@article {Berning2021COBME,
	title = {Myoelectric Control and Neuromusculoskeletal Modeling: Complementary Technologies for Rehabilitation Robotics},
	journal = {Current Opinion in Biomedical Engineering},
	year = {2021},
	pages = {100313},
	abstract = {<p>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{\textquoteright}s electromyography signals may provide accurate predictions of the subject{\textquoteright}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.</p>},
	keywords = {Electromyography, neuromusculoskeletal modeling, robotic rehabilitation, upper limb motor impairment},
	issn = {2468-4511},
	doi = {https://doi.org/10.1016/j.cobme.2021.100313},
	url = {https://www.sciencedirect.com/science/article/pii/S2468451121000532},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/BerningCOBME2021_preprint.pdf},
	author = {Jeffrey Berning and Gerard E. Francisco and Shuo-Hsiu Chang and Benjamin J. Fregly and Marcia K. O{\textquoteright}Malley}
}
@article {BHAGAT2020102502,
	title = {Neural activity modulations and motor recovery following brain-exoskeleton interface mediated stroke rehabilitation},
	journal = {NeuroImage: Clinical},
	volume = {28},
	year = {2020},
	pages = {102502},
	abstract = {<p>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\&nbsp;{\textpm}\&nbsp;22 repetitions were performed per participant, per session. BMI accuracy across all sessions and subjects was 79\&nbsp;{\textpm}\&nbsp;18\% with a false positives rate of 23\&nbsp;{\textpm}\&nbsp;20\%. Post-training clinical assessments found that FMA for upper extremity and ARAT scores significantly improved over baseline by 3.92\&nbsp;{\textpm}\&nbsp;3.73 and 5.35\&nbsp;{\textpm}\&nbsp;4.62 points, respectively. Also, 80\% participants (7 with moderate-mild impairment, 1 with severe impairment) achieved minimal clinically important difference (MCID: FMA-UE \&gt;5.2 or ARAT \&gt;5.7) during the course of the study. Kinematic measures indicate that, on average, participants{\textquoteright} 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\&nbsp;=\&nbsp;0.72, p\&nbsp;\&lt;\&nbsp;0.05) and marginally correlated with FMA-UE (ρ\&nbsp;=\&nbsp;0.63, p\&nbsp;=\&nbsp;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.</p>},
	keywords = {Brain-machine interface, Clinical trial, Exoskeletons, Movement related cortical potentials, stroke rehabilitation},
	issn = {2213-1582},
	doi = {https://doi.org/10.1016/j.nicl.2020.102502},
	url = {http://www.sciencedirect.com/science/article/pii/S2213158220303399},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/NeuroImage_2020_Bhagat_BMI_EEG_exo.pdf},
	author = {Nikunj A. Bhagat and Nuray Yozbatiran and Jennifer L. Sullivan and Ruta Paranjape and Colin Losey and Zachary Hernandez and Zafer Keser and Robert Grossman and Gerard E. Francisco and Marcia K. O{\textquoteright}Malley and Jose L. Contreras-Vidal}
}
@article {1787,
	title = {Transcranial direct current stimulation (tDCS) of the primary motor cortex and robot-assisted arm training in chronic incomplete cervical spinal cord injury: A proof of concept sham-randomized clinical study},
	journal = {NeuroRehabilitation},
	volume = {39},
	year = {2016},
	pages = {401{\textendash}411},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/TDCS_2016_Neurorehab.pdf},
	author = {Nuray Yozbatirana and Zafer Keser and Matthew Davis and Argyrios Stampas and Marcia K. O{\textquoteright}Malley and Catherine Cooper-Hay and Joel Fronteraa and Felipe Fregni and Gerard E. Francisco}
}
@proceedings {1691,
	title = {A Pre-Clinical Framework for Neural Control of a Therapeutic Upper-Limb Exoskeleton},
	year = {2013},
	month = {2013},
	pages = {1159-1162},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/BMI-EXO_2013_NER.pdf},
	author = {Amy Blank and Marcia K. O{\textquoteright}Malley and Gerard E. Francisco and Jose L. Contreras-Vidal}
}
@article {1698,
	title = {Robotic training and clinical assessment of upper extremity movements after spinal cord injury; a single case report},
	journal = {Journal of Rehabilitation Medicine},
	volume = {44},
	year = {2012},
	month = {01/2012},
	pages = {186-188},
	chapter = {186},
	attachments = {https://mahilab.rice.edu/sites/default/files/publications/J_Rehab_Medicine_2012_Final_press_version.pdf},
	author = {Yozbatiran, Nuray and Berliner, J. and O{\textquoteright}Malley, M.K. and Pehlivan, A.U. and Z. Kadivar and Boake, Corwin and Gerard E. Francisco}
}
