Development and evaluation of a hand tracker using depth images captured from an overhead perspective.

Purpose: We present the development and evaluation of a robust hand tracker based on single overhead depth images for use in the COACH, an assistive technology for people with dementia. The new hand tracker was designed to overcome limitations experienced by the COACH in previous clinical trials.Met...

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Publicado en:Disability & Rehabilitation: Assistive Technology Vol. 11; no. 2; pp. 150 - 158
Autores principales: Czarnuch, Stephen, Mihailidis, Alex
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Feb2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2016
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      pub: Taylor & Francis Ltd
      place: Philadelphia, Pennsylvania
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        10.3109/17483107.2015.1027304
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        atl: Development and evaluation of a hand tracker using depth images captured from an overhead perspective.
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        au:
          Czarnuch, Stephen
          Mihailidis, Alex
        affil: Faculties of Engineering and Medicine, Memorial University, St. John's, Newfoundland, Canada
      sug:
        subj:
          Dementia Psychosocial Factors
          Monitoring, Physiologic Methods
          Instrument Construction
          Assistive Technology Evaluation
          Human
          Funding Source
          Comparative Studies
          Decision Support Systems, Clinical
      ab: Purpose: We present the development and evaluation of a robust hand tracker based on single overhead depth images for use in the COACH, an assistive technology for people with dementia. The new hand tracker was designed to overcome limitations experienced by the COACH in previous clinical trials.Methods: We train a random decision forest classifier using ∼5000 manually labeled, unbalanced, training images. Hand positions from the classifier are translated into task actions based on proximity to environmental objects. Tracker performance is evaluated using a large set of ∼24 000 manually labeled images captured from 41 participants in a fully-functional washroom, and compared to the system’s previous colour-based hand tracker.Results: Precision and recall were 0.994 and 0.938 for the depth tracker compared to 0.981 and 0.822 for the colour tracker with the current data, and 0.989 and 0.466 in the previous study.Conclusions: The improved tracking performance supports integration of the depth-based tracker into the COACH toward unsupervised, real-world trials.Implications for RehabilitationThe COACH is an intelligent assistive technology that can enable people with cognitive disabilities to stay at home longer, supporting the concept of aging-in-place.Automated prompting systems, a type of intelligent assistive technology, can help to support the independent completion of activities of daily living, increasing the independence of people with cognitive disabilities while reducing the burden of care experienced by caregivers.Robust motion tracking using depth imaging supports the development of intelligent assistive technologies like the COACH.Robust motion tracking also has application to other forms of assistive technologies including gaming, human–computer interaction and automated assessments.
      pubtype: Academic Journal
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        equations & formulas
        pictorial
        research
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      ougenre: Article
    language: English
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