TY  - JOUR
A1  - Goerss, Doreen
A1  - Hein, Albert
A1  - Bader, Sebastian
A1  - Halek, Margareta
A1  - Kernebeck, Sven
A1  - Kutschke, Andreas
A1  - Heine, Christina
A1  - Krueger, Frank
A1  - Kirste, Thomas
A1  - Teipel, Stefan
T1  - Automated sensor‐based detection of challenging behaviors in advanced stages of dementia in nursing homes
T2  - Alzheimer's & Dementia
N2  - Sensor‐based assessment of challenging behaviors in dementia may be useful to support caregivers. Here, we investigated accelerometry as tool for identification and prediction of challenging behaviors. We set up a complex data recording study in two nursing homes with 17 persons in advanced stages of dementia. Study included four‐week observation of behaviors. In parallel, subjects wore sensors 24 h/7 d. Participants underwent neuropsychological assessment including MiniMental State Examination and Cohen‐Mansfield Agitation Inventory. We calculated the accelerometric motion score (AMS) from accelerometers. The AMS was associated with several types of agitated behaviors and could predict subject's Cohen‐Mansfield Agitation Inventory values. Beyond the mechanistic association between AMS and behavior on the group level, the AMS provided an added value for prediction of behaviors on an individual level. We confirm that accelerometry can provide relevant information about challenging behaviors. We extended previous studies by differentiating various types of agitated behaviors and applying long‐term measurements in a real‐world setting.
Y1  - 2020
UR  - https://www.hb.fh-muenster.de/opus4/frontdoor/index/index/docId/17335
SN  - 1552-5260
VL  - 16
SP  - 672
EP  - 680
ER  -