SYSTEM AND METHOD FOR ACTIVITY DETERMINATION

1 . A device comprising:

one or more sensors configured to detect acceleration;

one or more physical computer processors configured to at least:

obtain acceleration data from the one or more sensors for a time interval;

determine that the acceleration data is not indicative of a non-step-related activity;

average the acceleration data for the time interval to obtain a mean acceleration vector;

project the mean acceleration vector on a gravity acceleration vector to obtain a projection;

identify a peak using a derivative based at least partly on the projection; and

determine that a user of the device has taken a step based at least partly on the identified peak.

2 . The device of claim 1 , wherein the one or more computer processors are configured to determine that the acceleration data is not indicative of a non-step-related activity by extracting one or more features from the acceleration data and analyzing the features to determine whether they correspond to features of data associated with a non-step-related activity.

3 . The device of claim 1 , wherein the non-step-related activity comprises driving, eating, brushing teeth, or sleeping.

4 . The device of claim 1 , wherein the one or more computer processors are configured to determine that the acceleration data is not indicative of a non-step-related activity by analyzing the acceleration data with respect to data associated with mechanical vibrations.

5 . The device of claim 1 , wherein the one or more computer processors are further configured to determine whether a number of peaks identified in a window of time exceeds a threshold.

6 . The device of claim 1 , wherein the one or more sensors comprises a 3-axis accelerometer.

7 . The device of claim 1 , wherein the one or more processors are further configured to obtain data from a plurality of sensors.

8 . The device of claim 7 , wherein the plurality of sensors comprises an accelerometer and a gyroscope.

9 . The device of claim 1 , wherein the one or more processors are configured to at least:

identify a plurality of steps during a time window;

determine that the user is performing a stepping activity when the plurality of steps during the time window are above a threshold number; and

determine that the user is not performing a stepping activity when the plurality of steps during the time window are not above the threshold number.

10 . Non-transitory computer-readable storage storing executable instructions that cause one or more computer processors to perform a process comprising:

obtaining acceleration data for a first time interval;

determining that the acceleration data is indicative of an active state of a user;

averaging the acceleration data for the first time interval to obtain a mean acceleration vector;

projecting the mean acceleration vector on a gravity acceleration vector to obtain a projection;

identifying a peak using a derivative based at least partly on the projection; and

determining that the user has taken a step based at least partly on the identified peak.

11 . The non-transitory computer-readable medium of claim 10 , wherein determining that the acceleration data is indicative of an active state of a user comprises using a classification model trained to detect a signature of user activity in acceleration data.

12 . The non-transitory computer-readable medium of claim 10 , wherein the process further comprises:

obtaining acceleration data for a second time interval;

determining that the acceleration data is indicative of an inactive state of a user;

changing a rate at which acceleration data is sampled for a third time interval.

13 . The non-transitory computer-readable medium of claim 12 , wherein the process further comprises:

obtaining acceleration data for the third time interval;

determining that a movement magnitude represented by the acceleration data fails to exceed an idle state threshold; and

determining that the user is sleeping based at least partly on the determination that the movement magnitude fails to exceed the idle state threshold.

14 . The non-transitory computer-readable medium of claim 12 , wherein the process further comprises:

obtaining acceleration data for the third time interval;

determining that a movement magnitude represented by the acceleration data exceeds an idle state threshold; and

determining that the user is not sleeping based at least partly on the determination that the movement magnitude exceeds the idle state threshold.

15 . The non-transitory computer-readable medium of claim 12 , wherein the process further comprises:

obtaining acceleration data for the third time interval;

determining that a movement magnitude represented by the acceleration data fails to exceed a sleeping state threshold; and

determining that the acceleration for the third time interval is indicative of non-use.

16 . A system comprising:

one or more sensors configured to detect acceleration;

one or more computer processors configured to at least:

obtain acceleration data from the one or more sensors for a first time interval;

determine that the acceleration data for the first time interval is indicative of an active state of a user;

obtain acceleration data from the one or more sensors for a second time interval;

determine that the acceleration data for the second time interval is indicative of an inactive state of a user; and

change a rate at which acceleration data is sampled for a third time interval.

17 . The system of claim 16 , wherein the one or more computer processors are configured to determine that the acceleration data is indicative of an active state of a user comprises using a classification model trained to detect a signature of user activity in acceleration data.

18 . The system of claim 16 , wherein the one or more computer processors are configured to at least:

average the acceleration data for the first time interval to obtain a mean acceleration vector;

project the mean acceleration vector on a gravity acceleration vector to obtain a projection;

identify a peak using a derivative based at least partly on the projection; and

determine that the user has taken a step based at least partly on the identified peak.

19 . The system of claim 16 , wherein the one or more computer processors are further configured to at least:

obtain acceleration data for the third time interval;

determine that a movement magnitude represented by the acceleration data fails to exceed an idle state threshold; and

determine that the user is sleeping based at least partly on the determination that the movement magnitude fails to exceed the idle state threshold.

20 . The system of claim 16 , wherein the one or more computer processors are further configured to at least:

obtain acceleration data for the third time interval;

determine that a movement magnitude represented by the acceleration data exceeds an idle state threshold; and

determine that the user is not sleeping based at least partly on the determination that the movement magnitude exceeds the idle state threshold.

21 . The system of claim 16 , wherein the one or more computer processors are further configured to at least:

obtain acceleration data for the third time interval;

determine that a movement magnitude represented by the acceleration data fails to exceed a sleeping state threshold; and

determine that the acceleration for the third time interval is indicative of non-use.

22 . The system of claim 16 , wherein the one or more processors are configured to at least:

identify a plurality of steps during a time window;

determine that the user is performing a stepping activity when the plurality of steps during the time window are above a threshold number; and

determine that the user is not performing a stepping activity when the plurality of steps during the time window are not above the threshold number.