Browsing by Author "Francisco, Gerard E."
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Item Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors(Frontiers Media S.A., 2016) Bhagat, Nikunj A.; Venkatakrishnan, Anusha; Abibullaev, Berdakh; Artz, Edward J.; Yozbatiran, Nuray; Blank, Amy A.; French, James; Karmonik, Christof; Grossman, Robert G.; O’Malley, Marcia K.; Francisco, Gerard E.; Contreras-Vidal, Jose L.This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG)-based brain machine interface (BMI). Intent was inferred from movement related cortical potentials (MRCPs) measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II), to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: (1) an adaptive time window was used for extracting features during BMI calibration; (2) training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and (3) BMI predictions were gated by residual electromyography (EMG) activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR) = 62.7 ± 21.4% on day 4 and 67.1 ± 14.6% on day 5. The overall false positive rate (FPR) across subjects was 27.74 ± 37.46% on day 4 and 27.5 ± 35.64% on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10%). On average, motor intent was detected −367 ± 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration.Item Design of a parallel-group balanced controlled trial to test the effects of assist-as-needed robotic therapy(IEEE, 2015) Sergi, Fabrizio; Pehlivan, Ali Utku; Fitle, Kyle; Nedley, Kathryn; Yozbatiran, Nuray; Francisco, Gerard E.; O’Malley, Marcia K.; Mechatronics and Haptic Interfaces LaboratoryIn this methods paper, we report on the design of a clinical study testing the efficacy of a newly developed control scheme for robot-aided rehabilitation. To measure the value added by a new control scheme, we pursued a parallel-group controlled clinical study design. This approach enables comparing the effects of the novel scheme, based on the Assist-As-Needed (AAN) paradigm, with those of a less sophisticated, fixed gain, Subject-Triggered (ST) controller. We describe the steps followed in the design of this clinical study, including details on the implementation of the two control modes, and a power analysis to determine the required number of subjects to test a clinically significant difference hypothesis. Finally, we present a method for sequential group assignment with co-variates minimization, capable of guaranteeing a desired level of balance of prognostic factors in the two study groups, a crucial requisite for small-scale clinical studies in rehabilitation. To the best of our knowledge, the study presented is the first one testing, in a controlled fashion, the differential effects of a specific control mode in upper extremity rehabilitation after incomplete spinal cord injury.Item Effects of Assist-As-Needed Upper Extremity Robotic Therapy after Incomplete Spinal Cord Injury: A Parallel-Group Controlled Trial(Frontiers Media S.A., 2017) Frullo, John Michael; Elinger, Jared; Pehlivan, Ali Utku; Fitle, Kyle; Nedley, Kathryn; Francisco, Gerard E.; Sergi, Fabrizio; O’Malley, Marcia K.Background: Robotic rehabilitation of the upper limb following neurological injury has been supported through several large clinical studies for individuals with chronic stroke. The application of robotic rehabilitation to the treatment of other neurological injuries is less developed, despite indications that strategies successful for restoration of motor capability following stroke may benefit individuals with incomplete spinal cord injury (SCI) as well. Although recent studies suggest that robot-aided rehabilitation might be beneficial after incomplete SCI, it is still unclear what type of robot-aided intervention contributes to motor recovery. Methods: We developed a novel assist-as-needed (AAN) robotic controller to adjust challenge and robotic assistance continuously during rehabilitation therapy delivered via an upper extremity exoskeleton, the MAHI Exo-II, to train independent elbow and wrist joint movements. We further enrolled seventeen patients with incomplete spinal cord injury (AIS C and D levels) in a parallel-group balanced controlled trial to test the efficacy of the AAN controller, compared to a subject-triggered (ST) controller that does not adjust assistance or challenge levels continuously during therapy. The conducted study is a stage two, development-of-concept pilot study. Results: We validated the AAN controller in its capability of modulating assistance and challenge during therapy via analysis of longitudinal robotic metrics. For the selected primary outcome measure, the pre–post difference in ARAT score, no statistically significant change was measured in either group of subjects. Ancillary analysis of secondary outcome measures obtained via robotic testing indicates gradual improvement in movement quality during the therapy program in both groups, with the AAN controller affording greater increases in movement quality over the ST controller. Conclusion: The present study demonstrates feasibility of subject-adaptive robotic therapy after incomplete spinal cord injury, but does not demonstrate gains in arm function occurring as a result of the robot-assisted rehabilitation program, nor differential gains obtained as a result of the developed AAN controller. Further research is warranted to better quantify the recovery potential provided by AAN control strategies for robotic rehabilitation of the upper limb following incomplete SCI.Item Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial(IEEE, 