2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)最新文献_第10页

A New Process Using Magnetic Nanoparticles to Neuronal Cells Growth Orientation 磁性纳米颗粒诱导神经元细胞定向生长的新工艺

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-20 DOI: 10.1109/NER.2019.8717080

C. Loureiro, C. A. Parada, H. Ceragioli, L. Mendes

{"title":"A New Process Using Magnetic Nanoparticles to Neuronal Cells Growth Orientation","authors":"C. Loureiro, C. A. Parada, H. Ceragioli, L. Mendes","doi":"10.1109/NER.2019.8717080","DOIUrl":"https://doi.org/10.1109/NER.2019.8717080","url":null,"abstract":"Degenerative neural diseases after accidents are important matters in neuroscience field. Physical stimulus for neuronal growth and development can be achieved with tensile force. This experimental method consists of using magnetic nanoparticles attached to neuronal cells on which static magnetic field is applied to stimulate targeted cells’ growth in the field’s direction. Particles under a force of magnetic field can provide physical guidance for neuronal regeneration. Particles under a force of magnetic field can provide physical guidance for neuronal regeneration. Influence of particles’ concentration and intensity of the field was analyzed to determine the optimum values for higher oriented growth by processing the images data obtained using electronic microscopy. Higher directed growth of neuronal cells with MNPs was observed from qualitative and quantitative evaluation of images data, obtained in the experiments. Consistent and reliable results were achieved using data mining technique. The nanoparticles functionalization was made with less expensive biomaterial. The particles were homemade and they are biocompatible. The magnetic field was applied with magnets. This new experimental methodology is less costly than others found in the literature. The described technical characteristics combined made this work a new, simple and low cost strategy to stimulate neuronal cells oriented growth. Furthermore, this method shows viability for larger researches to develop therapies for recovery of neurodegenerative diseases, avoiding amputation.","PeriodicalId":356177,"journal":{"name":"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124886083","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

EEG Spectral Connectivity Analysis in a Large Clinical Population 大型临床人群脑电图频谱连通性分析

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-20 DOI: 10.1109/NER.2019.8716884

David O. Nahmias, K. Kontson

引用次数: 0

Cochlear implant artefact reduction in electroencephalography data obtained with the auditory oddball paradigm and stimuli with differing envelopes * 耳蜗植入物伪影减少与听觉怪异范式和不同包络刺激的脑电图数据*

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-20 DOI: 10.1109/NER.2019.8717040

Saskia M. Waechter, C. Simões‐Franklin, Jaclyn Smith, L. Viani, R. Reilly

{"title":"Cochlear implant artefact reduction in electroencephalography data obtained with the auditory oddball paradigm and stimuli with differing envelopes *","authors":"Saskia M. Waechter, C. Simões‐Franklin, Jaclyn Smith, L. Viani, R. Reilly","doi":"10.1109/NER.2019.8717040","DOIUrl":"https://doi.org/10.1109/NER.2019.8717040","url":null,"abstract":"Cortical auditory evoked potentials (CAEPs) are a popular neurophysiological measure in the assessment of auditory processing capabilities. Research evidence suggests that CAEPs may be employed to assess auditory discrimination abilities, which is of particular interest in monitoring clinical rehabilitation outcomes in cochlear implant (CI) users. However, the electrical artefact from CI stimulation poses a challenge for the signal analysis. Numerous artefact reduction procedures have been proposed, many of which are computationally costly or subjectively biased. This study investigated a simplified approach to CI artefact reduction based on subtraction, which was enabled by introducing an enhanced auditory oddball paradigm. Outcome CAEPs were compared to the gold-standard artefact reduction based on independent component analysis (ICA). Grand average difference potentials showed successful artefact reduction for both artefact rejection algorithms in the enhanced oddball paradigm. With the enhanced oddball paradigm, measured peak-to-peak amplitudes were significantly larger with subtraction-based processing than for ICA-based processing, suggesting that the removed independent components not only contained artefact, but also neural activity of interest.","PeriodicalId":356177,"journal":{"name":"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132278478","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: 2

Unsupervised Clustering of Micro-Electrophysiological Signals for localization of Subthalamic Nucleus during DBS Surgery DBS手术中丘脑下核定位微电生理信号的无监督聚类

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-20 DOI: 10.1109/NER.2019.8717184

M. Khosravi, S. F. Atashzar, G. Gilmore, M. Jog, Rajnikant V. Patel

{"title":"Unsupervised Clustering of Micro-Electrophysiological Signals for localization of Subthalamic Nucleus during DBS Surgery","authors":"M. Khosravi, S. F. Atashzar, G. Gilmore, M. Jog, Rajnikant V. Patel","doi":"10.1109/NER.2019.8717184","DOIUrl":"https://doi.org/10.1109/NER.2019.8717184","url":null,"abstract":"In this paper, an unsupervised machine learning technique is proposed to localize the Subthalamic Nucleus (STN) during deep brain stimulation (DBS) Surgery. DBS is one of most common treatments for advanced Parkinson’s disease (PD). The purpose of this surgery is to permanently implant stimulation electrodes inside the STN to deliver electrical currents. It is clinically shown that DBS surgery can significantly reduce motor symptoms of PD (such as tremor). However, the outcome of this surgery is highly dependent on the location of the stimulating electrode. Since STN is a very small region inside the basal ganglia, accurate placement of the electrode is a challenging task for the surgical team. During DBS surgery, the team uses Micro-Electrode Recording (MER) of electrophysiological neural activities to intraoperatively track the location of electrodes and estimate the borders of the STN. In this work, we propose a composite unsupervised machine learning clustering approach that is capable of detecting the dorsal borders of the STN during DBS operation. For this, MER signals from 50 PD patients were recorded and used to validate the performance of the proposed method. Results show that the approach is capable of detecting the dorsal border of the STN in an online manner with an accuracy of 80% without using any supervised training.","PeriodicalId":356177,"journal":{"name":"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125924399","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: 4

