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Electrocorticogram encoding of upper extremity movement duration

Po T. Wang, Christine E. King, Colin M. McCrimmon, Susan J. Shaw, David E. Millett, Charles Y. Liu, Luis A. Chui, Zoran Nenadic, An H. Do
2014 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
Electrocorticogram (ECoG) is a promising long-term signal acquisition platform for brain-computer interface (BCI) systems such as upper extremity prostheses.  ...  The persistence of power bursts for the duration of the movement suggests that the primary motor cortex (M1) is likely active for the entire duration of a movement, instead of providing a marker for the  ...  INTRODUCTION Subdurally-recorded electrocorticogram (ECoG) is a promising long-term signal acquisition platform for braincomputer interface (BCI) systems, such as upper extremity prostheses.  ... 
doi:10.1109/embc.2014.6943822 pmid:25570190 pmcid:PMC6508956 fatcat:gtrt7nloajcndmpxw4tyavs5eu

Electrocorticogram encoding of upper extremity movement trajectories

Po T. Wang, Christine E. King, Andrew Schombs, Jack J. Lin, Mona Sazgar, Frank P.K. Hsu, Susan J. Shaw, David E. Millett, Charles Y. Liu, Luis A. Chui, Zoran Nenadic, An H. Do
2013 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)  
This study seeks to improve the fundamental understanding of the ECoG signal features underlying upper extremity movements to guide better BCI design.  ...  Subjects undergoing ECoG electrode implantation performed a series of elementary upper extremity movements in an intermittent flexion and extension manner.  ...  Recently, there has been a growing interest in using electrocorticogram (ECoG) as a longterm signal acquisition platform for BCI-control of upper extremity prostheses.  ... 
doi:10.1109/ner.2013.6696212 fatcat:o4l22czufneqppimct43fc377u

Electrocorticogram encoding of upper extremity movement trajectories [article]

Po T. Wang, Christine E. King, Andrew Schombs, Jack J. Lin, Mona Sazgar, Frank P. K. Hsu, Susan J. Shaw, David E. Millett, Charles Y. Liu, Luis A. Chui, Zoran Nenadic, An H. Do
2014 arXiv   pre-print
This study seeks to improve the fundamental understanding of the ECoG signal features underlying upper extremity movements to guide better BCI design.  ...  Subjects undergoing ECoG electrode implantation performed a series of elementary upper extremity movements in an intermittent flexion and extension manner.  ...  Recently, there has been a growing interest in using electrocorticogram (ECoG) as a longterm signal acquisition platform for BCI-control of upper extremity prostheses.  ... 
arXiv:1402.5996v1 fatcat:dvh2wrdk7nacrau4fl3zfxdiia

MEG studies of motor cortex gamma oscillations: evidence for a gamma "fingerprint" in the brain?

Douglas Cheyne, Paul Ferrari
2013 Frontiers in Human Neuroscience  
Here we summarize contributions of MEG to our understanding of movement-evoked gamma oscillations, including evidence that transient gamma bursts during the performance of specific movements constitutes  ...  The human motor cortex exhibits transient bursts of high frequency gamma oscillations in the 60-90 Hz range during movement.  ...  For example, upper limb movements should activate a larger region of MI than lower limb movements, the latter showing significantly lower gamma frequency (Cheyne et al., 2008) .  ... 
doi:10.3389/fnhum.2013.00575 pmid:24062675 pmcid:PMC3774986 fatcat:zn7x4nmk7jbvjprxswac6reu5y

Application of Artificial Intelligence (AI) in Prosthetic and Orthotic Rehabilitation [chapter]

Smita Nayak, Rajesh Kumar Das
2020 Service Robotics [Working Title]  
The concept of neural network has been used by the leading manufacturers of rehabilitation aids for simulating various anatomical and biomechanical functions of the lost parts of the human body.  ...  Technological integration of Artificial Intelligence (AI) and machine learning in the Prosthetic and Orthotic industry and in the field of assistive technology has become boon for the Persons with Disabilities  ...  AI in upper extremity prosthesis and orthosis The artificial Intelligence in upper extremity prosthesis used as direct control and indirect control from the neural network by various signal, sensor, controller  ... 
doi:10.5772/intechopen.93903 fatcat:jp2h7xcms5h3tjx7ichkckplty

Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control

Gernot R. Müller-Putz, Reinmar J. Kobler, Joana Pereira, Catarina Lopes-Dias, Lea Hehenberger, Valeria Mondini, Víctor Martínez-Cagigal, Nitikorn Srisrisawang, Hannah Pulferer, Luka Batistić, Andreea I. Sburlea
2022 Frontiers in Human Neuroscience  
decoders' performance while participants attempt to perform upper-limb movements.  ...  Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project "Feel Your Reach".  ...  ACKNOWLEDGMENTS We acknowledge the participation of about 320 participants, about 10 with spinal cord injury, in more than 20 studies performed during the runtime of ''Feel Your Reach''.  ... 
doi:10.3389/fnhum.2022.841312 pmid:35360289 pmcid:PMC8961864 fatcat:mkselw7a5jemnlq5ibvqh2wpte

Transition from the locked in to the completely locked-in state: A physiological analysis

A. Ramos Murguialday, J. Hill, M. Bensch, S. Martens, S. Halder, F. Nijboer, B. Schoelkopf, N. Birbaumer, A. Gharabaghi
2011 Clinical Neurophysiology  
Results: At the very end of the LIS there was no facial muscle activity, nor external anal sphincter but eye control. Eye movements were slow and lasted for short periods only.  ...  During CLIS event related brain potentials (ERP) to passive limb movements and auditory stimuli were recorded, vibrotactile stimulation of different body parts resulted in no ERP response.  ...  Funding was provided by the Deutsche Forschungsgemeinschaft (DFG GH 94/2-1, DFG EC 307 BI 195), The ERC grant 227632-BCCI and the German Ministry of Education and Research (Bernstein Centers 01GQ0831  ... 
doi:10.1016/j.clinph.2010.08.019 pmid:20888292 fatcat:tnlz56f3ezdl3hqcwe7x2je6ne

DARPA-funded efforts in the development of novel brain–computer interface technologies

Robbin A. Miranda, William D. Casebeer, Amy M. Hein, Jack W. Judy, Eric P. Krotkov, Tracy L. Laabs, Justin E. Manzo, Kent G. Pankratz, Gill A. Pratt, Justin C. Sanchez, Douglas J. Weber, Tracey L. Wheeler (+1 others)
2015 Journal of Neuroscience Methods  
Finally, this review includes a summary of some of the remaining challenges for the field of BCI, as well as the goals of new DARPA efforts in this domain.  ...  This review highlights some of DARPA's major advances in the field of BCI, particularly those made in recent years.  ...  Major upper extremity disabilities are a significant problem for the Department of Defense (DoD).  ... 
doi:10.1016/j.jneumeth.2014.07.019 pmid:25107852 fatcat:onobe3y6c5a6dlej4sssck3gf4

Dominant frequencies of resting human brain activity as measured by the electrocorticogram

David M. Groppe, Stephan Bickel, Corey J. Keller, Sanjay K. Jain, Sean T. Hwang, Cynthia Harden, Ashesh D. Mehta
2013 NeuroImage  
One of the most studied and clinically utilized types of intrinsic brain activity are oscillations in the electrocorticogram (ECoG), a relatively localized measure of cortical synaptic activity.  ...  These results should help identify abnormal patterns of ECoG oscillations, inform the interpretation of EEG/MEG intrinsic activity, and provide insight into the functions of these different oscillations  ...  an earlier version of this manuscript.  ... 
doi:10.1016/j.neuroimage.2013.04.044 pmid:23639261 pmcid:PMC4269223 fatcat:hyg35kmnxbfedmtzrlr3n3rbpa

EEG-Based Control for Upper and Lower Limb Exoskeletons and Prostheses: A Systematic Review

