Systems, devices, and methods for gesture identification

A gesture identification system comprising:

• at least one sensor responsive to physical gestures performed by a user of the gesture identification system, wherein in response to a physical gesture performed by the user the at least one sensor provides at least one signal;
• a processor communicatively coupled to the at least one sensor;
• and
• a non-transitory processor-readable storage medium communicatively coupled to the processor, wherein the non-transitory processor-readable storage medium stores processor-executable gesture identification instructions that, when executed by the processor, cause the gesture identification device to:
• segment the at least one signal into data windows;
• for each ith data window in at least a subset of the data windows:
• determine a window class for the ith data window, the window class selected from a library of window classes, wherein each window class in the library of window classes exclusively characterizes at least one data window property;
• determine a respective probability that each gesture in a gesture library is the gesture performed by the user based on the window class for the ith data window;
• and
• identify a highest-probability gesture for the ith data window, the highest-probability gesture corresponding to the gesture in the gesture library that has a highest probability of being the gesture performed by the user for the ith data window;
• and
• identify the gesture performed by the user based on the highest-probability gesture for at least one data window in the at least a subset of data windows.

A method of operating a gesture identification system to identify a user-performed gesture, the gesture identification system including at least one sensor responsive to user-performed gestures and a processor communicatively coupled to the at least one sensor, the method comprising:

• in response to a user-performed gesture, providing at least one signal from the at least one sensor to the processor;
• segmenting the at least one signal into data windows;
• for each data window in at least a subset of the data windows, assigning a window class to the data window by the processor, each respective window class selected by the processor from a library of window classes, wherein each window class in the library of window classes exclusively characterizes at least one data window property;
• determining, by the processor, a respective probability that each gesture in a gesture library is the user-performed gesture based on the window class of at least one data window, wherein determining, by the processor, a respective probability that each gesture in a gesture library is the user-performed gesture includes:
• determining, by the processor and for each gesture in the gesture library, at least one respective transition model based on the window class of a single data window;
• and
• determining, by the processor and for each gesture in the gesture library, a probability that the gesture is the user-performed gesture based at least in part on the at least one transition model for the gesture;
• identifying the user-performed gesture by the processor based at least in part on the window class of at least one data window, wherein identifying the user-performed gesture by the processor includes identifying, by the processor, a highest-probability gesture, the highest-probability gesture corresponding to a gesture in the gesture library that has a highest probability of being the user-performed gesture.

A gesture identification system comprising:

• at least one sensor responsive to physical gestures performed by a user of the gesture identification system, wherein in response to a physical gesture performed by the user the at least one sensor provides at least one signal;
• a processor communicatively coupled to the at least one sensor;
• and
• a non-transitory processor-readable storage medium communicatively coupled to the processor, wherein the non-transitory processor-readable storage medium stores processor-executable gesture identification instructions that, when executed by the processor, cause the gesture identification device to:
• segment the at least one signal into data windows;
• for each data window in at least a subset of the data windows, assign a window class to the data window;
• determine a respective probability that each gesture in a gesture library is the user-performed gesture based on the window class of at least one data window, wherein the processor-executable gesture identification instructions that, when executed by the processor, cause the gesture identification device to determine a respective probability that each gesture in a gesture library is the user-performed gesture, cause the gesture identification device to:
• determine, for each gesture in the gesture library, at least one respective transition model based on the window class of a single data window;
• and
• determine, for each gesture in the gesture library, a probability that the gesture is the user-performed gesture based at least in part on the at least one transition model for the gesture;
• and
• identify the physical gesture performed by the user based at least in part on the window class of at least one data window, wherein the processor-executable gesture identification instructions that, when executed by the processor, cause the gesture identification device to identify the physical gesture performed by the user based at least in part on the window class of at least one data window, cause the gesture identification device to identify a highest-probability gesture, the highest-probability gesture corresponding to a gesture in the gesture library that has a highest probability of being the user-performed gesture.