2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)最新文献_第2页

Modulation of Intracortical S1 Responses Following Peripheral Nerve High-Frequency Electrical Stimulation in Danish Landrace Pigs 丹麦长白猪周围神经高频电刺激后皮质内S1反应的调节

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123841

T. Janjua, T. N. Nielsen, F. R. Andreis, S. Meijs, W. Jensen

{"title":"Modulation of Intracortical S1 Responses Following Peripheral Nerve High-Frequency Electrical Stimulation in Danish Landrace Pigs","authors":"T. Janjua, T. N. Nielsen, F. R. Andreis, S. Meijs, W. Jensen","doi":"10.1109/NER52421.2023.10123841","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123841","url":null,"abstract":"Long-term potentiation (LTP) has been extensively studied with rodents and human subjects to understand pain mechanisms. This phenomenon remains relatively less explored in pigs, even though pigs present a suitable translational model for neurophysiological research. This study aimed to investigate changes in the spike activity in the primary somatosensory cortex (S1) in response to spinal LTP-like neuroplasticity induced by high-frequency electrical stimulation (HFS) in Danish landrace pigs. Six animals were investigated (two controls and four interventions). A 16-channel multi-electrode array was implanted into the S1. A tripolar cuff was placed around the ulnar nerve. HFS (15 mA, 100 Hz, 1 ms) was induced on the ulnar nerve branches to induce LTP-like neuroplasticity, followed by non-nociceptive stimulation to probe the S1 response. Peristimulus time histograms (PSTHs) were constructed based on the neuronal spikes detected from S1. For the intervention group, the PSTH showed a significant increase in the area under the curve (AVC) 45 min (T2 phase) after applying the HFS. These results were in line with findings based on local-field potentials, i.e., the cortical excitability increased immediately after intervention and became significantly greater during the T2 phase. The result of this study is believed to be an essential contribution to developing a translational, large-animal model of LTP-like pain to bridge research between animal models and clinical applications.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131455071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synthesizing Speech by Decoding Intracortical Neural Activity from Dorsal Motor Cortex 解码背侧运动皮层皮层内神经活动的语音合成

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123880

M. Wairagkar, L. Hochberg, D. Brandman, S. Stavisky

{"title":"Synthesizing Speech by Decoding Intracortical Neural Activity from Dorsal Motor Cortex","authors":"M. Wairagkar, L. Hochberg, D. Brandman, S. Stavisky","doi":"10.1109/NER52421.2023.10123880","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123880","url":null,"abstract":"Losing the ability to speak due to brain injury or neurodegenerative diseases such as ALS can be debilitating. Brain-computer interfaces could potentially provide affected individuals a fast and intuitive way to communicate by decoding speech-related neural activity into a computer-synthesized voice. Current intracortical BCIs for communication using handwriting or point-and-click typing are substantially slower than natural speech and do not capture the full expressive range of speech. Recent studies have identified speech features from ECoG and sEEG recordings; however, intelligible speech synthesis has not yet been demonstrated. Our previous work has shown speech-related patterns in intracortical recordings from dorsal (arm/hand) motor cortex that enabled discrete word/phoneme classification. This motivates exploring an intracortical approach for continuous voice synthesis. Here, we present a neural decoding framework to synthesize speech by directly translating neural activity recorded from human motor cortex using intracortical multielectrode arrays into a low-dimensional speech feature space from which voice is synthesized.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132324913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Distributed Tactile Sensors for Palmar Surfaces of Prosthetic Hands 假手手掌表面的分布式触觉传感器

