WO2019058021A1 - Système et procédé de production d'informations indiquant un diabète - Google Patents

Système et procédé de production d'informations indiquant un diabète Download PDF

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WO2019058021A1
WO2019058021A1 PCT/FI2018/050638 FI2018050638W WO2019058021A1 WO 2019058021 A1 WO2019058021 A1 WO 2019058021A1 FI 2018050638 W FI2018050638 W FI 2018050638W WO 2019058021 A1 WO2019058021 A1 WO 2019058021A1
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gas
diabetes
intestinal
gas sensor
gas sample
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PCT/FI2018/050638
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English (en)
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Tuomas TIIRINKI
Risto Orava
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Halax Oy Finland
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
    • A61B5/082—Evaluation by breath analysis, e.g. determination of the chemical composition of exhaled breath
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
    • A61B5/097—Devices for facilitating collection of breath or for directing breath into or through measuring devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
    • A61B5/4216—Diagnosing or evaluating gastrointestinal ulcers
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
    • A61B5/4222—Evaluating particular parts, e.g. particular organs
    • A61B5/4255—Intestines, colon or appendix
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6891—Furniture
    • E—FIXED CONSTRUCTIONS
    • E03—WATER SUPPLY; SEWERAGE
    • E03D—WATER-CLOSETS OR URINALS WITH FLUSHING DEVICES; FLUSHING VALVES THEREFOR
    • E03D11/00—Other component parts of water-closets, e.g. noise-reducing means in the flushing system, flushing pipes mounted in the bowl, seals for the bowl outlet, devices preventing overflow of the bowl contents; devices forming a water seal in the bowl after flushing, devices eliminating obstructions in the bowl outlet or preventing backflow of water and excrements from the waterpipe
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
    • G01N33/4975—Physical analysis of biological material of gaseous biological material, e.g. breath other than oxygen, carbon dioxide or alcohol, e.g. organic vapours
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
    • A61B10/0038—Devices for taking faeces samples; Faecal examination devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
    • A61B2560/02—Operational features
    • A61B2560/0204—Operational features of power management
    • A61B2560/0214—Operational features of power management of power generation or supply
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/002—Monitoring the patient using a local or closed circuit, e.g. in a room or building
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement

Definitions

  • the disclosure relates to analysis of intestinal gases released by mammals, particularly to a method and a system for producing information indicative of diabetes.
  • Type 1 and Type 2 diabetes have been rapidly increasing in recent years 1 .
  • TIDM prevalence is estimated to double by 2020 in some populations 2 ; for T2DM, recent estimates indicate that in 2050 between 20% - 33% of all adults in the US may be diabetic.
  • T2DM recent estimates indicate that in 2050 between 20% - 33% of all adults in the US may be diabetic.
  • 3 Since a number of complications due to diabetes can be prevented by tight glycemic control, standard medical guidelines now call for patients to self-monitor their blood glucose multiple times a day. 4
  • Present diabetes management typically relies on painful finger lancing for glucose testing, a daily practice that many patients have come to hate, often resulting in fewer measurements and worsened glycemic control.
  • VOCs volatile organic compounds
  • T1DM and T2DM are expected to affect nearly 450 million people globally within the next 20 years 7 . Diagnosis and management of this epidemic currently depends on blood tests, which are expensive, unpractical, and often considered to be painful. Frequent blood testing is needed for patients undergoing insulin treatment, for whom the American Diabetes Association "ADA" recommends to self-monitor blood glucose concentrations more than three times daily by using finger sticks 8 .
