Technologies for micro-motion-based input gesture control of wearable computing devices

Patent metadata

Field	Value
Publication number	US-10585489-B2
Application number	US-201515576493-A
Country	US
Kind code	B2
Filing date	Jun 26, 2015
Priority date	Jun 26, 2015
Publication date	Mar 10, 2020
Grant date	Mar 10, 2020

Abstract

Technologies for detecting micro-motion based input gestures include a wrist-wearable computing device that includes sensors from which values for micro-motion states can be determined. Each micro-motion state is indicative of a motion-related characteristic of the wrist-wearable computing device that is used to determine whether a sequence of detected gesture steps matches an input gesture model associated with an input gesture. The input gesture model defines a required sequence of required gesture steps from which an input gesture may be determined.

First claim

The invention claimed is:

1. A wrist-wearable computing device to detect micro-motion states of an input gesture, the wrist-wearable computing device comprising:
a micro-motion detection circuit to (i) receive sensor data from one or more sensors of the wrist-wearable computing device, (ii) determine a present value for each of a plurality of micro-motion states based on the received sensor data, wherein each of the micro-motion states is indicative of a motion-related characteristic of the wrist-wearable computing device, wherein to determine a present value for each of a plurality of micro-motion states comprises to classify, for each of the plurality of micro-motion states, the corresponding micro-motion state into one of a plurality of pre-defined micro-motion state values, wherein the plurality of micro-motion states includes a linear motion micro-motion state, (iii) determine a present gesture step of a plurality of gesture steps based on the present values of the micro-motion states, and (iv) append the present gesture step to a sequence of detected gesture steps, wherein the sequence of detected gesture steps includes one or more previously detected gesture steps, and wherein each of the previously detected gesture steps is defined by associated previous values for each of the plurality of micro-motion states; and
an input gesture recognition circuit to determine whether the sequence of detected gesture steps matches an input gesture model associated with an input gesture, wherein the input gesture model defines a required sequence of required gesture steps.

2. The wrist-wearable computing device of claim 1 , wherein to determine whether the sequence of detected gesture steps matches the input gesture model comprises to compare, in sequential order, each detected gesture step of the sequence of detected gesture steps to a corresponding required gesture step of the required sequence of required gesture steps.

3. The wrist-wearable computing device of claim 1 , wherein the micro-motion detection circuit is further to (i) determine a subsequent value for each of the plurality of micro-motion states based on the sensor data in response to a determination by the input gesture recognition circuit that the sequence of detected gesture steps matches at least a portion of at least one input gesture model of a plurality of input gesture models, (ii) determine a subsequent gesture step of the plurality of gesture steps based on the subsequent values of the micro-motion states, (iii) append the subsequent gesture step to the sequence of detected gesture steps to generate an updated sequence of detected gesture steps, and
wherein the input gesture recognition circuit is further to determine whether the updated sequence of detected gesture steps matches the input gesture model associated with the input gesture.

4. The wrist-wearable computing device of claim 1 , wherein the micro-motion detection circuit is further to update the sequence of detected gesture steps in response to a determination by the input gesture recognition circuit that the sequence of detected gesture steps does not match at least a portion of at least one input gesture model of a plurality of input gesture models, wherein each input gesture model of the plurality of input gesture models defines a corresponding required sequence of required gesture steps.

5. The wrist-wearable computing device of claim 1 , wherein to receive sensor data from the one or more sensors of the wrist-wearable computing device comprises to receive the sensor data from at least one of an accelerometer of the wrist-wearable computing device, a gyroscope of the wrist-wearable computing device, and a magnetometer of the wrist-wearable computing device.

6. The wrist-wearable computing device of claim 1 , wherein to determine the present value for each of the micro-motion states of the plurality of micro-motion states comprises determining a present value for at least one of a motion micro-motion state, an orientation micro-motion state, a rotation micro-motion state, an impact micro-motion state, and a shaking micro-motion state.

7. The wrist-wearable computing device of claim 6 , wherein to determine the present value for the rotation micro-motion state comprises to determine a present value for at least one of a first rotation along an x-axis, a second rotation along a y-axis, and a third rotation along a z-axis.

8. The wrist-wearable computing device of claim 6 , wherein to determine the present value for the linear motion micro-motion state comprises to determine a present value for at least one of a first linear motion micro-motion state corresponding to an x-axis, a second linear motion micro-motion state corresponding to a y-axis, and a third linear motion micro-motion state corresponding to a z-axis.

9. The wrist-wearable computing device of claim 1 , wherein to determine the present value comprises to determine at least one of a movement, an orientation, a rotation, and a direction relative to a three-dimension axis.

10. The wrist-wearable computing device of claim 1 , wherein the input gesture model defines a maximum amount of time that may elapse between each of the required gesture steps.

11. The wrist-wearable computing device of claim 1 , wherein the input gesture recognition circuit is configured to:
receive a new input gesture model; and
add the new input gesture model to the input gesture recognition circuit.

12. The wrist-wearable computing device of claim 1 , wherein to determine the present value for each of the plurality of micro-motion states comprises to classify, for each of the plurality of micro-motion states, the corresponding micro-motion state into one of a plurality of pre-defined linear motion micro-motion state values,
wherein the plurality of pre-defined linear motion micro-motion state values correspond to no linear motion, a slow linear motion, and a fast linear motion.

13. The wrist-wearable computing device of claim 1 , wherein the plurality of micro-motion states comprises a finger snap state or an impact state.

14. The wrist-wearable computing device of claim 1 , wherein the plurality of micro-motion states comprises a front hand double knock or back hand double knock.

15. One or more non-transitory computer-readable storage media comprising a plurality of instructions stored thereon that in response to being executed cause a wrist-wearable computing device to:
receive sensor data from one or more sensors of the wrist-wearable computing device;
determine a present value for each of a plurality of micro-motion states based on the received sensor data, wherein each of the micro-motion states is indicative of a motion-related characteristic of the wrist-wearable computing device, wherein to determine a present value for each of a plurality of micro-motion states comprises to classify, for each of the plurality of micro-motion states, the corresponding micro-motion state into one of a plurality of pre-defined micro-motion state values, wherein the plurality of micro-motion states includes a linear motion micro-motion state;
determine a present gesture step of a plurality of gesture steps based on the present values of the micro-motion states;
append the present gesture step to a sequence of detected gesture steps, wherein the sequence of detected gesture steps includes one or more previously detected gesture steps, and wherein each of the previously detected gesture steps is defined by associated previous values for each of the plurality of micro-motion states; and
determine whether the sequence of detected gesture steps matches an input gesture model a

Assignees

• Intel Corp

Inventors

• Han Ke
• Ren Jinkui
• Wang Xun
• Ma Lili

Classifications

• G06F3/014 Primary

  Hand-worn input/output arrangements, e.g. data gloves · CPC title

• G06F1/163

  Wearable computers, e.g. on a belt · CPC title

• G06F3/0346

  with detection of the device orientation or free movement in a three-dimensional [3D] space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors · CPC title

• G06F3/017 Primary

  Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883) · CPC title