1. A method for recognizing sign language using at least one electromyogram sensor and at least one gyro sensor, the method comprising: storing a set of Gaussian candidate models for a plurality of fingerspelling motions; grouping the set of Gaussian candidate models into predetermined gyro groups; receiving a first gyro measurement signal from the at least one gyro sensor and a first electromyogram measurement signal from the at least one electromyogram sensor, wherein the at least one gyro sensor and the at least one electromyogram sensor are attached to a body of a subject and wherein the first gyro measurement signal includes a first pitch rotation and a first roll rotation; determining a first gyro group which is in closest proximity to the first gyro measurement signal among the predetermined gyro groups; acquiring a first Gaussian model for the first electromyogram measurement signal; comparing the first Gaussian model with the set of Gaussian candidate models in the first gyro group; determining a first Gaussian candidate model which is in closest proximity to the first Gaussian model, wherein the first Gaussian candidate model is an element of the set of Gaussian candidate models in the first gyro group; and determining a first fingerspelling motion which corresponds to the first Gaussian candidate model.