Novel navigation assistive device for deaf drivers.

There are over 466 million people in the world with disabling hearing loss. People with severe-to-profound hearing impairment need to lipread or use sign language, even with hearing aids. Assistive Technologies play a vital role in helping these people interact efficiently with their environment. De...

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Publicado en:Assistive Technology Vol. 34; no. 2; pp. 129 - 140
Autores principales: Otoom, Mwaffaq, Alzubaidi, Mohammad A., Aloufee, Rama
Formato: pictorial questionnaire/scale research tables/charts Journal Article
Publicado: Taylor & Francis Ltd 2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2022
      vid: 34
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      pub: Taylor & Francis Ltd
      place: Philadelphia, Pennsylvania
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        10.1080/10400435.2020.1712499
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        atl: Novel navigation assistive device for deaf drivers.
      aug:
        au:
          Otoom, Mwaffaq
          Alzubaidi, Mohammad A.
          Aloufee, Rama
        affil: Computer Engineering Department, Yarmouk University, Irbid, Jordan
      sug:
        subj:
          Assistive Technology Devices
          Global Positioning System
          Deafness
          Automobile Driving
          Systems Development
          Human
          Usability Study
          Descriptive Statistics
          Voice Recognition Systems
          Experimental Studies
          Questionnaires
          Computer Hardware
      ab: There are over 466 million people in the world with disabling hearing loss. People with severe-to-profound hearing impairment need to lipread or use sign language, even with hearing aids. Assistive Technologies play a vital role in helping these people interact efficiently with their environment. Deaf drivers are not currently able to take full advantage of voice-based navigation applications. In this paper, we describe research that is aimed at developing an assistive device that (1) recognizes voice-stream navigation instructions from GPS-based navigation applications, and (2) maps each voiced navigation instruction to a vibrotactile stimulus that can be perceived and understood by deaf drivers. A 13-element feature vector is extracted from each voice stream, and classified into one of six categories, where each category represents a unique navigation instruction. The classification of the feature vectors is done using a K-Nearest-Neighbor classifier (with an accuracy of 99.05%) which was found to outperform five other classifiers. Each category is then mapped to a unique vibration pattern, which drives vibration motors in real time. A usability study was conducted with ten participants. Three different alternatives were tested, to find the best body locations for mounting the vibration motors. The solution ultimately chosen was two sets of five vibrator motors, where each set was mounted on a bracelet. Ten drivers were asked to rate the proposed device (based on eight different factors) after they used the assistive device on 8 driving routes. The overall mean rating across all eight factors was 4.67 (out of 5) This indicates that the proposed assistive device was seen as useful and effective.
      pubtype: Academic Journal
      doctype:
        pictorial
        questionnaire/scale
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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