Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146706
R. Jegadeesan, N. Thakor, S. Yen
Plethora of implant devices reported in the last decade are enabled using wireless power delivery and telemetry systems. In this work, we present the design of wireless a platform that enables a completely implantable peripheral nerve prosthesis. Large power (over 100mW) delivery and large bandwidth telemetry (1.3 Mbps) demanded by this prosthesis application are addressed by the proposed platform whilst still adhering to the regulatory specific absorption rate safety limits (2W/Kg). The wireless platform is built and verified using acute rodent experiments.
{"title":"Wireless for peripheral nerve prosthesis and safety","authors":"R. Jegadeesan, N. Thakor, S. Yen","doi":"10.1109/NER.2015.7146706","DOIUrl":"https://doi.org/10.1109/NER.2015.7146706","url":null,"abstract":"Plethora of implant devices reported in the last decade are enabled using wireless power delivery and telemetry systems. In this work, we present the design of wireless a platform that enables a completely implantable peripheral nerve prosthesis. Large power (over 100mW) delivery and large bandwidth telemetry (1.3 Mbps) demanded by this prosthesis application are addressed by the proposed platform whilst still adhering to the regulatory specific absorption rate safety limits (2W/Kg). The wireless platform is built and verified using acute rodent experiments.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"599 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131641987","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146610
F. Lane, Kristian B. Nitsch, P. Troyk
A total of thirteen individuals were interviewed and asked to describe their experiences of participating in a cortical vision implant study conducted by William Dobelle between 2000 and 2005. The transcripts from the interviews were analyzed using MAXQDA software and themes that resulted from the interviews such as motivation to participate, sensory substitution expectations, decision-making process, experience of artificial vision and functional use of artificial vision is described in depth. Emotional experiences of participating in the study result in ethical and psychological implications for future research.
{"title":"Participant perspectives from a cortical vision implant study: Ethical and psychological implications","authors":"F. Lane, Kristian B. Nitsch, P. Troyk","doi":"10.1109/NER.2015.7146610","DOIUrl":"https://doi.org/10.1109/NER.2015.7146610","url":null,"abstract":"A total of thirteen individuals were interviewed and asked to describe their experiences of participating in a cortical vision implant study conducted by William Dobelle between 2000 and 2005. The transcripts from the interviews were analyzed using MAXQDA software and themes that resulted from the interviews such as motivation to participate, sensory substitution expectations, decision-making process, experience of artificial vision and functional use of artificial vision is described in depth. Emotional experiences of participating in the study result in ethical and psychological implications for future research.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131933064","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146754
Allison T. Connolly, W. Kaemmerer, Siddharth Dani, S. Stanslaski, E. Panken, Matthew D. Johnson, T. Denison
We have found that a set of support vector machines operating upon local field potentials sensed from an implanted DBS lead can identify the contact chosen by the physician for the patient's STN DBS therapy with 91% accuracy. The finding is based on a small data set and thus subject to change with further data collection and cross-validation. Nevertheless, the results suggest that an algorithm for selecting an effective contact for STN DBS based on the signals sensed from the DBS lead may be feasible.
{"title":"Guiding deep brain stimulation contact selection using local field potentials sensed by a chronically implanted device in Parkinson's disease patients","authors":"Allison T. Connolly, W. Kaemmerer, Siddharth Dani, S. Stanslaski, E. Panken, Matthew D. Johnson, T. Denison","doi":"10.1109/NER.2015.7146754","DOIUrl":"https://doi.org/10.1109/NER.2015.7146754","url":null,"abstract":"We have found that a set of support vector machines operating upon local field potentials sensed from an implanted DBS lead can identify the contact chosen by the physician for the patient's STN DBS therapy with 91% accuracy. The finding is based on a small data set and thus subject to change with further data collection and cross-validation. Nevertheless, the results suggest that an algorithm for selecting an effective contact for STN DBS based on the signals sensed from the DBS lead may be feasible.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133243735","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146621
Michael J. Crosse, H. ElShafei, John J. Foxe, E. Lalor
Neuroimaging research has demonstrated that observing visual speech in the absence of auditory speech activates primary auditory cortex. However, it remains unclear what this activation precisely reflects. It is well established that, during continuous auditory speech, neural activity in auditory cortex tracks the temporal envelope of the speech signal. Recently, it has been suggested that this process may in fact reflect an internal synthesis of the speech stream rather than the encoding of the envelope per se. Could silent lipreading therefore elicit a similar “entrainment” to the envelope in the absence of auditory speech? Here, we test this hypothesis by examining the impact of lipreading accuracy on envelope tracking using electroencephalography (EEG). We provide evidence to suggest that the EEG response over left temporal scalp tracks the unheard speech more faithfully during accurate lipreading. We also demonstrate that the envelope can be reconstructed from EEG data recorded during silent lipreading with accuracy above chance level. This could have implications for brain-computer interface technology.
