CN203263391U - Non-invasive detection system for early stage sub-clinical asymptomatic diabetes - Google Patents
Non-invasive detection system for early stage sub-clinical asymptomatic diabetes Download PDFInfo
- Publication number
- CN203263391U CN203263391U CN 201320262108 CN201320262108U CN203263391U CN 203263391 U CN203263391 U CN 203263391U CN 201320262108 CN201320262108 CN 201320262108 CN 201320262108 U CN201320262108 U CN 201320262108U CN 203263391 U CN203263391 U CN 203263391U
- Authority
- CN
- China
- Prior art keywords
- voltage
- resistance
- module
- electrode
- diabetes
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
Links
- 206010012601 diabetes mellitus Diseases 0.000 title claims abstract description 36
- 238000001514 detection method Methods 0.000 title claims abstract description 24
- 230000000694 effects Effects 0.000 claims abstract description 57
- 238000012360 testing method Methods 0.000 claims abstract description 36
- 238000012545 processing Methods 0.000 claims abstract description 27
- 238000004458 analytical method Methods 0.000 claims abstract description 17
- 238000005259 measurement Methods 0.000 claims abstract description 15
- 230000003902 lesion Effects 0.000 claims abstract description 7
- 230000008859 change Effects 0.000 claims description 9
- 238000003491 array Methods 0.000 claims description 8
- 230000001575 pathological effect Effects 0.000 claims description 4
- 210000001061 forehead Anatomy 0.000 claims description 3
- 230000013011 mating Effects 0.000 claims 1
- 230000005284 excitation Effects 0.000 abstract 1
- 210000003491 skin Anatomy 0.000 description 28
- 208000002249 Diabetes Complications Diseases 0.000 description 19
- 206010012655 Diabetic complications Diseases 0.000 description 19
- 208000002705 Glucose Intolerance Diseases 0.000 description 17
- 201000009104 prediabetes syndrome Diseases 0.000 description 17
- 238000000034 method Methods 0.000 description 11
- 231100000915 pathological change Toxicity 0.000 description 8
- 230000036285 pathological change Effects 0.000 description 8
- 230000006870 function Effects 0.000 description 7
- 210000003414 extremity Anatomy 0.000 description 6
- 210000000106 sweat gland Anatomy 0.000 description 6
- 230000001276 controlling effect Effects 0.000 description 5
- 238000012956 testing procedure Methods 0.000 description 5
- PXHVJJICTQNCMI-UHFFFAOYSA-N Nickel Chemical compound [Ni] PXHVJJICTQNCMI-UHFFFAOYSA-N 0.000 description 4
- NOESYZHRGYRDHS-UHFFFAOYSA-N insulin Chemical compound N1C(=O)C(NC(=O)C(CCC(N)=O)NC(=O)C(CCC(O)=O)NC(=O)C(C(C)C)NC(=O)C(NC(=O)CN)C(C)CC)CSSCC(C(NC(CO)C(=O)NC(CC(C)C)C(=O)NC(CC=2C=CC(O)=CC=2)C(=O)NC(CCC(N)=O)C(=O)NC(CC(C)C)C(=O)NC(CCC(O)=O)C(=O)NC(CC(N)=O)C(=O)NC(CC=2C=CC(O)=CC=2)C(=O)NC(CSSCC(NC(=O)C(C(C)C)NC(=O)C(CC(C)C)NC(=O)C(CC=2C=CC(O)=CC=2)NC(=O)C(CC(C)C)NC(=O)C(C)NC(=O)C(CCC(O)=O)NC(=O)C(C(C)C)NC(=O)C(CC(C)C)NC(=O)C(CC=2NC=NC=2)NC(=O)C(CO)NC(=O)CNC2=O)C(=O)NCC(=O)NC(CCC(O)=O)C(=O)NC(CCCNC(N)=N)C(=O)NCC(=O)NC(CC=3C=CC=CC=3)C(=O)NC(CC=3C=CC=CC=3)C(=O)NC(CC=3C=CC(O)=CC=3)C(=O)NC(C(C)O)C(=O)N3C(CCC3)C(=O)NC(CCCCN)C(=O)NC(C)C(O)=O)C(=O)NC(CC(N)=O)C(O)=O)=O)NC(=O)C(C(C)CC)NC(=O)C(CO)NC(=O)C(C(C)O)NC(=O)C1CSSCC2NC(=O)C(CC(C)C)NC(=O)C(NC(=O)C(CCC(N)=O)NC(=O)C(CC(N)=O)NC(=O)C(NC(=O)C(N)CC=1C=CC=CC=1)C(C)C)CC1=CN=CN1 NOESYZHRGYRDHS-UHFFFAOYSA-N 0.000 description 4
- 206010016654 Fibrosis Diseases 0.000 description 3
- 210000004027 cell Anatomy 0.000 description 3
- 230000005611 electricity Effects 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- 230000004761 fibrosis Effects 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 210000005036 nerve Anatomy 0.000 description 3
- 230000002889 sympathetic effect Effects 0.000 description 3
- 102000004877 Insulin Human genes 0.000 description 2
- 108090001061 Insulin Proteins 0.000 description 2
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 2
- 210000000467 autonomic pathway Anatomy 0.000 description 2
- 210000000038 chest Anatomy 0.000 description 2
- 229940125396 insulin Drugs 0.000 description 2
