Motion classification by epidural potential measurement of rat for low-invasive brain-machine interface

A low-invasive method to record neural activity is required for safe and practical brain-machine interfaces (BMI). BMIs are expected to be used to reintegrate motor functions of physically disabled persons; however, conventional invasive methods require electrodes inside the dura mater. In this study, the authors used epidural electrodes, which are located between the skull and dura mater, to record rat neural activity for low-invasive BMI. The signals were analyzed using short-time Fourier transform, and the power spectra were classified into rat motions by an artificial neural network. The accuracy was approximately 70% in two-motion classifications according to the tested electrodes' locations and frequency bands. The results indicated the feasibility of low-invasive BMI using epidural electrodes.