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dc.contributor.authorYang, Shufan
dc.contributor.authorWong-Lin, Kongfatt
dc.contributor.authorRano, Inaki
dc.contributor.authorLindsay, Anthony
dc.date.accessioned2017-03-07T14:51:49Z
dc.date.available2017-03-07T14:51:49Z
dc.date.issued2017-09-07
dc.identifier.citationIntelligent Systems Conference (IntelliSys) 2017, London, UK. IEEE. 4 pp.
dc.identifier.isbn9781509064359
dc.identifier.doi10.1109/IntelliSys.2017.8324291
dc.identifier.urihttp://hdl.handle.net/2436/620403
dc.description.abstractCurrent multisensory system face data communication overhead in integrating disparate sensor data to build a coherent and accurate global phenomenon. We present here a novel hardware and software co-design platform for a heterogeneous data fusion solution based on a perceptual decision making approach (the drift-diffusion model). It provides a convenient infrastructure for sensor data acquisition and data integration and only uses a single chip Xilinx ZYNQ-7000 XC7Z020 AP SOC. A case study of controlling the moving speed of a single ground-based robot, according to physiological states of the operator based on heart rates, is conducted and demonstrates the possibility of integrated sensor data fusion architecture. The results of our DDM-based data integration shows a better correlation coefficient with the raw ECG signal compare with a simply piecewise approach.
dc.language.isoen
dc.publisherIEEE
dc.relation.urlhttp://saiconference.com/IntelliSys2017
dc.subjectsensor-on-chip
dc.subjectdata fusion
dc.subjectZYNQ
dc.titleA Single Chip System for Sensor Data Fusion Based on a Drift-diffusion Model
dc.typeConference contribution
dc.conference.name2017 Intelligent Systems Conference (IntelliSys)
dc.conference.locationLondon, UK
pubs.finish-date2017-09-08
pubs.start-date2017-09-07
dc.date.accepted2017-01-20
rioxxterms.funderUniversity of Wolverhampton
rioxxterms.identifier.project1014-C4-Ph1-071
rioxxterms.versionAM
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
rioxxterms.licenseref.startdate2018-03-01
refterms.dateFCD2018-07-18T15:24:54Z
refterms.versionFCDAM
refterms.dateFOA2018-03-01T00:00:00Z
html.description.abstractCurrent multisensory system face data communication overhead in integrating disparate sensor data to build a coherent and accurate global phenomenon. We present here a novel hardware and software co-design platform for a heterogeneous data fusion solution based on a perceptual decision making approach (the drift-diffusion model). It provides a convenient infrastructure for sensor data acquisition and data integration and only uses a single chip Xilinx ZYNQ-7000 XC7Z020 AP SOC. A case study of controlling the moving speed of a single ground-based robot, according to physiological states of the operator based on heart rates, is conducted and demonstrates the possibility of integrated sensor data fusion architecture. The results of our DDM-based data integration shows a better correlation coefficient with the raw ECG signal compare with a simply piecewise approach.


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