invention and uses the surprising findings described above using known subcutaneous fat layer thickness measuring methods, is characterized in that it comprises at least one device (200) which can be positioned in a body-topographically defined manner for determining the thickness of the subcutaneous fat layer of a respective subject being examined, preferably a lipometer, as a device for detecting or early detecting chronic metabolic diseases, such as in particular atherosclerosis, coronary heart disease, gout and/or diseases of the diabetes group, preferably diabetes I and H, as a device for recording body-specific characteristics, which is connected or linked to a diagnosis creation device (300) for signal transmission,
which diagnostic device (300) in turn

at least one current signal storage unit (310) for recording, collecting, storing and forwarding signals or signal sequences corresponding to current fat layer thickness characteristics emitted by the subcutaneous fat layer thickness measuring device (lipometer) (200) at parts of the subject's body that are specifically selected in accordance with the diagnosis expectation,

at least one current signal processing unit (320) connected to the current signal storage unit (310) for processing and editing the said current signals or signal sequences or raw data derived therefrom to current fat layer thickness characteristics with a current characteristic data storage unit (330) for storing at least one with - from a first group of selected test subjects without health damage or from test subjects not suffering from chronic, in particular at least one of the metabolic diseases mentioned in detail above, each with body topographically precisely defined and - at least analogously - matching

Healthy comparison data storage unit (340) that can be used to store or access raw or characteristic data relating to the thickness of the subcutaneous fat layer obtained from a second group and/or further groups of comparison subjects each suffering from one of the chronic metabolic diseases suspected in the individual subjects currently being examined, each at body topographically precisely defined and - at least analogously - matching locations, and furthermore at least one raw or characteristic data relating to the thickness of the subcutaneous fat layer obtained from a second group and/or further groups of comparison subjects each suffering from one of the chronic metabolic diseases suspected in the individual subjects currently being examined, each at body topographically precisely defined and - at least analogously - matching locations, and furthermore at least one with the current signal processing unit (320) or the current characteristic data memory (330), furthermore with the healthy comparison data storage unit (340) and with at least one of the patient comparison data storage units (350,351,352....) connected diagnostic unit (360),
which diagnostic unit (360)

with at least one subunit (361) for standardizing the characteristics currently collected from the test subject and available from the current data storage unit (330) and/or for compatibilizing the same with healthy and sick comparison characteristics that can be provided by the comparison data storage units (340, 350, 351...), preferably already standardized, according to individual-specific, medical and/or other diagnosis-relevant criteria, such as in particular gender, age, body type, other illnesses of the test subject being examined, etc., with a comparison subunit (362) equipped with at least one comparison and evaluation algorithm for a comparison of the standardized or compatible current characteristics with the healthy and sick comparison characteristics, based on the desired criteria,

with a diagnostic output unit (364) connected to the latter subunit (362) and equipped with a diagnostic statement module (363), such as in particular a printer, screen and/or phonetic playback unit,
and at least one subject diagnosis storage unit (365).

The new device is able to make a specific diagnosis with a high degree of certainty based on the data supplied by the subcutaneous fat layer thickness measuring device, stored and processed at specifically selected and predetermined locations on the body of a test subject currently being examined, in connection with data entered from outside from similar measurements on a first group of healthy comparison subjects, on a second group of comparison subjects suffering from the same disease as the test subject currently being examined, and finally also from measurements on a third or further group of comparison subjects suffering from a different disease than the test subject currently being examined.

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It should be pointed out briefly that there are no limits to the way in which the thickness of the fat layer can be measured or the devices used for this purpose. It is of course advantageous if they provide digital values that can be processed by a computer.

The above-mentioned device units and sub-units as well as the storage and processing units are advantageously specific areas, sectors, modules or "cards" of a standard computer, PC, laptop or dig. They are advantageously freely programmable and loaded with data packets, statistics, discrimination and/or linking algorithms.

"Standardization" and "compatibilization" essentially mean a conversion of signals, raw data and/or characteristic data or statement data derived from them into data reduced to a standard value scale. It is therefore advisable to standardize all data, for example, to a standard body weight or height.

It should not go unmentioned that, for example, the comparison storage units for healthy and sick people can be filled with standardized, averaged data or data packets from a previously examined comparison group. If individual data that has not yet been pre-standardized has been read into the comparison storage, a standardization sub-unit can be provided for each storage group. This allows both the data from the test subjects currently being examined and the data from comparison groups to be brought into a desired format that is compatible with comparison data from elsewhere, for example, which then enables them to be compared and linked to one another in the subsequent comparator unit without any problems.

