Hearing devices with proactive power management

Patent metadata

Field	Value
Publication number	US-10834510-B2
Application number	US-201816156464-A
Country	US
Kind code	B2
Filing date	Oct 10, 2018
Priority date	Oct 10, 2018
Publication date	Nov 10, 2020
Grant date	Nov 10, 2020

Abstract

Systems and methods for hearing devices with proactive power management are provided. Various embodiments dynamically adapt power consumption to the preferences, needs, and behavior of the hearing device user such that the hearing device provides function until the hearing device can be recharged. Moreover, some embodiments exploit the trend of more intelligent devices and machine learning to create dynamic power management schedules which can be temporarily implemented to create an optimal blend of performance versus battery life while minimizing perception of the feature or performance reduction to the user. Moreover, the dynamic nature of the power management used in various embodiments can account for battery degradation, updated firmware, and/or other factors that may impact battery life as the hearing device ages.

First claim

What is claimed is:

1. A method for proactive power management of a hearing device, the method comprising:
predicting a duration of time until a refreshing of a battery in the hearing device;
estimating a remaining usage time of the battery in the hearing device;
modifying, when the duration of time until the refreshing is greater than the remaining usage time, an operational characteristic of the hearing device to increase the remaining usage time of the battery in the hearing device;
predicting an updated duration of time until the refreshing of the battery in the hearing device;
estimating an updated remaining usage time of the battery in the hearing device; and
restoring, when the updated duration of time until refreshing is less than the updated remaining usage time, the operational characteristic previously modified to increase performance in the hearing device.

2. The method of claim 1 , wherein predicting the duration of time until the refreshing of the battery in the hearing device is based, at least in part, on one or more of user preferences, historical usage patterns of the hearing device, current location, or calendar entries.

3. The method of claim 1 , further comprising developing an anticipated usage pattern of the hearing device during the duration of time, wherein estimating the remaining usage time of the battery in the hearing device is based, at least in part, on the anticipated usage pattern of the hearing device during the duration of time.

4. The method of claim 1 , wherein estimating the remaining usage time of the battery in the hearing device is based on hardware and software configurations of the hearing device.

5. The method of claim 1 , further comprising:
receiving a prioritization schedule that ranks available operational characteristics of the hearing device from a perspective of a user; and
selecting, from the prioritization schedule, the operational characteristic having a ranking indicative of lowest importance to the user.

6. The method of claim 1 , wherein modifying the operational characteristic includes performing at least one of an adaptation and a functionality adaptation.

7. The method of claim 6 , wherein the performance adaptation includes at least one of a reduction in an amount of sound amplification, a reduction in bandwidth of an amplified signal, a shift in the bandwidth of the amplified signal, a change in an audio codec type, and a reduction of frequency of monitoring sensors.

8. The method of claim 6 , wherein the functionality adaptation includes at least one of a reduction in wireless functionality, a reduction in supported wireless protocols, and a reduction in monitoring for a presence of an inductive loop.

9. The method of claim 1 , further comprising:
creating a wireless connection between the hearing device and a mobile computing device; and
off-loading one or more operational characteristics of the hearing device to the mobile computing device.

10. The method of claim 1 , wherein the battery is a rechargeable battery and the refreshing of the battery includes recharging, and wherein the method further comprising restoring, after a recharging cycle of the rechargeable battery, the operational characteristic of the hearing device to a previous state.

11. A hearing device capable of optimizing battery life, the hearing device comprising:
a processor;
a rechargeable battery;
a wireless communication component configured to communicate with an external computing device;
a proactive power manager to dynamically adjust one or more operational characteristics of the hearing device to minimize a difference between a predicted time until an initiation of a recharge cycle of the rechargeable battery and an estimate of remaining usage time; and
a power learning profile module to track short-term and long-term activity and develop a usage profile indicative of usage of the hearing device.

12. The hearing device of claim 11 , wherein the estimate of remaining usage time is based, at least in part on, hardware and software configurations of the hearing device, performance of the hearing device, and user behavior.

13. The hearing device of claim 11 , wherein the operational characteristics include one or more functionality adaptations and the proactive power manager is configured to off-load at least some of the one or more functional adaptations to the external computing device.

14. The hearing device of claim 11 , wherein the external computing device generates the predicted time until initiation of the recharge cycle is based, at least in part, on one or more of user preferences, historical usage patterns of the hearing device, current location, or calendar entries.

15. The hearing device of claim 14 , wherein the external computing device uses machine learning to generate at least one of the predicted time until initiation of the recharge cycle and the estimate of remaining usage time.

16. A method for proactive power management of a hearing device, the method comprising:
establishing a communication link between an external computing device and the hearing device;
estimating a date and time the hearing device is predicted to begin a recharge cycle;
generating a predicted time until initiation of the recharge cycle using a machine learning model based on device hardware, software configurations, and anticipated usage levels until the date and time the hearing device is precited to begin the recharge cycle; and
generating an adaption profile that when implemented will temporarily modify one or more operational characteristics to minimize a difference between the time until a next recharge cycle and a remaining usage time of a battery in the hearing device.

17. The method of claim 16 , further comprising transmitting the adaptation profile to the hearing device using the communication link.

18. The method of claim 16 , wherein estimating the date and time the hearing device is predicted to begin the recharge cycle is based, at least in part on, user preferences, usage patterns, current location, and calendar entries.

19. The method of claim 16 , wherein the one or more operational characteristics includes a reduction in an amount of sound amplification, reduction or shift in bandwidth of an amplified signal, a change in a codec type, a reduction of frequency of monitoring sensors, a reduction in wireless functionality, a reduction in supported wireless protocols, or a reduction in monitoring for a presence of an inductive loop.

20. A hearing device capable of optimizing non-rechargeable battery life, the hearing device comprising:
a processor;
a non-rechargeable battery;
a wireless communication component configured to communicate with an external computing device;
a proactive power manager to dynamically adjust one or more operational characteristics of the hearing device to minimize a difference between a predicted time until replacement of the non-rechargeable battery and an estimate of remaining usage time; and
a power learning profile module to track short-term and long-term activity and develop a usage profile indicative of usage of the hearing device.

21. The hearing device of claim 20 , wherein the one or more operational characteristics include one or more functionality adaptations and the proactive power manager is configured to off-load at least some of the one or more functional adaptations to the external computing device.

22. The hearing device of claim 20 , wherein the external computing dev

Assignees

• Sonova Ag

Inventors

• Gehring Stephan
• Feilner Manuela

Classifications

• H04R2460/03

  Aspects of the reduction of energy consumption in hearing devices · CPC title

• H04R25/552

  Binaural · CPC title

• G06N20/00

  Machine learning · CPC title

• H04R25/305 Primary

  Self-monitoring or self-testing · CPC title

• H04R25/554

  using a wireless connection, e.g. between microphone and amplifier or using Tcoils · CPC title