Device and method for automatically normalizing the physiological signals of a living being

• US 9,759,558 B2
• Filed: 08/28/2014
• Issued: 09/12/2017
• Est. Priority Date: 09/06/2013
• Status: Active Grant

• Current Assignee: Stichting Imec Nederland
• Original Assignee: Stichting Imec Nederland
• Inventors: Altini, Marco
• Primary Examiner(s): NEGIN, RUSSELL SCOTT
• Application Number:
  US14/471,158
• Publication Number:
  US 20150073720A1
• Time in Patent Office: 1,111 Days
• Field of Search: None
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/6802 Sensor mounted on worn items
• CPC Class Codes: G01B 21/00 Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
• CPC Class Codes: G01C 22/00 Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G06F 17/10 Complex mathematical operations function generation by table look-up G06F1/03; evaluation of elementary functions by calculation G06F7/544
• CPC Class Codes: G16B 5/00 ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks

Abstract

An example device includes: a data input module configured to receive information about a living being'"'"'s physiological signals, coordinates, and motion intensity; an activity recognition module configured to calculate, from information received about the living being'"'"'s motion intensity, a living being'"'"'s activity; a location recognition module, configured to calculate, from information received about the living being'"'"'s coordinates, a living being'"'"'s location; a memory storage configured to store information about the living being'"'"'s physiological signals and activity in association with the location; a normalization parameters estimator module configured to use a mathematical model to calculate a plurality of normalization parameters for a plurality of detected activities and locations; and a model selector module configured to determine, based on the plurality of normalization parameters and the living being'"'"'s location, a set of location-specific normalization parameters used to further calculate normalized physiological signals for the living being.

Claims

1. A device comprising:

a data input module configured to receive information about a living being'"'"'s physiological signals, coordinates, and motion intensity;

an activity recognition module configured to calculate, from information received about the living being'"'"'s motion intensity, activity of the living being;

a location recognition module, configured to calculate, from information received about the living being'"'"'s coordinates, a location of the living being;

a memory storage configured to store information about the living being'"'"'s physiological signals and the activity of the living being in association with the location of the living being;

a normalization parameters estimator module configured to calculate, from a plurality of physiological signal values associated with calculated activities and calculated locations, statistics of a distribution of the physiological signal values for each activity or a subset of activities in each location, and use a mathematical model to calculate a plurality of normalization parameters for each location; and

a model selector module configured to determine, based on the plurality of normalization parameters and the living being'"'"'s location, a set of location-specific normalization parameters used to further calculate normalized physiological signals for the living being, wherein the model selector module is further configured to calculate the normalized physiological signals for the living being by applying the location-specific normalization parameters to the physiological signals, depending on the living being'"'"'s location, and wherein the normalized physiological signals for the living being include information about one or more of heart rate, galvanic skin response, skin temperature, skin humidity, or respiration.

2. The device of claim 1, wherein the activity recognition module is configured to determine at least a rest activity and a moving activity of the living being.

3. The device of claim 2, wherein the moving activity is associated with at least a first motion intensity, and wherein the normalization parameters estimator module is configured to calculate, for each location, a first physiological signal values summary based on a distribution of physiological signal values associated with the first motion intensity and a second physiological signal values summary based on a distribution of physiological signal values associated with the rest activity.

4. The device of claim 1, wherein the location recognition module is configured to determine at least two different locations.

5. The device of claim 1, wherein the normalization parameters estimator module uses a mathematical model based on information about physiological signal values distribution, activity, and location.

6. The device of claim 5, wherein the mathematical model expresses a relation between a plurality of physiological signal values associated with each calculated activity and location and a baseline and range of physiological signal values for the living being.

7. The device of claim 6, wherein the mathematical model further considers information about anthropometric characteristics of the living being.

8. The device of claim 1, further comprising an application module configured to calculate, from the living being'"'"'s normalized physiological signals, an additional application-specific parameter associated with the living being.

9. The device of claim 8, wherein the application module is further configured to use information about the living being'"'"'s motion intensity, the livng being'"'"'s coordinates, and/or anthropometric characteristics of the living being for calculating the additional application-specific parameter.

10. The device of claim 9, wherein the additional application-specific parameter associated with the living being is an energy expenditure value or a stress level.

11. A system comprising:

a device, the device comprising;

a data input module configured to receive information about a living being'"'"'s physiological signals, coordinates, and motion intensity;

an activity recognition module configured to calculate, from information received about the living being'"'"'s motion intensity, activity of the living being;

a location recognition module, configured to calculate, from information received about the living being'"'"'s coordinates, a location of the living being;

a memory storage configured to store information about the living being'"'"'s physiological signals and the activity of the living being in association with the location of the living being;

a normalization parameters estimator module configured to calculate, from a plurality of physiological signal values associated with calculated activities and calculated locations, statistics of a distribution of the physiological signal values for each activity or a subset of activities in each location, and use a mathematical model to calculate a plurality of normalization parameters for each location; and

a model selector module configured to determine, based on the plurality of normalization parameters and the living being'"'"'s location, a set of location-specific normalization parameters used to further calculate normalized physiological signals for the living being, wherein the model selector module is further configured to calculate the normalized physiological signals for the living being by applying the location-specific normalization parameters to the physiological signals, depending on the living being'"'"'s location, and wherein the normalized physiological signals for the living being include information about one or more of heart rate, galvanic skin response, skin temperature, skin humidity, or respiration.

12. The system of claim 11, wherein the device further comprises an application module configured to calculate, from the living being'"'"'s normalized physiological signals, an additional application-specific parameter associated with the living being.

13. The system of claim 12, wherein the additional application-specific parameter associated with the living being is an energy expenditure value or a stress level.

14. A method for calculating normalized physiological signals of a living being, the method comprising:

receiving information about physiological signals, motion intensity, and coordinates of the living being;

detecting activity of the living being from information received about the living being'"'"'s motion intensity and storing information about the living being'"'"'s physiological signals and the motion intensity in association with the detected activity;

detecting a location of the living being from information received about the living being'"'"'s coordinates and storing information about the living being'"'"'s physiological signals and the coordinates in association with the detected activity and location;

determining, from a plurality of physiological signal values associated with a plurality of activities and locations, statistics of a distribution of physiological signal values for each activity or a subset of activities and in each location;

calculating, using the statistics of the distribution of physiological signal values, a baseline and range of the physiological signals for the location of the living being; and

normalizing, using the baseline and range of the physiological signals and depending on the living being'"'"'s location, the living being'"'"'s physiological signals, wherein the normalized physiological signals include information about one or more of heart rate, galvanic skin response, skin temperature, skin humidity, or respiration.

15. The method of claim 14, further comprising calculating, from the living being'"'"'s normalized physiological signals, an additional application-specific parameter associated with the living being.

16. The method of claim 15, wherein the additional application-specific parameter associated with the living being is an energy expenditure value or a stress level.