Personalized model with regular integration of data

Patent metadata

Field	Value
Publication number	US-2017235915-A1
Application number	US-201715417941-A
Country	US
Kind code	A1
Filing date	Jan 27, 2017
Priority date	Feb 17, 2016
Publication date	Aug 17, 2017
Grant date	—

Abstract

For personalized modeling with regular integration from a sensor, a wearable sensor and/or sensor outside of the medical facility or environment provides health-related data on a regular, periodic, or continuous basis (e.g., every few minutes or hours). Rather than using that data alone, the data is used to update a previously created personalized model of anatomy of the patient. After updating a parameter value for the personalized model, the updated model is used to output more complex health-related information than provided by the sensors.

First claim

I (we) claim:

1 . A method for personalized modeling with regular integration from a sensor system, the method comprising:
capturing spatial data of an organ of a patient with a medical scanner; generating a model of dynamic behavior of the organ, the model personalized to the patient with the spatial data; acquiring periodic readings from a wearable sensor worn by the patient; in response to the periodic readings, periodically updating the model with a most recent reading; periodically modeling the dynamic behavior of the organ with the model as updated; and outputting a risk of an adverse event for the organ based on at least one iteration of the periodic modeling.

2 . The method of claim 1 wherein capturing the spatial data comprises capturing ultrasound data of a heart of the patient with an ultrasound scanner, and wherein the model is of the heart.

3 . The method of claim 1 wherein generating the model comprises generating an electro-mechanical model based on hemodynamics and electrophysiology.

4 . The method of claim 1 wherein acquiring the periodic readings comprises acquiring heart rate, temperature, pressure, breathing cycle, oxygen saturation, glucose level, or step frequency.

5 . The method of claim 1 wherein acquiring the periodic readings comprises acquiring with the wearable sensor being worn on a wrist, neck, or ankle of the patient outside of a medical facility.

6 . The method of claim 1 wherein acquiring the periodic readings comprises acquiring a new one of the readings at least every hour, and wherein periodically updating and modeling comprise updating and modeling in response to each of the new ones of the readings.

7 . The method of claim 1 wherein acquiring the periodic readings comprises acquiring a new one of the readings during and prior to completion of one of the periodic updates; and
further comprising storing the new one of the readings during the one of the periodic updates and using the new one for a subsequent one of the periodic updates.

8 . The method of claim 1 wherein periodic updating and periodic modeling use a circular buffer with the updating occurring, for every other iteration, in a first slot of the circular buffer using a first thread and with the modeling occurring in a second slot of the circular buffer using a second thread, wherein the first and second slots are switched for other iterations.

9 . The method of claim 1 further comprising wirelessly transmitting the readings from the wearable sensor to a server, and wherein the periodic updating and periodic modeling are performed by the server.

10 . The method of claim 9 wherein wirelessly transmitting comprises wirelessly transmitting from the wearable sensor to a phone, and wirelessly transmitting from the phone to the server.

11 . The method of claim 1 wherein acquiring the periodic readings comprises acquiring from the wearable sensor and at least another sensor worn by the patient.

12 . The method of claim 1 wherein outputting the risk comprises outputting diagnosis, prognosis, or event occurrence.

13 . The method of claim 1 wherein outputting the risk comprises warning of malfunction of the organ.

14 . The method of claim 1 further comprising:
gating the medical scanner or another medical scanner for imaging the heart of the patient based on the modeling of the dynamic behavior.

15 . The method of claim 1 further comprising:
generating an image of the organ on a mobile device, the image generated from the model.

16 . The method of claim 1 further comprising:
calculating information from the modeling for the patient and modeling for other patients.

17 . The method of claim 16 further comprising:
providing a mitigation recommendation based on the information.

18 . A system for personalized modeling with regular integration of data, the system comprising:
a sensor for on-going sensing of a patient; a memory configured to store values from the on-going sensing and a physics model of the patient; and a processor configured to regularly fit the physics model to the patient based on the values received from the sensor since a previous update, to determine a state of the patient from the updated model, and to generate an output for the patient based on the state.

19 . The system of claim 18 wherein the memory comprises a circular lock-free buffer with at least two slots cycling between storing the values while the processor fits the physics model and determines the state.

20 . A method for personalized modeling with regular integration from a sensor system, the method comprising:
sensing signals from a patient outside a medical facility with an e-health sensor; modifying a parameter personalizing a mechanistic model of organ function of the patient based on signals from the sensing; modeling the organ function with the mechanistic model as modified; repeating the sensing, modifying, and modeling in real-time; and transmitting health data for the patient from at least one iteration of the modeling.

Assignees

• Siemens Healthcare Gmbh

Inventors

• Mansi Tommaso
• Paulus Jr John
• Passerini Tiziano

Classifications

• G06F19/3437 Primary

  Physics · mapped topic

• G06F19/322

  Physics · mapped topic

• G06F19/3418

  Physics · mapped topic

• G16H10/60 Primary

  for patient-specific data, e.g. for electronic patient records · CPC title

• G16H50/50

  for simulation or modelling of medical disorders · CPC title