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123819

Hoang Truong, N. Correll, Jacob L. Segil

{"title":"Distributed Tactile Sensors for Palmar Surfaces of Prosthetic Hands","authors":"Hoang Truong, N. Correll, Jacob L. Segil","doi":"10.1109/NER52421.2023.10123819","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123819","url":null,"abstract":"Sensory feedback provided by prosthetic hands shows promise in increasing functional abilities and promoting embodiment of the prosthetic device. However, sensory feedback is limited based on where sensors are placed on the prosthetic device and has mainly focused on sensorizing the fingertips. Here we describe distributed tactile sensors for the palmar surfaces of prosthetic hands. We believe a sensing system that can detect interactions across the palmar surfaces in addition to the fingertips will further improve the experience for the prosthetic user and may increase embodiment of the device as well. This work details the design of a compliant distributed sensor which consists of PiezoResistive and PiezoElectric layers to produce a robust force measurement of both static and dynamic loads. This assembled sensor system is easy to customize to cover different areas of the prosthetic hand, simple to scale up, and flexible to different fabrication form-factors. The experimental results detail a load estimation accuracy of 95.4% and sensor response time of less than 200ms. Cycle tests of each sensor shows a drifting of within 10% of sensing capability under load and 6.37% in a no-load longitudinal test. These validation experiments reinforce the ability of the DualPiezo structure to provide a valuable sensor design for the palmar surfaces of prosthetic hands.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130718702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Transfer Learning-based Model for Individualized Clustered Seizure Prediction Using Intracranial EEG 基于迁移学习的颅内脑电图个体化聚类癫痫预测模型

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123862

Yurui Cao, Krishnakant V. Saboo, V. Kremen, V. Sladky, N. Gregg, P. Arnold, S. Pappu, P. Karoly, D. Freestone, M. Cook, G. Worrell, Ravishankar K. Iyer

{"title":"A Transfer Learning-based Model for Individualized Clustered Seizure Prediction Using Intracranial EEG","authors":"Yurui Cao, Krishnakant V. Saboo, V. Kremen, V. Sladky, N. Gregg, P. Arnold, S. Pappu, P. Karoly, D. Freestone, M. Cook, G. Worrell, Ravishankar K. Iyer","doi":"10.1109/NER52421.2023.10123862","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123862","url":null,"abstract":"Clustered seizures are prevalent among people with epilepsy and can increase mortality risk. While past research has mainly focused on seizure cluster detection, a few recent studies predict seizure clustering by determining whether there will be more seizures in the next 24 hours after the termination of a seizure. Moreover, personalized prediction of clustered seizures in the presence of limited and imbalanced data remains an outstanding problem. We address this problem using a novel transfer learning model to predict seizure clustering within a 24-hour window. To compensate for the limited and imbalanced available data, for each target patient, the model combines trained individual-level predictive models of the target patient and two other patients whose seizure patterns are similar to those of the target patient. Approximate Kullback-Leibler divergence is used to measure the similarity between patients in high-dimensional data. The proposed model is evaluated on a long-term ambulatory intracranial EEG dataset. Compared with individualized predictive models, the proposed model improves F1 scores for patients with limited or highly imbalanced data by up to 51.0%. In addition, the proposed model achieves an average F1 score of 0.702 and an area under the precision-recall curve of 0.809. Our model can be clinically helpful in guiding the treatment of clustered seizures.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132162437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Downstream Effects of Photoreceptor Degeneration and Electrical Retinal Stimulation on Visual Cortex Macrostructure and Function 光感受器变性和视网膜电刺激对视觉皮层宏观结构和功能的下游影响

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123879

Beomseo Koo, James D. Weiland

引用次数: 0

Frontal gamma as a marker of effective training during neurofeedback to improve memory in patients with mild cognitive impairment 额叶伽玛作为轻度认知障碍患者在神经反馈过程中有效训练以改善记忆的标志

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123807

Yayu Lin, I-Wei Shu, Fiza Singh

{"title":"Frontal gamma as a marker of effective training during neurofeedback to improve memory in patients with mild cognitive impairment","authors":"Yayu Lin, I-Wei Shu, Fiza Singh","doi":"10.1109/NER52421.2023.10123807","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123807","url":null,"abstract":"Currently, more than 23 million people in the United States are affected by early Alzheimer's disease (AD), mild cognitive impairment (MCI), or subjective cognitive decline (SCD). Despite widespread awareness of the high costs to individuals and communities, treatment options for those at risk of, or with, AD is limited. To help meet this urgent need for new treatments, we identified frontal gamma activity, a neural signature of optimal memory function, as a promising treatment target. More specifically, patients with AD and MCI exhibit deficient frontal gamma activity, which we can help restore using electroencephalographic (EEG) neurofeedback (NFB). In brief, our MATLAB/EEGLAB-based brain-computer interface (BCI) converts frontal gamma coherence into re-inforcement signals, enabling patients with MCI to directly modulate frontal gamma activity. Preliminary results from our current double-blind, placebo-controlled randomized clinical trial (RCT) demonstrate that, compared to patients receiving placebo-NFB, patients receiving active-NFB (gamma-NFB, 30 min, 2/week, 12 weeks) exhibit significantly-increased frontal gamma coherence during training. Furthermore, among active gamma-NFB patients, baseline/pre-NFB gamma power at F4 (but not at other electrodes) significantly correlates with slope of training-related increases in frontal gamma coherence. These results support a model where, in patients with MCI, frontal gamma EEG-NFB specifically engages and increases frontal gamma activity. Furthermore, baseline/pre-NFB gamma power at F4 may serve as a predictor of training efficacy, a promising step towards more efficient and personalized treatment protocols for improving memory in patients with MCI or related neuropsychiatric difficulties.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128365073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Freeform Stimulator (FS) Implant Design for Non-Pulsatile Arbitrary Waveform Neuromodulation 用于非脉动任意波形神经调节的自由形式刺激器(FS)植入设计