  • a measurement of plasma insulin is clinically useful in assessing pre-diabetic states. As an indicator of impaired glucose metabolism, it increases prior to onset of glycemia itself 9 . The progression of T2DM from initial insulin resistance to eventual pancreatic failure, and to differentiate the increasingly common states in which components of both T1DM and T2DM are simultaneously present. Monitoring insulin also gives insight to other aspects of metabolism; insulin not only regulates glucose disposal but also exerts a strong anti- lipolytic effect, which is markedly reduced in patients
  • intestinal gas-based devices have multiple advantages. Notably, gas analysis is readily acceptable, or even remain unnoticed, by patients, promising a potentially marked increase in testing compliance, which is currently one of the major obstacles to good glycemic control. Further, sample collection is easy and can even be obtained from unconscious patients. Such monitoring could thus facilitate tighter glucose management during surgery, which is currently difficult to achieve but believed to result in better clinical or private household outcomes 12 . There is also virtually no limit in intestinal gas collection volume, which is a critical issue in neonates with extremely small circulating volumes. Intestinal gas collection can also be useful for wide screening when phlebotomy is problematic, i.e. in obese subjects with difficult vein access or in apprehensive primary school children who may refuse to participate in screening procedures involving phlebotomy.
  • the present innovation concentrates on the usage of intestinal gases as an alternative non-invasive tool for the diagnosis and analysis of diseases.
  • intestinal gases By combining the analysis of intestinal and exhaled breath gases as tools of an early detection of diseases, important breakthroughs could be achieved.
  • breath odors are traditionally associated with specific pathological states. For instance, renal failure is associated with a 'fishy' smell and diabetes with a 'fruity' smell.
  • 19 th century the 19 th century
  • VOCs Volatile Organic Compounds
  • FDA US Food and Drug Administration
  • the US Food and Drug Administration “FDA” has approved the breath-based diagnosis of alcohol intoxication, asthma, heart transplant rejection, Helicobacter pylori infection, carbon monoxide CO poisoning, and lactose intolerance 15 .
  • Diabetes and its related dysmetabolic states now greatly benefit from these non-invasive tests in diagnostic, prevention and monitoring using intestinal gases and correlations between the gas based and other analysis methods.
  • the interest on non- invasive, realtime analysis methods is rapidly growing and the intestinal gas test for plasma glucose, and foreseen parallel tests for plasma insulin and lipids, are of key interest today.
  • VOCs Volatile organic compounds
  • aerosolized particles in intestinal gases arise from many sources including inhaled room air, airways surfaces, blood, and peripheral tissues throughout the body. Some gases appear to be by-products of biochemical reactions, while others may be produced for specific physiological roles, such as cell-to-cell signaling. Production of other gases may only be present, or greatly amplified, during infections or other pathological conditions. An increasing number of previously undetected gases is being identified in gases released by humans, and there is growing interest in the direct identification of the origins of these compounds through the study of cellular and tissue gas emissions under a variety of physiological and experimental conditions.
  • VOCs An obvious source of breath VOCs is inhalation from the immediate surroundings, e.g. pollutants like ethane and n-pentane. High atmospheric concentrations of VOCs will directly result in high out-gas concentrations 16 . Such exposure may also lead to increased uptake of the compounds beyond the
  • VOCs e.g. trichloroethene, toluene, tetrachloroethylene, for instance, are absorbed into the systemic circulation and have been reported in blood samples of non-occupationally-exposed adult US populations 17 .
  • the inhaled VOCs once absorbed into the bloodstream, may undergo partial or total endogenous enzymatic metabolism, altering the ratio between inhaled and out-gassed concentrations.
  • the internal surfaces of the lungs may also directly contribute gases to the out-gassed mixture, i.e. by either generating lung-specific gases or increasing production of gases also produced elsewhere in the body.
  • gases for example, ten VOCs, 4 hydrocarbons, 2 esters, 2 ketones, 2-methyl-2-propanol, and ethyl tert-butyl ether, were produced by human bronchial epithelial primary cells 18 .
  • Ethane, isoprene, pentane, and other light hydrocarbons have been proposed as biomarkers of metabolic processes occurring on a systemic scale, such as fat oxidation 19 , cholesterol/LDL concentrations 20 , and oxidative stress levels 21 .
  • Patients with insulin resistance may have increased lipid production and therefore increased out-gassed ketones: acetone, 2-pentanone and 2-butanone, from subsequent lipolysis 8 .
  • VOCs are not detected in blood because they are bound to carrier proteins en route to delivery to the alveolar space.
