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brain interfaced controlled arm

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https://www.readbyqxmd.com/read/29674949/effect-of-different-movement-speed-modes-on-human-action-observation-an-eeg-study
#1
Tian-Jian Luo, Jitu Lv, Fei Chao, Changle Zhou
Action observation (AO) generates event-related desynchronization (ERD) suppressions in the human brain by activating partial regions of the human mirror neuron system (hMNS). The activation of the hMNS response to AO remains controversial for several reasons. Therefore, this study investigated the activation of the hMNS response to a speed factor of AO by controlling the movement speed modes of a humanoid robot's arm movements. Since hMNS activation is reflected by ERD suppressions, electroencephalography (EEG) with BCI analysis methods for ERD suppressions were used as the recording and analysis modalities...
2018: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/29616982/a-fast-intracortical-brain-machine-interface-with-patterned-optogenetic-feedback
#2
Aamir Abbasi, Dorian Goueytes, Daniel E Shulz, Valerie Ego-Stengel, Luc Estebanez
OBJECTIVE: The development of brain-machine interfaces (BMIs) brings a new perspective to patients with a loss of autonomy. By combining online recordings of brain activity with a decoding algorithm, patients can learn to control a robotic arm in order to perform simple actions. However, in contrast to the vast amounts of somatosensory information channeled by limbs to the brain, current BMIs are devoid of touch and force sensors. Patients must therefore rely solely on vision and audition, which are maladapted to the control of a prosthesis...
April 4, 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29381054/mesh-nanoelectronics-seamless-integration-of-electronics-with-tissues
#3
Xiaochuan Dai, Guosong Hong, Teng Gao, Charles M Lieber
Nanobioelectronics represents a rapidly developing field with broad-ranging opportunities in fundamental biological sciences, biotechnology, and medicine. Despite this potential, seamless integration of electronics has been difficult due to fundamental mismatches, including size and mechanical properties, between the elements of the electronic and living biological systems. In this Account, we discuss the concept, development, key demonstrations, and future opportunities of mesh nanoelectronics as a general paradigm for seamless integration of electronics within synthetic tissues and live animals...
January 30, 2018: Accounts of Chemical Research
https://www.readbyqxmd.com/read/29357477/emergent-coordination-underlying-learning-to-reach-to-grasp-with-a-brain-machine-interface
#4
Mukta Vaidya, Karthikeyan Balasubramanian, Joshua Southerland, Islam Badreldin, Ahmed Eleryan, Kelsey Shattuck, Suchin Gururangan, Marc Slutzky, Leslie Osborne, Andrew Fagg, Karim Oweiss, Nicholas G Hatsopoulos
The development of coordinated reach-to-grasp movement has been well studied in infants and children. However, the role of motor cortex during this development is unclear because it is difficult to study in humans. We took the approach of using a brain-machine interface (BMI) paradigm in rhesus macaques with prior therapeutic amputations to examine the emergence of novel, coordinated reach to grasp. Previous research has shown that after amputation, the cortical area previously involved in the control of the lost limb undergoes reorganization, but prior BMI work has largely relied on finding neurons that already encode specific movement-related information...
April 1, 2018: Journal of Neurophysiology
https://www.readbyqxmd.com/read/29209023/motor-cortical-activity-changes-during-neuroprosthetic-controlled-object-interaction
#5
John E Downey, Lucas Brane, Robert A Gaunt, Elizabeth C Tyler-Kabara, Michael L Boninger, Jennifer L Collinger
Brain-computer interface (BCI) controlled prosthetic arms are being developed to restore function to people with upper-limb paralysis. This work provides an opportunity to analyze human cortical activity during complex tasks. Previously we observed that BCI control became more difficult during interactions with objects, although we did not quantify the neural origins of this phenomena. Here, we investigated how motor cortical activity changed in the presence of an object independently of the kinematics that were being generated using intracortical recordings from two people with tetraplegia...
December 5, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29192609/superior-arm-movement-decoding-from-cortex-with-a-new-unsupervised-learning-algorithm
#6
Joseph G Makin, Joseph E O'Doherty, Mariana M B Cardoso, Philip N Sabes
OBJECTIVE: The aim of this work is to improve the state of the art for motor-control with a brain-machine interface (BMI). BMIs use neurological recording devices and decoding algorithms to transform brain activity directly into real-time control of a machine, archetypically a robotic arm or a cursor. The standard procedure treats neural activity-vectors of spike counts in small temporal windows-as noisy observations of the kinematic state (position, velocity, acceleration) of the fingertip...
