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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

174 related items for PubMed ID: 24110003

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  • 2. An integrated neuro-robotic interface for stroke rehabilitation using the NASA X1 powered lower limb exoskeleton.
    He Y, Nathan K, Venkatakrishnan A, Rovekamp R, Beck C, Ozdemir R, Francisco GE, Contreras-Vidal JL.
    Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():3985-8. PubMed ID: 25570865
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  • 3. High accuracy decoding of user intentions using EEG to control a lower-body exoskeleton.
    Kilicarslan A, Prasad S, Grossman RG, Contreras-Vidal JL.
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():5606-9. PubMed ID: 24111008
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  • 4. Brain-machine interfaces for controlling lower-limb powered robotic systems.
    He Y, Eguren D, Azorín JM, Grossman RG, Luu TP, Contreras-Vidal JL.
    J Neural Eng; 2018 Apr; 15(2):021004. PubMed ID: 29345632
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  • 5. EEG-Based Detection of Starting and Stopping During Gait Cycle.
    Hortal E, Úbeda A, Iáñez E, Azorín JM, Fernández E.
    Int J Neural Syst; 2016 Nov; 26(7):1650029. PubMed ID: 27354191
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  • 6. Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients.
    Donati AR, Shokur S, Morya E, Campos DS, Moioli RC, Gitti CM, Augusto PB, Tripodi S, Pires CG, Pereira GA, Brasil FL, Gallo S, Lin AA, Takigami AK, Aratanha MA, Joshi S, Bleuler H, Cheng G, Rudolph A, Nicolelis MA.
    Sci Rep; 2016 Aug 11; 6():30383. PubMed ID: 27513629
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  • 7. Simultaneous scalp electroencephalography (EEG), electromyography (EMG), and whole-body segmental inertial recording for multi-modal neural decoding.
    Bulea TC, Kilicarslan A, Ozdemir R, Paloski WH, Contreras-Vidal JL.
    J Vis Exp; 2013 Jul 26; (77):. PubMed ID: 23912203
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  • 9. Classification of stand-to-sit and sit-to-stand movement from low frequency EEG with locality preserving dimensionality reduction.
    Bulea TC, Prasad S, Kilicarslan A, Contreras-Vidal JL.
    Annu Int Conf IEEE Eng Med Biol Soc; 2013 Jul 26; 2013():6341-4. PubMed ID: 24111191
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  • 10. Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.
    McMullen DP, Hotson G, Katyal KD, Wester BA, Fifer MS, McGee TG, Harris A, Johannes MS, Vogelstein RJ, Ravitz AD, Anderson WS, Thakor NV, Crone NE.
    IEEE Trans Neural Syst Rehabil Eng; 2014 Jul 26; 22(4):784-96. PubMed ID: 24760914
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  • 13. Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain-computer interface to a virtual reality avatar.
    Luu TP, He Y, Brown S, Nakagame S, Contreras-Vidal JL.
    J Neural Eng; 2016 Jun 26; 13(3):036006. PubMed ID: 27064824
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  • 16. Control of an Ambulatory Exoskeleton with a Brain-Machine Interface for Spinal Cord Injury Gait Rehabilitation.
    López-Larraz E, Trincado-Alonso F, Rajasekaran V, Pérez-Nombela S, Del-Ama AJ, Aranda J, Minguez J, Gil-Agudo A, Montesano L.
    Front Neurosci; 2016 Jun 26; 10():359. PubMed ID: 27536214
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