The essential criteria according to which an at least imaginary division of the various storage units is of course advantageous concern age and gender, etc., as expressed in claim 2.

It is particularly advantageous for practical reasons of handling if, as provided in claim 3, a unit for entering subject-specific criteria is arranged directly on the patient examination device itself.

For diagnosis, it is advantageous - as described in claim 4 - to have comparison data stored in separate storage units right from the start or to read them quickly - ideally during the examination - into the comparison storage units. Of course, the flexibility of use of the system in terms of the variety of diagnoses increases if a growing number of different chronic metabolic diseases are available in the storage in the form of fat thickness data based on examinations of suitable comparison test subjects.

It is particularly clear and facilitates the diagnosis if the new device creates a fat layer thickness characteristic data pattern or profile according to claim 5, which corresponds to the selected sequence of the body parts examined, which

can be easily compared with profiles of healthy and specifically diseased comparison subjects created in the same way.

The function of the embodiment of the new system according to claim 6 is also to be seen in this sense.

If, as stated in claim 7, a device for comparing the profiles of the currently examined test subject, of a comparison group of healthy test subjects and/or of at least one comparison group of, for example, a disease suspected in the test subject is provided in the device according to the invention, then a clear diagnosis can be made practically immediately just by checking the congruence of the profile patterns.

Preferred, because it is uncomplicated, is an embodiment of the device with a programmed difference formation algorithm in the comparator subunit according to claim 8.

In a device with a quotient formation algorithm according to claim 9, the advantage of standardizing the data of the respective reference group, whether ill or not, on a horizontal-linear comparison characteristic data background corresponding to a standard value is given.

It can also be advantageous to assign a signal profile generation unit to the line within the diagnostic unit which is intended for transmission, storage and processing of the signals coming from the fat layer thickness measuring device, i.e. to anticipate the characteristic data profile creation at the signal level, so to speak.

In the event that, for example, only one and the same type of fat layer thickness measuring device is used in an institute, in a hospital or the like, it is advantageous to design the system according to the invention in accordance with claim 10.

If storage is provided which only includes the data supplied by said devices of a uniform type, an embodiment according to claim 11 may be advantageous.

Modern aspects of collecting and managing a large number of body characteristics made possible by non-invasive fat thickness measuring devices are best met by the use of a conventional computer or PC for practically all functions attributable to the diagnostic device of the device according to the invention.

According to claim 12, a remote data transmission connection, e.g. via radio or satellite radio, between the fat layer thickness measuring device and the diagnostic device is possible, e.g. in a large institute or for on-site investigations, e.g. in a school, in developing countries, etc.

In this situation, it may be advantageous to have the diagnostic output directly on the examination device itself, in accordance with claim 13.

The current state of modern miniaturization technology makes it possible to build a diagnostic device of the type described for truly independent examinations that take place far away from any centers, in which the subcutaneous fat layer thickness measuring device and the diagnosis creation device, which contains all the comparison data, e.g. collected on permanent memories, circuit boards, modules or the like, are housed in a handy unit, as provided for in claim 14, including an output printer, which, for example, prints the cards for a patient file or documentation that is useful to the doctor.

Example:

Clinically healthy subjects were selected as a comparison group for subcutaneous fat measurements. They were 20 women with an average age of 29.4 (±4.7) years (age from 22.8 to 40.1 years). Their average height was 167.9 cm (±7.5 cm), heights from 164 to 181 cm. The average body weight of these women was 61.4 kg (±7.7 kg), (weights from 47.0 to 80.4 kg).

The men examined had a mean age of 31.6 years (± 3.3 years), (age from 24.9 to 38 years); mean height 180.9 cm (± 6.8 cm), (heights from 168 to 195 cm), mean body weight 77.4 kg (± 8.1 kg), (weights from 67.8 to 103.0 kg). Diabetes sufferers:

19 women and 20 men with clinically evident diabetes mellitus, type 1, attending the Department of Internal Medicine, Karl-Franzens University, Graz, Austria; mean age of women: 32.3 years (± 7.7 years), (age range 21.2 to 45.4 years); height: 166.0 cm (± 4.3 cm) (heights range 158 to 175 cm); mean body weight: 62.6 kg (± 9.5 kg), (weight: 49.7 to 80.0 kg).

