Core temperature estimation from skin and ambient temperature sensors using a dynamic model

1. A temperature measurement device for determining a body temperature of a subject, the temperature measurement device comprising:

a first temperature sensor configured to measure a plurality of skin temperatures of the subject at a plurality of time instants;

a second temperature sensor spaced apart from the first temperature sensor and configured to measure a plurality of ambient temperatures at the plurality of time instants;

a thermal insulation material between the first temperature sensor and the second temperature sensor;

a memory device configured to store the plurality of skin temperatures and the plurality of ambient temperatures; and

a controller configured to estimate, using a regression model, the body temperature of the subject based on the plurality of skin temperatures and the plurality of ambient temperatures, wherein the regression model includes a nonlinear autoregressive exogenous (NARX) model.

2. The temperature measurement device of claim 1 , further comprising a user interface device configured to display the body temperature of the subject estimated by the controller or generate a signal indicating a high temperature event based on the body temperature of the subject.

3. The temperature measurement device of claim 1 , wherein the temperature measurement device is in a form of a wearable device or is embedded in a garment.

4. The temperature measurement device of claim 1 , wherein the temperature measurement device further comprises a third temperature sensor spaced apart from the first temperature sensor and configured to measure a second plurality of skin temperatures of the subject at the plurality of time instants.

5. The temperature measurement device of claim 1 , wherein

the regression model includes a set of regressors and corresponding weights.

6. The temperature measurement device of claim 5 , wherein the set of regressors of the regression model includes skin temperatures and ambient temperatures measured at two or more past time instants.

7. The temperature measurement device of claim 5 , wherein the set of regressors of the regression model includes each of the plurality of skin temperatures and the plurality of ambient temperatures raised to powers of two or more values.

8. The temperature measurement device of claim 5 , wherein the weights of the regression model are trained to minimize a mean square error.

9. The temperature measurement device of claim 5 , further comprising a user interface device configured to receive at least one of:

a number of time instants in the plurality of time instants;

a degree of polynomial in the regression model; or

a measurement frequency of the first temperature sensor.

10. The temperature measurement device of claim 9 , wherein the controller is further configured to set the measurement frequency of the first temperature sensor.

11. A method of determining a body temperature of a subject, the method comprising:

measuring, by a first temperature sensor, a plurality of skin temperatures of the subject at a plurality of time instants;

measuring, by a second temperature sensor spaced apart from the first temperature sensor, a plurality of ambient temperatures at the plurality of time instants;

storing the plurality of skin temperatures and the plurality of ambient temperatures in a memory device;

obtaining, by a controller from the memory device, the plurality of skin temperatures and the plurality of ambient temperatures; and

determining, by the controller based on a regression prediction-model, the body temperature of the subject based on the plurality of skin temperatures and the plurality of ambient temperatures, wherein the regression model includes a nonlinear autoregressive exogenous (NARX) model.

12. The method of claim 11 , further comprising at least one of:

displaying the body temperature of the subject determined by the controller; or

generating a signal indicating a high temperature event based on the body temperature of the subject.

13. The method of claim 11 , wherein the regression model includes a set of regressors and corresponding weights.

14. The method of claim 13 , wherein the set of regressors of the regression model includes skin temperatures and ambient temperatures measured at two or more past time instants.

15. The method of claim 13 , wherein the set of regressors of the regression model includes each of the plurality of skin temperatures and the plurality of ambient temperatures raised to powers of two or more values.

16. The method of claim 13 , further comprising receiving, by a user interface device, at least one of:

a number of time instants in the plurality of time instants;

a degree of polynomial in the regression model; or

a measurement frequency of the first temperature sensor.

17. A non-transitory computer-readable storage medium storing instructions executable by one or more processors, the instructions, when executed by the one or more processors, cause the one or more processors to perform operations including:

obtaining a plurality of skin temperatures of a subject measured at a plurality of time instants;

obtaining a plurality of ambient temperatures measured at the plurality of time instants; and

determining, based on a regression model that includes a set of regressors and corresponding weights, a body temperature of the subject based on the plurality of skin temperatures and the plurality of ambient temperatures, wherein the regression model includes a nonlinear autoregressive exogenous (NARX) model.

18. The non-transitory computer-readable storage medium of claim 17 , wherein:

the set of regressors of the regression model includes skin temperatures and ambient temperatures measured at two or more past time instants; and

the set of regressors of the regression model includes each of the plurality of skin temperatures and the plurality of ambient temperatures raised to powers of two or more values.