TMS ioFit estimates neural recruitment or input-output (IO) curves and parameters in a closed-loop system, by using the EMG data and  sequential estimation method. In the sequential estimation method, a train of TMS pulses is applied, the estimation is updated after each pulse, and the process continues until the IO curve and parameters are estimated with a desired level of accuracy. The current version of TMS ioFit supports uniform and optimal sampling methods. In the uniform sampling, the intensity of TMS pulses is uniformly distributed. In the optimal sampling method, the intensity of TMS pulses is chosen based on the Fisher information matrix (FIM). In comparison with the uniform sampling method, the FIM-based optimal sampling method results in more accurate estimation of the IO curve and parameters with fewer TMS pulses. 

This website is to provide you with all information, update, training videos & document, and technical support of TMS ioFit.