The aim of this study was to develop a model that predicts the effects of repetitive transcranial magnetic stimulation (rTMS), allowing stimulation of parameters for individual subjects. Modulation of cortical excitability induced by rTMS can be evaluated through motor evoked potential (MEP) amplitude. We establish a model that can predict how the MEP amplitude is modulated by entering rTMS intensity and number of pulses. First, MEPs are measured under various rTMS conditions of stimulus intensity and number of pulses. Then, cluster analysis is performed to classify the subjects, as rTMS affects individuals differently. Finally, a predictive model is created by applying multiple regression analysis to the data from each cluster. As a result, subjects are classified into two groups. For Cluster A, the inhibitive effect of rTMS is difficult to induce and the facilitative effect is induced depending on the stimulus condition. Then, the average predictive error is 46.19%. For Cluster B, the inhibitive effect is strongly induced by rTMS, and the average error is 20.25%. In the model, for both clusters, about 90% of measurement data is in the predictive interval. This paper describes the development of our prediction model and its efficiency.
|Number of pages||7|
|Journal||IEEJ Transactions on Electrical and Electronic Engineering|
|Publication status||Published - Jul 2017|
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering