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Neural prosthetics

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https://www.readbyqxmd.com/read/28427290/a-real-time-method-for-decoding-the-neural-drive-to-muscles-using-single-channel-intra-muscular-emg-recordings
#1
Saeed Karimimehr, Hamid Reza Marateb, Silvia Muceli, Marjan Mansourian, Miguel Angel MaƱanas, Dario Farina
The neural command from motor neurons to muscles - sometimes referred to as the neural drive to muscle - can be identified by decomposition of electromyographic (EMG) signals. This approach can be used for inferring the voluntary commands in neural interfaces in patients with limb amputations. This paper proposes for the first time an innovative method for fully automatic and real-time intramuscular EMG (iEMG) decomposition. The method is based on online single-pass density-based clustering and adaptive classification of bivariate features, using the concept of potential measure...
March 20, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28320845/decoding-information-for-grasping-from-the-macaque-dorsomedial-visual-stream
#2
Matteo Filippini, Rossella Breveglieri, M Ali Akhras, Annalisa Bosco, Eris Chinellato, Patrizia Fattori
Neurodecoders have been developed by researchers mostly to control neuroprosthetic devices, but also to shed new light on neural functions. In this study, we show that signals representing grip configurations can be reliably decoded from neural data acquired from area V6A of the monkey medial posterior parietal cortex. Two Macaca fascicularis monkeys were trained to perform an instructed-delay reach-to-grasp task in the dark and in the light toward objects of different shapes. Population neural activity was extracted at various time intervals on vision of the objects, the delay before movement, and grasp execution...
April 19, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28269817/features-extraction-and-multi-classification-of-semg-using-a-gpu-accelerated-ga-mlp-hybrid-algorithm
#3
Weizhen Luo, Zhongnan Zhang, Tingxi Wen, Chunfeng Li, Ziheng Luo
BACKGROUND: Surface electromyography (sEMG) signal is the combined effect of superficial muscle EMG and neural electrical activity. In recent years, researchers did large amount of human-machine system studies by using the physiological signals as control signals. OBJECTIVE: To develop and test a new multi-classification method to improve performance of analyzing sEMG signals based on public sEMG dataset. METHODS: First, ten features were selected as candidate features...
2017: Journal of X-ray Science and Technology
https://www.readbyqxmd.com/read/28269552/ecog-data-analyses-to-inform-closed-loop-bci-experiments-for-speech-based-prosthetic-applications
#4
Tejaswy Pailla, Werner Jiang, Benjamin Dichter, Edward F Chang, Vikash Gilja
Brain Computer Interfaces (BCIs) assist individuals with motor disabilities by enabling them to control prosthetic devices with their neural activity. Performance of closed-loop BCI systems can be improved by using design strategies that leverage structured and task-relevant neural activity. We use data from high density electrocorticography (ECoG) grids implanted in three subjects to study sensory-motor activity during an instructed speech task in which the subjects vocalized three cardinal vowel phonemes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269486/tuning-electrical-stimulation-for-thalamic-visual-prosthesis-an-autoencoder-based-approach
#5
Amr Jawwad, Hossam H Abolfotuh, Bassem Abdullah, Hani M K Mahdi, Seif Eldawlatly
Visual prosthesis holds hope of vision restoration for millions with retinal degenerative diseases. Machine learning techniques such as artificial neural networks could help in improving prosthetic devices as they could learn how the brain encodes information and imitate that code. This paper introduces an autoencoder-based approach for tuning thalamic visual prostheses. The objective of the proposed approach is to estimate electrical stimuli that are equivalent to a given natural visual stimulus, in a way such that they both elicit responses that are as similar as possible when introduced to a Lateral Geniculate Nucleus (LGN) population...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269405/24-dof-emg-controlled-hybrid-actuated-prosthetic-hand
#6
A Atasoy, E Kaya, E Toptas, S Kuchimov, E Kaplanoglu, M Ozkan
A complete mechanical design concept of an electromyogram (EMG) controlled hybrid prosthetic hand, with 24 degree of freedom (DOF) anthropomorphic structure is presented. Brushless DC motors along with Shape Memory Alloy (SMA) actuators are used to achieve dexterous functionality. An 8 channel EMG is used for detecting 7 basic hand gestures for control purposes. The prosthetic hand will be integrated with the Neural Network (NNE) based controller in the next phase of the study.
