Wearable Technology for Detecting Significant Moments in Individuals with Dementia.
The detection of significant moments can support the care of individuals with dementia by making visible what is most meaningful to them and maintaining a sense of interpersonal connection. We present a novel intelligent assistive technology (IAT) for the detection of significant moments based on pa...
| Publicado en: | BioMed Research International pp. 1 - 14 |
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| Autores principales: | , , , , , |
| Formato: | research tables/charts tracings Journal Article |
| Publicado: |
Wiley-Blackwell
9/25/2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=138802834&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 138802834 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 9/25/2019 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 138802834 138802834 138802834 10.1155/2019/6515813 138802834 ppf: 1 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Wearable Technology for Detecting Significant Moments in Individuals with Dementia. aug: au: Lai Kwan, Chelsey Mahdid, Yacine Motta Ochoa, Rossio Lee, Keven Park, Melissa Blain-Moraes, Stefanie affil: Biosignal Interaction and Personhood Technology Lab, McGill University, Montreal, Quebec H3G 1A4, Canada sug: subj: Dementia Signal Transduction Wearable Sensors Signal Processing, Computer Assisted Human Assistive Technology Devices Feedback Algorithms Caregivers Emotions Pain Anxiety ab: The detection of significant moments can support the care of individuals with dementia by making visible what is most meaningful to them and maintaining a sense of interpersonal connection. We present a novel intelligent assistive technology (IAT) for the detection of significant moments based on patterns of physiological signal changes in individuals with dementia and their caregivers. The parameters of the IAT are tailored to each individual's idiosyncratic physiological response patterns through an iterative process of incorporating subjective feedback on videos extracted from candidate significant moments identified through the IAT algorithm. The IAT was tested on three dyads (individual with dementia and their primary caregiver) during an eight-week movement program. Upon completion of the program, the IAT identified distinct, personal characteristics of physiological responsiveness in each participant. Tailored algorithms could detect moments of significance experienced by either member of the dyad with an agreement with subjective reports of 70%. These moments were constituted by both physical and emotional significances (e.g., experiences of pain or anxiety) and interpersonal significance (e.g., moments of heighted connection). We provide a freely available MATLAB toolbox with the IAT software in hopes that the assistive technology community can benefit from and contribute to these tools for understanding the subjective experiences of individuals with dementia. pubtype: Academic Journal doctype: research tables/charts tracings Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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