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123811

Alexandra Cheng, Paul Adkisson, Chaojun Cheng, G. Fridman

{"title":"Freeform Stimulator (FS) Implant Design for Non-Pulsatile Arbitrary Waveform Neuromodulation","authors":"Alexandra Cheng, Paul Adkisson, Chaojun Cheng, G. Fridman","doi":"10.1109/NER52421.2023.10123811","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123811","url":null,"abstract":"In contrast to conventional pulsatile stimulation that evokes action potentials in phase with pulse presentations, ionic direct current (iDC) or low frequency current is capable of excitation, inhibition, sensitization to synaptic input, and synaptic connectivity control. Despite its versatility, iDC cannot be delivered via metal electrodes for safety concerns such as pH changes, electrolysis, and corrosion. Our lab has previously proposed a microfluidic device design that rectifies pulses delivered safely to embedded metal electrodes into iDC. However, this design lacked reliability and consistency that were linked to using fluid electrolyte as the ionic charge carrier. Here, we overcame these limitations by designing a microfluidic chip not filled with liquid but with agar gel as the means of ionic conduction. The device has two plungers coated with agar gel that act as ionic switches to control the direction of ionic current flow. When the plungers are closed, the agar on the plunger and the agar on the chip connect to create a gel bridge for the ionic current to pass through. Movement of the plungers is actuated with a $50mu m$ diameter nitinol shape memory alloy wire (Flexinol HT) which shrinks when activated with electrical current. To open the plungers, the device has a silicone ring on the plunger that functions as a spring to pull the plungers back to the open position after the nitinol wire is deactivated. With this design, the device can deliver up to 100 $mu mathrm{A}$ of iDC and has a reduced form factor of 75% from the previous generation, to facilitate behavioral animal experiments with FS. We fabricated three devices to compare their performance. The switches had conducting and non-conducting impedances of $3.62 kOmegapmtheta.43kOmega$ and $980 kOmegapm 12kOmega$ respectively. We also simulated the output characteristics of the FS by using actual impedance data collected from the devices.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130738263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

First Demonstration of Nociceptive and Non-Nociceptive Responses from Spinal Neurons in a Porcine Model 猪脊髓神经元损伤性和非损伤性反应的首次证明

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123833

S. Meijs, C. Bjarkam, F. R. Andreis, W. Jensen

{"title":"First Demonstration of Nociceptive and Non-Nociceptive Responses from Spinal Neurons in a Porcine Model","authors":"S. Meijs, C. Bjarkam, F. R. Andreis, W. Jensen","doi":"10.1109/NER52421.2023.10123833","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123833","url":null,"abstract":"The spinal cord plays a key role in pain processing, but it remains unexplored in large animal models. We have developed a methodology to record from spinal neurons using three pigs. Here we aim to determine (1) at which rostro-caudal level ulnar nerve evoked responses can be recorded and (2) at which depth distinctly different responses can be recorded after noxious and non-noxious stimulation. Neural signals were evoked by ulnar nerve stimulation and recorded at different levels of the spinal cord in anesthetized pigs. Event-related potentials and peri-stimulus histograms showed that most activity was recorded at the C7 level, which diminished when the electrodes were moved towards C6 or C8. At 1 mm depth, spinal neurons responded primarily to noxious stimulation, which is typical for nociceptive specific neurons. While at 2 mm depth, neurons showed responses typical for wide dynamic range neurons by responding differently to noxious and non-noxious stimulation. Histological analysis showed that these signals may indeed have been recorded from lamina I/II and IV/V, respectively. This method opens new possibilities for studying pain and other spinal mechanisms in large animals and can be combined with peripheral and brain recordings to provide a more integrated picture of (chronic) pain mechanisms.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132485396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Influence of Spatial Smoothing Kernel Size on ICA Model Order and Spatial Maps of Intrinsic Connectivity Networks 空间平滑核大小对ICA模型阶数和内在连通性网络空间映射的影响

