Proof-of-concept energy-efficient and real-time hemodynamic feature extraction from bioimpedance signals using a mixed-signal field programmable analog array

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dc.citation.epage236en_US
dc.citation.spage233en_US
dc.contributor.authorTöreyin, Hakanen_US
dc.contributor.authorShah, S.en_US
dc.contributor.authorHersek, S.en_US
dc.contributor.authorİnan, O. T.en_US
dc.contributor.authorHasler, J.en_US
dc.coverage.spatialOrlando, FL, USAen_US
dc.date.accessioned2018-04-12T11:46:24Z
dc.date.available2018-04-12T11:46:24Z
dc.date.issued2017en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 16-19 February 2017en_US
dc.descriptionConference Name: IEEE EMBS International Conference on Biomedical & Health Informatics, BHI 2017en_US
dc.description.abstractWe present a mixed-signal system for extracting hemodynamic parameters in real-time from noisy electrical bioimpedance (EBI) measurements in an energy-efficient manner. The proof-of-concept system consists of floating-gate-based analog signal processing (ASP) electronics implemented on a field programmable analog array (FPAA) chip interfaced with an on-chip low-power microcontroller. Physiological features important for calculating hemodynamic parameters (e.g., heart rate, blood volume, and blood flow) are extracted using the custom signal processing circuitry, which consumes a total power of 209 nW. Testing of the signal processing circuitry has been performed using ∼580 sec of an impedance plethysmography dataset collected from the knee of a subject using a custom analog EBI front-end. Results show the similarities of variations in heart rate, blood volume, and blood flow calculated using features extracted by the ASP circuitry implemented on an FPAA and a MATLAB digital signal processing algorithm.en_US
dc.identifier.doi10.1109/BHI.2017.7897248en_US
dc.identifier.urihttp://hdl.handle.net/11693/37636
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/BHI.2017.7897248en_US
dc.source.titleProceedings of the IEEE EMBS International Conference on Biomedical & Health Informatics, BHI 2017en_US
dc.subjectBiomedical signal processingen_US
dc.subjectBlooden_US
dc.subjectDigital signal processingen_US
dc.subjectElectric impedanceen_US
dc.subjectElectric signal systemsen_US
dc.subjectEnergy efficiencyen_US
dc.subjectFeature extractionen_US
dc.subjectField programmable gate arrays (FPGA)en_US
dc.subjectHearten_US
dc.subjectHemodynamicsen_US
dc.subjectMATLABen_US
dc.subjectPhysiological modelsen_US
dc.subjectPlethysmographyen_US
dc.subjectSignal systemsen_US
dc.subjectStatistical testsen_US
dc.subjectAnalog signal processingen_US
dc.subjectDigital signal processing algorithmsen_US
dc.subjectElectrical bio-impedanceen_US
dc.subjectField programmable analog arraysen_US
dc.subjectHemodynamic parametersen_US
dc.subjectImpedance plethysmographyen_US
dc.subjectLow-power microcontrollersen_US
dc.subjectPhysiological featuresen_US
dc.subjectSignal processingen_US
dc.titleProof-of-concept energy-efficient and real-time hemodynamic feature extraction from bioimpedance signals using a mixed-signal field programmable analog arrayen_US
dc.typeConference Paperen_US

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