  • hemoglobin has been seriously considered, in addition, of course, to its known ability to transport oxygen, C0 2 , CO, and NO 22 .
  • PMNs polymorphonuclear leukocytes
  • Bacteria Bacteria and other micro-organisms can also produce unique gas profiles which, if identified within out-gassed mixtures, may be used for diagnostic or monitoring purposes.
  • Atypical example involves the ingestion of radiolabeled urea to detect Helicobacter pylori, a urease-positive bacterium which causes gastroduodenal ulcers; only if the microorganism is present, urea will be hydro lyzed into radiolabeled CO2 and ammonia 28 .
  • Hydrogen cyanide has been shown to be released by cells infected by Pseudomonas aeruginosa and investigated as target for noninvasive diagnosis 29 .
  • Lactose ingestion by patients with hypolactasia is also known to increase their breath hydrogen concentrations, 48-168 ppmv vs 0- 3 ppmv in controls, due to the increased fermentation of carbohydrates by gut flora 30 .
  • a group of VOCs were found produced in vitro by Mycobacterium tuberculosis and also associated with active infection (including derivatives of cyclohexane, benzene, heptane and hexane) 31 . More importantly to the field of diabetes, ethanol and other alcohols can be produced by gut bacteria in response to glucose ingestion or changes in systemic glycemia.
  • VOCs present in human systems from established signaling pathways in other organisms. While these considerations are certainly just speculative, it is indeed possible that neutrophil-derived ethylene and/or other related gases contribute to a complex signaling network involving multiple aspects of glucose regulation. Alterations in this interactive pattern may have obvious implications in patients with diabetes and impaired glucose metabolism.
  • Ethyl nitrate possesses vasodilatory activity and suppresses methemoglobin formation 32 .
  • Methyl iodide can dose-dependently increase serum cholesterol, HDL, LDL, and decrease triglycerides in both rat and rabbit toxicity studies 33 .
  • Inhalation of dichloromethane, ethylbenzene, and trichloroethylene were shown to make 1,217 identifiable changes in rat gene expression 34 .
  • Intestinal functions and pulmonary vasculature are both thought to be impaired in diabetes, potentially affecting gas exchange kinetics of multiple VOC, concepts that need to be addressed if utilizing these compounds in the development of out-gas based tests.
  • As the disease worsens, for instance, increasingly severe pathological changes may render it necessary to perform frequent recalibrations or exclude specific VOCs from use in out-gas testing.
  • VOCs can now be routinely identified and quantified with a high degree of accuracy 40 . Additionally, direct measurements of compounds in EBC is now possible 41 ; typically, exhaled breath is trapped in a collection tube, cooled to an aqueous form, and analyzed by various chromatographic techniques 3 . New technologies with more frequent gas sampling or real-time analysis have been developed, which allow repeated testing during and following metabolic perturbations. These approaches include atmospheric pressure ionization mass spectrometry coupled with electrospray charging, which has been used for on-line measurements of volatilized fatty acids 42 as well as proton transfer reaction mass spectrometry (PTR-MS) 43 for measurement of breath VOCs.
  • PTR-MS proton transfer reaction mass spectrometry
  • Miekisch et al and Di Francesco et al introduced general instrumental techniques (chromatography and electronic sensors) and some clinical applications for breath testing 44 .
  • Buszewski et al later elaborated on several considerations for breath sampling, preconcentration, and analysis 45 . More recently, Smith et al reviewed selected ion flow tube mass spectrometry and PTR-MS technology for VOC breath analysis in diabetes mellitus 46 . Other non- invasive glucose monitoring methods are still being actively pursued.
  • Tura et al. 47 including several spectroscopic techniques, and newer breath and skin technologies 48 .
  • Greiter et al distinguished patients with T2DM from healthy controls with a 90% sensitivity and 92% specificity 49 .
  • Kulikov et al found light hydrocarbons (C2-C3 including ethanol and acetaldehyde) to be elevated in the exhaled breath of women who had risk factors for T2DM (i.e. relatives with diabetes and smoking) as compared to those without 50 . None of these tests have yet been translated into commercial devices, these studies constitute an important foundation for future research (especially on their underlying biochemical pathways) and product development.