2017) Sullivan, Jennifer L.; Bhagat, Nikunj A.; Yozbatiran, Nuray; Paranjape, Ruta; Losey, Colin G.; Grossman, Robert G.; Contreras-Vidal, Jose L.; Francisco, Gerard E.; O’Malley, Marcia K.This 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.Item Myoelectric control and neuromusculoskeletal modeling: Complementary technologies for rehabilitation robotics(Elsevier, 2021) Berning, Jeffrey; Francisco, Gerard E.; Chang, Shuo-Hsiu; Fregly, Benjamin J.; O'Malley, Marcia K.Stroke and spinal cord injury (SCI) are a leading cause of disability in the United States, and researchers have pursued using robotic devices to aid rehabilitation efforts for resulting upper-extremity impairments. To date, however, robotic rehabilitation of the upper limb has produced only limited improvement in functional outcomes compared to traditional therapy. This paper explores the potential of myoelectric control and neuromusculoskeletal modeling for robotic rehabilitation using the current state of the art of each individual field as evidence. Continuing advances in the fields of myoelectric control and neuromusculoskeletal modeling offer opportunities for further improvements of rehabilitation robot control strategies. Specifically, personalized neuromusculoskeletal models driven by a subject's electromyography signals may provide accurate predictions of the subject's muscle forces and joint moments, which, when used to design novel control strategies, could yield new approaches to robotic therapy for stroke and SCI that surpass the efficacy of traditional therapy.Item Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation(Elsevier, 2020) Bhagat, Nikunj A.; Yozbatiran, Nuray; Sullivan, Jennifer L.; Paranjape, Ruta; Losey, Colin; Hernandez, Zachary; Keser, Zafer; Grossman, Robert; Francisco, Gerard E.; O'Malley, Marcia K.; Contreras-Vidal, Jose L.; Mechatronics and Haptic Interfaces LaboratoryBrain-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.Item A Pre-Clinical Framework for Neural Control of a Therapeutic Upper-Limb Exoskeleton(IEEE, 2013) Blank, Amy; O'Malley, Marcia K.; Francisco, Gerard E.; Contreras-Vidal, Jose L.In this paper, we summarize a novel approach to robotic rehabilitation that capitalizes on the benefits of patient intent and real-time assessment of impairment. Specifically, an upper-limb, physical human-robot interface (the MAHI EXO-II robotic exoskeleton) is augmented with a noninvasive brain-machine interface (BMI) to include the patient in the control loop, thereby making the therapy “active” and engaging patients across a broad spectrum of impairment severity in the rehabilitation tasks. Robotic measures of motor impairment are derived from real-time sensor data from the MAHI EXO-II and the BMI. These measures can be validated through correlation with widely used clinical measures and used to drive patient-specific therapy sessions adapted to the capabilities of the individual, with the MAHI EXO-II providing assistance or challenging the participant as appropriate to maximize rehabilitation outcomes. This approach to robotic rehabilitation takes a step towards the seamless integration of BMIs and intelligent exoskeletons to create systems that can monitor and interface with brain activity and movement. Such systems will enable more focused study of various issues in development of devices and rehabilitation strategies, including interpretation of measurement data from a variety of sources, exploration of hypotheses regarding large scale brain function during robotic rehabilitation, and optimization of device design and training programs for restoring upper limb function after stroke.Item Robot-Assisted Training of Arm and Hand Movement Shows Functional Improvements for Incomplete Cervical Spinal Cord Injury(Wolters Kluwer, 2017) Francisco, Gerard E.; Yozbatiran, Nuray; Berliner, Jeffrey; O'Malley, Marcia K.; Pehlivan, Ali Utku; Kadivar, Zahra; Fitle, Kyle; Boake, CorwinObjective The aim of the study was to demonstrate the feasibility, tolerability, and effectiveness of robotic-assisted arm training in incomplete chronic tetraplegia. Design Pretest/posttest/follow-up was conducted. Ten individuals with chronic cervical spinal cord injury were enrolled. Participants performed single degree-of-freedom exercise of upper limbs at an intensity of 3-hr per session for 3 times a week for 4 wks with MAHI Exo-II. Arm and hand function tests (Jebsen-Taylor Hand Function Test, Action Research Arm Test), strength of upper limb (upper limb motor score, grip, and pinch strength), and independence in daily living activities (Spinal Cord Independence Measure II) were performed at baseline, end of training, and 6 mos later. Results After 12 sessions of training, improvements in arm and hand functions were observed. Jebsen-Taylor Hand Function Test (0.14[0.04]–0.21[0.07] items/sec, P = 0.04), Action Research Arm Test (30.7[3.8]–34.3[4], P = 0.02), American Spinal Injury Association upper limb motor score (31.5[2.3]–34[2.3], P = 0.04) grip (9.7[3.8]–12[4.3] lb, P = 0.02), and pinch strength (4.5[1.1]–5.7[1.2] lb, P = 0.01) resulted in significant increases. Some gains were maintained at 6 mos. No change in Spinal Cord Independence Measure II scores and no adverse events were observed. Conclusions Results from this pilot study suggest that repetitive training of arm movements with MAHI Exo-II exoskeleton is safe and has potential to be an adjunct treatment modality in rehabilitation of persons with spinal cord injury with mild to moderate impaired arm functions.