Allison Bayro, Noelle Brown, Shannon Mcgarry, Joseph Coyne, Kaylin Strong, Mikaela Aiken, Rebecca Nesmith, Ciara Sibley, Cyrus Foroughi
{"title":"弥合差距:调查生理指标在捕获海军人员认知状态变化中的作用","authors":"Allison Bayro, Noelle Brown, Shannon Mcgarry, Joseph Coyne, Kaylin Strong, Mikaela Aiken, Rebecca Nesmith, Ciara Sibley, Cyrus Foroughi","doi":"10.54941/ahfe1004395","DOIUrl":null,"url":null,"abstract":"This study supplements findings from traditional cognitive assessments using physiological markers—Heart Rate Variability (HRV) and Galvanic Skin Response (GSR)—in conjunction with self-report psychological measures to better understand changes in cognitive state. Forty-nine sailors and marines completed pre-experiment surveys, including the Stanford Sleepiness Scale, the Short Stress State Questionnaire (SSSQ), and a Cognitive State Survey. These assessed various psychological parameters, including arousal, distress, engagement, and sleep quality. Resting GSR and HRV data were collected using Gazepoint Biometric sensors before and after participants completed a set of cognitive tasks. BIOPAC and Kubios software analyses revealed significant changes in several psychophysiological parameters from baseline to post-task, including average skin conductance level (SCL), minimum SCL, and maximum heart rate. Notably, a strong correlation emerged between the low-frequency power feature of HRV and the task-oriented thought score from the SSSQ and between the maximum heart rate and the distress score from the SSSQ. Despite data quality challenges that reduced the sample size, the study uncovers valuable insights into the use of physiological markers in detecting cognitive state changes. These findings highlight the potential of such an approach and underscore the need for further research.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bridging the Gap: Investigating the Role of Physiological Indicators in Capturing Cognitive State Changes among Naval Personnel\",\"authors\":\"Allison Bayro, Noelle Brown, Shannon Mcgarry, Joseph Coyne, Kaylin Strong, Mikaela Aiken, Rebecca Nesmith, Ciara Sibley, Cyrus Foroughi\",\"doi\":\"10.54941/ahfe1004395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study supplements findings from traditional cognitive assessments using physiological markers—Heart Rate Variability (HRV) and Galvanic Skin Response (GSR)—in conjunction with self-report psychological measures to better understand changes in cognitive state. Forty-nine sailors and marines completed pre-experiment surveys, including the Stanford Sleepiness Scale, the Short Stress State Questionnaire (SSSQ), and a Cognitive State Survey. These assessed various psychological parameters, including arousal, distress, engagement, and sleep quality. Resting GSR and HRV data were collected using Gazepoint Biometric sensors before and after participants completed a set of cognitive tasks. BIOPAC and Kubios software analyses revealed significant changes in several psychophysiological parameters from baseline to post-task, including average skin conductance level (SCL), minimum SCL, and maximum heart rate. Notably, a strong correlation emerged between the low-frequency power feature of HRV and the task-oriented thought score from the SSSQ and between the maximum heart rate and the distress score from the SSSQ. Despite data quality challenges that reduced the sample size, the study uncovers valuable insights into the use of physiological markers in detecting cognitive state changes. These findings highlight the potential of such an approach and underscore the need for further research.\",\"PeriodicalId\":470195,\"journal\":{\"name\":\"AHFE international\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AHFE international\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54941/ahfe1004395\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AHFE international","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1004395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bridging the Gap: Investigating the Role of Physiological Indicators in Capturing Cognitive State Changes among Naval Personnel
This study supplements findings from traditional cognitive assessments using physiological markers—Heart Rate Variability (HRV) and Galvanic Skin Response (GSR)—in conjunction with self-report psychological measures to better understand changes in cognitive state. Forty-nine sailors and marines completed pre-experiment surveys, including the Stanford Sleepiness Scale, the Short Stress State Questionnaire (SSSQ), and a Cognitive State Survey. These assessed various psychological parameters, including arousal, distress, engagement, and sleep quality. Resting GSR and HRV data were collected using Gazepoint Biometric sensors before and after participants completed a set of cognitive tasks. BIOPAC and Kubios software analyses revealed significant changes in several psychophysiological parameters from baseline to post-task, including average skin conductance level (SCL), minimum SCL, and maximum heart rate. Notably, a strong correlation emerged between the low-frequency power feature of HRV and the task-oriented thought score from the SSSQ and between the maximum heart rate and the distress score from the SSSQ. Despite data quality challenges that reduced the sample size, the study uncovers valuable insights into the use of physiological markers in detecting cognitive state changes. These findings highlight the potential of such an approach and underscore the need for further research.