The men suffering from diabetes had an average age of 36.3 years (±8.8 years) (age: 23.6 to 55.6 years); average height: 175.9 cm (± 6.8 cm) (heights: 166 to 189 cm); average weight: 76.5 kg (± 11.03 kg) (weights: 62.0 to 97.0 kg). The medical histories of the patients examined were very heterogeneous; for example, the duration of the disease varied from a few weeks to 27 years in women and from 0 to 36 years in men. Their requirements for insulin doses and laboratory measurements, e.g. HbAIc, also varied in a similar way.
Measuring device-lipometer:

A lipometer of the type described in EP 516.251 was used. Briefly, the sensor head of the device has a set of LEDs as light sources and a photodetector.

The LEDs illuminate the subcutaneous fat layer at a specific location on the body with bursts of light in predetermined patterns and pattern sequences. The photodiode measures the corresponding backscattered light intensities. These light signals are amplified, digitized and transmitted to the computer via a specific interface card

stored. Calibration and evaluation were carried out based on computer tomography data collected at the same time.

Measuring technology:

All measurements were taken on fasting subjects in the morning: The measurements with different measuring devices were always recorded in the same sequence, as explained below, in order to avoid irritation of the skin and subcutaneous fat tissue.

(Measuring devices: "Lipometer" and "Futrex" with IR measurement). To assess the individual lipometer results, age and gender-dependent risk areas were used in a diagram of total body fat percentage versus age. There was a high degree of agreement between the fat layer thickness data obtained with the two measuring devices.

The lipometer measurements were taken on the subjects at 13 standardized body locations, see Fig. 2a-2c, the subjects stood upright, the measurements were taken on the right side of the body.

Statistics:

For each individual tested, the lipometer measurements provide absolute values Aj(i=1,13) for the thickness of the fat layers. In order to compare the subjects, relative values Rj are calculated by estimating the mean D of a subject:

TO

and then each individual absolute measurement is related to this mean value:

From these relative values for each subject tested, a characteristic profile of the subcutaneous fat distribution is generated. These profiles are displayed as histograms. By combining such individual profiles for selected groups of subjects, average profiles are obtained that are typical subcutaneous fat patterns for the respective subject group and can be compared graphically or statistically, for example. The step discriminant analysis was used to compare non-diabetic and diabetic women and men. The fat layer thickness at the body parts examined was chosen as the independent variable, and the diabetes status was taken as the group variable. With this type of analysis, a combination of independent variables is sought that allows maximum discrimination between the groups defined by the group variable. To assess the

The "jackknife technique" (“leave one out method”) was used to determine the discriminatory reliability of the obtained discriminant models.

The statistical analyses were carried out using EXCEL 5.0 (Microsoft, Unterschleißheim, Germany) or using the BMDP software package (BMDP Statistical Software, Cork, Ireland). Results:

Profiles of subcutaneous fat layer thicknesses of healthy control subjects and patients with type I diabetes:

As shown in Fig. 2, the lipometer measurements provide a fat layer thickness profile of specified body sites for a tested individual. Such profiles are combined for the members of a homogeneous group of subjects and typical average profiles for such a group can be created and combined. Fig. 3 shows average profiles for women and men ordered by their disease status in relation to diabetes mellitus type 1, Fig. 3a compares, in values of absolute fat thickness measurements, healthy women (zig-zag curve) and women with clinically diagnosed diabetes mellitus type I (bars). The same subjects are compared in Fig. 3c, only here the mean fat thicknesses of each body site are set to a unit value, related to the healthy comparison group; for the diabetes patients these data were transformed accordingly, which makes the differences between the two groups particularly transparent.

It is quite obvious that female diabetes patients differ from the healthy comparison group of women in terms of their subcutaneous fat thickness distribution, particularly in the breast region. On average, diabetes patients show a 70% higher value in this area.

In an analogous manner, data from healthy male subjects and diabetic subjects were compared, with the results shown in Fig. 3b and 3d. Apart from the considerable differences between the profiles of female and male subjects, there are also notable differences between healthy male subjects and diabetic subjects. Especially in the hip region, male diabetic patients show values that are around 30% lower than those of healthy men.

Multivariate models for discrimination between healthy and diabetic subjects:

Linear step discriminant analyses were carried out separately for both sexes in order to relate the individual profiles of the subcutaneous fat layer thickness to the disease status of the tested individuals. The following was shown: For women, the combination of position 1 (neck) and 4 (front chest) was selected as the one with the best discriminant functions from all available body locations. For men, 3 body locations were selected, namely 5 (side of the chest), 8 (hip) and 11

(posterior thigh) were found to be the most suitable composite indicator for the presence or absence of type I diabetes mellitus.

