A neural monitoring system for detecting an artificially-induced mechanical response of a muscle to a stimulus provided within an intracorporeal treatment area of a human subject, the intracorporeal treatment area including a nerve that innervates the muscle, the neural monitoring system comprising: a non-invasive mechanical sensor (22, 22a, 22b, 22c, 22d) configured to be placed in mechanical communication with the muscle and to generate a mechanomyography output signal that corresponds to a sensed mechanical movement of the muscle; a stimulator configured to provide a periodic stimulus within the intracorporeal treatment area, the periodic stimulus including at least a first stimulus beginning at a first time,T 1, and a second, consecutive stimulus beginning at a second time,T 2; and a processor in communication with the mechanical sensor and the stimulator, the processor configured to: provide the periodic stimulus to the stimulator; receive the mechanomyography output signal from the mechanical sensor; analyze a response window (102, 154, 174) of the mechanomyography output signal to determine if the first stimulus induced a response of the muscle; and provide an indication to a user if it is determined that the first stimulus induced a response of the muscle within the response window; wherein the response window corresponds to a period of time when an induced response to the first stimulus is likely to occur; characterized in that the response window extends between a third time, T 3, and a fourth time, T 4, such that T 1 ≤ T 3 < T 4 < T 2; and in that the processor is further configured to determine if the first stimulus induced a response of the muscle by examining one or more characteristics of the mechanomyography output signal within the response window using a supervised learning algorithm; and wherein the supervised learning algorithm is operative to classify the response window into one of a plurality of classifications comprising: the response window is representative of an artificially-induced mechanical response of the muscle; and the response window is not representative of an artificially-induced mechanical response of the muscle. a non-invasive mechanical sensor (22, 22a, 22b, 22c, 22d) configured to be placed in mechanical communication with the muscle and to generate a mechanomyography output signal that corresponds to a sensed mechanical movement of the muscle; a stimulator configured to provide a periodic stimulus within the intracorporeal treatment area, the periodic stimulus including at least a first stimulus beginning at a first time,T 1, and a second, consecutive stimulus beginning at a second time,T 2; and a processor in communication with the mechanical sensor and the stimulator, the processor configured to: provide the periodic stimulus to the stimulator; receive the mechanomyography output signal from the mechanical sensor; analyze a response window (102, 154, 174) of the mechanomyography output signal to determine if the first stimulus induced a response of the muscle; and provide an indication to a user if it is determined that the first stimulus induced a response of the muscle within the response window; wherein the response window corresponds to a period of time when an induced response to the first stimulus is likely to occur; characterized in that the response window extends between a third time, T 3, and a fourth time, T 4, such that T 1 ≤ T 3 < T 4 < T 2; and in that the processor is further configured to determine if the first stimulus induced a response of the muscle by examining one or more characteristics of the mechanomyography output signal within the response window using a supervised learning algorithm; and wherein the supervised learning algorithm is operative to classify the response window into one of a plurality of classifications comprising: the response window is representative of an artificially-induced mechanical response of the muscle; and the response window is not representative of an artificially-induced mechanical response of the muscle. provide the periodic stimulus to the stimulator; receive the mechanomyography output signal from the mechanical sensor; analyze a response window (102, 154, 174) of the mechanomyography output signal to determine if the first stimulus induced a response of the muscle; and provide an indication to a user if it is determined that the first stimulus induced a response of the muscle within the response window; wherein the response window corresponds to a period of time when an induced response to the first stimulus is likely to occur; characterized in that the response window extends between a third time, T 3, and a fourth time, T 4, such that T 1 ≤ T 3 < T 4 < T 2; and in that the processor is further configured to determine if the first stimulus induced a response of the muscle by examining one or more characteristics of the mechanomyography output signal within the response window using a supervised learning algorithm; and wherein the supervised learning algorithm is operative to classify the response window into one of a plurality of classifications comprising: the response window is representative of an artificially-induced mechanical response of the muscle; and the response window is not representative of an artificially-induced mechanical response of the muscle. the response window is representative of an artificially-induced mechanical response of the muscle; and the response window is not representative of an artificially-induced mechanical response of the muscle.