A method of training a software-based application for a gesture-based access control system, comprising: communicating first training instructions to a user of a mobile device via a human interface device of the mobile device, wherein the training instructions instruct the user to perform a first motion with the mobile device at a first location on the user; performing the first motion with the mobile device at the first location on the user; preprogramming scenario data comprising a user specific model utilizing information received from at least one detection system (46, 48, 50, 130) of the mobile device while the user performs the first motion, wherein the information includes motion data; communicating second training instructions to the user via the human interface device, wherein the second training instructions instruct the user to perform the first motion with the mobile device at the first location on the user with a chosen intentional gesture (25, 94, 99, 140, 334) representative of an intent of the user to gain access to an access assembly; performing the first motion with the mobile device at the first location on the user with the chosen intentional gesture; preprogramming the scenario data utilizing information received from the at least one detection system while the user performs the first motion with the chosen intentional gesture, wherein the information includes motion data; and training, using the scenario data, a machine learning algorithm for gesture recognition, wherein the machine learning algorithm is configured to determine or confirm an intent of the user based on an explicit intent signal generated by the at least one detection system, and to determine user authentication based on the intent signal generated by the at least one detection system and the user specific model. communicating first training instructions to a user of a mobile device via a human interface device of the mobile device, wherein the training instructions instruct the user to perform a first motion with the mobile device at a first location on the user; performing the first motion with the mobile device at the first location on the user; preprogramming scenario data comprising a user specific model utilizing information received from at least one detection system (46, 48, 50, 130) of the mobile device while the user performs the first motion, wherein the information includes motion data; communicating second training instructions to the user via the human interface device, wherein the second training instructions instruct the user to perform the first motion with the mobile device at the first location on the user with a chosen intentional gesture (25, 94, 99, 140, 334) representative of an intent of the user to gain access to an access assembly; performing the first motion with the mobile device at the first location on the user with the chosen intentional gesture; preprogramming the scenario data utilizing information received from the at least one detection system while the user performs the first motion with the chosen intentional gesture, wherein the information includes motion data; and training, using the scenario data, a machine learning algorithm for gesture recognition, wherein the machine learning algorithm is configured to determine or confirm an intent of the user based on an explicit intent signal generated by the at least one detection system, and to determine user authentication based on the intent signal generated by the at least one detection system and the user specific model.