- 230000002045 lasting effect Effects 0.000 description 2
- 229910052744 lithium Inorganic materials 0.000 description 2
- 229910052759 nickel Inorganic materials 0.000 description 2
- 230000002085 persistent effect Effects 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- VEXZGXHMUGYJMC-UHFFFAOYSA-M Chloride anion Chemical compound [Cl-] VEXZGXHMUGYJMC-UHFFFAOYSA-M 0.000 description 1
- 208000032131 Diabetic Neuropathies Diseases 0.000 description 1
- 206010012645 Diabetic autonomic neuropathy Diseases 0.000 description 1
- 206010018429 Glucose tolerance impaired Diseases 0.000 description 1
- 206010018473 Glycosuria Diseases 0.000 description 1
- 102000001554 Hemoglobins Human genes 0.000 description 1
- 108010054147 Hemoglobins Proteins 0.000 description 1
- YZCKVEUIGOORGS-UHFFFAOYSA-N Hydrogen atom Chemical compound [H] YZCKVEUIGOORGS-UHFFFAOYSA-N 0.000 description 1
- 229910021607 Silver chloride Inorganic materials 0.000 description 1
- FKNQFGJONOIPTF-UHFFFAOYSA-N Sodium cation Chemical compound [Na+] FKNQFGJONOIPTF-UHFFFAOYSA-N 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 230000001166 anti-perspirative effect Effects 0.000 description 1
- 239000003213 antiperspirant Substances 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000002146 bilateral effect Effects 0.000 description 1
- 210000001124 body fluid Anatomy 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 150000001720 carbohydrates Chemical class 0.000 description 1
- 210000000170 cell membrane Anatomy 0.000 description 1
- 230000019771 cognition Effects 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 208000035475 disorder Diseases 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000004064 dysfunction Effects 0.000 description 1
- 238000003487 electrochemical reaction Methods 0.000 description 1
- 210000002615 epidermis Anatomy 0.000 description 1
- 210000000245 forearm Anatomy 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 150000002500 ions Chemical class 0.000 description 1
- 230000002427 irreversible effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 238000007410 oral glucose tolerance test Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 229910052709 silver Inorganic materials 0.000 description 1
- 239000004332 silver Substances 0.000 description 1
- HKZLPVFGJNLROG-UHFFFAOYSA-M silver monochloride Chemical compound [Cl-].[Ag+] HKZLPVFGJNLROG-UHFFFAOYSA-M 0.000 description 1
- 229910001415 sodium ion Inorganic materials 0.000 description 1
- 230000000638 stimulation Effects 0.000 description 1
- 238000007920 subcutaneous administration Methods 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000008719 thickening Effects 0.000 description 1
- 210000000115 thoracic cavity Anatomy 0.000 description 1
Images
Landscapes
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
The utility model provides a non-invasive detection system for early stage sub-clinical asymptomatic diabetes. The diabetes detection system comprises a power source module, a voltage reference module, an electrode array, an adjustable resistor, a switch array, a measurement module, a data processing module and an analyzing module. After resistance and capacitance effect equivalent resistance of a human body of a subject, and the excitation voltage range are prejudged, voltage of a positive electrode and a negative electrode, and voltage and a resistance value of an adjustable precise resistor are tested, then data processing is carried out, and galvanic skin biological parameters are obtained, so that analysis of diabetes lesion features is carried out, and the testing results comprising stage range judgment and risk magnitude assessment of the diabetes are output. By means of the non-invasive way, the non-invasive detection system can accurately detect patients in the early stage sub-clinic or asymptomatic stage.
Description
Technical field
This utility model relates to medical apparatus and instruments, relates generally to a kind of noinvasive detection system for early stage subclinical asymptomatic diabetes.
