LEADER 03179nam 22003613 450 001 9910869164603321 005 20240703080304.0 010 $a9783658446888 035 $a(CKB)32609760400041 035 $a(MiAaPQ)EBC31508247 035 $a(Au-PeEL)EBL31508247 035 $a(EXLCZ)9932609760400041 100 $a20240703d2024 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEmpowering Independent Living Using the ICF $eAn Unobtrusive Home Monitoring Sensor System for Older Adults 205 $a1st ed. 210 1$aWiesbaden :$cSpringer Vieweg. in Springer Fachmedien Wiesbaden GmbH,$d2024. 210 4$d©2024. 215 $a1 online resource (141 pages) 311 08$a9783658446871 327 $aIntro -- Acknowledgements -- Abstract -- Kurzzusammenfassung -- Contents -- List of Figures -- List of Tables -- 1 Introduction -- 2 A Deep Learning Approach for TUG and SPPB Score Prediction of (Pre-) Frail Older Adults on Real-Life IMU Data -- 2.1 Introduction -- 2.2 State of the Art -- 2.3 Methods and Materials -- Data Acquisition -- Preprocessing -- Network Architecture -- 2.4 Results -- 2.5 Discussion -- 2.6 Conclusions and Future Work -- References -- 3 Detecting Impending Malnutrition of (Pre-) Frail Older Adults in Domestic Smart Home Environments -- 3.1 Introduction -- 3.2 State of the Art -- Nutritional Intake and Body Weight -- Activities of Daily Living -- 3.3 Materials and Methods -- Data Acquisition -- Data Preprocessing -- Meal Preparation Time Estimation -- Minimal Clinically Important Difference -- Statistical Analysis -- 3.4 Results -- 3.5 Discussion -- 3.6 Conclusions -- References -- 4 Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults -- 4.1 Introduction -- 4.2 State of the Art -- 4.3 Materials and Methods -- Study Design -- Data Acquisition -- Sensor Graph -- Difference Function -- Preprocessing -- Statistical and Computational Methods -- 4.4 Results -- 4.5 Discussion -- 4.6 Conclusions -- References -- 5 Unsupervised Statistical Concept Drift Detection for Behaviour Abnormality Detection -- 5.1 Introduction -- 5.2 State of the Art -- 5.3 Materials and Methods -- Data Acquisition -- Data Preprocessing -- Activity Probability Maps -- Feature Engineering -- Unsupervised Statistical Concept Drift Detection -- Central Limit Theorem -- Variational Autoencoder -- Method Validation -- 5.4 Results -- Underlying Distribution Approximation -- Artificial dataset -- Real-world Dataset -- 5.5 Discussion -- 5.6 Conclusions -- References. 327 $a6 A System for Monitoring the Functional Status of Older Adults in Daily Life -- 6.1 Introduction -- 6.2 State of the Art -- 6.3 Methods -- 6.4 Results -- 6.5 Discussion -- 6.6 Conclusion -- References -- 7 General Discussion -- Bibliography. 700 $aFriedrich$b Bjö$01743761 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910869164603321 996 $aEmpowering Independent Living Using the ICF$94171969 997 $aUNINA