Sullivan, Jennifer L.Bhagat, Nikunj A.Yozbatiran, NurayParanjape, RutaLosey, Colin G.Grossman, Robert G.Contreras-Vidal, Jose L.Francisco, Gerard E.O’Malley, Marcia K.2018-07-032018-07-032017Sullivan, Jennifer L., Bhagat, Nikunj A., Yozbatiran, Nuray, et al.. "Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial." <i>2017 International Conference on Rehabilitation Robotics (ICORR),</i> (2017) IEEE: 122-127. https://doi.org/10.1109/ICORR.2017.8009233.https://hdl.handle.net/1911/102349This paper presents the preliminary findings of a multi-year clinical study evaluating the effectiveness of adding a brain-machine interface (BMI) to the MAHI-Exo II, a robotic upper limb exoskeleton, for elbow flexion/extension rehabilitation in chronic stroke survivors. The BMI was used to trigger robot motion when movement intention was detected from subjects' neural signals, thus requiring that subjects be mentally engaged during robotic therapy. The first six subjects to complete the program have shown improvements in both Fugl-Meyer Upper-Extremity scores as well as in kinematic movement quality measures that relate to movement planning, coordination, and control. These results are encouraging and suggest that increasing subject engagement during therapy through the addition of an intent-detecting BMI enhances the effectiveness of standard robotic rehabilitation.engThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE.Journal articlehttps://doi.org/10.1109/ICORR.2017.8009233