16. The gesture identification system of claim 15 wherein the at least one sensor includes a sensor selected from the group consisting of: a muscle activity sensor, an electromyography (EMG) sensor, a mechanomyography (MMG) sensor, an inertial sensor, an accelerometer, a gyroscope, and an inertial measurement unit (IMU).
15. 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 i th data window in at least a subset of the data windows: determine a window class for the i th 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 a) the window class for the i th data window and, when i>1, b) the window class for at least one j th data window, where j<i; and identify a highest-probability gesture for the i th 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 i th data window; and identify the gesture performed by the user based on the respective highest-probability gestures for at least two data windows in the at least a subset of data windows.