  • Aromatic compounds e.g. ethylbenzene, o/m/p-xylene, toluene
  • Alkyl nitrates e.g. 2-, 3-pentyl nitrate, methyl nitrate
  • Ketones e.g. acetone, 2-pentanone
  • This improved 4-gas model allowed breath-based glucose prediction with a mean correlation coefficient of 0.91, range r 0.70- 0.98, when compared to standard glucose measurements 15 .
  • a breath-based lipid test could contribute to the overall management of diabetic patients, whose systemic lipid levels represent a critical risk factor for cardiovascular events; of course, this test could be extended to many non-diabetic populations too.
  • a new system for producing information indicative of diabetes comprising:
  • - means, e.g. a bowl of a toilet seat, for collection of excrement
  • the gas sensor is configured to determine, from the intestinal, gas sample, presence and concentrations of pre-determined volatile organic compounds, and the system comprises processing means for producing the information indicative of diabetes as a weighted linear combination of the determined concentrations of the pre-determined volatile organic compounds.
  • the present invention is based on identifying, analyzing and matching signatures of specific gaseous compounds found in intestinal/exhaled gases, released by an individual, with the known candidate biomarkers of Diabetes Mellitus "DM".
  • Different gases such as, but not limited to, acetone (CH3) 2 CO, ethanol C 2 H 6 0, methyl nitrate CH3NO3, ethyl benzene CeHsC bC b, plasma triglycerides TG e.g.
  • C55H98O6, 2-pentyl nitrate C5H11NO3, propane C3H8, methanol CH3OH are identified and measured in the flow of intestinal/exhaled gas and are matched with a set of predicted biomarkers connected to plasma insulin, lipid and fatty acid related gaseous signatures of T1DM & T2DM by using a machine learning algorithm and individual calibrations.
  • measurement of the intestinal and/or exhaled gas and ambient air in the vicinity of the intestinal gas measurement is used.
  • the ambient gas measurement may be simultaneous or it can be performed by the same sensor before or after the actual measurement.
  • a battery chargeable by using the existing auxiliary toilet mechanics e.g.
  • a button for flushing the WC and the toilet seat may be utilized.
  • the power may be harvested from mechanical energy, like generation of electricity from toilet seat cover opening and closing, or generating electricity from the pressurized incoming water same way as LED-lighted shower heads.
  • the power need for analysis is small, and also the data amount that may be sent by for example Bluetooth or by Wi-Fi is moderately small and doesn't consume much energy.
  • a sampling system may comprise at least one fan or other gas pump for moving gas samples and valves for taking samples.
  • the samples may be drawn to one or more gas collection chambers, and from the chamber to sensors, and the used samples may be flushed away by fresh air.
  • the odorless toilet like in Finnish utility model U20100452 may be used, and the house ventilation can be used for means of suction of gasses.
  • a gas pump or fan for moving the sample to the sensor array and mixing the sample, and flushing the chamber and sensor with fresh air.
  • the sampling may be continuous and/or discrete.
  • the gas is carried past the sensors without storing the sample first.
  • the continuous sample may be used for only some sensors, and the output of those sensors can be used for timing the sampling, that is opening the gas collection chamber and storing the gas sample for analysis.
  • the exhale air sampling may be done by measuring continuously only CO2 -concentration for recognizing when the sample is proper exhaust air and taking the sample for analysis only after the CO2 -concentration is high enough.
  • the tubes and chambers may be ventilated for example by a fan or by opening the air passage to house ventilation system and ambient air.
  • the present invention concerns a system for intestinal gas characterization including: an intestinal gas sampling device, a pipe for the intestinal gas flow out from the toilet bowl, a gas collection chamber integrated with the pipe outputting the intestinal gas, a gas sensor within the gas collection chamber, equipped with integrated signal processing means for intestinal gas flows, a gas sensor outside the gas collection chamber, equipped with integrated signal processing means for measuring the surrounding gas, means for data acquisition and data transmission, real-time data display, an electricity supply for charging the battery of the gas sensor.
