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A 2.45μW Patient-Specific Non-Invasive Transcranial Electrical Stimulator with an Adaptive Skin-Electrode Impedance Monitor

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dc.contributor.authorBin Altaf, Muhammad Awais-
dc.contributor.authorYoo, Jerald-
dc.date.accessioned2024-05-03T04:34:08Z-
dc.date.available2024-05-03T04:34:08Z-
dc.date.created2024-05-02-
dc.date.issued2015-
dc.identifier.citation2015 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS), pp.270-273-
dc.identifier.issn2163-4025-
dc.identifier.urihttps://hdl.handle.net/10371/200834-
dc.description.abstractThis paper presents a power-efficient noninvasive transcranial electrical stimulator (tES) with patient-specific impedance adaptation. The proposed tES exploits the varying skin-electrode impedance which results in different RC relaxation time, where the tES adapts the number of pulses to deliver a constant charge. This eliminates the need of an additional current source for impedance monitoring widely used in conventional stimulation techniques, thereby reducing power consumption. To ensure safety for patients, a charge balanced bi-phasic stimulation is implemented with maximum current of < 1mA. The proposed tES is implemented in 0.18 mu m CMOS with an area and power consumption of 0.035mm(2) and 2.45 mu W, respectively.-
dc.language영어-
dc.publisherIEEE-
dc.titleA 2.45μW Patient-Specific Non-Invasive Transcranial Electrical Stimulator with an Adaptive Skin-Electrode Impedance Monitor-
dc.typeArticle-
dc.citation.journaltitle2015 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS)-
dc.identifier.wosid000398907900079-
dc.identifier.scopusid2-s2.0-84962733752-
dc.citation.endpage273-
dc.citation.startpage270-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorYoo, Jerald-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.subject.keywordAuthorImpedance monitoring-
dc.subject.keywordAuthornon-invasive-
dc.subject.keywordAuthorpulsating voltage mode stimulation-
dc.subject.keywordAuthortranscranial stimulation-
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부교수
  • College of Engineering
  • Department of Electrical and Computer Engineering
Research Area Biomedical Applications, Energy-Efficient Integrated Circuits

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