Sedentary period detection utilizing a wearable electronic device

• US 10,497,246 B2
• Filed: 08/07/2017
• Issued: 12/03/2019
• Est. Priority Date: 01/15/2013
• Status: Active Grant

• Current Assignee: Fitbit, Inc. (Alphabet Inc.)
• Original Assignee: Fitbit, Inc. (Alphabet Inc.)
• Inventors: Arnold, Jacob Antony, Russell, Allison Maya, Wasson, II, Zachariah Lord, Yuen, Shelten Gee Jao
• Primary Examiner(s): Luan, Scott
• Application Number:
  US15/671,063
• Publication Number:
  US 20180061204A1
• Time in Patent Office: 848 Days
• CPC Class Codes: A61B 2560/0209 adapted for power saving
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0533 Measuring galvanic skin response
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• 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 5/222 combined with detection or measurement of physiological parameters, e.g. heart rate
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: G01C 22/006 Pedometers
• CPC Class Codes: G08B 21/0415 detecting absence of activity per se
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/40 : relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 40/63 : for local operation

Abstract

Systems and methods for determining a sedentary state of a user are described. Sensor data is collected and analyzed to calculate metabolic equivalent of task (MET) measures for a plurality of moments of interest. Based on the MET measures and a time period for which the MET measures exceed a threshold value, it is determined whether the user is in a sedentary state. If the user is in the sedentary state, the user is provided a notification to encourage the user to perform a non-sedentary activity.

Claims

1. An electronic device, comprising:

a communication device configured to communicate with a wearable device including one or more biometric sensors configured to generate samples of biometric information for a plurality of moments of interest;

at least one processor; and

a memory storing computer-executable instructions for controlling the at least one processor to;

receive, via the communication device, the samples from the wearable device,

compare the samples for each of the moments of interest to a first predetermined threshold,

classify the samples for each of the moments of interest into at least a sedentary status or a non-sedentary status based on the comparison,

determine a first time period for which a defined number of consecutive samples have been classified into the sedentary status,

classify the first time period as having a sedentary state in response to determining that the first time period is greater than a first threshold time period;

send an indication to the wearable device that the first time period is classified as having a sedentary state, wherein the wearable device is configured to present a notification in response to the indication;

determine a time of day when the notification was presented;

determine, based on the samples, that a second time period following presentation of the notification is classified as having the sedentary state; and

send instructions to the wearable device via the communication device to not present subsequent notifications responsive to further indications of time periods that have been classified as having the sedentary state and during a window of time corresponding to the time of day when the notification was presented.

2. The electronic device of claim 1, wherein the memory further stores computer-executable instructions for controlling the at least one processor to:

send to the wearable device via the communication device the notification for presentation by the wearable device, and

wherein the notification includes a message recommending ending of the sedentary state.

3. The electronic device of claim 1, wherein the memory further stores computer-executable instructions for controlling the at least one processor to:

detect a third time period for which a number of consecutive samples have been classified into the non-sedentary status,

determine that the third time period is greater than a second threshold time period, and

classify the third time period as having a non-sedentary state upon determining that the third time period is greater than the second threshold time period.

4. The electronic device of claim 3, wherein the memory further stores computer-executable instructions for controlling the at least one processor to:

determine that the third time period is contiguous with a time period that has been classified as having the sedentary state,

identify a transition from the sedentary state to the non-sedentary state upon determining that the third time period is contiguous with the time period that has been classified as having the sedentary state, and

send to the wearable device via the communication device a second notification including a motivational message for display via the wearable device upon identifying the transition from the sedentary state to the non-sedentary state.

5. The electronic device of claim 1, wherein the memory further stores computer-executable instructions for controlling the at least one processor to:

determine that values of the samples for a group of consecutive moments of interest are each greater than the first predetermined threshold and each less than a second predetermined threshold, the second predetermined threshold being higher than the first predetermined threshold,

determine that a value of one of the samples for a moment of interest preceding the group of consecutive moments of interest is classified as having the sedentary status,

determine that a value of one of the samples for a moment of interest subsequent to the group of consecutive moments of interest is classified as having the sedentary status, and

classify each of the samples for the group of consecutive moments of interest as having the sedentary status.

6. The electronic device of claim 5, wherein the memory further stores computer-executable instructions for controlling the at least one processor to:

determine that a size of the group of consecutive moments of interest is less than a size threshold prior to classifying each of the samples for the group of consecutive moments of interest as having the sedentary status.

7. The electronic device of claim 5, wherein each of the samples is classified as having the sedentary status, the non-sedentary status, or an asleep status.