{"title":"Investigating the temporal dynamics of auditory cortical activation to silent lipreading","authors":"Michael J. Crosse, H. ElShafei, John J. Foxe, E. Lalor","doi":"10.1109/NER.2015.7146621","DOIUrl":"https://doi.org/10.1109/NER.2015.7146621","url":null,"abstract":"Neuroimaging research has demonstrated that observing visual speech in the absence of auditory speech activates primary auditory cortex. However, it remains unclear what this activation precisely reflects. It is well established that, during continuous auditory speech, neural activity in auditory cortex tracks the temporal envelope of the speech signal. Recently, it has been suggested that this process may in fact reflect an internal synthesis of the speech stream rather than the encoding of the envelope per se. Could silent lipreading therefore elicit a similar “entrainment” to the envelope in the absence of auditory speech? Here, we test this hypothesis by examining the impact of lipreading accuracy on envelope tracking using electroencephalography (EEG). We provide evidence to suggest that the EEG response over left temporal scalp tracks the unheard speech more faithfully during accurate lipreading. We also demonstrate that the envelope can be reconstructed from EEG data recorded during silent lipreading with accuracy above chance level. This could have implications for brain-computer interface technology.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122293042","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146753
Qin Zhang, C. Xiong, Chengfei Zheng
Surface Electromyography (EMG) has been considered as a viable human-machine interface in the context of human-centered robotics. In order to interpret human muscle activities into motion intentions, various pattern classification methods was proposed for human motion/gesture classification, which provided binary command for myoelectric control. To obtain complex motions coordinated by multiple DoFs, single DoF was usually sequentially classified and activated, which is not intuitive and efficient comparing with the natural motor strategy of the human. In this work, we investigated the motion classification methods from EMG for intuitive and simultaneous activation of multiple DoFs during 3-D arm motions. In the experiments, all motions were performed naturally rather than under the condition of maximum muscle contractions or other kinematic constraints. The combination of two EMG time-domain features after principal component analysis (PCA) processing is considered as the suitable choice considering both the classification accuracy and feasibility for robot control. For the motion classification method, least-square support vector machine (LS-SVM) represents higher classification accuracy for five arm motion classification across eight subjects with respect to other four methods which were popularly used in the previous works. The proposed method is hopefully applied in a EMG-driven simultaneous and proportional kinematics estimation systems for decoding model selection according to the motion intention.
