TY - JOUR T1 - Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation JF - NeuroImage: Clinical Y1 - 2020 A1 - Nikunj A. Bhagat A1 - Nuray Yozbatiran A1 - Jennifer L. Sullivan A1 - Ruta Paranjape A1 - Colin Losey A1 - Zachary Hernandez A1 - Zafer Keser A1 - Robert Grossman A1 - Gerard E. Francisco A1 - Marcia K. O'Malley A1 - Jose L. Contreras-Vidal KW - Brain-machine interface KW - Clinical trial KW - Exoskeletons KW - Movement related cortical potentials KW - stroke rehabilitation AB -

Brain-machine interfaces (BMI) based on scalp EEG have the potential to promote cortical plasticity following stroke, which has been shown to improve motor recovery outcomes. However, the efficacy of BMI enabled robotic training for upper-limb recovery is seldom quantified using clinical, EEG-based, and kinematics-based metrics. Further, a movement related neural correlate that can predict the extent of motor recovery still remains elusive, which impedes the clinical translation of BMI-based stroke rehabilitation. To address above knowledge gaps, 10 chronic stroke individuals with stable baseline clinical scores were recruited to participate in 12 therapy sessions involving a BMI enabled powered exoskeleton for elbow training. On average, 132 ± 22 repetitions were performed per participant, per session. BMI accuracy across all sessions and subjects was 79 ± 18% with a false positives rate of 23 ± 20%. Post-training clinical assessments found that FMA for upper extremity and ARAT scores significantly improved over baseline by 3.92 ± 3.73 and 5.35 ± 4.62 points, respectively. Also, 80% participants (7 with moderate-mild impairment, 1 with severe impairment) achieved minimal clinically important difference (MCID: FMA-UE >5.2 or ARAT >5.7) during the course of the study. Kinematic measures indicate that, on average, participants’ movements became faster and smoother. Moreover, modulations in movement related cortical potentials, an EEG-based neural correlate measured contralateral to the impaired arm, were significantly correlated with ARAT scores (ρ = 0.72, p < 0.05) and marginally correlated with FMA-UE (ρ = 0.63, p = 0.051). This suggests higher activation of ipsi-lesional hemisphere post-intervention or inhibition of competing contra-lesional hemisphere, which may be evidence of neuroplasticity and cortical reorganization following BMI mediated rehabilitation therapy.

VL - 28 UR - http://www.sciencedirect.com/science/article/pii/S2213158220303399 ER - TY - Generic T1 - A Neuromuscular Elbow Model for Analysis of Force and Movement Variability in Slow Movements T2 - IEEE EMBC Y1 - 2011 A1 - O. Celik A1 - O'Malley, M.K. JF - IEEE EMBC ER - TY - JOUR T1 - Normalized movement quality measures for therapeutic robots strongly correlate with clinical motor impairment measures JF - IEEE Transactions on Neural Systems and Rehabilitation Engineering Y1 - 2010 A1 - Ozkan Celik A1 - O'Malley, M.K. A1 - Boake, Corwin A1 - H.S. Levin A1 - Yozbatiran, Nuray A1 - Reistetter, Timothy AB - In this paper, we analyze the correlations between four clinical measures (Fugl–Meyer upper extremity scale, Motor Activity Log, Action Research Arm Test, and Jebsen-Taylor Hand Function Test) and four robotic measures (smoothness of movement, trajectory error, average number of target hits per minute, and mean tangential speed), used to assess motor recovery. Data were gathered as part of a hybrid robotic and traditional upper extremity rehabilitation program for nine stroke patients. Smoothness of movement and trajectory error, temporally and spatially normalized measures of movement quality defined for point-to-point movements, were found to have significant moderate to strong correlations with all four of the clinical measures. The strong correlations suggest that smoothness of movement and trajectory error may be used to compare outcomes of different rehabilitation protocols and devices effectively, provide improved resolution for tracking patient progress compared to only pre- and post-treatment measurements, enable accurate adaptation of therapy based on patient progress, and deliver immediate and useful feedback to the patient and therapist. VL - 18 UR - http://dx.doi.org/10.1109/TNSRE.2010.2047600 ER - TY - JOUR T1 - Negative Efficacy of Fixed Gain Error Reducing Shared Control for Training in Virtual Environments JF - ACM Transactions on Applied Perception Y1 - 2009 A1 - Yanfang Li A1 - Volkan Patoglu A1 - O'Malley, M.K. AB -

Virtual reality with haptic feedback provides a safe and versatile practice medium for many manual control tasks. Haptic guidance has been shown to improve performance of manual control tasks in virtual environments; however, the efficacy of haptic guidance for training in virtual environments has not been studied conclusively. This article presents experimental results that show negative efficacy of haptic guidance during training in virtual environments. The haptic guidance in this study is a fixed-gain error-reducing shared controller, with the control effort overlaid on the dynamics of the manual control task during training. Performance of the target-hitting manual control task in the absence of guidance is compared for three training protocols. One protocol contained no haptic guidance and represented virtual practice. Two protocols utilized haptic guidance, varying the duration of exposure to guidance during the training sessions. Exposure to the fixed-gain error-reducing shared controller had a detrimental effect on performance of the target-hitting task at the conclusion of a month-long training protocol, regardless of duration of exposure. While the shared controller was designed with knowledge of the task and an intuitive sense of the motions required to achieve good performance, the results indicate that the acquisition of motor skill is a complex phenomenon that is not aided with haptic guidance during training as implemented in this experiment.

VL - 6 ER -