I. Forsyth, Megan Dunston, G. Lombardi, G. Rind, S. Ronayne, Y. Wong, C. May, D. Grayden, T. Oxley, N. Opie, Sam E. John
{"title":"微创血管内神经接口对运动活动解码的评估","authors":"I. Forsyth, Megan Dunston, G. Lombardi, G. Rind, S. Ronayne, Y. Wong, C. May, D. Grayden, T. Oxley, N. Opie, Sam E. John","doi":"10.1109/NER.2019.8717000","DOIUrl":null,"url":null,"abstract":"Endovascular devices like the Stentrode™ provide a minimally invasive approach to brain-machine-interfaces that mitigates safety concerns while maintaining good signal quality. Our research aims to evaluate the feasibility of using a stent-electrode array (Stentrode) to decode movements in sheep. In this study, two sheep were trained to perform an automated forced-choice task designed to elicit left and right head movement following an external stimulus. Cortical, movement-related signals were recorded using a Stentrode placed in the superior sagittal sinus adjacent to the motor cortex. Recorded brain signal was used to train a support vector machine classifier. Our results show that the Stentrode can be used to acquire motor-related brain signals to detect movement of the sheep in a forced-choice task. These results support the validity of using the Stentrode as a minimally invasive brain-machine interface.","PeriodicalId":356177,"journal":{"name":"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Evaluation of a minimally invasive endovascular neural interface for decoding motor activity\",\"authors\":\"I. Forsyth, Megan Dunston, G. Lombardi, G. Rind, S. Ronayne, Y. Wong, C. May, D. Grayden, T. Oxley, N. Opie, Sam E. John\",\"doi\":\"10.1109/NER.2019.8717000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Endovascular devices like the Stentrode™ provide a minimally invasive approach to brain-machine-interfaces that mitigates safety concerns while maintaining good signal quality. Our research aims to evaluate the feasibility of using a stent-electrode array (Stentrode) to decode movements in sheep. In this study, two sheep were trained to perform an automated forced-choice task designed to elicit left and right head movement following an external stimulus. Cortical, movement-related signals were recorded using a Stentrode placed in the superior sagittal sinus adjacent to the motor cortex. Recorded brain signal was used to train a support vector machine classifier. Our results show that the Stentrode can be used to acquire motor-related brain signals to detect movement of the sheep in a forced-choice task. These results support the validity of using the Stentrode as a minimally invasive brain-machine interface.\",\"PeriodicalId\":356177,\"journal\":{\"name\":\"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NER.2019.8717000\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NER.2019.8717000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluation of a minimally invasive endovascular neural interface for decoding motor activity
Endovascular devices like the Stentrode™ provide a minimally invasive approach to brain-machine-interfaces that mitigates safety concerns while maintaining good signal quality. Our research aims to evaluate the feasibility of using a stent-electrode array (Stentrode) to decode movements in sheep. In this study, two sheep were trained to perform an automated forced-choice task designed to elicit left and right head movement following an external stimulus. Cortical, movement-related signals were recorded using a Stentrode placed in the superior sagittal sinus adjacent to the motor cortex. Recorded brain signal was used to train a support vector machine classifier. Our results show that the Stentrode can be used to acquire motor-related brain signals to detect movement of the sheep in a forced-choice task. These results support the validity of using the Stentrode as a minimally invasive brain-machine interface.