This paper presents an approach for an asynchronous BMI proposed as a switching part of a tremor suppression system developed for real-time continuous conditions. The main purpose of this BMI-switch is to anticipate the execution of self-initiated movements performed after relatively long periods of inactivity. The performance indicators used for the detector validation are specially suited for the continuous characteristic of the paradigm used and it is demonstrated that our ERD-based bayesian classifier solution is a reliable option, detecting a high rate of positive cases and generating very few false positives during long intervals of inactivity. The subjects analyzed for our detector validation were patients with neurological tremor caused by different pathologies in order to assure the adaptability of our system.