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The second term, âindependent livingâ is deïŹnedas âahousing andcommunity ar-
rangement thatmaximizes independence and self-determinationâ. Both termswere in-
troduced in2003and2010 respectively.
It isworthnoting that the terms: living independent, communitydwelling, andage-
ing inplace, arealsoused inhealthcareas synonyms for independent living.
4.3. SmartHouse
According to a review on smart houses welfare technology, âSmart house commonly
refers toany livingorworkingenvironment carefullydesigned toassist residents incar-
ryingoutdailyactivitiesand topromote independent lifestylesâ [7,10].Thegeneralgoal
is toadapt thehouse to theoccupantâspreferences.
When searching inMeSH , there are two terms found.TheïŹrst term is from1992,
âhousing for the elderlyâ, deïŹned as âhousing arrangements for the elderly or aged, in-
tended to foster independent living. The housingmay take the form of group homes
or small apartments. The concept includes housing for the elderlywith some physical
limitationsâ.
Thesecondterm is from1968,âhomesfor theagedâ,deïŹnedasâgeriatric long-term
care facilitieswhichprovide supervision andassistance in activities of daily livingwith
medical andnursingserviceswhen requiredâ.
Synonymsfoundinthehealthcaresciencesforhousingfortheelderlyare:retirement
life care centers, continuing care retirement centers. In the sameway, the synonym for
homes for theaged isoldagehomes.
4.4. ActivityRecognition
Activity recognitionhas been implemented for several decades [4]. People usually tend
tofollowapattern in theirdaily life[33,34].Hence, recognizingthepatternof theperson
helps toadapt a smart house to the inhabitant.
Commonly, theactions recognizedareactivitiesofdalily life (ADL), suchas sleep-
ing, toileting,showering,dressing,eating,etc.Theseareactions that requireâbasicskills
and focus on activities to take care of oneâs ownbodyâ [35]. ByïŹnding repetitive pat-
terns on the personâs activity, it is possible to predict the next activity of the person for
assistance ifneeded [5].
4.5. BehaviourModelling
There is a few studies on behaviourmodeling as described in section 2. Yet, the term
behaviour has not been fully deïŹned as the previous terms presented in this section.At
USN, behaviour is deïŹned as the activity, duration, posture, and location of the person.
E.g., havingbreakfast.Thus, abehaviour is anactivitywithduration [8,9].
HBMhelps to predict the next behaviour of the person and thus adapt better the
smart home to its resident aswell as construct a safer environment. In addition,mod-
elling the behaviour of the person allows detecting any anomaly on the personâs daily
pattern. âAnomalydetection refers to theproblemofïŹndingpatterns indata that donot
conform to expected behaviourâ [36].Detecting anomalies can help alert familymem-
bersor caretakers incaseofdangerous situations suchas falls.
V.G.Sanchez
/WelfareTechnology,Healthcare,andBehaviourModellingâAnAnalysis300
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Titel
- Intelligent Environments 2019
- Untertitel
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Autoren
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-CĂa
- Verlag
- IOS Press BV
- Datum
- 2019
- Sprache
- deutsch
- Lizenz
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Abmessungen
- 16.0 x 24.0 cm
- Seiten
- 416
- Kategorie
- TagungsbÀnde