April 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29180616/changes-in-cortical-network-connectivity-with-long-term-brain-machine-interface-exposure-after-chronic-amputation
#7
Karthikeyan Balasubramanian, Mukta Vaidya, Joshua Southerland, Islam Badreldin, Ahmed Eleryan, Kazutaka Takahashi, Kai Qian, Marc W Slutzky, Andrew H Fagg, Karim Oweiss, Nicholas G Hatsopoulos
Studies on neural plasticity associated with brain-machine interface (BMI) exposure have primarily documented changes in single neuron activity, and largely in intact subjects. Here, we demonstrate significant changes in ensemble-level functional connectivity among primary motor cortical (MI) neurons of chronically amputated monkeys exposed to control a multiple-degree-of-freedom robot arm. A multi-electrode array was implanted in M1 contralateral or ipsilateral to the amputation in three animals. Two clusters of stably recorded neurons were arbitrarily assigned to control reach and grasp movements, respectively...
November 27, 2017: Nature Communications
https://www.readbyqxmd.com/read/29163123/closed-loop-hybrid-gaze-brain-machine-interface-based-robotic-arm-control-with-augmented-reality-feedback
#8
Hong Zeng, Yanxin Wang, Changcheng Wu, Aiguo Song, Jia Liu, Peng Ji, Baoguo Xu, Lifeng Zhu, Huijun Li, Pengcheng Wen
Brain-machine interface (BMI) can be used to control the robotic arm to assist paralysis people for performing activities of daily living. However, it is still a complex task for the BMI users to control the process of objects grasping and lifting with the robotic arm. It is hard to achieve high efficiency and accuracy even after extensive trainings. One important reason is lacking of sufficient feedback information for the user to perform the closed-loop control. In this study, we proposed a method of augmented reality (AR) guiding assistance to provide the enhanced visual feedback to the user for a closed-loop control with a hybrid Gaze-BMI, which combines the electroencephalography (EEG) signals based BMI and the eye tracking for an intuitive and effective control of the robotic arm...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/29160240/remapping-cortical-modulation-for-electrocorticographic-brain-computer-interfaces-a-somatotopy-based-approach-in-individuals-with-upper-limb-paralysis
#9
Alan D Degenhart, Shivayogi V Hiremath, Ying Yang, Stephen Foldes, Jennifer L Collinger, Michael Boninger, Elizabeth C Tyler-Kabara, Wei Wang
OBJECTIVE: Brain-computer interface (BCI) technology aims to provide individuals with paralysis a means to restore function. Electrocorticography (ECoG) uses disc electrodes placed on either the surface of the dura or the cortex to record field potential activity. ECoG has been proposed as a viable neural recording modality for BCI systems, potentially providing stable, long-term recordings of cortical activity with high spatial and temporal resolution. Previously we have demonstrated that a subject with spinal cord injury (SCI) could control an ECoG-based BCI system with up to three degrees of freedom (Wang et al 2013 PLoS One)...
April 2018: Journal of Neural Engineering
https://www.readbyqxmd.com/read/29059844/multiscale-decoding-for-reliable-brain-machine-interface-performance-over-time
#10
Han-Lin Hsieh, Yan T Wong, Bijan Pesaran, Maryam M Shanechi
Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28948168/towards-rehabilitation-robotics-off-the-shelf-bci-control-of-anthropomorphic-robotic-arms
#11
Alkinoos Athanasiou, Ioannis Xygonakis, Niki Pandria, Panagiotis Kartsidis, George Arfaras, Kyriaki Rafailia Kavazidi, Nicolas Foroglou, Alexander Astaras, Panagiotis D Bamidis
Advances in neural interfaces have demonstrated remarkable results in the direction of replacing and restoring lost sensorimotor function in human patients. Noninvasive brain-computer interfaces (BCIs) are popular due to considerable advantages including simplicity, safety, and low cost, while recent advances aim at improving past technological and neurophysiological limitations. Taking into account the neurophysiological alterations of disabled individuals, investigating brain connectivity features for implementation of BCI control holds special importance...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28887545/human-to-human-closed-loop-control-based-on-brain-to-brain-interface-and-muscle-to-muscle-interface
#12
M Ebrahim M Mashat, Guangye Li, Dingguo Zhang
Novel communication techniques have always been fascinating for humankind. This pilot study presents an approach to human interaction by combining direct brain-to-brain interface (BBI) and muscle-to-muscle interface (MMI) in a closed-loop pattern. In this system, artificial paths (data flows) functionally connect natural paths (nerves). The intention from one subject (sender) is recognized using electroencephalography (EEG) based brain-computer interface (BCI), which is sent out to trigger transcranial magnetic stimulation (TMS) on the other subject (receiver) and induce hand motion; meanwhile TMS results in a significant change on the motor evoked potentials (MEP) recorded by electromyography (EMG) of the receiver's arm, which triggers functional electrical stimulation (FES) applied to the sender's arm and generates hand motion...