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269402/myoelectric-intuitive-control-and-transcutaneous-electrical-stimulation-of-the-forearm-for-vibrotactile-sensation-feedback-applied-to-a-3d-printed-prosthetic-hand
#7
Enrique I Germany, Esteban J Pino, Pablo E Aqueveque
This paper presents the development of a myoelectric prosthetic hand based on a 3D printed model. A myoelectric control strategy based on artificial neural networks is implemented on a microcontroller for online position estimation. Position estimation performance achieves a correlation index of 0.78. Also a study involving transcutaneous electrical stimulation was performed to provide tactile feedback. A series of stimulations with controlled parameters were tested on five able-body subjects. A single channel stimulator was used, positioning the electrodes 8 cm on the wrist over the ulnar and median nerve...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269360/development-of-high-impedance-measurement-system-for-water-leakage-detection-in-implantable-neuroprosthetic-devices
#8
Aziz Yousif, Shawn K Kelly
There has been a push for a greater number of channels in implantable neuroprosthetic devices; but, that number has largely been limited by current hermetic packaging technology. Microfabricated packaging is becoming reality, but a standard testing system is needed to prepare these devices for clinical trials. Impedance measurements of electrodes built into the packaging layers may give an early warning of device failure and predict device lifetime. Because the impedance magnitudes of such devices can be on the order of gigaohms, a versatile system was designed to accommodate ultra-high impedances and allow future integrated circuit implementation in current neural prosthetic technologies...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269307/tolerance-of-neural-decoding-errors-for-powered-artificial-legs-a-pilot-study
#9
Fan Zhang, Ming Liu, He Huang
Neural-machine interface (NMI) decoding errors challenge the clinical value of neural control of powered artificial legs, because these errors can dangerously disturb the user's walking balance, cause stumbles or falls, and thus threaten the user's confidence and safety in prosthesis use. Although extensive research efforts have been made to minimize the NMI decoding error rate, none of the current approaches can completely eliminate the errors in NMI. This study aimed at improving the robustness of prosthesis control system against neural decoding errors by introducing a fault-tolerant control (FTC) strategy...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269305/biologically-inspired-multi-layered-synthetic-skin-for-tactile-feedback-in-prosthetic-limbs
#10
Luke Osborn, Harrison Nguyen, Joseph Betthauser, Rahul Kaliki, Nitish Thakor
The human body offers a template for many state-of-the-art prosthetic devices and sensors. In this work, we present a novel, sensorized synthetic skin that mimics the natural multi-layered nature of mechanoreceptors found in healthy glabrous skin to provide tactile information. The multi-layered sensor is made up of flexible piezoresistive textiles that act as force sensitive resistors (FSRs) to convey tactile information, which are embedded within a silicone rubber to resemble the compliant nature of human skin...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268714/investigation-on-the-hermeticity-of-an-implantable-package-with-32-feedthroughs-for-neural-prosthetic-applications
#11
Lorenzo Bisoni, Matthias Mueller, Paul Cvancara, Caterina Carboni, Roberto Puddu, Luigi Raffo, Massimo Barbaro, Thomas Stieglitz
This paper presents an implantable package aimed at hosting a bidirectional neural interface for neural prosthetic applications. The package has been conceived to minimize the invasivity for the patient, for this reason a cylindrical container with an outer diameter of 7 mm and a length of 21 mm has been designed. The package, realized in alumina (Al2O3), presents 32 hermetic feedthroughs located at the top and bottom base of the cylinder. The hermetic housing has been assembled using a low-temperature soldering method based on a previous platinum/gold (Pt/Au) metallization of the ceramic parts...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268676/an-implantable-designed-for-human-use-peripheral-nerve-stimulation-and-recording-system-for-advanced-prosthetics
#12
John R Lachapelle, Caroline K Bjune, Alexander L Kindle, Andrew Czarnecki, John R Burns, Julianne E Grainger, Carlos A Segura, Brian D Nugent, Tirunelveli S Sriram, Philip D Parks, Edward Keefer, Jonathan Cheng
Complex suture prostheses that deliver sensory and position feedback require a more sophisticated integration with the human user. Here a micro-size active implantable system that provides many-degree-of-freedom neural feedback in both sensory stimulation and motor control is shown, as one potential human-use solution in DARPA's HAPTIX program. Various electrical and mechanical challenge and solutions in meeting both sensory /motor performance as well as ISO 14708 FDA-acceptable human use in an aspirin-size active implementation are discussed...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268628/idle-state-classification-using-spiking-activity-and-local-field-potentials-in-a-brain-computer-interface
#13
Jordan J Williams, Rex N Tien, Yoh Inoue, Andrew B Schwartz
Previous studies of intracortical brain-computer interfaces (BCIs) have often focused on or compared the use of spiking activity and local field potentials (LFPs) for decoding kinematic movement parameters. Conversely, using these signals to detect the initial intention to use a neuroprosthetic device or not has remained a relatively understudied problem. In this study, we examined the relative performance of spiking activity and LFP signals in detecting discrete state changes in attention regarding a user's desire to actively control a BCI device...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28261002/automatic-grasp-selection-using-a-camera-in-a-hand-prosthesis
#14
Joseph DeGol, Aadeel Akhtar, Bhargava Manja, Timothy Bretl
