Introduction Stroke often initially leads to motor impairments of the upper limb. The largest improvements in recovery take place during the _rst half year after stroke. With more knowledge about neurological recovery, it may be possible to predict motor recovery after stroke with the use of neurological biomarkers. Prediction of stroke recovery can be used in the selection and development of rehabilitation therapies. By applying continuous perturbations to a joint with the use of a robotic manipulator during di_erent control tasks, the evoked cortical responses of the sensorimotor cortex can be studied. With this method, evaluating the relation between EEG activity and motor function of the upper limb may provide meaningful EEG biomarkers for motor recovery after stroke. Methods A selection of 13 sub-acute stroke patients who participated in the 4D EEG project were longitudinally measured four times during the _rst half year after stroke. EEG was measured during relax, position and force tasks while a robotic wrist manipulator applied continuous perturbations to the a_ected wrist. The upper limb part of the Fugl-Meyer assesment (FMA) was used to asses the upper limb motor function. The index of the signal-to- noise ratio (iSNR) was obtained from the EEG data. Results The FMA score was strongly related to time post stroke. Also, FMA score during the _rst measurement was lower than during the second, third and fourth. The iSNR was lower during the position task than during the relax and force tasks. A moderate relation was found between the FMA score and the iSNR during the position task, but not during the relax and force task. Conclusion The iSNR during the position task is potentially a EEG biomarker for upper limb motor recovery after stroke. 1