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123835

B. Jarrahi

{"title":"The Influence of Spatial Smoothing Kernel Size on ICA Model Order and Spatial Maps of Intrinsic Connectivity Networks","authors":"B. Jarrahi","doi":"10.1109/NER52421.2023.10123835","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123835","url":null,"abstract":"Earlier studies indicate that fMRI preprocessing methods can affect the properties of the brain intrinsic connectivity networks (ICNs). Previously, we showed that spatial smoothing, a standard preprocessing step, would influence time-varying whole-brain network connectivity patterns and meta-states metrics. Here, we study the influence of spatial smoothing on the dimensionality of the fMRI data and ICN spatial maps. To this end, we collected resting-state fMRI data of healthy subjects using a 3.0 T MRI scanner. During preprocessing, we applied various levels of spatial smoothing to the data with an isotropic Gaussian kernel with full width at half maximum (FWHM) sizes 0 to 12 mm with a step of 2 mm and calculated ICA model order to estimate the number of informative components. We examined the significant changes in the spatial maps of the data that were preprocessed with 4, 8, and 12 mm smoothing kernels pairwise using a paired $t$-test with a false discovery rate correction. Results revealed that the level of spatial smoothing clearly impacts the network dimensionality, intensities of spatial maps, and peak voxel location. Using minimum description length (MDL) criteria, dimensionality generally decreased as smoothing kernel size increased. In contrast, entropy-rate based order selection indicated a general increase in model order as smoothing kernel size increased. Intensities of spatial maps, which are associated with the cohesiveness and connectivity inside the network, decreased in most ICNs, including the default-mode and salience networks as the smoothing kernel size decreased. Our findings provide a preliminary insight into the effects of spatial smoothing on ICA model order and spatial maps. Larger samples are needed to further investigate these effects.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"133 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130960430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-Quality 0.5mm Isotropic fMRI: Random Matrix Theory Meets Physics-Driven Deep Learning 高质量的0.5mm各向同性fMRI:随机矩阵理论满足物理驱动的深度学习

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123799

Ö. Demirel, S. Moeller, L. Vizioli, Burhaneddin Yaman, Logan T Dowdle, E. Yacoub, K. Uğurbil, M. Akçakaya

{"title":"High-Quality 0.5mm Isotropic fMRI: Random Matrix Theory Meets Physics-Driven Deep Learning","authors":"Ö. Demirel, S. Moeller, L. Vizioli, Burhaneddin Yaman, Logan T Dowdle, E. Yacoub, K. Uğurbil, M. Akçakaya","doi":"10.1109/NER52421.2023.10123799","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123799","url":null,"abstract":"Submillimeter fMRI plays a vital role in studying the brain function at the mesoscale level, allowing investigation of functional activity in small cortical structures. However, such resolutions require extreme trade-offs between SNR, spatio-temporal resolution and coverage leading to numerous challenges. Therefore, interpretable locally low-rank denoising methods based on random matrix theory have been proposed and built into fMRI pipelines, but they require well-characterized noise distributions on reconstructed images, which hinders the use of emerging physics-driven deep learning reconstructions. In this work, we re-envision the conventional fMRI computational imaging pipeline to an alternative where denoising is performed prior to reconstruction. This allows for a synergistic combination of random matrix theory based thermal noise suppression and physics-driven deep learning re-construction, enabling high-quality 0.5mm isotropic functional MRI. Our results show that the proposed strategy improves on denoising or physics-driven deep learning reconstruction alone, with better delineation of brain structures, higher tSNR particularly in mid-brain areas and the largest expected extent of activation in GLM-derived t-maps.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126397272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0