Based on a very simple discriminant model, a correct classification was made for 33 of 39 women (84.6%) and for 32 of 38 men (84.2%). 2 women (and 2 men) who were not actually ill were classified as having diabetes, while for 4 women (and 4 men) with proven diabetes the classification was incorrectly negative. It should be noted here that the same classification results were obtained using the jackknife option.

It is important to emphasize at this point that these are still tests on relatively small groups of test subjects and that development is in rapid flux.

It should also be mentioned that the first series of tests have also shown the excellent usability of the fat layer thickness measuring system based on the new diagnostic method according to the invention for a clear diagnosis of coronary heart disease, early detection of gout, etc. The results regarding the diagnosis of diabetes 11 (Fig. 6) are well secured.

The invention is explained in more detail with reference to the drawing:

Fig. 1 shows a schematic sketch of the diagnosis creation system according to the invention, Figs. 2a to 2d show, using three schematic female figures, the body parts that should be examined for fat layer thickness when diagnosing diabetes mellitus type I, and generally a histogram of a fat layer thickness examination on a female test subject, Figs. 3a and 3b show profiles and histograms of the fat layer thickness values found at the individually designated body parts of healthy (zig-zag curve) and diabetes I test subjects (histograms) of the female and male sex, Figs. 3c and 3d show standard fat profile histograms of the diabetes I patients of the male and female sex based on the fat layer thickness data reduced to standard values (1.00) from Figs. 5 and 6, and Figs. 5 and 6 Comparison of fat layer thickness profile of two groups of male subjects with diabetes mellitus type I and type II.

Fig. 1 shows the diagram of an embodiment of a diagnostic device according to the invention 100 with a fat layer thickness measuring device 200, ζ. B. a lipometer, according to EP 516.251, which is connected to a diagnostic device 300 for signal transmission.

The diagnostic device 300 itself receives the current signals or signal sequences supplied by the examination device 200 and stores them in accordance with the order of the body parts examined in a first current signal storage unit 310, from where they are supplied, if necessary continuously or on demand, to an current signal processing and processing unit 320, in which they are converted into fat layer thickness raw data or characteristic data and then stored in the characteristic data storage unit 330 connected to the unit 320.

At the same hierarchical level are the comparison storage units 340 to 352 arranged below in Fig. 1, namely a first 340 for storing subcutaneous fat layer thickness data from a group of healthy subjects, a second patient comparison data storage unit 350, for example, loaded with fat layer thickness data from a comparison group of subjects suffering from diabetes mellitus type I, a further (third) storage unit 351 loaded with the data from a person suffering from a metabolic disease, e.g. diabetes II, another patient comparison data storage unit 352 intended for another metabolic disease, etc.

The current characteristic data storage unit 330 is connected to the comparator subunit 362 of the diagnostic unit 360 via a data compatibility subunit 361, the healthy comparison data storage unit 340 and finally the patient comparison data storage unit 350, 351, 352 and supply it with current characteristic data defined by body topography of the respective test subject being examined, with healthy characteristic data and with patient characteristic data - possibly associated with several diseases. There, these data are compared with one another, linked and/or related to one another according to one or a plurality of imposed calculation and/or statistical algorithms and are used as diagnostic result raw data of a device with a corresponding output module, e.g. B. for visualization, phonetic output, etc., and finally fed into a standard output form that is usable by the doctor and for documentation, such as a protocol, screen recording, phonetic playback and/or patient documentation.

It should be mentioned in addition that it is practical according to claim 13 if a desired type of output unit 363 is arranged on the examination device 200 itself.

This applies in particular to the case where the diagnosis creation computer 300 is arranged dislocated from the examination device 200, in which case, for example, an output radio connection between the computer and the examination device is provided.

The diagrams show the body site numbers 1 and 4 for women and 5, 8 and 11 for men, which are statistically particularly significant for diabetes I.

To explain Fig. 2a to 2d, the coincidence of the measuring point numbers given in Fig. 2a to 2c and the specific body parts shown there is first given, whereby the measuring points mentioned are characteristic for the female sex:

Tabel:

Measuring point no. Measuring points 1 neck 2 Triceps 3 Back top 4 Chest front 5 Chest side 6 Belly up 7 Belly down 8th Hip &thetas; Front thigh 10 Thigh side 11 Back thigh 12 Inner thigh 13 calf

As an example, Fig. 2d shows a histogram of the thicknesses of the subcutaneous fat layer determined at the above-mentioned body sites of a test subject suffering from type I diabetes.