8. A method, comprising:

receiving, via a communication device, samples of biometric information for a plurality of moments of interest from a wearable device, the wearable device comprising one or more biometric sensors configured to generate the samples;

comparing, via a processor, the samples for each of the moments of interest to a first predetermined threshold;

classifying the samples for each of the moments of interest into at least a sedentary status or a non-sedentary status based on the comparison of the samples;

determining a first time period for which a defined number of consecutive samples have been classified into the sedentary status;

classifying the first time period as having a sedentary state in response to determining that the first time period is greater than a first threshold time period;

sending an indication to the wearable device that the first time period is classified as having the sedentary state, wherein the wearable device is configured to present a notification in response to the indication;

determining a time of day when the notification was presented;

determining, based on the samples, that a second time period following presentation of the notification is classified as having the sedentary state; and

sending instructions to the wearable device via the communication device to not present subsequent notifications responsive to further indications of time periods that have been classified as having the sedentary state and during a window of time corresponding to the time of day when the notification was presented.

9. The method of claim 8, further comprising:

sending to the wearable device via the communication device the notification for presentation by the wearable device,

wherein the notification includes a message recommending ending of the sedentary state, and

wherein the communication device is configured to send the notification at another time of the day.

10. The method of claim 8, further comprising:

detecting a third time period for which a number of consecutive samples have been classified into the non-sedentary status;

determining that the third time period is greater than a second threshold time period; and

classify the third time period as having a non-sedentary state upon determining that the third time period is greater than the second threshold time period.

11. The method of claim 10, further comprising:

determining that the third time period is contiguous with a time period that has been classified as having the sedentary state;

identifying a transition from the sedentary state to the non-sedentary state upon determining that the third time period is contiguous with the time period that has been classified as having the sedentary state; and

sending to the wearable device via the communication device a second notification including a motivational message for display via the wearable device upon identifying the transition from the sedentary state to the non-sedentary state.

12. The method of claim 8, further comprising:

determining that values of the samples for a group of consecutive moments of interest are each greater than the first predetermined threshold and each less than a second predetermined threshold, the second predetermined threshold being higher than the first predetermined threshold,

determining that a value of one of the samples for a moment of interest preceding the group of consecutive moments of interest is classified as having the sedentary status,

determining that a value of one of the samples for a moment of interest subsequent to the group of consecutive moments of interest is classified as having the sedentary status, and

classifying each of the samples for the group of consecutive moments of interest as having the sedentary status.

13. The method of claim 12, further comprising:

determining that a size of the group of consecutive moments of interest is less than a size threshold prior to the classifying each of the samples for the group of consecutive moments of interest as having the sedentary status.

14. The method of claim 12, wherein each of the samples is classified as having the sedentary status, the non-sedentary status, or an asleep status.

15. A device comprising:

one or more processors; and

a memory storing a first configuration parameter, a second configuration parameter, and computer-executable instructions that, when executed, cause the one or more processors to;

receive activity data generated by a wearable electronic device indicative of activity of a user of the wearable electronic device,

determine, based on the activity data, a state of the user for each period of time of a plurality of periods of time,

generate a first message based on the states of the user and the first configuration parameter, the first message being a first type of notification,

communicate, via an output device, the first message to the user,

generate a second message based on the states of the user and the second configuration parameter, the second message being a second type of notification different from the first type of notification,

communicate, via the output device, the second message to the user,

determine whether the communication of the first message to the user or the communication of the second message to the user resulted in a greater change of the state of the user, and

change the first and second configuration parameters based on the determination of whether the communication of the first message to the user or the communication of the second message to the user resulted in the greater change of the state of the user.

16. The device of claim 15, wherein:

the change in the state of the user is from a sedentary state to a non-sedentary state,

the memory further stores computer-executable instructions that, when executed, cause the one or more processors to

change, responsive to determining that the communication of the first message to the user resulted in the greater change of the state of the user, the first configuration parameter to increase a rate of generating the first message and the second configuration parameter to decrease a rate of generating the second message.

17. The device of claim 16, wherein the memory further stores computer-executable instructions that, when executed, cause the one or more processors to:

determine that the state of the user has changed from the sedentary state to the non-sedentary state, and

communicate, via the output device, the first message in response to determining that the state of the user has changed from the sedentary state to the non-sedentary state.

18. The device of claim 15, wherein the memory further stores computer-executable instructions that, when executed, cause the one or more processors to:

determine that the state of the user has remained in a sedentary state for a number of periods of time greater than a threshold number of periods of time, and

communicate, via the output device, the second message in response to determining that the state of the user has remained in the sedentary state for the number of periods of time greater than the threshold number of periods of time.

19. The device of claim 15, wherein the memory further stores a third configuration parameter and computer-executable instructions that, when executed, cause the one or more processors to:

determine, based on the state of the user, progress towards an activity goal,

communicate, via the output device, a third message to the user indicative of the progress towards the activity goal and based on the third configuration parameter,

determine, based on the states of the user, whether the communication of the third message to the user resulted in a greater change of state of the user than the communication of the first and second messages to the user, and

change the third configuration parameter based on the determination that the communication of the third message resulted in the greater change of state of the user than the communication of the first and second messages to the user.

20. The device of claim 15, wherein the first message comprises a motivational message for display via the wearable electronic device.