Context Aware Fall Detection Using a Mobile Device

1 . A method comprising:

receiving, by a mobile device, sensor data obtained by one or more sensor over a time period, wherein the one or more sensors are worn by a user;

determining, by the mobile device, a context of the user based on the sensor data;

obtaining, by the mobile device based on the context, a set of rules for processing the sensor data, wherein the set of rules is specific to the context;

determining, by the mobile device, at least one of a likelihood that the user has fallen or a likelihood that the user requires assistance based on the sensor data and the set of rules; and

generating, by the mobile device, one or more notifications based on at least one of the likelihood that the user has fallen or the likelihood that the user requires assistance.

2 . The method of claim 1 , wherein the sensor data comprises location data obtained by one or more location sensors of the mobile device.

3 . The method of claim 1 , wherein the sensor data comprises acceleration data obtained by one or more acceleration sensors of the mobile device.

4 . The method of claim 1 , wherein the sensor data comprises orientation data obtained by one or more orientation sensors of the mobile device.

5 . The method of claim 1 , the context corresponds to the user bicycling during the time period.

6 . The method of claim 5 , wherein determining the likelihood that the user has fallen and/or the likelihood that the user requires assistance comprises:

determining, based on the sensor data, that a distance traveled by the user prior over the period of time is greater than a first threshold value,

determining, based on the sensor data, that a variation in a direction of impacts experienced by the user over the period of time is less than a second threshold value,

determining, based on the sensor data, that a rotation of the user's wrist over the period of time is less than a third threshold value, and

determining that the user has fallen and/or requires assistance based on the determination that the distance traveled by the user prior over the period of time is greater than the first threshold value, the determination that the variation in a direction of impacts experienced by the user over the period of time is less than the second threshold value, and the determination that the rotation of the user's wrist over the period of time is less than the third threshold value.

7 . The method of claim 5 , wherein determining the likelihood that the user has fallen and/or the likelihood that the user requires assistance comprises:

determining, based on the sensor data, that a magnitude of an impact experienced by the user over the period of time in a first direction is greater than a first threshold value, and

determining that the user has fallen and/or requires assistance based on the determination that the magnitude of the impact experienced by the user over the period of time in the first direction is greater than the first threshold value.

8 . The method of claim 5 , wherein determining the likelihood that the user has fallen and/or the likelihood that the user requires assistance comprises:

determining, based on the sensor data, that a change in an orientation of the user's hand over the period of time is greater than a first threshold value,

determining, based on the sensor data, that a magnitude of an impact experienced by the user over the period of time in a first direction is greater than a second threshold value, wherein the first direction is orthogonal to the second threshold value, and

determining, based on the sensor data, that a magnitude of an impact experienced by the user over the period of time in a second direction is greater than a third threshold value,

determining that the user has fallen and/or requires assistance based on the determination that the change in an orientation of the user's hand over the period of time is greater than the first threshold value, the determination that the magnitude of the impact experienced by the user over the period of time in the first direction is greater than the second threshold value, and the determination that the magnitude of an impact experienced by the user over the period of time in the second direction is greater than the third threshold value.

9 . The method of claim 5 , further comprising:

receiving, by the mobile device, second sensor data obtained by the one or more sensor over a second time period;

determining, by the mobile device, a second context of the user based on the second sensor data;

obtaining, by the mobile device based on the second context, a second set of rules for processing the sensor data, wherein the second set of rules is specific to the second context;

determining, by the mobile device, at least one of a likelihood that the user has fallen and/or a likelihood that the user requires assistance based on the sensor data and the second set of rules; and

generating, by the mobile device, one or more second notifications based on at least one of the likelihood that the user has fallen or the likelihood that the user requires assistance.

10 . The method of claim 1 , wherein the second context corresponds to the user walking during the second time period.

11 . The method of claim 1 , wherein the second context corresponds to the user playing at least one of basketball or volleyball during the second time period.

12 . The method of claim 1 , wherein generating the one or more notifications comprises:

transmitting a first notification to a communications device remote from the mobile device, the first notification comprising an indication that the user has fallen.

13 . The method of claim 12 , wherein the communications device is an emergency response system.

14 . The method of claim 1 , wherein the mobile device is a wearable mobile device.

15 . The method of claim 1 , wherein at least some of the one or more sensors are disposed on or in the mobile device.

16 . The method of claim 1 , wherein at least some of the one or more sensors are remote from the mobile device.

17 . A system comprising:

one or more sensors;

one or more processors; and

one or more non-transitory computer readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving sensor data obtained by the one or more sensor over a time period, wherein the one or more sensors are worn by a user;

determining a context of the user based on the sensor data;

obtaining, based on the context, a set of rules for processing the sensor data, wherein the set of rules is specific to the context;

determining at least one of a likelihood that the user has fallen or a likelihood that the user requires assistance based on the sensor data and the set of rules; and

generating one or more notifications based on at least one of the likelihood that the user has fallen or the likelihood that the user requires assistance.

18 . One or more non-transitory computer readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

receiving sensor data obtained by the one or more sensor over a time period, wherein the one or more sensors are worn by a user;

determining a context of the user based on the sensor data;

obtaining, based on the context, a set of rules for processing the sensor data, wherein the set of rules is specific to the context;

determining at least one of a likelihood that the user has fallen or a likelihood that the user requires assistance based on the sensor data and the set of rules; and

generating one or more notifications based on at least one of the likelihood that the user has fallen or the likelihood that the user requires assistance.