Thermal stress risk assessment using body worn sensors

1. A method comprising:

receiving body ambient temperature data captured by a sensor in contact with a person;

characterizing one or more types of activities performed by the person during a time range associated with the body ambient temperature data; and

determining a risk classification individualized for the person based at least on one or more respective workloads and the corresponding allocations of work and rest experienced by the person during performance of the characterized types of activities.

2. The method of claim 1 , wherein the body ambient temperature data captured by a sensor comprises timestamped data representing at least one of:

body segment motion, body temperature, heart rate, galvanic skin response (GSR), electromyograms (EMG); and

environmental conditions data comprising at least one of: humidity, pressure and positional information associated with a global navigation satellite system.

3. The method of claim of claim 1 , wherein characterizing one or more types of activities comprises:

identifying external data related to a geographic location of the person; and

generating transformed data based on the body ambient temperature data synchronized with the external data to represent risk conditions associated with one or more activities performed by the person during the time range of the body ambient temperature data.

4. The method of claim 3 , wherein the external data comprises at least one of: weather data and land survey data.

5. The method of claim 3 , wherein generating transformed data based on the body ambient temperature data synchronized with the external data comprises:

trimming the external data to identify trimmed external data contemporaneous to the time range of the body ambient temperature data;

generating synchronized data based on synchronizing the trimmed external data and the body ambient temperature data; and

transforming the synchronized data to generate transformed data, the transformed data includes one or more of:

(i) physical orientation data of the body ambient temperature data transformed to representations of one or more body motions;

(ii) positional information of the body ambient temperature data combined with at least one of: accelerometer data, local ambient pressure from the external data, altitude data from the external data and motion data from the body ambient temperature data converted into data representing a relationship between physical energy burn and caloric consumption.

6. The method of claim 1 , wherein characterizing one or more types of activities performed by the person during a time range associated with the body ambient temperature data comprises:

applying one or more pattern recognition techniques to transformed data based on external data synchronized with the body ambient temperature data, the one or more pattern recognition techniques matching at least one or more segments of time associated with the transformed data that is indicative of a time epoch of a performed pre-defined activity available from a plurality of pre-defined activities.

7. The method of claim 6 , wherein plurality of pre-defined activities comprises: lifting an object, pushing an object, pulling an object, carrying an object, walking, running, standing, sitting, sitting in a moving vehicle and climbing stairs.

8. The method of claim 1 , wherein determining a risk classification individualized for the person comprises:

identifying respective workloads associated with the one or more types of characterized activities and one or more allocations of work and rest when the person incurred each the respective workloads.

9. The method of claim 8 , wherein a respective workload is based on an established metabolic rate experienced during a pre-defined activity that matches a respective activity represented in part by the body ambient temperature data; and

wherein a respective allocation of work and rest describes a ratio of rest and non-rest during an interval of time in which the respective workload was experienced.

10. A computer program product comprising computer-readable program code to be

executed by one or more processors when retrieved from a non-transitory computer-readable medium, the program code including at least one instruction to:

receive body ambient temperature data captured by a sensor in contact with a person;

characterize one or more types of activities performed by the person during a time range associated with the body ambient temperature data; and

determine a risk classification individualized for the person based at least on one or more respective workloads and the corresponding allocations of work and rest experienced by the person during performance of the characterized types of activities.

11. The computer program product of claim 10 , wherein the body ambient temperature data captured by a sensor comprises timestamped data representing at least one of:

body segment motion, body temperature, heart rate, galvanic skin response (GSR), electromyograms (EMG); and

environmental conditions data comprising at least one of: humidity, pressure and positional information associated with a global navigation satellite system.

12. The computer program product of claim 10 , wherein the program code to characterize one or more types of activities further includes instructions to:

identify external data related to a geographic location of the person; and

generate transformed data based on the body ambient temperature data synchronized with the external data to represent risk conditions associated with one or more activities performed by the person during the time range of the body ambient temperature data.

13. The computer program product of claim 12 , wherein the external data comprises at least one of: weather data and land survey data.

14. The computer program product of claim 12 , wherein the program code to generate transformed data further includes instructions to:

trim the external data to identify trimmed external data contemporaneous to the time range of the body ambient temperature data;

generate synchronized data based on synchronizing the trimmed external data and the body ambient temperature data; and

transform the synchronized data to generate transformed data, the transformed data includes one or more of:

(i) physical orientation data of the body ambient temperature data transformed to representations of one or more body motions;

(ii) positional information of the body ambient temperature data combined with at least one of: accelerometer data, local ambient pressure from the external data, altitude data from the external data and motion data from the body ambient temperature data converted into data representing a relationship between physical energy burn and caloric consumption.

15. The computer program product of claim 10 , wherein the program code to characterize one or more types of activities further includes instructions to:

apply one or more pattern recognition techniques to transformed data based on external data synchronized with the body ambient temperature data, the one or more pattern recognition techniques matching at least one or more segments of time associated with the transformed data that is indicative of a time epoch of a performed pre-defined activity available from a plurality of pre-defined activities.

16. The computer program product of claim 15 , wherein plurality of pre-defined activities comprises: lifting an object, pushing an object, pulling an object, carrying an object, walking, running, standing, sitting, sitting in a moving vehicle and climbing stairs.

17. The computer program product of claim 10 , wherein the program code to determine a risk classification individualized for the person further includes instructions to:

identify respective workloads associated with the one or more types of characterized activities and one or more allocations of work and rest when the person incurred each the respective workloads.

18. The computer program product of claim 17 , wherein a respective workload is based on an established metabolic rate experienced during a pre-defined activity that matches a respective activity represented in part by the body ambient temperature data; and

wherein a respective allocation of work and rest describes a ratio of rest and non-rest during an interval of time in which the respective workload was experienced.

19. A system comprising:

one or more processors; and

a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to:

receive body ambient temperature data captured by a sensor in contact with a person;

characterize one or more types of activities performed by the person during a time range associated with the body ambient temperature data; and

determine a risk classification individualized for the person based at least on one or more respective workloads and the corresponding allocations of work and rest experienced by the person during performance of the characterized types of activities.

20. The system of claim 19 , wherein the plurality of instructions, which when executed, cause the one or more processors to characterize one or more types of activities further includes one or more instructions to:

apply one or more pattern recognition techniques to transformed data based on external data synchronized with the body ambient temperature data, the one or more pattern recognition techniques matching at least one or more segments of time associated with the transformed data that is indicative of a time epoch of a performed pre-defined activity available from a plurality of pre-defined activities; and

wherein the plurality of instructions, which when executed, cause the one or more processors to determine a risk classification further includes one or more instructions to:

identify respective workloads associated with the one or more types of characterized activities and one or more allocations of work and rest when the person incurred each the respective workloads, wherein a respective workload is based on an established metabolic rate experienced during a pre-defined activity that matches a respective activity represented in part by the body ambient temperature data and wherein a respective allocation of work and rest describes a ratio of rest and non-rest during an interval of time in which the respective workload was experienced.