In this paper, we demonstrate how automatic grasp selection can be achieved by placing a camera in the palm of a prosthetic hand and training a convolutional neural network on images of objects with corresponding grasp labels. Our labeled dataset is built from common graspable objects curated from the ImageNet dataset and from images captured from our own camera that is placed in the hand. We achieve a grasp classification accuracy of 93.2% and show through real-time grasp selection that using a camera to augment current electromyography controlled prosthetic hands may be useful...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227807/ecog-data-analyses-to-inform-closed-loop-bci-experiments-for-speech-based-prosthetic-applications
#15
Tejaswy Pailla, Werner Jiang, Benjamin Dichter, Edward F Chang, Vikash Gilja, Tejaswy Pailla, Werner Jiang, Benjamin Dichter, Edward F Chang, Vikash Gilja, Vikash Gilja, Werner Jiang, Tejaswy Pailla, Benjamin Dichter, Edward F Chang
Brain Computer Interfaces (BCIs) assist individuals with motor disabilities by enabling them to control prosthetic devices with their neural activity. Performance of closed-loop BCI systems can be improved by using design strategies that leverage structured and task-relevant neural activity. We use data from high density electrocorticography (ECoG) grids implanted in three subjects to study sensory-motor activity during an instructed speech task in which the subjects vocalized three cardinal vowel phonemes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227738/tuning-electrical-stimulation-for-thalamic-visual-prosthesis-an-autoencoder-based-approach
#16
Amr Jawwad, Hossam H Abolfotuh, Bassem Abdullah, Hani M K Mahdi, Seif Eldawlatly, Amr Jawwad, Hossam H Abolfotuh, Bassem Abdullah, Hani M K Mahdi, Seif Eldawlatly, Amr Jawwad, Hani M K Mahdi, Bassem Abdullah, Seif Eldawlatly, Hossam H Abolfotuh
Visual prosthesis holds hope of vision restoration for millions with retinal degenerative diseases. Machine learning techniques such as artificial neural networks could help in improving prosthetic devices as they could learn how the brain encodes information and imitate that code. This paper introduces an autoencoder-based approach for tuning thalamic visual prostheses. The objective of the proposed approach is to estimate electrical stimuli that are equivalent to a given natural visual stimulus, in a way such that they both elicit responses that are as similar as possible when introduced to a Lateral Geniculate Nucleus (LGN) population...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227648/24-dof-emg-controlled-hybrid-actuated-prosthetic-hand
#17
A Atasoy, E Kaya, E Toptas, S Kuchimov, E Kaplanoglu, M Ozkan, A Atasoy, E Kaya, E Toptas, S Kuchimov, E Kaplanoglu, M Ozkan, S Kuchimov, A Atasoy, M Ozkan, E Kaplanoglu, E Kaya, E Toptas
A complete mechanical design concept of an electromyogram (EMG) controlled hybrid prosthetic hand, with 24 degree of freedom (DOF) anthropomorphic structure is presented. Brushless DC motors along with Shape Memory Alloy (SMA) actuators are used to achieve dexterous functionality. An 8 channel EMG is used for detecting 7 basic hand gestures for control purposes. The prosthetic hand will be integrated with the Neural Network (NNE) based controller in the next phase of the study.
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227645/myoelectric-intuitive-control-and-transcutaneous-electrical-stimulation-of-the-forearm-for-vibrotactile-sensation-feedback-applied-to-a-3d-printed-prosthetic-hand
#18
Enrique I Germany, Esteban J Pino, Pablo E Aqueveque, Enrique I Germany, Esteban J Pino, Pablo E Aqueveque, Enrique I Germany, Pablo E Aqueveque, Esteban J Pino
This paper presents the development of a myoelectric prosthetic hand based on a 3D printed model. A myoelectric control strategy based on artificial neural networks is implemented on a microcontroller for online position estimation. Position estimation performance achieves a correlation index of 0.78. Also a study involving transcutaneous electrical stimulation was performed to provide tactile feedback. A series of stimulations with controlled parameters were tested on five able-body subjects. A single channel stimulator was used, positioning the electrodes 8 cm on the wrist over the ulnar and median nerve...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227602/development-of-high-impedance-measurement-system-for-water-leakage-detection-in-implantable-neuroprosthetic-devices
#19
Aziz Yousif, Shawn K Kelly, Aziz Yousif, Shawn K Kelly, Shawn K Kelly, Aziz Yousif
There has been a push for a greater number of channels in implantable neuroprosthetic devices; but, that number has largely been limited by current hermetic packaging technology. Microfabricated packaging is becoming reality, but a standard testing system is needed to prepare these devices for clinical trials. Impedance measurements of electrodes built into the packaging layers may give an early warning of device failure and predict device lifetime. Because the impedance magnitudes of such devices can be on the order of gigaohms, a versatile system was designed to accommodate ultra-high impedances and allow future integrated circuit implementation in current neural prosthetic technologies...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227544/tolerance-of-neural-decoding-errors-for-powered-artificial-legs-a-pilot-study
#20
Fan Zhang, Ming Liu, He Huang, Fan Zhang, Ming Liu, He Huang, He Huang, Ming Liu, Fan Zhang
Neural-machine interface (NMI) decoding errors challenge the clinical value of neural control of powered artificial legs, because these errors can dangerously disturb the user's walking balance, cause stumbles or falls, and thus threaten the user's confidence and safety in prosthesis use. Although extensive research efforts have been made to minimize the NMI decoding error rate, none of the current approaches can completely eliminate the errors in NMI. This study aimed at improving the robustness of prosthesis control system against neural decoding errors by introducing a fault-tolerant control (FTC) strategy...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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