Development of Custom Sound® Pro software utilising big data and its clinical evaluation.

To inform and optimise a cochlear implant (CI) fitting software design through an analysis of big data to define array-specific comfort (C) level profiles, frequently-used MAP parameters, and the minimum number of Neural Response Telemetry thresholds (tNRT) needed to create an accurate profile. To e...

Descripción completa

Detalles Bibliográficos
Publicado en:International Journal of Audiology Vol. 63; no. 2; pp. 87 - 99
Autores principales: Maruthurkkara, Saji, Bennett, Christopher
Formato: pictorial research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Feb2024
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=175642995&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 175642995
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        14992027
        JW2
      jtl: International Journal of Audiology
      issn: 14992027
      maglogo: Y
    pubinfo:
      dt: Feb2024
      vid: 63
      iid: 2
      pid: 377
      pub: Taylor & Francis Ltd
      place: Philadelphia, Pennsylvania
    artinfo:
      ui:
        175642995
        160883820
        175642995
        175642995
        10.1080/14992027.2022.2155880
        175642995
      ppf: 87
      ppct: 12
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Development of Custom Sound® Pro software utilising big data and its clinical evaluation.
      aug:
        au:
          Maruthurkkara, Saji
          Bennett, Christopher
        affil: Cochlear Limited, Sydney, Australia
      sug:
        subj:
          Software Design
          Cochlear Implant
          Auditory Threshold
          Data Analytics
          Cochlear Implant Programming
          Human
          Male
          Female
          Adolescence
          Young Adult
          Adult
          Middle Age
          Aged
          Aged, 80 and Over
          Prospective Studies
          Deafness Therapy
          Neural Pathways
          Loudness Perception
          Speech Perception
          Telemetry
          Goal-Setting
          Algorithms
          User-Computer Interface
          Automation
          Adolescent: 13-18 years
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Aged, 80 & over
          Male
          Female
      ab: To inform and optimise a cochlear implant (CI) fitting software design through an analysis of big data to define array-specific comfort (C) level profiles, frequently-used MAP parameters, and the minimum number of Neural Response Telemetry thresholds (tNRT) needed to create an accurate profile. To evaluate the software's ease of use and completion time for AutoNRT®s. MAPs analysis. Clinical study evaluating software use in creating MAPs, addressing sound-quality issues and setting patient goals. MAPs (N = 39,885); CI recipients (N = 47) and clinicians (N = 19). Distinct C-level profiles were observed for lateral-wall, contour, and slim-modiolar electrode arrays. Default settings were used for most MAP parameters (13/16) except for Pulse Width, Rate, and Maxima. Nine tNRT measurements were required for an accurate C-level profile. Measurement-time of nine tNRTs via the new algorithm was comparable to five tNRTs using the previous algorithm. Nearly all (99%) clinical tasks were completed by clinicians with the first use of the software. Most CI recipients (79.5%) rated goal-setting as valuable. Custom Sound Pro fitting software developed based on big data analysis incorporates a guided fitting workflow and expected fitting ranges. It helps to improve clinical efficiency, is easy to use and supports patient-centred care.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N