Automated detection and configuration of wearable devices based on on-body status, location, and/or orientation

1. An electronic device worn on a user, the electronic device comprising:

one or more accelerometers configured to generate acceleration information based on acceleration experienced by the electronic device;

a temperature sensor configured to measure temperature information associated with the electronic device;

a processor; and

one or more associated memories, the one or more associated memories including computer program code executable by the processor, the processor, configured by the computer program code, causes the electronic device to:

process the temperature information to determine a temperature, a change in temperature, a rate of change in temperature, or a combination thereof;

determine a state of the electronic device based, at least in part, on the temperature, the change in temperature, the rate of change in temperature, or a combination thereof;

process the acceleration information to extract features from the acceleration information; and

process the features based on a decision tree analysis to determine a location of the electronic device on the user from a plurality of predefined locations,

wherein the decision tree analysis is based, at least in part, on the state of the electronic device.

2. The electronic device according to claim 1 , wherein the features comprise one or more of a dominant frequency, a frequency range, an acceleration scale, an acceleration range, an energy, and an entropy of the acceleration information.

3. The electronic device according to claim 1 , wherein the temperature sensor is a sub-component of at least one of the one or more accelerometers.

4. The electronic device according to claim 3 , wherein the state is an on-body status of the electronic device on the user.

5. The electronic device according to claim 1 , wherein, in response to determining the location, the processor, configured by the computer program code, causes the electronic device to:

in response to determining the location, process the acceleration information according to one or more location-specific metrics selected based on the location to generate location-specific information.

6. The electronic device according to claim 1 , further comprising:

one or more components,

wherein, in response to determining the location, the processor, configured by the computer program code, causes the electronic device to:

activate at least one of the one or more components based on the location; and

process information generated by the at least one component according to one or more location-specific metrics selected based on the location to generate location-specific information.

7. The electronic device according to claim 1 , wherein the acceleration information is generated continuously, periodically, and/or on demand.

8. The electronic device according to claim 1 , wherein the acceleration information is processed continuously, periodically, and/or on demand, and the features are processed continuously, periodically, and/or on demand.

9. The electronic device according to claim 1 , wherein the processor, configured by the computer program code, causes the electronic device to:

compare the location to one or more previously determined locations of the electronic device on the user; and

validate the determination of the location based on the comparison.

10. The electronic device according to claim 1 , wherein the processor, configured by the computer program code, causes the electronic device to:

configure functionality of the electronic device based on the determined location and one or more location-specific metrics associated with the determined location.

11. The electronic device according to claim 1 , wherein the plurality of predefined locations comprises a chest, an abdomen, an upper arm, a lower arm, a wrist, an upper leg, a lower leg, and an ankle of the user.

12. The electronic device according to claim 1 , wherein the decision tree analysis is generated based on previously determined acceleration information associated with the plurality of predefined locations.

13. A method of determining a location of a wearable device on a user, the method comprising:

measuring temperature information associated with the wearable device based on a temperature sensor within the wearable device;

processing the temperature information to determine a temperature, a change in temperature, a rate of change in temperature, or a combination thereof;

determining a state of the wearable device based, at least in part, on the temperature, the change in temperature, the rate of change in temperature, or a combination thereof;

generating acceleration information based on acceleration experienced by the wearable device;

processing the acceleration information to extract features from the acceleration information; and

processing the features based on a decision tree analysis to determine the location of the wearable device on the user from a plurality of predefined locations,

wherein the decision tree analysis is based, at least in part, on the state of the wearable device.

14. The method according to claim 13 , wherein the features comprise one or more of a dominant frequency, a frequency range, an acceleration scale, an acceleration range, an energy, and an entropy of the acceleration information.

15. The method according to claim 13 , wherein a motion sensor within wearable device generates the acceleration information, and the temperature sensor is a sub-component of the motion sensor.

16. The method according to claim 15 , wherein the state is an on-body status of the wearable device on the user.

17. The method according to claim 13 , further comprising:

in response to determining the location, processing the acceleration information according to one or more location-specific metrics selected based on the location to generate location-specific information.

18. The method according to claim 13 , further comprising:

activating one or more components of the wearable device based on the location; and

processing information generated by the one or more components according to one or more location-specific metrics selected based on the location to generate location-specific information.

19. The method according to claim 13 , wherein the acceleration information is generated continuously, periodically, and/or on demand.

20. The method according to claim 13 , wherein the acceleration information is processed continuously, periodically, and/or on demand, and the features are processed continuously, periodically, and/or on demand.

21. The method according to claim 13 , further comprising:

comparing the location to one or more previously determined locations of the electronic device on the user; and

validating the determination of the location based on the comparison.

22. The method according to claim 13 , further comprising:

configuring functionality of the wearable device based on the determined location and one or more location-specific metrics associated with the determined location.

23. An electronic device worn on a user, the electronic device comprising:

at least two electrical contacts configured to detect an electrical signal at the surface of the user, the electrical signal being an electrocardiogram signal;

an accelerometer configured to generate acceleration information experienced by the at least two electrical contacts;

a processor; and

one or more associated memories, the one or more associated memories including computer program code executable by the processor, the processor, configured by the computer program code, causes the electronic device to:

acquire the electrical signal at the surface of the user through the at least two electrical contacts during detected movement of the electronic device, the user, or a combination thereof based on the acceleration information;

process the acceleration information generated by the accelerometer to determine an orientation of the at least two electrical contacts relative to the user;

determine which limb lead electrocardiogram signal the electrical signal represents based on the orientation; and

configure functionality of the electronic device based on the determined limb lead electrocardiogram signal.

24. The electronic device of claim 23 , wherein an orientation of the at least two electrical contacts of about 0° relative to horizontal represents a Lead I limb lead, an orientation of the at least two electrical contacts of about 60° below horizontal represents a Lead II limb lead, and an orientation of the at least two electrical contacts of about 120° below horizontal represents a Lead III limb lead.

25. The electronic device of claim 23 , wherein the processor, configured by the computer program code, causes the electronic device to:

apply one or more algorithms to the electrical signal based on the determined limb lead.

26. The electronic device of claim 23 , wherein the processor, configured by the computer program code, causes the electronic device to:

acquire the electrical signal, process the acceleration information, or a combination thereof continuously, periodically, and/or on demand.

27. A method of determining a location of a wearable device on a user, the method comprising:

generating one or more physiological and/or biometric parameters of the user with the wearable device;

processing the one or more physiological and/or biometric parameters to extract one or more features;

processing the features to determine the location of the wearable device on the user from a plurality of predefined locations; and

configuring functionality of the wearable device based on the determined location and one or more location-specific metrics associated with the determined location,

wherein the one or more physiological and/or biometric parameters include one or more of heart rate, blood pressure, ECG signals, EMG signals, or EEG signals,

wherein the one or more physiological and/or biometric parameters indicate an ability to detect one or more of the heart rate, the blood pressure, the ECG signals, the EMG signals, or the EEG signals, and

wherein the one or more physiological and/or biometric parameters indicate a strength of one or more of a heart rate signal, a blood pressure signal, the ECG signals, the EMG signals, or the EEG signals.