Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia
Reljin N, Zimmer G, Malyuta Y, Shelley K, Mendelson Y, Blehar DJ, Darling CE, Chon KH. Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia. PLOS ONE 2018, 13: e0195087. PMID: 29596477, PMCID: PMC5875841, DOI: 10.1371/journal.pone.0195087.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlgorithmsBlood VolumeCase-Control StudiesFemaleHemorrhageHumansHypovolemiaMalePhotoplethysmographySupport Vector MachineWater-Electrolyte ImbalanceWounds and InjuriesConceptsBlood lossTrauma patientsTraditional vital signsLast time pointBlood pressureHemorrhagic shockCombat casualty careBlood withdrawalHealthy volunteersPhotoplethysmographic recordingsHeart rateBlood volumeEuvolemiaVital signsHypovolemiaPercentage changeTime pointsAbsolute changeCasualty carePatientsBattlefield settingsEarly stagesHemorrhageRecordingsHospital