2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)最新文献

Observation-based calibration of brain-machine interfaces for grasping 基于观测的抓取脑机接口标定

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6695856

Harshavardhan A. Agashe, J. Contreras-Vidal

{"title":"Observation-based calibration of brain-machine interfaces for grasping","authors":"Harshavardhan A. Agashe, J. Contreras-Vidal","doi":"10.1109/NER.2013.6695856","DOIUrl":"https://doi.org/10.1109/NER.2013.6695856","url":null,"abstract":"Brain-machine interfaces (BMIs) are increasingly being used in rehabilitation research to improve the quality of life of clinical populations. Current BMI technology allows us to control, with a high level of accuracy, the positioning of robotic hands in space. We have shown previously that it is possible to decode the dexterous movements of fingers during grasping, from noninvasively recorded electroencephalographic (EEG) activity. Due to the absence of overt movement in clinical subjects with impaired hand function, however, it is not possible to construct decoder models directly by simultaneously recording brain activity and kinematics. The mirror neuron system is activated in a similar fashion during both overt movements and observing movements performed by other agents. Here, we investigate action-observation as a strategy to calibrate decoders for grasping in human subjects. Subjects observed while a robotic hand performed grasping movements, and decode models were calibrated using the EEG activity of the subjects and the kinematics of the robotic hand. Decoding accuracy was tested on unseen data, in an 8-fold cross validation scheme, as the correlation coefficient between the predicted and actual trajectories. High decoding accuracies were obtained (r = 0.70 ± 0.07), demonstrating the feasibility of using action-observation as a calibration technique for decoding grasping movements.","PeriodicalId":156952,"journal":{"name":"2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116001307","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: 3

Effects of transcutaneous spinal DC stimulation on plasticity of the spinal circuits and corticospinal tracts in humans 经皮脊髓直流电刺激对人脊髓回路和皮质脊髓束可塑性的影响

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6695925

Tomofumi Yamaguchi, S. Fujimoto, Y. Otaka, Satoshi Tanaka

引用次数: 10

Detecting event-related motor activity using functional near-infrared spectroscopy 使用功能性近红外光谱检测事件相关的运动活动

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6696237

T. Ozawa, Takatsugu Aihara, Yusuke Fujiwara, Y. Otaka, I. Nambu, R. Osu, J. Izawa, Y. Wada

{"title":"Detecting event-related motor activity using functional near-infrared spectroscopy","authors":"T. Ozawa, Takatsugu Aihara, Yusuke Fujiwara, Y. Otaka, I. Nambu, R. Osu, J. Izawa, Y. Wada","doi":"10.1109/NER.2013.6696237","DOIUrl":"https://doi.org/10.1109/NER.2013.6696237","url":null,"abstract":"Measuring discrete-trial motor-related brain activity using functional near-infrared spectroscopy (fNIRS) is considered difficult. This is because its spatial resolution is much lower than that of functional magnetic resonance imaging (fMRI), and its signals include non-motion-related artifacts. To detect changes in hemoglobin induced by movements, most fNIRS studies have used a block design in which a subject conducts a set of repetitive movements for over a few seconds. Changes in hemoglobin induced by the series of movements are accumulated. Here, we address whether fNIRS can detect a phasic change induced by a discrete ballistic movement using an event-related design similar to those often adopted in fMRI experiments. To detect only event-related brain activity and to reduce the effect of artifacts, we adopted a general linear model whose design matrix contains data from the short transmitter-receiver distance channels that are considered components of artifacts. As a result, high event-related activity was detected in the contralateral sensorimotor cortex. We also compared the topographic functional map produced by fNIRS with the map given by an event-related fMRI experiment in which the same subjects performed exactly the same task. Both maps showed activity in equivalent areas, and the similarity was significant. We conclude that fNIRS affords the opportunity to explore motor-related brain activity even for discrete ballistic movements.","PeriodicalId":156952,"journal":{"name":"2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121755188","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

Classifying the intent of novel users during human locomotion using powered lower limb prostheses 使用动力下肢假体进行人类运动时新使用者的意图分类

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6695934

Aaron J. Young, A. M. Simon, Nicholas P. Fey, L. Hargrove

{"title":"Classifying the intent of novel users during human locomotion using powered lower limb prostheses","authors":"Aaron J. Young, A. M. Simon, Nicholas P. Fey, L. Hargrove","doi":"10.1109/NER.2013.6695934","DOIUrl":"https://doi.org/10.1109/NER.2013.6695934","url":null,"abstract":"Intent recognition systems using pattern recognition technology to control powered lower-limb prostheses are promising for seamlessly changing between locomotion modes- such as transitioning from level walking to stair ascent. These transitions can be accomplished by training an algorithm to recognize the patterns of mechanical and/or myoelectric signals an amputee generates during and between different locomotion modes. While low error rates can be achieved with this method, it typically requires a substantial amount of training data to be gathered. To alleviate this burden, this study investigated training a user-independent classifier from a pool of lower limb amputees performing level walking, ramps and stairs on a powered prosthesis and tested generalization of the classifier to a novel subject. The effect of using the amputee's EMG signals in combination with the mechanical sensors on the leg was also evaluated for this user-independent classifier. Generalization was poor to a novel subject- 48% overall recognition rate with EMG and 62% without (mechanical sensors only). However, an important system improvement could be made by including a few level walking trials of the novel subject (only a few minutes of data collection) in the training data, the overall recognition rate improved to 86% with EMG and 83% without.","PeriodicalId":156952,"journal":{"name":"2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132682281","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: 50

An automatic classifier of pain scores in chronic pain patients from local field potentials recordings 慢性疼痛患者局部场电位记录疼痛评分的自动分类器

