Bruno Donato, Francesca Stradolini, Abuduwaili Tuoheti, F. Angiolini, D. Demarchi, G. Micheli, S. Carrara
{"title":"Raspberry Pi driven flow-injection system for electrochemical continuous monitoring platforms","authors":"Bruno Donato, Francesca Stradolini, Abuduwaili Tuoheti, F. Angiolini, D. Demarchi, G. Micheli, S. Carrara","doi":"10.1109/BIOCAS.2017.8325134","DOIUrl":null,"url":null,"abstract":"The degree of interest in bio-sensing platforms brings to the forefront a corresponding need for effective testing of their capabilities. This necessity is even more crucial when examining the properties of a sensor for continuous monitoring of a concentration trend in time, before in vivo implementations. Moreover, in the framework of personalised medical practices, it is imperative to introduce a robust way to represent and parametrise the highly variable responses of human metabolism. The aim of this paper is to propose a novel solution for the design of an automatic flow-injection environment that can assess the performance of systems for continuous monitoring. The setup is also approved for successfully reproducing a paracetamol concentration trend in buffer solution.","PeriodicalId":361477,"journal":{"name":"2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOCAS.2017.8325134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The degree of interest in bio-sensing platforms brings to the forefront a corresponding need for effective testing of their capabilities. This necessity is even more crucial when examining the properties of a sensor for continuous monitoring of a concentration trend in time, before in vivo implementations. Moreover, in the framework of personalised medical practices, it is imperative to introduce a robust way to represent and parametrise the highly variable responses of human metabolism. The aim of this paper is to propose a novel solution for the design of an automatic flow-injection environment that can assess the performance of systems for continuous monitoring. The setup is also approved for successfully reproducing a paracetamol concentration trend in buffer solution.