Background technology
Along with the raising of people's living standard, diabetics is increasing, and diabetes and complication thereof are brought great spirit and economic burden to the patient.In fact, many potential patients of diabetes that are in the reversible stage if can early find early treatment, can stop it to develop into the irreversible clinical definite stage.Therefore, if the diabetes patient's in early stage subclinical or asymptomatic stage potential risk can accurately be detected, bring glad tidings for the potential patient of vast diabetes.
Physiological Study shows: at first human body when morbidity be to begin to change from body fluid, and secondly cell begins to change, until membranolysis, degenerate, then further develops and reach the organic pathological changes that clinical monitoring arrives.The dysfunction initial stage does not have organic pathological changes embodies, but on microcosmic point, and the variation of form is that the variation with function is synchronous.
Clinic study shows: the pathological changes of diabetes can be involved the pathological changes of autonomic nerve, and the sympathetic nerve pathological changes of wherein controlling sweat gland is very obvious.Although early stage subclinical diabetes mellitus is clinically without any symptom, yet pathological changes has occured its sympathetic nerve of controlling sweat gland, causes the fibrosis of sweat gland tissue, functional disorder.The resistance of its skin histology, capacity effect all can cause to give birth to significantly and change.Simultaneously, the fibrosis of sweat gland tissue causes the electrochemical phenomena of perspiration also can change.Therefore, the electro-detection method has been applied in the earlier detection of diabetes.
Yet traditional electro-detection method is all this incomplete cognition of a simple resistance based on human body, and impedance method detection mode commonly used adopts the real part and the imaginary part message reflection pathological characters that extract the impedance spectrogram.Judge the order of severity of diabetics based on the fluorescence oblique fire method detection signal after the absorption of hands forearm AGEs, it is subject to weak output signal and is difficult to and differentiates, and accuracy is not high.The feedback signal that detects electric current after the employing galvanic stimulation judges, has same problem.
Experiment shows: human body has the characteristic of resistance and capacity effect simultaneously, and human body skin also possesses perspiration functions simultaneously, and the ion of perspiration also possesses specific electrochemical effect.Therefore, which kind of human body resistance model no matter traditional impedance method detection mode adopt, and considers the different characteristic factor of extraneous factor and human body, has many queries or strict tested condition on accuracy.The method has been ignored the skin histology resistance that causes due to diabetic autonomic neuropathy, the factor that capacity effect obviously changes, the special delay phenomenon that does not have consideration to cause due to capacity effect on the processing method of human body equivalent resistance, testing result often differs greatly with the clinical trial result.
Under specified human-body safety DC voltage, the variation of the resistance of human body is jumpy within the test time started, and it needs just can reach stable value for a long time.Be applied to the moment of human body at DC voltage, each cell of human body is equivalent to a small electric capacity, and the capacity effect of each cell is superimposed, and its effect is can not ignore on the result impact of test.Therefore, traditional impedance method detection mode wants to reach accurate result, can only lean on the time long enough of test, yet this is again unrealistic in the middle of actual clinical, and particularly test need to apply in the situation that different DC voltages just can complete.
The utility model content
Provide this utility model content so that some concepts that will further describe with the form introduction of simplifying in the following specific embodiment.This utility model content is not intended to identify specially key feature or the essential feature of theme required for protection, is not intended to for the scope that helps to determine theme required for protection yet.
This utility model considers based on the human body resistance variation under DC voltage, capacity effect, electrochemical change, has proposed a kind of early stage subclinical asymptomatic noinvasive detection system and method for diabetes, possesses quick, accurate, noninvasive characteristics.
Detection system of the present utility model comprises: power module 105, voltage reference module 108, electrod-array 101, adjustable resistance 104, switch arrays 102, measurement module 103, data processing module 106 and analysis module 107.Power module 105 provides a specific DC voltage to each electrode of electrod-array 101; Voltage reference module 108 is used for calibration voltage; Electrod-array 101 adopts information, capacity effect and the electrochemical effect test of human body resistance to use sensor electrode, is positioned over the positions such as extremity or hand, chest, forehead, is close to skin surface; Adjustable resistance 104 is serially connected between power module 105 and electrode; By switch arrays 102, some electrodes are connected on power module 105; Measurement module 103 is used for the voltage and current of circuit is measured; Data processing module 106 is connected to power module 105, switch arrays 102 and measurement module 103 they is controlled, and simultaneously the skin bioelectrical signals that collects is processed, is calculated and stores, and controlling the frequency of sampling; Analysis module 107, connection data processing module 106 is analyzed the diabetes characteristics of lesion, and the output analysis result.
Comprise the following steps according to detection method of the present utility model: through resistance and the capacity effect equivalent resistance of coarse adjustment and two step anticipation experimenter human bodies of fine tuning; The anticipation actuation voltage range; The voltage of test electrode both positive and negative polarity and adjustable precision resistive voltage and resistance value; Carry out date processing, obtain skin electricity biological parameter; Carry out the analysis of diabetes characteristics of lesion and output test result, comprising diabetes stage scope and risk size.
