Matches in SemOpenAlex for { <https://semopenalex.org/work/W4367011967> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W4367011967 endingPage "564" @default.
- W4367011967 startingPage "551" @default.
- W4367011967 abstract "The collective effects of sleep loss and sleep disorders are correlated with many adverse health consequences, including increased risk of high blood pressure, obesity, diabetes, depressive state, and cardiovascular symptoms. Research in eHealth can provide methods to enrich personal health care with information and communication technologies (ICTs). An eCoach system may allow people to manage a healthy lifestyle with extended health state monitoring (e.g., sleep) and tailored recommendation generation. Using supervised machine learning (ML) techniques, this study investigated the possibility of classifying sleep stages at night for adults on hourly and daily basis. The daily total sleep minutes and hourly total sleep minutes for defined sleeping period served as input for the classification models. We first used publicly available Fitbit dataset to build the initial classification models. Second, using the transfer learning approach, we re-used the top five best-performing models on a real dataset as collected from the MOX2-5 wearable medical-grade activity device. We found that support vector classifier (SVC) with “linear” kernel outdated other classifiers with a mean accuracy score of 99.92% for hourly sleep classification and a K-nearest neighbor (KNN) outpaced other classifiers with a mean accuracy score of 99.47% for daily sleep classification, for the public Fitbit datasets. Moreover, to determine the practical efficacy of the classifier models, we conceptualized to use the classifier models in an eCoach prototype system to attain tailored sleep goals (e.g., a weekly goal of 49–63 h of sleeping)." @default.
- W4367011967 created "2023-04-27" @default.
- W4367011967 creator A5007832073 @default.
- W4367011967 creator A5041662804 @default.
- W4367011967 creator A5063683767 @default.
- W4367011967 creator A5072236225 @default.
- W4367011967 creator A5087675927 @default.
- W4367011967 date "2023-01-01" @default.
- W4367011967 modified "2023-09-25" @default.
- W4367011967 title "Sleep Monitoring with Wearable Sensor Data in an eCoach Recommendation System: A Conceptual Study with Machine Learning Approach" @default.
- W4367011967 cites W1989259731 @default.
- W4367011967 cites W2147197409 @default.
- W4367011967 cites W2735376054 @default.
- W4367011967 cites W2782822570 @default.
- W4367011967 cites W2928467655 @default.
- W4367011967 cites W2953978366 @default.
- W4367011967 cites W2961604456 @default.
- W4367011967 cites W2987123595 @default.
- W4367011967 cites W2999008244 @default.
- W4367011967 cites W3021083477 @default.
- W4367011967 cites W3129203550 @default.
- W4367011967 cites W3176549743 @default.
- W4367011967 cites W3209034279 @default.
- W4367011967 cites W49116051 @default.
- W4367011967 doi "https://doi.org/10.1007/978-981-19-5191-6_44" @default.
- W4367011967 hasPublicationYear "2023" @default.
- W4367011967 type Work @default.
- W4367011967 citedByCount "0" @default.
- W4367011967 crossrefType "book-chapter" @default.
- W4367011967 hasAuthorship W4367011967A5007832073 @default.
- W4367011967 hasAuthorship W4367011967A5041662804 @default.
- W4367011967 hasAuthorship W4367011967A5063683767 @default.
- W4367011967 hasAuthorship W4367011967A5072236225 @default.
- W4367011967 hasAuthorship W4367011967A5087675927 @default.
- W4367011967 hasConcept C119857082 @default.
- W4367011967 hasConcept C121687571 @default.
- W4367011967 hasConcept C12267149 @default.
- W4367011967 hasConcept C148524875 @default.
- W4367011967 hasConcept C149635348 @default.
- W4367011967 hasConcept C150594956 @default.
- W4367011967 hasConcept C154945302 @default.
- W4367011967 hasConcept C160735492 @default.
- W4367011967 hasConcept C162324750 @default.
- W4367011967 hasConcept C202645933 @default.
- W4367011967 hasConcept C41008148 @default.
- W4367011967 hasConcept C50522688 @default.
- W4367011967 hasConcept C54290928 @default.
- W4367011967 hasConcept C95623464 @default.
- W4367011967 hasConceptScore W4367011967C119857082 @default.
- W4367011967 hasConceptScore W4367011967C121687571 @default.
- W4367011967 hasConceptScore W4367011967C12267149 @default.
- W4367011967 hasConceptScore W4367011967C148524875 @default.
- W4367011967 hasConceptScore W4367011967C149635348 @default.
- W4367011967 hasConceptScore W4367011967C150594956 @default.
- W4367011967 hasConceptScore W4367011967C154945302 @default.
- W4367011967 hasConceptScore W4367011967C160735492 @default.
- W4367011967 hasConceptScore W4367011967C162324750 @default.
- W4367011967 hasConceptScore W4367011967C202645933 @default.
- W4367011967 hasConceptScore W4367011967C41008148 @default.
- W4367011967 hasConceptScore W4367011967C50522688 @default.
- W4367011967 hasConceptScore W4367011967C54290928 @default.
- W4367011967 hasConceptScore W4367011967C95623464 @default.
- W4367011967 hasLocation W43670119671 @default.
- W4367011967 hasOpenAccess W4367011967 @default.
- W4367011967 hasPrimaryLocation W43670119671 @default.
- W4367011967 hasRelatedWork W2048547120 @default.
- W4367011967 hasRelatedWork W2896186666 @default.
- W4367011967 hasRelatedWork W2950370906 @default.
- W4367011967 hasRelatedWork W3005154454 @default.
- W4367011967 hasRelatedWork W3048726935 @default.
- W4367011967 hasRelatedWork W3170211675 @default.
- W4367011967 hasRelatedWork W3194539120 @default.
- W4367011967 hasRelatedWork W4249229055 @default.
- W4367011967 hasRelatedWork W4313549251 @default.
- W4367011967 hasRelatedWork W4367011967 @default.
- W4367011967 isParatext "false" @default.
- W4367011967 isRetracted "false" @default.
- W4367011967 workType "book-chapter" @default.