  • the present invention concerns a system for intestinal gas characterization including: an intestinal gas sampling device, a pipe for the intestinal gas flow out from the toilet bowl, a gas mask for exhaled air with an output pipe connected to the pipe outputting the intestinal gas, a gas collection chamber integrated with the pipe outputting the intestinal gas from the toilet bowl, a gas sensor within the gas collection chamber, equipped with integrated signal processing means for intestinal gas flows, a switch operating the gas sensor alternatively for the input during the exhaling of breath gas into the gas mask, or for the input during the intestinal gas sampling , a gas sensor outside the gas collection chamber, equipped with integrated signal processing means for measuring the surrounding gas, means for data acquisition and data transmission, real-time data display, an electricity supply for charging a battery of the gas sensor.
  • the present invention concerns a method of detecting the presence of T1DM or T2DM, comprising: identifying and analyzing the collected intestinal and breath gas for a presence of volatile organic compounds "VOC" as markers of T1DM or T2DM as inputs to an adaptable machine learning algorithm.
  • the volatile organic compounds include, for example but not limited to, the following: acetone (CH3) 2 CO, ethanol C2H6O, methyl nitrate CH3NO3, ethyl benzene C6H5CH2CH3, plasma triglycerides TG e.g. C55H98O6, 2-pentyl nitrate C5H11NO3, propane C3H8, methanol CH3OH.
  • the adaptable machine learning algorithm optimizes, for each individual case, an initial equation
  • [TnDM: (t - 3t)] X Q + 1 [VOC 1 (t)] + 3 ⁇ 4 [VOC 2 (t)] + X 3 [VOC 3 (t)] + ... + 3 ⁇ 4 [VOC 8 (t)], where t denotes time, At is a time off-set, and 3 ⁇ 4 Xi, X2, X3, Xs are coefficients that represent the expected difference in glucose when the concentration of each corresponding gas is increased by one unit, whereas all the other gases are kept at constant concentrations.
  • the algorithm is adapted for each individual patient and calibrated for each individual indicator VOC and, for an 'empty' case, the surrounding air.
  • the measured and predicted TnDM values are displayed by the real-time data acquisition system, for example, as a Parkes glucose consensus error grid 56 and in terms of Bland- Altman plots 57 .
  • the real-time data acquisition system also produces statistical analysis measures, such as Pearson's product-moment correlation coefficients used for accessing the clinical relevance of the findings.
  • Figure 1 shows a system according to an exemplifying embodiment of the invention for producing information indicative of diabetes
  • Figure 2 shows a system according to another exemplifying embodiment of the invention for producing information indicative of diabetes
  • Figure 3 illustrates means for charging a battery of a system according to an exemplifying embodiment of the invention for producing information indicative of diabetes
  • Figure 4 shows a device for flushing a toilet and for charging a battery of a system according to an exemplifying embodiment of the invention for producing information indicative of diabetes.
  • Figure 5 shows a flowchart of a method according to an exemplifying embodiment of the invention for producing information indicative of diabetes.
  • Figure 1 shows a system according to an embodiment of the invention for producing information indicative of diabetes.
  • the system comprises: means 1 for collection of excrement, a gas sensor 3 for analyzing an intestinal gas sample, and means 2 for drawing the intestinal gas sample to the gas sensor.
  • the gas sensor 3 is configured to determine, from the intestinal gas sample, presence and concentrations of pre-determined volatile organic compounds.
  • the system comprises processing ⁇ means for producing the information indicative of diabetes as a weighted linear combination of the determined concentrations of the pre-determined volatile organic compounds.
  • the gas sensor 1 is configured to determine, from the intestinal gas sample, the presence and the concentrations of the following predetermined volatile organic compounds: acetone, ethanol, methyl nitrate, ethyl benzene, plasma triglycerides, 2-pentyl nitrate, propane, and methanol.
  • the means 1 for collection of excrement comprises a toilet seat bowl and the means 2 for drawing the intestinal gas sample comprises an odor exhaust ventilation adapted to conduct the intestinal gas sample from the toilet seat bowl to the gas sensor 3.