By reading the following specific embodiment and with reference to relevant drawings, characteristics of the present utility model and advantage will be apparent.Be appreciated that aforementioned utility model content and the following specific embodiment are all illustrative, do not limit each side required for protection.
Description of drawings
Fig. 1 is the block diagram of diabetes detection system of the present utility model.
Fig. 2 is the flow chart of diabetes detection method of the present utility model.
Fig. 3 is the current-voltage curve figure according to an embodiment of this utility model.
Fig. 4 is the voltage-to-current curve chart according to the pair of electrodes of an embodiment of this utility model.
Fig. 5 is the voltage-to-current curve chart according to two pairs of electrodes of the correspondence of an embodiment of this utility model.
Fig. 6 carries out to normal person, impaired glucose tolerance patients, diabetics the skin bioelectrical signals correlation curve figure that skin bio electricity Validity Test obtains according to this utility model.
The specific embodiment
The detailed description that provides below in conjunction with accompanying drawing is intended to as the description to each example of this utility model, but not expression is used for explaining or utilizing unique form of each example of this utility model.
No matter be three element bio-impedance model, cole-cole theory or frequency dispersion theory think that all the people carries the cell membrane capacity and reduces along with the increase of frequency, and specific conductance raises with frequency and increases.When in the direct current situation, be all fixed value, thereby HFreiberger, RScherbaum, GBiegelmeier, Type Equivalent Circuit Model is all thought and in the direct current situation, human body resistance is considered as a non inductive resistor.Yet the applicant tests discovery, the relation that the human body impedance under low dc voltage and voltage are linear.Capacity effect be can not ignore simultaneously.
Based on electrochemical appliances such as silver/silver chloride electrode, lithium electrode, nickel electrodes, be placed in epidermis, under the DC voltage less than 10V, the ratio of electric current and voltage is not a steady state value, and electric current and voltage curve have comprised information, capacity effect and the electrochemical effect of human body resistance.It shows that the curve forward part under low-voltage has human body resistance and capacity effect to determine, and after the voltage increase, the curve latter half is to be determined by the information of human body resistance, capacity effect and electrochemical effect three parts.At curve, the flex point latter half appears particularly, and leading by electrochemical effect.
And, give the vdct lower than 10V, its health some position, such as: extremity, thoracic cavity section, hand etc., impedance is compared with normal people, significantly changes.This is in showing that the SSR experiment has been perfectly clear: the pathological changes of diabetes can be involved the pathological changes of autonomic nerve, wherein affects the most with the sympathetic nerve of controlling sweat gland again.The fibrosis that causes the sweat gland tissue, the antiperspirant pipe is inaccessible, and subcutaneous perspiration reduces, cuticle thickening.Thereby human body resistance increases, and electrochemical effect reduces.
The skin bioelectrical signals has not only comprised electrochemical effect and has also comprised human body resistance and body capacity effect, and this utility model applies to this phenomenon in the judgement of the order of severity of diabetes, provides a kind of degree of accuracy high diabetes detection system.
As shown in Figure 1, this detection system comprises: power module 105, voltage reference module 108, electrod-array 101, adjustable resistance 104, switch arrays 102, measurement module 103, data processing module 106 and analysis module 107.
Electrod-array 101 adopts information, capacity effect and the electrochemical effect test sensor electrode of human body resistances, such as lithium material, ag material, nickel material preparation can be under given voltage and the electrode of the generation electrochemical reactions such as the sodium ion of perspiration, hydrion, chloride ion.The quantity of electrode, can form the test sensor mutually by common 2～8 between every two electrodes.Be positioned over the positions such as extremity or hand, chest, forehead, be close to skin surface.It will be understood by those skilled in the art that based on needs, can increase and decrease number of electrodes.Simultaneously, for obtaining enough large skin bioelectrical signals of intensity, the area of electrode is enough large, preferably area 〉=1cm
2
Take 4 electrodes as example: human body left side hand: L1; Human body right side hand: L2; Human body left side foot: L3; Human body right side foot: L4, can be composed as follows the electrode test order:
L1～L2 or L2～L1: investigate the left side hand to the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of right side hand;
L1～L3 or L3～L1: investigate the left side hand to the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of left side foot;
L1～L4 or L4～L1: investigate the left side hand to the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of right side foot;
L2～L3 or L3～L2: investigate the right side hand to the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of left side foot;
L2～L4 or L4～L2: investigate the left side hand to the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of right side foot;
L3～L4 or L4～L3: the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of investigating left side foot to right side foot;
And then can also form:
L1～L3, L4 or L2～L3, L4: investigate hand to the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of foot;
L3～L1, L2 or L4～L1, L2: investigate foot to the skin bioelectrical signals (human body resistance variation, capacity effect, electrochemical effect) of hand.
