Control of a Robot Arm Using Decoded Joint Angles from Electrocorticograms in Primate

Shin, Duk; Kambara, Hiroyuki; Yoshimura, Natsue; Koike, Yasuharu

doi:10.1155/2018/2580165

Cited by 4 publications

(5 citation statements)

References 34 publications

(46 reference statements)

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“…Several articles also reported that γ rhythm was useful for 3D hand trajectory (Shimoda et al, 2012) and EMG prediction (Shin et al, 2012) in monkeys. Also, some reports indicated that the δ and γ bands were suitable for decoding arm motion (Chao et al, 2010), arm movement trajectories (Pistohl et al, 2008), grasp force profile (Chen et al, 2013), joint angle and muscle activity (Shin et al, 2018) based on the ECoG. Our results are in good agreement with the previous reports (Chao et al, 2010;Chen et al, 2013;Shin et al, 2012Shin et al, , 2018.…”

Section: Discussionsupporting

confidence: 91%

“…Also, some reports indicated that the δ and γ bands were suitable for decoding arm motion (Chao et al, 2010), arm movement trajectories (Pistohl et al, 2008), grasp force profile (Chen et al, 2013), joint angle and muscle activity (Shin et al, 2018) based on the ECoG. Our results are in good agreement with the previous reports (Chao et al, 2010;Chen et al, 2013;Shin et al, 2012Shin et al, , 2018. Although we identified the ECoG frequency bands with the highest performance, the best overall performance was achieved when all sensorimotor rhythms were considered.…”

Section: Discussionsupporting

confidence: 90%

“…Finally, each smoothed signal x i (t) at time t was z-score normalized to produce the final ECoG features z i (t), using Eq. 3 (Shin et al, 2018):…”

Section: Processing Brain Electrical Activity and Designing A Neural mentioning

confidence: 99%

See 2 more Smart Citations

Application of a neural interface for restoration of leg movements: Intra-spinal stimulation using the brain electrical activity in spinally injured rabbits

Heravi¹,

Maghooli²,

Rahatabad³

et al. 2020

JAB

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This study aimed to design a neural interface that extracts movement commands from the brain to generate appropriate intraspinal stimulation to restore leg movement. This study comprised four steps: (1) Recording electrocorticographic (ECoG) signals and corresponding leg movements in different trials. (2) Partial laminectomy to induce spinal cord injury (SCI) and detect motor modules in the spinal cord. (3) Delivering appropriate intra-spinal stimulation to the motor modules for restoration of the movements to those documented before SCI. (4) Development of a neural interface created by sparse linear regression (SLiR) model to detect movement commands transmitted from the brain to the modules. Correlation coefficient (CC) and normalized root mean square (NRMS) error was calculated to evaluate the neural interface effectiveness. It was found that by stimulating detected spinal cord modules, joint angle evaluated before SCI was not significantly different from that of post-SCI (P > 0.05). Based on results of SLiR model, overall CC and NRMS values were 0.63 ± 0.14 and 0.34 ± 0.16 (mean ± SD), respectively. These results indicated that ECoG data contained information about intra-spinal stimulations and the developed neural interface could produce intra-spinal stimulation based on ECoG data, for restoration of leg movements after SCI.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 90%

See 1 more Smart Citation

Application of a neural interface for restoration of leg movements: Intra-spinal stimulation using the brain electrical activity in spinally injured rabbits

Heravi¹,

Maghooli²,

Rahatabad³

et al. 2020

JAB

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“…Other NHP and human epidural datasets have been used to decode two-dimensional position of one arm (Flint et al, 2012;Marathe & Taylor, 2013), the wrist Spüler et al, 2016) or the three-dimensional trajectory of both arms using grids with an IED ranging from 1 to 10 mm. The results of these studies displayed similar, albeit slightly inferior (range of correlation coefficients for epidural r = $0.3-0.7 < subdural r = $0.5-0.9, where the reported r2 scores were translated to r; Table S3), results compared with NHP and human subdural studies that decoded trajectories of the arm (e.g., Nakanishi et al, 2017;Shin et al, 2018;Talakoub et al, 2017) and fingers (e.g., Flint et al, 2020;Xie et al, 2018). Of particular interest is a study from Flint et al (2017) who attempted to directly compare performance between epidural and subdural recordings using both standard clinical and high-density grids (4-mm IED) to decode continuous grasp kinematics.…”

Section: Offline Regression Studiesmentioning

confidence: 81%

Nine decades of electrocorticography: A comparison between epidural and subdural recordings

Branco

Geukes

Aarnoutse

et al. 2023

Eur J of Neuroscience

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In recent years, electrocorticography (ECoG) has arisen as a neural signal recording tool in the development of clinically viable neural interfaces. ECoG electrodes are generally placed below the dura mater (subdural) but can also be placed on top of the dura (epidural). In deciding which of these modalities best suits long‐term implants, complications and signal quality are important considerations. Conceptually, epidural placement may present a lower risk of complications as the dura is left intact but also a lower signal quality due to the dura acting as a signal attenuator. The extent to which complications and signal quality are affected by the dura, however, has been a matter of debate. To improve our understanding of the effects of the dura on complications and signal quality, we conducted a literature review. We inventorized the effect of the dura on signal quality, decodability and longevity of acute and chronic ECoG recordings in humans and non‐human primates. Also, we compared the incidence and nature of serious complications in studies that employed epidural and subdural ECoG. Overall, we found that, even though epidural recordings exhibit attenuated signal amplitude over subdural recordings, particularly for high‐density grids, the decodability of epidural recorded signals does not seem to be markedly affected. Additionally, we found that the nature of serious complications was comparable between epidural and subdural recordings. These results indicate that both epidural and subdural ECoG may be suited for long‐term neural signal recordings, at least for current generations of clinical and high‐density ECoG grids.

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“…The missing muscle signals are proposed to be predicted from the remaining muscles using the muscle synergy methods [24][25][26][27]. In our previous works, we developed a method for estimating myoelectric signals and arm trajectories and forces in real time from electrocorticogram (ECoG) [28][29][30][31][32] and control of robotic arms using joint angles and myoelectric signals predicted by ECoG [33]. In patients who are completely deficient and unable to measure sEMG signals, these BMI techniques could control prosthetic hands.…”

Section: Discussionmentioning

confidence: 99%

A Design of Biomimetic Prosthetic Hand

et al. 2022

Self Cite

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Many patients with upper limb defects desire myoelectric prosthetic hands, but they are still not used for some reasons. One of the most significant reasons is its external appearance, which has the discomfort caused by the structural difference between a human hand and a robotic link. The structure must be based on human anatomy to create a more natural-looking prosthesis. This study designed a biomimetic prosthetic hand with bones, ligaments, tendons, and multiple muscles based on the human musculoskeletal system. We verified the proposed prosthetic hand using the viscoelastic angle sensor to determine whether it works like a human hand. We also compared the finger force of the prosthetic hand with that of a human finger. It could be capable of controlling the angle and the stiffness of the joint by multiple extensor and flexor muscles, like humans.

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Control of a Robot Arm Using Decoded Joint Angles from Electrocorticograms in Primate

Cited by 4 publications

References 34 publications

Application of a neural interface for restoration of leg movements: Intra-spinal stimulation using the brain electrical activity in spinally injured rabbits

Application of a neural interface for restoration of leg movements: Intra-spinal stimulation using the brain electrical activity in spinally injured rabbits

Nine decades of electrocorticography: A comparison between epidural and subdural recordings

A Design of Biomimetic Prosthetic Hand

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