# US 10,478,557 B2 · Personalized parameter modeling methods and related devices and systems > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,478,557 B2 - Document ID: US10478557B2 - Status: Granted - Kind: B2 - Application number: 15/240,726 - Filed: 2016-08-18 - Published: 2017-02-23 - Granted: 2019-11-19 - Earliest claimed: 2015-08-21 - Assignees: Medtronic MiniMed, Inc. - Applicants: Medtronic Minimed, Inc. - Inventors: Andrea Varsavsky; Yunfeng Lu; Keith Nogueira; Jeffrey Nishida - Web page: https://patentgrep.com/patent/US10478557B2 ## CPC - A61M 5/1723: {using feedback of body parameters, e.g. blood sugar or pressure} - A61B 5/14532: {for measuring glucose, e.g. by tissue impedance measurement} - A61B 5/4839: {combined with drug delivery} - G16H 10/60: for patient-specific data, e.g. for electronic patient records - G16H 20/17: delivered via infusion or injection - G16H 40/40: for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades - G16H 40/63: for local operation - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 50/50: for simulation or modelling of medical disorders - A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet} - A61B 5/02438: {with portable devices, e.g. worn by the patient} - A61B 5/7239: {using differentiation including higher order derivatives} - A61B 5/7242: {using integration} - A61B 2560/0242: adapted to measure environmental factors, e.g. temperature, pollution - A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches - A61M 5/14244: {adapted to be carried by the patient, e.g. portable on the body} - A61M 2205/3569: sublocal, e.g. between console and disposable - A61M 2205/502: User interfaces, e.g. screens or keyboards - A61M 2205/52: with memories providing a history of measured variating parameters of apparatus or patient - A61M 2205/70: with testing or calibration facilities - A61M 2230/005: Parameter used as control input for the apparatus - A61M 2230/06: Heartbeat rate only - A61M 2230/201: Glucose concentration - G16H 15/00: ICT specially adapted for medical reports, e.g. generation or transmission thereof - A61M: DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY (introducing media into or onto the bodies of animals A61D7/00; means for inserting tampons A61F13/26; devices for administering food or medicines orally A61J; containers for collecting, storing or administering blood or medical fluids A61J1/05); DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY (surgery A61B; chemical aspects of surgical articles A61L); DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR {(Electrotherapy, e.g. producing anaesthesia by the use of alternating or intermittent currents A61N1/36021)} - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract Medical devices and related patient management systems and parameter modeling methods are provided. An exemplary method of operating a sensing device associated with a patient involves obtaining current operational context information associated with the sensing device, obtaining a parameter model associated with the patient, calculating a current parameter value based on the parameter model and the current operational context information, obtaining one or more signals from a sensing element configured to measure a condition in a body of the patient, and providing an output that is influenced by the calculated current parameter value and the one or more signals. ## Claims ### Claim 1 A method of operating a sensing device associated with a patient, the sensing device including a control module coupled to a sensing element configured to measure a physiological condition in a body of the patient, the method comprising: obtaining, by the control module of the sensing device, current operational context information associated with the sensing device; obtaining, by the control module, an expected calibration factor parameter model associated with the patient; calculating, by the control module, an expected calibration factor value based on the expected calibration factor parameter model and the current operational context information; obtaining, by the control module, one or more electrical signals from the sensing element of the sensing device, the one or more electrical signals having a signal characteristic indicative of the physiological condition in the body of the patient; converting, by the control module, the one or more electrical signals into a calibrated measurement value for the physiological condition in the body of the patient using the expected calibration factor value; and outputting, by the control module, the calibrated measurement value for the physiological condition in the body of the patient. ### Claim 2 (depends on 1) The method of claim 1, wherein outputting the calibrated measurement value comprises transmitting the calibrated measurement value to an infusion device, wherein the infusion device is autonomously operated to deliver fluid to the body of the patient based on a difference between the calibrated measurement value and a reference value. ### Claim 3 (depends on 1) The method of claim 1, further comprising: obtaining historical operational context information associated with preceding operation of the sensing device; obtaining historical values for a calibration factor associated with the preceding operation of the sensing device; and determining the expected calibration factor model associated with the patient based on the historical operational context information and the historical values. ### Claim 4 (depends on 3) The method of claim 3, wherein: determining the expected calibration factor model comprises: identifying a subset of predictive variables from among the historical operational context information based on a correlation between the subset of predictive variables and the historical values for the calibration factor; determining the expected calibration factor model as a function of the subset of predictive variables based on historical values for the subset of predictive variables and the historical values for the calibration factor; the current operational context information includes current values for the subset of predictive variables; and calculating the expected calibration factor value comprises calculating the expected calibration factor value as the function of the current values for the subset of predictive variables according to the expected calibration factor model. ### Claim 5 (depends on 4) The method of claim 4, wherein outputting the calibrated measurement value