By switch arrays 102, some electrodes are connected on power module 105, other electrodes are in the pattern of disconnection simultaneously.
Data processing module 106 is connected to power module 105, switch arrays 102 and measurement module 103 they is controlled, and simultaneously the skin bioelectrical signals that collects is processed, is calculated and stores, and controlling the frequency of sampling.
Fig. 2 is the flow chart of diabetes detection method of the present utility model.The below sets forth as test electrode is combined as example take above-mentioned L1～L2.
Resistance sizes and the capacity effect of different human body are different, therefore at first in step 201, the resistance of anticipation experimenter human body and capacity effect equivalent resistance, purpose is to make within human body resistance variation, capacity effect, electrochemical effect change in voltage appear at suitable scope, thereby can be detected.Equivalent resistance is realized by regulating adjustable precision resistance.The scope of adjustable precision resistance is at 0～1M Ω, and precision is 100 Ω.
Due to the impact of capacity effect, human body has the delay phenomenon appearance to the response of the change of voltage, particularly in the situation that the amplitude that voltage changes is large.In order more accurately to obtain out the equivalent resistance of human body resistance and capacity effect, take first to carry out large-scale coarse adjustment, obtain one and carry out again among a small circle fine tuning.
Regulative mode is subdivided into coarse adjustment and two steps of fine tuning:
At first carry out coarse adjustment, take L1 as anode, L2 is negative electrode, applies galvanic current and presses V, and V is the arbitrary value of 0～10V, at predetermined T in the time, with △ R
0Amplitude, the resistance of regulating adjustable precision resistance is reduced to 0 gradually from 1M Ω, wherein △ R
0What depend on time T and each step applies voltage time t, and the scope of T belongs to that (10s～300s), the scope of t is (0.5s～3s), data processing module 106 records voltage of each step adjustable precision resistance.And the voltage of finding out adjustable precision resistance is approximately half some U of supply voltage
0, i.e. U
0≈ V/2, the resistance of the adjustable precision resistance that this moment is corresponding is designated as R
0Data processing module 106 is with (R
0+ R
0/ 2, R
0-R
0/ 2) as the scope of next step fine tuning.
Then carry out fine tuning, take L1 as anode, L2 is negative electrode, applies a galvanic current and presses V, and voltage herein is consistent with the voltage V of coarse adjustment, in the same scheduled time T of coarse adjustment, with the amplitude of △ R, regulates the resistance of adjustable precision resistance, from R
0+ R
0/ 2 are reduced to R gradually
0-R
0/ 2, what wherein △ R depended on time T and each step applies voltage time t, wherein each step of t and coarse adjustment to apply voltage time t consistent, data processing module 106 records voltage of each step adjustable precision resistance.And the voltage of finding out adjustable precision resistance is half some U of supply voltage, i.e. U=V/2, and the resistance of the adjustable precision resistance that this moment is corresponding is designated as R.
Data processing module 106 stores the resistance R of adjustable precision resistance, and adjustable precision resistance R has herein not only reflected the resistance of human body, has also reflected the capacity effect of human body, and namely R is the equivalent resistance of human body resistance and electric capacity.
Between every a pair of electrode, the equivalent resistance of human body resistance and electric capacity all through identical test, stores each test resistance R to electrode by data processing module 106.In the anticipation actuation voltage range and testing procedure of every pair of follow-up electrode, the adjustable precision resistance is adjusted to the equivalent resistance R of counter electrode.
Then enter step 202, in this step anticipation actuation voltage range: take L1 as anode, L2 is negative electrode, the adjustable precision resistance is the equivalent resistance R of corresponding L1～L2 electrode, give DC voltage in anode 0～10V in the mode that increases progressively gradually or successively decrease gradually, such as: begin with 0.6V, the amplitude take △ V as amplification increases progressively, to 9V.The testing procedure number depends on the value of △ V, and each voltage steps persistent period is t, and the scope of t is at (0.5s～3s).The sample frequency scope is 10～1000HZ.Record anode and cathode voltage, record simultaneously the magnitude of voltage of adjustable precision resistance on each testing procedure.And stored by data processing module 106.
Voltage to each increasing or decreasing step adopts the average computation to ask its meansigma methods.Electric current calculates by resistance and the magnitude of voltage of adjustable precision resistance, and according to this, take the voltage of anode as X-axis, take electric current as Y-axis, makes current-voltage curve figure, as shown in Figure 3.