表面肌电图(EMG)已被认为是在以人为中心的机器人环境下可行的人机界面。为了将人体肌肉活动解释为运动意图，提出了多种模式分类方法进行人体运动/手势分类，为肌电控制提供了二进制指令。为了获得由多个自由度协调的复杂运动，通常对单个自由度进行顺序分类和激活，与人类的自然运动策略相比，这种方法并不直观和高效。在这项工作中，我们研究了基于肌电图的运动分类方法，以直观地同时激活三维手臂运动中的多个DoFs。在实验中，所有的运动都是自然进行的，而不是在最大肌肉收缩或其他运动学约束的条件下进行的。考虑到分类精度和机器人控制的可行性，结合主成分分析(PCA)处理后的两种肌电信号时域特征是比较合适的选择。对于运动分类方法，最小二乘支持向量机(least-square support vector machine, LS-SVM)相对于以往常用的4种方法，在8个受试者的5个手臂运动分类中具有更高的分类精度。该方法有望应用于肌电驱动的同步和比例运动估计系统中，用于根据运动意图选择解码模型。
{"title":"Intuitive motion classification from EMG for the 3-D arm motions coordinated by multiple DoFs","authors":"Qin Zhang, C. Xiong, Chengfei Zheng","doi":"10.1109/NER.2015.7146753","DOIUrl":"https://doi.org/10.1109/NER.2015.7146753","url":null,"abstract":"Surface Electromyography (EMG) has been considered as a viable human-machine interface in the context of human-centered robotics. In order to interpret human muscle activities into motion intentions, various pattern classification methods was proposed for human motion/gesture classification, which provided binary command for myoelectric control. To obtain complex motions coordinated by multiple DoFs, single DoF was usually sequentially classified and activated, which is not intuitive and efficient comparing with the natural motor strategy of the human. In this work, we investigated the motion classification methods from EMG for intuitive and simultaneous activation of multiple DoFs during 3-D arm motions. In the experiments, all motions were performed naturally rather than under the condition of maximum muscle contractions or other kinematic constraints. The combination of two EMG time-domain features after principal component analysis (PCA) processing is considered as the suitable choice considering both the classification accuracy and feasibility for robot control. For the motion classification method, least-square support vector machine (LS-SVM) represents higher classification accuracy for five arm motion classification across eight subjects with respect to other four methods which were popularly used in the previous works. The proposed method is hopefully applied in a EMG-driven simultaneous and proportional kinematics estimation systems for decoding model selection according to the motion intention.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"10 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116962189","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146551
D. Valeriani, R. Poli, C. Cinel
Detecting a target in a complex environment can be a difficult task, both for a single individual and a group, especially if the scene is very rich of structure and there are strict time constraints. In recent research, we have demonstrated that collaborative Brain-Computer Interfaces (cBCIs) can use neural signals and response times to estimate the decision confidence of participants and use this to improve group decisions in visual-matching and visual-search tasks with artificial stimuli. This paper extends that work in two ways. Firstly, we use a much harder target detection task where observers are presented with complex natural scenes where targets are very difficult to identify. Secondly, we complement the neural and behavioural information used in our previous cBCIs with physiological features representing eye movements and eye blinks of participants in the period preceding their decisions. Results obtained with 10 participants indicate that the proposed cBCI improves decision errors by up to 3.4% (depending on group size) over group decisions made by a majority vote. Furthermore, results show that providing the system with information about eye movements and blinks further significantly improves performance over our best previously reported method.
{"title":"A collaborative Brain-Computer Interface for improving group detection of visual targets in complex natural environments","authors":"D. Valeriani, R. Poli, C. Cinel","doi":"10.1109/NER.2015.7146551","DOIUrl":"https://doi.org/10.1109/NER.2015.7146551","url":null,"abstract":"Detecting a target in a complex environment can be a difficult task, both for a single individual and a group, especially if the scene is very rich of structure and there are strict time constraints. In recent research, we have demonstrated that collaborative Brain-Computer Interfaces (cBCIs) can use neural signals and response times to estimate the decision confidence of participants and use this to improve group decisions in visual-matching and visual-search tasks with artificial stimuli. This paper extends that work in two ways. Firstly, we use a much harder target detection task where observers are presented with complex natural scenes where targets are very difficult to identify. Secondly, we complement the neural and behavioural information used in our previous cBCIs with physiological features representing eye movements and eye blinks of participants in the period preceding their decisions. Results obtained with 10 participants indicate that the proposed cBCI improves decision errors by up to 3.4% (depending on group size) over group decisions made by a majority vote. Furthermore, results show that providing the system with information about eye movements and blinks further significantly improves performance over our best previously reported method.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116871754","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146695
G. Lanzani, M. Antognazza, N. Martino, D. Ghezzi, F. Benfenati
The capability to selectively affect vital functions in cell networks and sub-cell compartments in vitro or in vivo is a mission critical tool in neuroscience and medicine. Optical excitation is one of the main strategies used to achieve high spatial and temporal resolution. In the following we describe recent results and future approaches of cell photostimulation mediated by organic semiconducting polymers.