It shows a histogram profile that is, as we now know, specific to diabetes 1.

Diagrams 3a and 3c show, in real layer thicknesses and in layer thicknesses standardized to a value of 1, the pattern of a fat thickness distribution of a group of healthy women as a measuring point connecting curve and the profile of the distribution of the average fat layer thickness of women suffering from diabetes I as a histogram.

Diagrams 3b and 3d show the similarly recorded or standardized patterns of groups of healthy men and men who also suffer from diabetes I (average age 36 years). The body measurement point numbers of the male subjects are analogous to those given for women above in Fig. 2a to 2c.

Figures 4a and 4b show the average subcutaneous fat layer thickness patterns, which were recorded for healthy men (group of 18) and men suffering from diabetes I (group of 13) and their striking differences in a very clear manner.

Figures 5 and 6 show that the new diagnostic device also enables clear disease detection by comparing the patterns of two groups of women suffering from diabetes I and diabetes II with their fat layer thickness profiles or patterns.

disease-specific courses does not pose any problem, as there are also significant differences in the "disease patterns".

Dr. Reinhard Möller, Graz (Austria) official ref.: 295 19 697.1 current ref.: GM 1471/1-95Ch

-list of reference symbols (body measurement points = body cell numbers)

1: neck in front 2: Triceps laterally 3: Back rear 4: Chest front Inside 5: Chest side 6: Belly up 7: Belly down 8th: Hip 9: Thigh 10: Thighs! 11: Thigh T2: Thigh 13: WaJe

Claims (15)

