FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4205497195> ?p ?o ?g. }

• W4205497195 abstract "<sec> <title>UNSTRUCTURED</title> Leading a sedentary lifestyle may cause numerous health problems. Therefore, sedentary lifestyle changes should be given priority to avoid severe damage. Research in eHealth can provide methods to enrich personal healthcare with Information and Communication Technologies (ICTs). An eCoach system may allow people to manage a healthy lifestyle with health state monitoring and personalized recommendations. Using machine learning (ML) techniques, this study investigated the possibility of classifying daily physical activity for adults into the following classes - sedentary, low active, active, active, highly active, and rigorous active. The daily total step count, total daily minutes of sedentary time, low physical activity (LPA), medium physical activity (MPA), and vigorous physical activity (VPA) served as input for the classification models. We first used publicly available Fitbit data to build the 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 sensor. We found that ensemble ExtraTreesClassifier with an estimator value of 150 outperformed other classifiers with a mean accuracy score of 99.72% for single feature and support vector classifier (SVC) with “linear” kernel outpaced other classifiers with a mean accuracy score of 99.14% for five features, for the public Fitbit datasets. To demonstrate the practical usefulness of the classifiers, we conceptualized how the classifier model can be used in an eCoach prototype system to attain personalized activity goals (e.g., stay active for the entire week). After transfer learning, K-Nearest-Neighbor (KNN) outpaced the other four classifiers for a single feature, and SVC with a “linear” kernel outdid the other four classifiers for multiple features. </sec>" @default.
• W4205497195 created "2022-01-25" @default.
• W4205497195 creator A5063683767 @default.
• W4205497195 date "2021-12-22" @default.
• W4205497195 modified "2023-09-27" @default.
• W4205497195 title "Physical Activity Classification with Wearable Sensor Data in an eCoach Recommendation System (Preprint)" @default.
• W4205497195 cites W1233152270 @default.
• W4205497195 cites W1517185146 @default.
• W4205497195 cites W1901616594 @default.
• W4205497195 cites W1968670561 @default.
• W4205497195 cites W1974344651 @default.
• W4205497195 cites W2029242464 @default.
• W4205497195 cites W2039648153 @default.
• W4205497195 cites W2106868420 @default.
• W4205497195 cites W2107464298 @default.
• W4205497195 cites W2111535615 @default.
• W4205497195 cites W2139229745 @default.
• W4205497195 cites W2147801106 @default.
• W4205497195 cites W2156879797 @default.
• W4205497195 cites W2199078232 @default.
• W4205497195 cites W2273462684 @default.
• W4205497195 cites W2294364812 @default.
• W4205497195 cites W2318181068 @default.
• W4205497195 cites W2343910825 @default.
• W4205497195 cites W2467819909 @default.
• W4205497195 cites W2493206641 @default.
• W4205497195 cites W2523479654 @default.
• W4205497195 cites W2528113844 @default.
• W4205497195 cites W2560473567 @default.
• W4205497195 cites W2575460524 @default.
• W4205497195 cites W2594795921 @default.
• W4205497195 cites W2605488491 @default.
• W4205497195 cites W2735376054 @default.
• W4205497195 cites W2744204866 @default.
• W4205497195 cites W2746003952 @default.
• W4205497195 cites W2788583916 @default.
• W4205497195 cites W2928467655 @default.
• W4205497195 cites W3021083477 @default.
• W4205497195 cites W3128701031 @default.
• W4205497195 cites W3129203550 @default.
• W4205497195 cites W3176549743 @default.
• W4205497195 cites W3192249167 @default.
• W4205497195 cites W355023161 @default.
• W4205497195 doi "https://doi.org/10.2196/preprints.35938" @default.
• W4205497195 hasPublicationYear "2021" @default.
• W4205497195 type Work @default.
• W4205497195 citedByCount "0" @default.
• W4205497195 crossrefType "posted-content" @default.
• W4205497195 hasAuthorship W4205497195A5063683767 @default.
• W4205497195 hasConcept C119857082 @default.
• W4205497195 hasConcept C121687571 @default.
• W4205497195 hasConcept C12267149 @default.
• W4205497195 hasConcept C124101348 @default.
• W4205497195 hasConcept C136764020 @default.
• W4205497195 hasConcept C149635348 @default.
• W4205497195 hasConcept C150594956 @default.
• W4205497195 hasConcept C154945302 @default.
• W4205497195 hasConcept C1862650 @default.
• W4205497195 hasConcept C3020255362 @default.
• W4205497195 hasConcept C41008148 @default.
• W4205497195 hasConcept C43169469 @default.
• W4205497195 hasConcept C71924100 @default.
• W4205497195 hasConcept C95623464 @default.
• W4205497195 hasConceptScore W4205497195C119857082 @default.
• W4205497195 hasConceptScore W4205497195C121687571 @default.
• W4205497195 hasConceptScore W4205497195C12267149 @default.
• W4205497195 hasConceptScore W4205497195C124101348 @default.
• W4205497195 hasConceptScore W4205497195C136764020 @default.
• W4205497195 hasConceptScore W4205497195C149635348 @default.
• W4205497195 hasConceptScore W4205497195C150594956 @default.
• W4205497195 hasConceptScore W4205497195C154945302 @default.
• W4205497195 hasConceptScore W4205497195C1862650 @default.
• W4205497195 hasConceptScore W4205497195C3020255362 @default.
• W4205497195 hasConceptScore W4205497195C41008148 @default.
• W4205497195 hasConceptScore W4205497195C43169469 @default.
• W4205497195 hasConceptScore W4205497195C71924100 @default.
• W4205497195 hasConceptScore W4205497195C95623464 @default.
• W4205497195 hasLocation W42054971951 @default.
• W4205497195 hasOpenAccess W4205497195 @default.
• W4205497195 hasPrimaryLocation W42054971951 @default.
• W4205497195 hasRelatedWork W2101819884 @default.
• W4205497195 hasRelatedWork W2937631562 @default.
• W4205497195 hasRelatedWork W2961085424 @default.
• W4205497195 hasRelatedWork W3048726935 @default.
• W4205497195 hasRelatedWork W3136979370 @default.
• W4205497195 hasRelatedWork W3168994312 @default.
• W4205497195 hasRelatedWork W3194539120 @default.
• W4205497195 hasRelatedWork W4205958290 @default.
• W4205497195 hasRelatedWork W4249229055 @default.
• W4205497195 hasRelatedWork W4361795583 @default.
• W4205497195 isParatext "false" @default.
• W4205497195 isRetracted "false" @default.
• W4205497195 workType "article" @default.