J. Ahmadi-Farsani, Davide Caron, G. Panuccio, B. Linares-Barranco, T. Serrano-Gotarredona
{"title":"A Real-Time DSP-Based Biohybrid MEA System for Seizure Detection In Vitro","authors":"J. Ahmadi-Farsani, Davide Caron, G. Panuccio, B. Linares-Barranco, T. Serrano-Gotarredona","doi":"10.1109/MeMeA52024.2021.9478753","DOIUrl":null,"url":null,"abstract":"This paper presents a biohybrid arrangement made of a commercial microelectrode array (MEA) system for seizure-like activity detection in brain slices. The set-up takes advantage of an embedded fixed-point digital signal processor (DSP) to implement a neuron model and a field-potential to spike converter (FP2SP). The neuron model is biologically plausible and capable of generating various firing modalities. Based on a three-step algorithm, FP2SP extracts spikes from the epileptiform activity generated by brain slices. The seizure detector system is developed by connecting the FP2SP to the model neuron and properly tuning the FP2SP parameters. The results show that all the blocks of this system can operate properly in real-time mode and recognize seizure-like activity.","PeriodicalId":429222,"journal":{"name":"2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MeMeA52024.2021.9478753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper presents a biohybrid arrangement made of a commercial microelectrode array (MEA) system for seizure-like activity detection in brain slices. The set-up takes advantage of an embedded fixed-point digital signal processor (DSP) to implement a neuron model and a field-potential to spike converter (FP2SP). The neuron model is biologically plausible and capable of generating various firing modalities. Based on a three-step algorithm, FP2SP extracts spikes from the epileptiform activity generated by brain slices. The seizure detector system is developed by connecting the FP2SP to the model neuron and properly tuning the FP2SP parameters. The results show that all the blocks of this system can operate properly in real-time mode and recognize seizure-like activity.