The front decay part main reflection human body resistance of curve and the variation of capacity effect, electric current reduces along with the increase of voltage.Curve flex point occurs at 2.8V, and electric current increases gradually with the increase of voltage afterwards, three kinds of effect stacks, and electrochemical effect accounts for leading.
Can find out from above-mentioned curve, human body resistance variation, capacity effect, electrochemical effect all for example have been included in 0.60～6V voltage range.The voltage range of therefore testing below as this combination of electrodes with 0.60～6V.
The test of exchange combination of electrodes is to all combinations test one by one.The voltage range of testing is stored by data processing module 106, and below resulting anticipation result is brought into, correspondence is surveyed in the middle of the testing procedure in each step of compound electrode, as the voltage range of test.
Then enter step 203, in voltage and adjustable precision resistive voltage and the resistance value of this pacing examination electrode both positive and negative polarity, concrete operation method is:
The DC voltage of positive direction 0.6V is applied on the L1 anode electrode, a lasting time t(0.5S～5S), by voltage and adjustable precision resistive voltage and the resistance value of data processing module 106 recording electrode both positive and negative polarities;
Then apply immediately the DC voltage of an equidirectional 0.6+ △ U, wherein △ U can be the arbitrary value of 0～1V.And can be selected according to the rate request of test, the persistent period is similarly t.Voltage and adjustable precision resistive voltage and resistance value by data processing module 106 recording electrode both positive and negative polarities;
Until reaching 6V, test voltage finishes.Testing procedure is counted N=6-0.6/ △ U.Data processing module 106 records voltage and adjustable precision resistive voltage and the resistance value of each pacing examination electrode both positive and negative polarity.
Then, the test of voltage access in the other direction in the same way, data processing module 106 records voltage and adjustable precision resistive voltage and the resistance value of each pacing examination electrode both positive and negative polarity.
Exchange another electrode (in the same way) is tested, all electrodes are completed successively.Data processing module 106 records voltage and adjustable precision resistive voltage and the resistance value of each pacing examination electrode both positive and negative polarity.
Then enter step 204, in this step, carry out date processing by data processing module 106, make the U of corresponding a pair of test electrode～I curve chart, calculated curve areal array and flex point result:
Take the result of every pair of test electrode test as a data set, such as L1～L2, the data averaging method of the voltage of each lasting step is obtained meansigma methods.Make U=U
Just-U
Negative, U wherein
JustFor being applied to anodal voltage, U
NegativeVoltage for negative pole.Electric current calculates by resistance and the magnitude of voltage of adjustable precision resistance.Be designated as I.Take U as abscissa, I is vertical coordinate, makes U～I curve chart, as shown in Figure 4.
Then for the electrode of correspondence, such as corresponding with L1～L2 be L2～L1, make with Fig. 4 in curve with respect to another curve of abscissa symmetry.Article two, curve, be plotted in together as shown in Figure 5.
Area between calculated curve and X-axis is designated as σ, as shown in Figure 4.
Calculate successively, the result of calculating the area of gained is designated as combination { σ
1σ
2σ
n.
The foundation that acquired results is analyzed as next step diabetes characteristics of lesion.
Then enter step 205, in this step, carry out the analysis of diabetes characteristics of lesion by analysis module 107:
According to many cases experimenter (comprising normal person, impaired glucose tolerance patients, diabetics) is carried out skin bio electricity Validity Test, obtain normal person, impaired glucose tolerance patients, the typical skin bioelectrical signals of diabetics as shown in Figure 6.As seen, the area that diabetics curve and X-axis comprise is greater than normal person, impaired glucose tolerance patients, and the area that impaired glucose tolerance patients and X-axis comprise takes second place, and normal person's area is minimum.
Usually diabetes are symmetrical on the impact that the bilateral of extremity is subject to, and the extremity distance is far away, and the impact that is subject to is larger.Can investigate extremity separately from Point of View of Clinical, be the area under the curve σ of hands～hands
Hands, the area σ of foot～foot
FootThe difference of the curve of the curve of hands and the area of X-axis and foot and the area of X-axis is Δ σ very.
For through age, corrected all objects of MBI value, with age (Age), Body Mass Index value (BMI), σ
Hands, σ
Foot, Δ σ is as the factor of influence in pathological data storehouse, the factor of influence of parameter different range builds different data bases, has set up many such data bases in analysis module 107.