comprises transmitting the calibrated measurement value to an infusion device, wherein the infusion device is autonomously operated to deliver fluid to the body of the patient based on a difference between the calibrated measurement value and a reference value. ### Claim 6 (depends on 1) The method of claim 1, further comprising: obtaining a measurement offset model associated with the patient; calculating an expected offset value based on the current operational context information using the measurement offset model; and subtracting the expected offset value from the one or more electrical signals prior to converting the one or more electrical signals into the calibrated measurement value. ### Claim 7 (depends on 6) The method of claim 6, wherein converting the one or more electrical signals into the calibrated measurement value comprises multiplying one or more results of subtracting the expected offset value from the one or more electrical signals by the expected calibration factor value. ### Claim 8 (depends on 7) The method of claim 7, further comprising: obtaining historical operational context information associated with preceding operation of the sensing device; obtaining historical values for a calibration factor associated with the preceding operation of the sensing device; obtaining historical values for a measurement offset associated with the preceding operation of the sensing device; and determining the expected calibration factor model associated with the patient based on the historical operational context information and the historical values for the calibration factor; and determining the measurement offset model associated with the patient based on the historical operational context information and the historical values for the measurement offset. ### Claim 9 (depends on 1) The method of claim 1, further comprising generating a user notification based at least in part on the expected calibration factor value. ### Claim 10 (depends on 9) The method of claim 9, further comprising determining a remaining usage life associated with the sensing device based at least in part on the expected calibration factor value, wherein generating the user notification comprises providing an indication of the remaining usage life. ### Claim 11 (depends on 9) The method of claim 9, further comprising determining an optimal calibration time based at least in part on the expected calibration factor value, wherein generating the user notification comprises providing an indication of the optimal calibration time. ### Claim 12 (depends on 9) The method of claim 9, further comprising determining a recommended sensor site location based at least in part on the expected calibration factor value, wherein generating the user notification comprises providing an indication of the recommended sensor site location. ### Claim 13 (depends on 1) A non-transitory computer-readable medium having instructions stored thereon that are executable by the control module of the sensing device to perform the method of claim 1. ### Claim 14 A sensing device comprising: a sensing element to output one or more electrical signals having a signal characteristic indicative of a physiological condition in a body of a patient; a data storage element to store an expected calibration factor parameter model associated with the patient; an output interface; and a control module coupled to the sensing element, the data storage element, and the output interface to calculate an expected calibration factor value based on the expected calibration factor parameter model and current operational context information, convert the one or more electrical signals into a calibrated measurement value for the physiological condition in the body of the patient using the expected calibration factor value, and provide the calibrated measurement value at the output interface. ### Claim 15 (depends on 14) The sensing device of claim 14, wherein: the output interface comprises a communications interface to transmit the calibrated measurement value to an infusion device; and operation of the infusion device to regulate the physiological condition of the patient based on the calibrated measurement value. ### Claim 16 (depends on 14) The sensing device of claim 14, wherein: the output interface comprises an output user interface element; and the output comprises a user notification generated based at least in part on the expected calibration factor value. ### Claim 17 (depends on 16) The sensing device of claim 16, wherein: the control module determines a remaining usage life associated with the sensing device based at least in part on the expected calibration factor value; and the user notification comprises an indication of the remaining usage life. ### Claim 18 A system comprising: a computing device communicatively coupled to a network to obtain historical operational context information associated with a patient via the network, obtain historical values for a calibration factor associated with the patient via the network, and determine a patient-specific model for the calibration factor based on a relationship between the historical operational context information and the historical values; and a sensing device communicatively coupled to the computing device to obtain the patient-specific model, obtain current operational context information associated with the sensing device, calculate an expected value for the calibration factor based on the patient-specific model and the current operational context information, obtain one or more electrical signals having a signal characteristic indicative of a physiological condition in a body of the patient from a sensing element of the sensing device, convert the one or more electrical signals into a calibrated measurement value for the physiological condition in the body of the patient using the expected value for the calibration factor, and output the calibrated measurement value. ### Claim 19 (depends on 18) The system of claim 18, further comprising an infusion device coupled to the sensing device, wherein: the infusion device is operable to deliver fluid to the body of the patient based on the calibrated measurement value. ### Claim 20 (depends on 1) The method of claim 1, wherein: the current operational context comprises a current sensor site location on the body of the patient; and calculating the expected calibration factor value comprises determining the expected calibration factor value as a function of the current sensor site location.