{"title":"Controlling cell functions by light","authors":"G. Lanzani, M. Antognazza, N. Martino, D. Ghezzi, F. Benfenati","doi":"10.1109/NER.2015.7146695","DOIUrl":"https://doi.org/10.1109/NER.2015.7146695","url":null,"abstract":"The capability to selectively affect vital functions in cell networks and sub-cell compartments in vitro or in vivo is a mission critical tool in neuroscience and medicine. Optical excitation is one of the main strategies used to achieve high spatial and temporal resolution. In the following we describe recent results and future approaches of cell photostimulation mediated by organic semiconducting polymers.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115214627","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146688
Rishabh Gupta, T. Falk
Affective states are typically characterized using spectral power information obtained from electroencephalography (EEG) data collected over specific brain regions. However, while experiencing a complex emotional audio-video stimuli, brain networks transfer information in a highly interactive manner. To characterize this information, we propose using graph theoretical features. Towards this end, first, we established graph theoretical features as meaningful correlates of affective states through Pearson correlation. Then we compared the classification performance of these features with that of conventional spectral power features where percentage increases in classification performance of 7% and 11% were found in arousal and valence, respectively. Moreover, feature level fusion was explored and resulted in better performance as compared to the feature sets alone thus, highlighting the complementarity of EEG graph based features and spectral powers. Overall it is hoped that this study will enhance affective state evaluation via passive brain computer interfaces, thus leading to a plethora of applications such as user experience perception modelling and affective indexing/tagging of videos, to name a few.
{"title":"Affective state characterization based on electroencephalography graph-theoretic features","authors":"Rishabh Gupta, T. Falk","doi":"10.1109/NER.2015.7146688","DOIUrl":"https://doi.org/10.1109/NER.2015.7146688","url":null,"abstract":"Affective states are typically characterized using spectral power information obtained from electroencephalography (EEG) data collected over specific brain regions. However, while experiencing a complex emotional audio-video stimuli, brain networks transfer information in a highly interactive manner. To characterize this information, we propose using graph theoretical features. Towards this end, first, we established graph theoretical features as meaningful correlates of affective states through Pearson correlation. Then we compared the classification performance of these features with that of conventional spectral power features where percentage increases in classification performance of 7% and 11% were found in arousal and valence, respectively. Moreover, feature level fusion was explored and resulted in better performance as compared to the feature sets alone thus, highlighting the complementarity of EEG graph based features and spectral powers. Overall it is hoped that this study will enhance affective state evaluation via passive brain computer interfaces, thus leading to a plethora of applications such as user experience perception modelling and affective indexing/tagging of videos, to name a few.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"83 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121315250","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146721
Yu-Fei Zhang, Xiang-Yu Gao, Jia-Yi Zhu, Wei-Long Zheng, Bao-Liang Lu
Various studies have shown that the traditional electrooculograms (EOGs) are effective for driving fatigue detection. However, the electrode placement of the traditional EOG recording method is around eyes, which may disturb the subjects' activities, and is not convenient for practical applications. To deal with this problem, we propose a novel electrode placement on forehead and present an effective method to extract horizon electrooculogram (HEO) and vertical electrooculogram (VEO) from forehead EOG. The correlation coefficients between the extracted HEO and VEO and the corresponding traditional HEO and VEO are 0.86 and 0.78, respectively. To alleviate the inconvenience of manually labelling fatigue states, we use the videos recorded by eye tracking glasses to calculate the percentage of eye closure over time, which is a conventional indicator of driving fatigue. We use support vector machine (SVM) for regression analysis and get a rather high prediction correlation coefficient of 0.88 on average.