September 8, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28873855/usability-of-jaco-arm-interfaces-designed-with-a-user-centred-design-method
#13
Damien Sauzin, Nadine Vigouroux, Frédéric Vella
Utility, usability and acceptability of robotic arm for helping motor impairment people (quadriplegic, muscular dystrophy, Amyotrophic Lateral Sclerosis) must be improved. The robotic arm JACO of company ©Kinova is controlled by a joystick, sometimes unusable by patients. The IRIT laboratory has designed three types of virtual interfaces: one based on virtual keyboards and two others on Pie Menu concepts. These interfaces were designed by mean of a user centred design approach (UCDA) including brain storming, focus group, iterative prototyping and trials...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28860986/classification-of-movement-and-inhibition-using-a-hybrid-bci
#14
Jennifer Chmura, Joshua Rosing, Steven Collazos, Shikha J Goodwin
Brain-computer interfaces (BCIs) are an emerging technology that are capable of turning brain electrical activity into commands for an external device. Motor imagery (MI)-when a person imagines a motion without executing it-is widely employed in BCI devices for motor control because of the endogenous origin of its neural control mechanisms, and the similarity in brain activation to actual movements. Challenges with translating a MI-BCI into a practical device used outside laboratories include the extensive training required, often due to poor user engagement and visual feedback response delays; poor user flexibility/freedom to time the execution/inhibition of their movements, and to control the movement type (right arm vs...
2017: Frontiers in Neurorobotics
https://www.readbyqxmd.com/read/28827605/neuroprosthetic-enabled-control-of-graded-arm-muscle-contraction-in-a-paralyzed-human
#15
David A Friedenberg, Michael A Schwemmer, Andrew J Landgraf, Nicholas V Annetta, Marcia A Bockbrader, Chad E Bouton, Mingming Zhang, Ali R Rezai, W Jerry Mysiw, Herbert S Bresler, Gaurav Sharma
Neuroprosthetics that combine a brain computer interface (BCI) with functional electrical stimulation (FES) can restore voluntary control of a patients' own paralyzed limbs. To date, human studies have demonstrated an "all-or-none" type of control for a fixed number of pre-determined states, like hand-open and hand-closed. To be practical for everyday use, a BCI-FES system should enable smooth control of limb movements through a continuum of states and generate situationally appropriate, graded muscle contractions...
August 21, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28821649/effector-invariant-movement-encoding-in-the-human-motor-system
#16
Shlomi Haar, Ilan Dinstein, Ilan Shelef, Opher Donchin
Ipsilateral motor areas of cerebral cortex are active during arm movements and even reliably predict movement direction. Is coding similar during ipsilateral and contralateral movements? If so, is it in extrinsic (world-centered) or intrinsic (joint-configuration) coordinates? We addressed these questions by examining the similarity of multivoxel fMRI patterns in visuomotor cortical regions during unilateral reaching movements with both arms. The results of three complementary analyses revealed that fMRI response patterns were similar across right and left arm movements to identical targets (extrinsic coordinates) in visual cortices, and across movements with equivalent joint-angles (intrinsic coordinates) in motor cortices...
September 13, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28813929/soft-brain-machine-interfaces-for-assistive-robotics-a-novel-control-approach
#17
Lucia Schiatti, Jacopo Tessadori, Giacinto Barresi, Leonardo S Mattos, Arash Ajoudani
Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual functions must be exploited for the control of the robot movements and the underlying dynamic interaction through intuitive and effective human-robot interfaces. Towards this end, this work aims at exploring the potential of a novel Soft Brain-Machine Interface (BMI), suitable for dynamic execution of remote manipulation tasks for a wide range of patients...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28722685/neural-control-of-finger-movement-via-intracortical-brain-machine-interface
#18
Z T Irwin, K E Schroeder, P P Vu, A J Bullard, D M Tat, C S Nu, A Vaskov, S R Nason, D E Thompson, J N Bentley, P G Patil, C A Chestek
OBJECTIVE: Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques. APPROACH: In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets...
December 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28660211/noninvasive-electroencephalogram-based-control-of-a-robotic-arm-for-writing-task-using-hybrid-bci-system
#19
Qiang Gao, Lixiang Dou, Abdelkader Nasreddine Belkacem, Chao Chen
A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, "teeth clenching" state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control. MI-based BCI was used as single-pole double throw brain switch (SPDTBS). By combining the SPDTBS with 4-class SSEVP-based BCI, movement of robotic arm was controlled in three-dimensional (3D) space...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28553694/investigation-of-different-classifiers-and-channel-configurations-of-a-mobile-p300-based-brain-computer-interface
#20
Simone A Ludwig, Jun Kong
Innovative methods and new technologies have significantly improved the quality of our daily life. However, disabled people, for example those that cannot use their arms and legs anymore, often cannot benefit from these developments, since they cannot use their hands to interact with traditional interaction methods (such as mouse or keyboard) to communicate with a computer system. A brain-computer interface (BCI) system allows such a disabled person to control an external device via brain waves. Past research mostly dealt with static interfaces, which limit users to a stationary location...
December 2017: Medical & Biological Engineering & Computing
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