Maged AL-Quraishi, Irraivan Elamvazuthi, Siti Daud, S. Parasuraman, Alberto Borboni
2018 Sensors  
The study of EEG-based control of assistive devices is still in early stages.  ...  a means of offering researchers and experts a comprehensive summary of the present, state-of-the-art EEG-based control techniques used for assistive technology.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s18103342 fatcat:nacqsogy5jfdvnq2pzviasdqdy

Applied Exoskeleton Technology: A Comprehensive Review of Physical and Cognitive Human-Robot-Interfac [article]

Farhad Nazari, Navid Mohajer, Darius Nahavandi, Abbas Khosravi, Saeid Nahavandi
2022 arXiv   pre-print
The outcomes of modelling show the potential use of single-channel input in low-power assistive devices.  ...  To accommodate this insufficiency, different aspects of this technology need to be analysed and improved.  ...  Such a model should involve DoF of the assisting joints and all possible body parts movements and their limitations. Figure 2 shows the possible motions of human upper limbs.  ... 
arXiv:2111.12860v6 fatcat:h7y6crlveffalg3vxrdclubvim

A review and consideration on the kinematics of reach-to-grasp movements in macaque monkeys

Umberto Castiello, Marco Dadda
2019 Journal of Neurophysiology  
The temporal incidence of key kinematic landmarks diverges significantly between species, indicating disparities in the overall organization of movement.  ...  A thorough understanding of macaques' prehensile movements is manifestly critical, in light of their role in biomedical research as valuable models for studying neuromotor disorders and brain mechanisms  ...  Using a similar technique, Schaffelhofer and colleagues (2015a; see also Schaffelhofer and Scherberger 2012) proposed a musculoskeletal approach to the study of the upper extremity, thereby employing a  ... 
doi:10.1152/jn.00598.2018 fatcat:wc7fy3kj2fbypmig2pg67whar4

Rehabilitation Treatment of Motor Dysfunction Patients Based on Deep Learning Brain–Computer Interface Technology

Huihai Wang, Qinglun Su, Zhenzhuang Yan, Fei Lu, Qin Zhao, Zhen Liu, Fang Zhou
2020 Frontiers in Neuroscience  
It can avoid the blindness and time-consuming problems caused by the machine learning method based on feature extraction of EEG data due to the lack of a large amount of prior knowledge.  ...  To avoid the blindness and complexity of electroencephalogram (EEG) feature extraction, the deep learning method is applied to the automatic feature extraction of EEG signals.  ...  body motor area controls the movement of the lower limbs, the middle controls the movement of the upper limbs, the lower part controls the movement of the head, and so does the somatosensory area. (3)  ... 
doi:10.3389/fnins.2020.595084 pmid:33192282 pmcid:PMC7642128 fatcat:dql3kksmt5gijhllpe2bmx5ptq

Active triggering control of pneumatic rehabilitation gloves based on surface electromyography sensors

Yongfei Feng, Mingwei Zhong, Xusheng Wang, Hao Lu, Hongbo Wang, Pengcheng Liu, Luige Vladareanu
2021 PeerJ Computer Science  
It can trigger the hand movement based on the patient's hand movement trend, which may improve the enthusiasm and efficiency of patient training.  ...  Using the back propagation (BP) neural network, the classifier of hand movement is established.  ...  human body, which provides an extremely important means for the prediction of human limb movement trend.  ... 
doi:10.7717/peerj-cs.448 pmid:33977130 pmcid:PMC8064233 fatcat:wzeiw2krpbem5elbry7z5ahcte

Continuous decoding of human grasp kinematics using epidural and subdural signals

Robert D Flint, Joshua M Rosenow, Matthew C Tate, Marc W Slutzky
2016 Journal of Neural Engineering  
Two competing prerequisites for the widespread adoption of any hand neuroprosthesis are: accurate control over the fine details of movement, and minimized invasiveness.  ...  Epidural placement of electrodes is less invasive, and therefore may incur less risk of encephalitis or stroke than subdural placement of electrodes.  ...  We also thank Derek Kamper for the use of the Cyberglove. This research was supported by the Brain Research Foundation  ... 
doi:10.1088/1741-2560/14/1/016005 pmid:27900947 pmcid:PMC5528155 fatcat:cehi636dffcy3l746mfdyebydi
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