Molly Alexandre, Song Luan, Z. Mari, W. Anderson, Y. Salimpour, T. Constandinou, L. Grand
{"title":"基于相位振幅耦合的嵌入式帕金森病闭环平台","authors":"Molly Alexandre, Song Luan, Z. Mari, W. Anderson, Y. Salimpour, T. Constandinou, L. Grand","doi":"10.1109/BIOCAS.2018.8584699","DOIUrl":null,"url":null,"abstract":"Deep Brain Stimulation (DBS) is a widely used clinical therapeutic modality to treat Parkinsons disease refractory symptoms and complications of levodopa therapy. Currently available DBSsystems use continuous, open-loop stimulation strategies. It might be redundant and we could extend the battery life otherwise. Recently, robust electrophysiological signatures of Parkinsons disease have been characterized in motor cortex of patients undergoing DBS surgery. Reductions in the beta-gamma Phase-Amplitude coupling (PAC) correlated with symptom improvement, and the therapeutic effects of DBS itself. We aim to develop a miniature, implantable and adaptive system, which only stimulates the neural target, when triggered by the output of the appropriate PAC algorithm. As a first step, in this paper we compare published PAC algorithms by using human data intra-operatively recorded from Parkinsonian patients. We then introduce IIR masking for later achieving fast and low-power FPGA implementation of PAC mapping for intra-operative studies. Our closed-loop application is expected to consume significantly less power than current DBS systems, therefore we can increase the battery life, without compromising clinical benefits.","PeriodicalId":259162,"journal":{"name":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Embedded Phase-Amplitude Coupling Based Closed-loop Platform for Parkinson's Disease\",\"authors\":\"Molly Alexandre, Song Luan, Z. Mari, W. Anderson, Y. Salimpour, T. Constandinou, L. Grand\",\"doi\":\"10.1109/BIOCAS.2018.8584699\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep Brain Stimulation (DBS) is a widely used clinical therapeutic modality to treat Parkinsons disease refractory symptoms and complications of levodopa therapy. Currently available DBSsystems use continuous, open-loop stimulation strategies. It might be redundant and we could extend the battery life otherwise. Recently, robust electrophysiological signatures of Parkinsons disease have been characterized in motor cortex of patients undergoing DBS surgery. Reductions in the beta-gamma Phase-Amplitude coupling (PAC) correlated with symptom improvement, and the therapeutic effects of DBS itself. We aim to develop a miniature, implantable and adaptive system, which only stimulates the neural target, when triggered by the output of the appropriate PAC algorithm. As a first step, in this paper we compare published PAC algorithms by using human data intra-operatively recorded from Parkinsonian patients. We then introduce IIR masking for later achieving fast and low-power FPGA implementation of PAC mapping for intra-operative studies. Our closed-loop application is expected to consume significantly less power than current DBS systems, therefore we can increase the battery life, without compromising clinical benefits.\",\"PeriodicalId\":259162,\"journal\":{\"name\":\"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIOCAS.2018.8584699\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Biomedical Circuits and Systems Conference (BioCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOCAS.2018.8584699","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Embedded Phase-Amplitude Coupling Based Closed-loop Platform for Parkinson's Disease
Deep Brain Stimulation (DBS) is a widely used clinical therapeutic modality to treat Parkinsons disease refractory symptoms and complications of levodopa therapy. Currently available DBSsystems use continuous, open-loop stimulation strategies. It might be redundant and we could extend the battery life otherwise. Recently, robust electrophysiological signatures of Parkinsons disease have been characterized in motor cortex of patients undergoing DBS surgery. Reductions in the beta-gamma Phase-Amplitude coupling (PAC) correlated with symptom improvement, and the therapeutic effects of DBS itself. We aim to develop a miniature, implantable and adaptive system, which only stimulates the neural target, when triggered by the output of the appropriate PAC algorithm. As a first step, in this paper we compare published PAC algorithms by using human data intra-operatively recorded from Parkinsonian patients. We then introduce IIR masking for later achieving fast and low-power FPGA implementation of PAC mapping for intra-operative studies. Our closed-loop application is expected to consume significantly less power than current DBS systems, therefore we can increase the battery life, without compromising clinical benefits.