Example of data base based on the above-mentioned factor is as follows:
After experimenter's test, resulting result (Age, BMI, σ
Hands, σ
Foot, Δ σ parameter value) enter into the data base and mate, just can draw the experimenter and belong to which kind of pathological condition.For example, experimenter's test result falls in data base's impaired glucose tolerance scope, so just determines that this experimenter is in impaired glucose tolerance.For another example, experimenter's test result falls into data base's diabetics scope, so just determines that this experimenter belongs to diabetics.
Next judge experimenter's diabetes risk value.
Obtaining respectively impaired glucose tolerance (IGT), insulin resistant (IR), diabetic complication (DC) and Δ sigma function relation by oral glucose tolerance test, glycolated hemoglobin analysis, heart rate variability experiments of measuring (HRV) clinical trial supplementary means is:
F(IGT)～f(Δ σ): the function of expression impaired glucose tolerance and trick skin signal of telecommunication area difference;
F(IR)～f(Δ σ): the function of expression insulin resistant and trick skin signal of telecommunication area difference;
F(DC)～f(Δ σ): the function of expression carbohydrate tolerance complication and trick skin signal of telecommunication area difference.
According to these empirical function relations, analysis module 107 just can calculate F(IGT according to the above-mentioned experimenter's who measures Δ σ value), F(IR) and F(DC) three values.
The diabetes risk size is obtained by following rule, and wherein K is constant, the constant that the different phase value is different.Diabetes risk (rise) scope:
Normal person: IR≤50, IGT≤40, rise≤25, and F(rise)=K * f(IGT) * f(IR);
Impaired glucose tolerance but be not glycosuria patient: IR≤50, IGT〉40,25＜rise≤50, and F(rise)=K * f(IGT) * f(IR);
Patient of diabetes but without complications: IR 50, DC＜60,50＜rise≤75, and F(rise)=K * f(IR) * f(DC);
Patient of diabetes and with complications: IR 50, DC〉60,75＜rise≤100, and F(rise)=K * f(IR) * f(DC).
Accordingly, can calculate the diabetes risk value, and the output final result.
More than describe noinvasive detection system and the method thereof of the early stage subclinical asymptomatic diabetes of this utility model in detail.Above description provides with the form of example, and is not intended to limit the claimed scope of this utility model.It will be appreciated by those skilled in the art that described this utility model technology embodiment modification and according to the embodiment of the various combination of this utility model technology.
Claims (9)
1. noinvasive detection system that is used for early stage subclinical asymptomatic diabetes comprises:
Electrod-array (101) comprises two with top electrode, can mutually form test between every two electrodes and use sensor, for being placed on human body a plurality of positions;
Power module (105) is used for providing DC voltage to each electrode of described electrod-array (101);
Switch arrays (102) are used for partial electrode is connected to power module (105), and other electrodes are in the pattern of disconnection simultaneously;
Measurement module (103) is used for the voltage and current of system is measured;
Adjustable resistance (104) is serially connected between power module (105) and electrode, and the described adjustable resistance of scalable (104) is to realize different experimenters' equivalent resistance;
Data processing module (106) is controlled described power module (105), switch arrays (102) and measurement module (103), and measurement result is processed, calculated and stores, and the sample frequency of control survey; And
Analysis module (107) is connected to described data processing module (106), the diabetes characteristics of lesion analyzed, and the output analysis result.
2. the system as claimed in claim 1, it is characterized in that: described electrod-array (101) adopts information, capacity effect and the electrochemical effect test sensor electrode of human body resistance, be positioned over extremity or hand, chest, forehead position, be close to skin surface.
3. the system as claimed in claim 1, it is characterized in that: described power module (105) provides the DC voltage of a specific gradual change to produce the driving voltage of skin bioelectrical signals as electrode to each electrode of described electrod-array (101), being chosen between 0～10V of voltage wave band.
4. the system as claimed in claim 1 is characterized in that: at 0～1M Ω, precision is the adjustable precision resistance of 100 Ω to described adjustable resistance (104) for scope.
5. the system as claimed in claim 1, it is characterized in that: described data processing module (106) records described power module (105) to the voltage of described electrod-array (101) described adjustable resistance (104) when applying voltage each time, calculate and store the resistance value of described adjustable resistance (104), make the U of corresponding test electrode～I curve chart, the calculated curve areal array outputs to described analysis module (107) with result.
6. the system as claimed in claim 1 is characterized in that: described analysis module (107) is with mating from the result of calculation of described data processing module (106) and pathological data storehouse of receiving, and the output detections result.
7. the system as claimed in claim 1, is characterized in that, also comprises the voltage reference module (108) for calibration voltage.
8. the system as claimed in claim 1, is characterized in that, described measurement module (103) also comprises holding circuit and anti-jamming circuit.