Protection claims: 1. Device (100) for diagnosing the health status of human individuals, in particular for detecting pathological changes or diseases and/or for classifying metabolic disorders, with at least one device (200) for collecting, determining and/or measuring body-specific characteristics and at least one device (300) for recording, storing, processing and editing them as well as for creating diagnoses, characterized, that the diagnostic device (100) for the detection or early detection of chronic metabolic diseases, such as in particular atherosclerosis, coronary heart disease, gout and/or diseases of the diabetes group, preferably diabetes I and II, comprises as a device for recording body-specific characteristics at least one device (200) which can be positioned in a body-topographically defined manner for determining the thickness of the subcutaneous fat layer of a respective examined subject, preferably a lipometer, which is connected or linked to a diagnosis creation device (300) for signal transmission,
which diagnostic device (300) in turn at least one current signal storage unit (310) for recording, collecting, storing and forwarding signals or signal sequences corresponding to current fat layer thickness characteristics emitted by the subcutaneous fat layer thickness measuring device (üpometer) (200) at specific locations on the subject's body selected in accordance with the diagnosis expectation at least one current signal processing unit (320) connected to the current signal storage unit (310) for processing and editing the said current signals or signal sequences or raw data derived therefrom to produce current fat layer thickness characteristics with a current characteristics storage unit (330) for storing them, at least one healthy comparison data storage unit (340) that can be verified or loaded with raw or characteristic data relating to subcutaneous fat layer thickness obtained from a first group of selected test subjects without health damage or from test subjects not suffering from chronic, in particular at least one of the above-mentioned metabolic diseases, at body topographically precisely defined and - at least analogously - matching locations and/or at least one raw sample obtained from a second group and/or further groups of comparison subjects suffering from one of the chronic metabolic diseases suspected in the individual subjects currently being examined, each from body topographically precisely defined and - at least analogously - corresponding locations or characteristic data regarding subcutaneous fat layer thickness verifiable or loadable patient comparison data storage unit (350,351,352.,.) and further at least one diagnostic unit (360) connected to the current signal processing unit (320) or the current characteristic data memory (330), further to the healthy comparison data memory unit (340) and to at least one of the sick comparison data memory units (350,351,352....),
which diagnostic unit (360) with at least one subunit (361) for standardizing the characteristics currently collected on the test subject and deliverable from the current data storage unit (330) and/or for compatibilizing the same with healthy and sick comparison characteristics that can be delivered from the comparison data storage units (340, 350, 351...), preferably already standardized, according to individual-specific, medical and/or other diagnosis-relevant criteria, such as in particular gender, age, body type, other illnesses of the test subject being examined, etc., with a comparison sub-unit (362) equipped with at least one respective comparison and evaluation algorithm for a comparison of the standardized or compatible current characteristics with the healthy and sick comparison characteristics according to the respective desired criteria, with a diagnostic output unit (363) connected to the last-mentioned subunit (362) and equipped with a diagnostic statement module (364), such as in particular a printer, screen and/or phonetic playback unit, and at least one subject diagnosis storage unit (365). 2. Device according to claim 1, characterized in that the storage units (330, 340, 350, 351, 352) are each divided into separate storage areas or storage sub-units according to criteria such as, in particular, gender, body size and weight, age group, other illnesses and the like. 3. Device according to claim 1 or 2, characterized in that it has a unit arranged on the fat layer thickness measuring device (200) itself for entering criteria characterizing a currently examined subject, such as age, gender, height, body weight and the like. 4. Device according to one of claims 1 to 3, characterized in that in the individual comparison data storage units (340, 350, 351, 352) there are stored, if necessary, weighted mean values of the values measured at disease-detection-specific body parts of groups of healthy subjects and subjects suffering from respective metabolic diseases. -.ts- The subcutaneous fat layer thickness data collected or obtained are stored or can be read into them. 5. Device according to one of claims 1 to 4, characterized in that the current signal processing unit (310) or its current signal storage unit (320) or the current characteristic data storage unit (330) which can be supplied with subcutaneous solid layer thickness data by the same is assigned a unit (321) for generating a fat layer thickness profile or pattern on the basis of the signals or signal sequences supplied by the fat layer thickness measuring device (200) from the individual disease-specific body topographically defined measuring points in a sequence predetermined for a suspected disease, or from fat layer thickness characteristic data derived therefrom. 6. Device according to claim 5, in that fat layer thickness profiles or patterns from healthy subjects and/or from subjects suffering from one of the above-mentioned chronic metabolic diseases or from groups of such subjects, each obtained in an analogous manner to claim 5, are stored in the comparison data storage units (340, 350, 351). 7. Device according to one of claims 1 to 6, characterized in that the comparison subunit (362) is equipped with an algorithm created on the basis of body characteristic data statistics for the multivariate comparison of current, healthy and/or sick fat layer thickness characteristic data profiles or patterns with one another and/or for obtaining classification functions by linear determinant analysis. 8. Device according to one of claims 1 to 7, characterized in that the comparison subunit (362) is equipped with a fat layer thickness profile difference formation algorithm connected for data transmission to the current characteristic data storage unit (330) and at least the healthy (340) and/or one of the sick comparison data storage units (350,351,352...). 9. Device according to one of claims 1 to 7, characterized in that the comparison subunit (362) connected for data transmission to the current characteristic data storage unit (330) and at least the healthy (340) and/or at least one of the sick comparison data storage units (350, 351, 352...) is equipped with a fat layer thickness profile quotient formation algorithm. 10. Device according to one of claims 1 to 9, characterized in that in the case of the use of only one specific type of Sukutan fat layer thickness measuring device (200 with -.te - high measurement reproductivity, omitting or bypassing the actual signal processing unit (320), the actual signal storage unit (330) is directly connected to the diagnostic unit (362) or its upstream standardization subunit (361) for signal transmission, whereby the healthy comparison data storage unit (340) as a healthy comparison signal storage unit is loaded or occupied with signals from a group of healthy test subjects from an identical fat layer thickness measuring device (200) and the sick comparison data storage unit (350, 351, 352) as a sick comparison signal storage unit is loaded or occupied with signals from a group of sick test subjects suffering from one of the chronic metabolic diseases in question from an equally similar fat layer thickness measuring device. 11. Device according to claim 10, characterized in that in addition to the current signal storage unit mentioned therein, the healthy comparison signal storage unit and the sick comparison signal storage units are connected to the comparison subunit (362) with the interposition of an individual or a common standardization subunit (361). 12. Device according to one of claims 1 to 11, characterized in that the subcutaneous fat layer thickness measuring device (200) is connected to the diagnostic unit (300) via an immaterial signal or data transmission path. 13. Device according to one of claims 1 to 12, characterized in that at least the diagnostic output unit (363) is arranged on the subcutaneous fat layer thickness measuring device (200) itself. 14. Device according to one of claims 1 to 11, characterized in that the subcutaneous fat layer thickness measuring device (200) and the diagnostic unit (300), preferably with a common housing or the like, are combined to form a uniform compact diagnostic device. 15. Device according to one of claims 1 to 13, characterized in that the diagnostic unit (300) is formed with a computer or personal computer. · · ■