  • the gas sensor 3 further comprises gas collection chamber for gas sampling.
  • a system according to an exemplifying embodiment of the invention is adapted take samples from air for calibration when the means 1 for collection of excrement is not in use.
  • a system according to an exemplifying embodiment of the invention comprises at least one pump or valve for controlling the intestinal gas sample flow to one or more gas sample collection chambers and for ventilation the gas sample collection chambers and the gas sensor with fresh air after analyzing the intestinal gas sample.
  • Figure 2 shows a system according to an embodiment of the invention for producing information indicative of diabetes.
  • the system comprises: a toilet seat bowl for collection of excrement, a gas sensor 3 for analyzing an intestinal gas sample, and means 2 for drawing the intestinal gas sample to the gas sensor.
  • the system further comprises a gas mask 11 for exhaled air with an output pipe connected to the gas sensor 3.
  • the gas sensor 3 is configured to determine, from the intestinal gas sample or from the exhaled air, presence and concentrations of pre-determined volatile organic compounds.
  • the system comprises processing means for producing the information indicative of diabetes as a weighted linear combination of the determined concentrations of the pre-determined volatile organic compounds.
  • the system comprises a switch operated valve 4 for choosing the operational mode of gas sampling: intestinal gas sampling or exhaled breath gas sampling. 2Q
  • FIG 3 shows an exemplary toilet seat for generating electricity to charge a battery which powers the gas sensor, see Figures 1 and 2.
  • the toilet seat comprises a piezoelectric module with a piezoelectric element underneath, a circuit to transmit the electricity generated by the piezoelectric effect, due to the weight of a person sitting on the seat, gravitational force F, to the battery of the gas sensor.
  • Figure 4 shows an exemplifying device for flushing the toilet and for charging the battery of the gas sensor.
  • the device comprises a wall mounted housing and a piezoelectric module.
  • Figure 5 shows a flowchart of a method according to an exemplifying embodiment of the invention for producing information indicative of diabetes.
  • the method comprises the following actions:
  • action 1 receiving excrement with means for collection of the excrement
  • action 3 using the gas sensor for determining, from the intestinal gas sample, presence and concentrations of pre-determined volatile organic compounds, and
  • action 4 producing the information indicative of diabetes as a weighted linear combination of the determined concentrations of the pre-determined volatile organic compounds.
  • a method according to an exemplifying embodiment of the invention further comprises actions 8 for system calibration, environmental controls, and/or mode selection.
  • action 6 analyzing the information with machine learning algorithms for disease recognition
  • action 7 sending the analysis results wirelessly to e.g. a portable phone or some other communication device.

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Abstract

L'invention concerne un système de production d'informations indiquant un diabète comprenant des moyens (1) de collecte d'excréments, un capteur de gaz (3) permettant d'analyser un échantillon de gaz intestinal, et un moyen (2) permettant d'acheminer l'échantillon de gaz intestinal vers le capteur de gaz. Le capteur de gaz est conçu pour déterminer, à partir de l'échantillon de gaz intestinal, la présence et des concentrations de composés organiques volatils prédéterminés. Le système comprend un moyen de traitement permettant de produire des informations indiquant un diabète en tant que combinaison linéaire pondérée des concentrations déterminées des composés organiques volatils prédéterminés.
PCT/FI2018/050638 2017-09-20 2018-09-10 Système et procédé de production d'informations indiquant un diabète WO2019058021A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FI20175835A FI20175835A1 (en) 2017-09-20 2017-09-20 Tarmgasanalys
FI20175835 2017-09-20

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GB2600938A (en) * 2020-11-11 2022-05-18 Roboscientific Ltd Automatic monitoring of an environment for disease
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EP4085832A1 (fr) * 2021-05-04 2022-11-09 Roche Diabetes Care GmbH Détermination non invasive des niveaux de glucose sanguin
WO2022233771A1 (fr) * 2021-05-04 2022-11-10 F. Hoffmann-La Roche Ag Détermination non invasive de taux de glycémie

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