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6696153

Suyi Zhang, A. Green, P. P. Smith

{"title":"An automatic classifier of pain scores in chronic pain patients from local field potentials recordings","authors":"Suyi Zhang, A. Green, P. P. Smith","doi":"10.1109/NER.2013.6696153","DOIUrl":"https://doi.org/10.1109/NER.2013.6696153","url":null,"abstract":"This paper investigates measures to assess automatically the level of pain in a group of chronic pain patients implanted with electrodes for deep brain stimulation. Electrical activity in local field potentials in particular frequency bands has been shown to be associated with changes in the perception of pain. In this paper we develop a method to classify pain intensity with two groups of patients, one with electrodes implanted in the thalamus (VPL) and the other with implants in periaqueductal grey (PAG/PVG), using wavelet analysis to process the local field potential data from the deep brain electrodes. A fuzzy network classifier is used to relate sections of the data to the pain intensity, as recorded by patients using a visual analogue scale (VAS) scale. Our results suggest that in the PAG implanted patients alpha activity is a good measure of pain in a single patient, whereas correlation with beta activity is more appropriate in thalamus implanted patients. The relation between such activity and pain level shows some consistency within a session. This suggests that a closed loop form of DBS may be possible for these patients to optimize their treatment. However it was not possible to train a classifier consistently across the groups of patients, possibly because of differences in pain perception across individuals.","PeriodicalId":156952,"journal":{"name":"2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125100291","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: 11

Assessment of surgeon's stress level and alertness using EEG during laparoscopic simple nephrectomy 应用脑电图评估腹腔镜单纯肾切除术中外科医生的应激水平和警觉性

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6695969

D. G. Duru, Adil Deniz Duru, D. Barkana, O. Sanli, M. Ozkan

引用次数: 19

Powered prosthesis control during walking, sitting, standing, and non-weight bearing activities using neural and mechanical inputs 在行走、坐着、站立和非负重活动中使用神经和机械输入的动力假肢控制

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6696148

A. M. Simon, Nicholas P. Fey, Kimberly A. Ingraham, Aaron J. Young, L. Hargrove

{"title":"Powered prosthesis control during walking, sitting, standing, and non-weight bearing activities using neural and mechanical inputs","authors":"A. M. Simon, Nicholas P. Fey, Kimberly A. Ingraham, Aaron J. Young, L. Hargrove","doi":"10.1109/NER.2013.6696148","DOIUrl":"https://doi.org/10.1109/NER.2013.6696148","url":null,"abstract":"Lower limb prostheses that can generate near physiological joint power have the potential to improve the way amputees go about their activities of daily living. Amputees who have lost both their knee and ankle would also benefit from a system that allowed them to easily perform sit-to-stand and stand-to-sit movements, reposition their prosthesis using neural control, and intuitively transition between these modes of operation and walking. In this study, we developed such a system and evaluated it with two transfemoral amputees. Both amputees were able to stand up and sit down comfortably using the powered prosthesis. Two neural control systems were configured using a linear discriminant analysis classifier trained from data recorded from eight residual thigh muscles. One classifier, trained to recognize when amputees sat down from walking mode, was on average 96.5% accurate. A second classifier, trained to recognize amputees' intent to reposition the knee and ankle joints, was on average 87.3% accurate. This integrated control system allowing transfemoral amputees to walk as well as perform weight transfers (sitting down and standing up) and seated non-weight bearing activities demonstrates an advancement towards improving the performance and viability of powered prostheses during daily use.","PeriodicalId":156952,"journal":{"name":"2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130969775","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: 21

An exploration of the effects of audio-visual entrainment on Parkinson's disease tremor 视听干扰对帕金森病震颤影响的探讨

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6696245

C. Cinel, R. Poli, L. Citi, D. Roberson

引用次数: 3

Identification of spectral landmarks on the single fiber action potential waveform for unit tracking 用于单元跟踪的单纤维动作电位波形的谱标识别

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6696222

Shaoyu Qiao, Ken Yoshida

引用次数: 0

Estimation of stiffening strategy of ankle and hip based on joint sway 基于关节摆动的踝关节和髋关节僵硬策略估计

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2013-12-01 DOI: 10.1109/NER.2013.6696243

A. Azaman, Shin-ichiroh Yamamoto

{"title":"Estimation of stiffening strategy of ankle and hip based on joint sway","authors":"A. Azaman, Shin-ichiroh Yamamoto","doi":"10.1109/NER.2013.6696243","DOIUrl":"https://doi.org/10.1109/NER.2013.6696243","url":null,"abstract":"Stiffening strategy is a posture strategy to maintain a desired position of the body. This strategy is generated by the Central Nervous System (CNS), which creates muscle forces around a specific joint; and thus, affects joint movement. In this study, stiffening strategy at the ankle and hip joints of five young healthy subjects was observed based on joint sway. Based on stiffness pattern, both joints were seen to oscillate slower from external perturbation sway, when exposed to a high frequency of translation perturbation. Furthermore, stiffness ratio between ankle and hip joints, at four different frequencies of translation perturbation (0.2, 0.4, 0.6, and 0.8 Hz), indicated the transition of posture strategy from ankle to hip strategy when responding to a high intensity of external disturbance which useful to determine adaptation to instability. Besides, additional parameters are suggested to represent the change of sway pattern of the ankle and hip joint model, which was built based on an inverted pendulum model. Estimated sway pattern produced a high correlation (r2>0.5) with actual data. In conclusion, stiffening strategy can be seen through the change of sway pattern and the value of stiffness at the joint. Therefore, development of a control model, according to the improvement suggested for both joints is warranted, in order to develop a reliable simulation model for a posture control measurement system.","PeriodicalId":156952,"journal":{"name":"2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131259454","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: 3