Sensorimotor rhythm modulation depends on resting-state oscillations and cortex integrity in severely paralyzed stroke patients 严重瘫痪脑卒中患者的感觉运动节律调节依赖于静息状态振荡和皮层完整性

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-20 DOI: 10.1109/NER.2019.8717112

E. López-Larraz, Andreas M. Ray, N. Birbaumer, A. Ramos-Murguialday

引用次数: 5

Continuous estimation of wrist torques with stack-autoencoder based deep neural network: A preliminary study 基于堆栈自编码器的深度神经网络腕部扭矩连续估计的初步研究

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-01 DOI: 10.1109/NER.2019.8716941

Yang Yu, Chen Chen, X. Sheng, Xiangyang Zhu

引用次数: 3

Functional Electrical Stimulation Capability Maps 功能性电刺激能力图

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-01 DOI: 10.1109/NER.2019.8717134

Eric M. Schearer, D. Wolf

{"title":"Functional Electrical Stimulation Capability Maps","authors":"Eric M. Schearer, D. Wolf","doi":"10.1109/NER.2019.8717134","DOIUrl":"https://doi.org/10.1109/NER.2019.8717134","url":null,"abstract":"We introduce capability maps visualizing the abilities of the arm of a person with a cervical spinal cord injury activated by functional electrical stimulation (FES). We map the arm’s workspace at different wrist positions using a person-specific arm model based on force data gathered during interactions with a robot. We describe four maps: 1) a map of the maximum force the person can produce in one direction, 2) a map of wrist configurations that FES can hold against gravity and other passive forces, 3) a map of the maximum force the person can apply in all directions, and 4) a map of the directions the arm can move with FES. To demonstrate these maps we applied electrical stimulation to nine muscle groups of a person with high tetraplegia, measured the resulting force with a robot attached to the person’s wrist, created a Gaussian process regression model relating the forces to the wrist positions, and used this model to create the four capability maps. The results are 2D images displaying the arm’s force production and movement capabilities for a person with high tetraplegia as a function of wrist position. As these maps predict functional benefits of specific interventions, they can reduce risk in developing new interventions to restore function to people with whole-arm paralysis.","PeriodicalId":356177,"journal":{"name":"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116894030","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

Removing TMS Artifacts from EEG Recordings Using a Deep Gated Recurrent Unit 使用深门控循环单元从EEG记录中去除TMS伪影

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-01 DOI: 10.1109/NER.2019.8717084

Andac Demir, M. Yarossi, Damon E. Hyde, M. Shafi, D. Brooks, Deniz Erdoğmuş

引用次数: 1

Exploratory Analysis of Brain Signals through Low Dimensional Embedding 基于低维嵌入的脑信号探索性分析

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-01 DOI: 10.1109/NER.2019.8716924

Yuxiao Wang, C. Ting, Xu Gao, H. Ombao

{"title":"Exploratory Analysis of Brain Signals through Low Dimensional Embedding","authors":"Yuxiao Wang, C. Ting, Xu Gao, H. Ombao","doi":"10.1109/NER.2019.8716924","DOIUrl":"https://doi.org/10.1109/NER.2019.8716924","url":null,"abstract":"In this paper, we develop computationally efficient and theoretically justified tools for analyzing high dimensional brain signals. Our approach is to extract the optimal lower dimensional representations for each brain region and then characterize and estimate connectivity between regions through these factors. This approach is motivated by our observation that electroencephalograms (EEGs) from many channels within each region exhibit a high degree of multicollinearity and synchrony thereby suggesting that it would be sensible to extract summary factors for each region. Here, the summary factors are the encodings that lead to the lowest reconstruction error. We focus on two special cases of linear auto encoder and decoder. The first characterizes the factors as instantaneous linear mixing of the observed signals. In the second approach, the factors are convolutions of the observed signals (which is more general than the first). These methods were compared through simulations under different conditions and the results provide insights on advantages and limitations of each. Finally, we performed exploratory analysis of resting state EEG data. The spectral properties of the factors were estimated and connectivity between regions via the factors using coherence measures were computed. We implemented these methods in a Matlab toolbox XHiDiTS (https://goo.gl/uXc8ei). The toolbox was utilized to investigate consistency of these factors across all epochs during the entire resting-state period.","PeriodicalId":356177,"journal":{"name":"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122899835","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: 6

Real-Time Prosthetic Digit Actuation by Optical Read-out of Activity-Dependent Calcium Signals in an Ex Vivo Peripheral Nerve 利用光学读出离体外周神经中活动依赖的钙信号来实时驱动假肢手指

2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2019-03-01 DOI: 10.1109/NER.2019.8717033

Arjun K. Fontaine, Jacob L. Segil, J. Caldwell, R. Weir

引用次数: 2