9. the system as claimed in claim 1, is characterized in that, described measurement module (103) also comprises the skin bioelectrical signals that collects is amplified the circuit that transforms with A/D.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201320262108 CN203263391U (en) | 2013-05-14 | 2013-05-14 | Non-invasive detection system for early stage sub-clinical asymptomatic diabetes |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201320262108 CN203263391U (en) | 2013-05-14 | 2013-05-14 | Non-invasive detection system for early stage sub-clinical asymptomatic diabetes |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN203263391U true CN203263391U (en) | 2013-11-06 |
Family
ID=49493900
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201320262108 Expired - Lifetime CN203263391U (en) | 2013-05-14 | 2013-05-14 | Non-invasive detection system for early stage sub-clinical asymptomatic diabetes |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN203263391U (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103230273A (en) * | 2013-05-14 | 2013-08-07 | 上海中嘉衡泰医疗科技有限公司 | Noninvasive detection system and method for early-stage subclinical asymptomatic diabetes |
| CN105361882A (en) * | 2015-12-08 | 2016-03-02 | 合肥芯福传感器技术有限公司 | Biological coherence degree detecting device and method |
-
2013
- 2013-05-14 CN CN 201320262108 patent/CN203263391U/en not_active Expired - Lifetime
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103230273A (en) * | 2013-05-14 | 2013-08-07 | 上海中嘉衡泰医疗科技有限公司 | Noninvasive detection system and method for early-stage subclinical asymptomatic diabetes |
| CN103230273B (en) * | 2013-05-14 | 2016-01-27 | 上海中嘉衡泰医疗科技有限公司 | The non-invasive detection system of early stage subclinical asymptomatic diabetes and method thereof |
| CN105361882A (en) * | 2015-12-08 | 2016-03-02 | 合肥芯福传感器技术有限公司 | Biological coherence degree detecting device and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Blad et al. | Impedance spectra of tumour tissue in comparison with normal tissue; a possible clinical application for electrical impedance tomography | |
| CN103230273B (en) | The non-invasive detection system of early stage subclinical asymptomatic diabetes and method thereof | |
| US8918170B2 (en) | Electrophysiological analysis system | |
| CN1297229C (en) | Non-invasive detection device of pulse impedance spectrum blood sugar or other biood component and its detection method | |
| JP2009519765A (en) | IN-VIVO non-invasive bioelectrical impedance analysis of glucose-mediated changes in tissues | |
| Clemente et al. | EIS measurements for characterization of muscular tissue by means of equivalent electrical parameters | |
| CA2558239A1 (en) | Methods and devices for non-invasively measuring quantitative information of substances in living organisms | |
| CN103239215B (en) | For the method for testing of sweat gland of skin perspiration ion | |
| CN203263391U (en) | Non-invasive detection system for early stage sub-clinical asymptomatic diabetes | |
| Lackermeier et al. | In vivo ac impedance spectroscopy of human skin: theory and problems in monitoring of passive percutaneous drug delivery | |
| Sunny et al. | Feasibility experiments to detect skin hydration using a bio-impedance sensor | |
| CN101889862B (en) | Three-dimensional scanning body electrographic apparatus used for detecting human body functions and detection method thereof | |
| Kuzmin et al. | Signal Processing in the Problem of Breast Tumors Detection by Impedansometry Method Based on Havriliak-Negami Model | |
| CN1860988A (en) | Apparatus for testing and analyzing functions of internal organs | |
| Prună et al. | Dual-channel self-balancing electrodermal impedance reactometer for autonomic response studies | |
| Bosnjak et al. | Characterizing dry electrodes impedance by parametric modeling for arm wearable long-term cardiac rhythm monitoring | |
| US20230233146A1 (en) | Edema detection | |
| CN203369889U (en) | Non-invasive detection system for automatic neuropathy | |
| CN103815916A (en) | Rapid blood glucose testing system with built-in bioimpedance analysis method | |
| Joshi | System Identification of Electrode-Skin Interface for Flexible PDMS Electrodes and Microelectrode Arrays | |
| Zheng et al. | Imageless Electrical Impedance Tomography for Highly Sensitive Object Dynamics Detection | |
| Alhaq et al. | Bioelectrical Impedance Spectroscopy (BIS) for Ratiometric Identification | |
| Shinomiya et al. | Analysis of the characteristics of electrooculogram applied a battery model to the eyeball | |
| CN109498011A (en) | A kind of bio-electrical impedance measuring apparatus | |
| Uhryn et al. | Ivan Franko Drohobych State Pedagogical University Drohobych, Ukraine |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CX01 | Expiry of patent term |
Granted publication date: 20131106 |
|
| CX01 | Expiry of patent term |