{"title":"A novel approach to driving fatigue detection using forehead EOG","authors":"Yu-Fei Zhang, Xiang-Yu Gao, Jia-Yi Zhu, Wei-Long Zheng, Bao-Liang Lu","doi":"10.1109/NER.2015.7146721","DOIUrl":"https://doi.org/10.1109/NER.2015.7146721","url":null,"abstract":"Various studies have shown that the traditional electrooculograms (EOGs) are effective for driving fatigue detection. However, the electrode placement of the traditional EOG recording method is around eyes, which may disturb the subjects' activities, and is not convenient for practical applications. To deal with this problem, we propose a novel electrode placement on forehead and present an effective method to extract horizon electrooculogram (HEO) and vertical electrooculogram (VEO) from forehead EOG. The correlation coefficients between the extracted HEO and VEO and the corresponding traditional HEO and VEO are 0.86 and 0.78, respectively. To alleviate the inconvenience of manually labelling fatigue states, we use the videos recorded by eye tracking glasses to calculate the percentage of eye closure over time, which is a conventional indicator of driving fatigue. We use support vector machine (SVM) for regression analysis and get a rather high prediction correlation coefficient of 0.88 on average.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123219782","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}
Pub Date : 2015-04-22DOI: 10.1109/NER.2015.7146749
Lizhi Pan, Dingguo Zhang, X. Sheng, Xiangyang Zhu
In this study, we analyzed the existence of rate-dependent hysteresis in the electromyography (EMG)-force relationship. Eight able-bodied subjects participated in the experiment. Surface EMG signals were acquired from flexor pollicis longus muscle from 0% to 100% maximum voluntary contraction (MVC). The subject was asked to gradually increase grasping force from 0% to 100% MVC and decrease grasping force from 100% to 0% MVC at five different frequencies (1.5, 1, 0.5, 0.25 and 0.125 Hz). Mean absolute value (MAV) was chosen to represent the EMG signals and force signals. In order to compare differences in force between contraction and relaxation periods to EMG activity among different frequency conditions, a hysteresis index (HI), defined as an area inside the hysteresis cycle, was adopted. The results showed that all mean values of HI in different frequency conditions were larger than 0, which proved that hysteresis cycles existed in all frequency conditions. The results also showed that the HI values in different frequency conditions were significantly different from each other (p <; 0.005), which proved hysteresis effects in EMG-force relationship were rate-dependent. The rate-dependent hysteresis in EMG-force relationship has a huge potential to improve the estimation performance of grasping force from EMG.
{"title":"Rate-dependent hysteresis in the EMG-force relationship: A new discovery in EMG-force relationship","authors":"Lizhi Pan, Dingguo Zhang, X. Sheng, Xiangyang Zhu","doi":"10.1109/NER.2015.7146749","DOIUrl":"https://doi.org/10.1109/NER.2015.7146749","url":null,"abstract":"In this study, we analyzed the existence of rate-dependent hysteresis in the electromyography (EMG)-force relationship. Eight able-bodied subjects participated in the experiment. Surface EMG signals were acquired from flexor pollicis longus muscle from 0% to 100% maximum voluntary contraction (MVC). The subject was asked to gradually increase grasping force from 0% to 100% MVC and decrease grasping force from 100% to 0% MVC at five different frequencies (1.5, 1, 0.5, 0.25 and 0.125 Hz). Mean absolute value (MAV) was chosen to represent the EMG signals and force signals. In order to compare differences in force between contraction and relaxation periods to EMG activity among different frequency conditions, a hysteresis index (HI), defined as an area inside the hysteresis cycle, was adopted. The results showed that all mean values of HI in different frequency conditions were larger than 0, which proved that hysteresis cycles existed in all frequency conditions. The results also showed that the HI values in different frequency conditions were significantly different from each other (p <; 0.005), which proved hysteresis effects in EMG-force relationship were rate-dependent. The rate-dependent hysteresis in EMG-force relationship has a huge potential to improve the estimation performance of grasping force from EMG.","PeriodicalId":137451,"journal":{"name":"2015 7th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123438290","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}
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