PURPOSE: People enjoy supervision during visual field assessment, although resource demands often make this difficult. We evaluated outcomes and subjective experience of methods of receiving feedback during perimetry, with specific goals to compare a humanoid robot to a computerized voice in participants with minimal prior perimetric experience. Human feedback and no feedback also were compared. METHODS: Twenty-two younger (aged 21-31 years) and 18 older (aged 52-76 years) adults participated. Visual field tests were conducted using an Octopus 900, controlled with the Open Perimetry Interface. Participants underwent four tests with the following feedback conditions: (1) human, (2) humanoid robot, (3) computer speaker, and (4) no feedback, in random order. Feedback rules for the speaker and robot were identical, with the difference being a social interaction with the robot before the test. Quantitative perimetric performance compared mean sensitivity (dB), fixation losses, and false-positives. Subjective experience was collected via survey. RESULTS: There was no significant effect of feedback type on the quantitative measures. For younger adults, the human and robot were preferred to the computer speaker (P < 0.01). For older adults, the experience rating was similar for the speaker and robot. No feedback was the least preferred option of 77% younger and 50% older adults. CONCLUSIONS: During perimetry, a social robot was preferred to a computer speaker providing the same feedback, despite the robot not being visible during the test. Making visual field testing more enjoyable for patients and operators may improve compliance and attitude to perimetry, leading to improved clinical outcomes. TRANSLATIONAL RELEVANCE: Our data suggest that humanoid robots can replace some aspects of human interaction during perimetry and are preferable to receiving no human feedback.
PURPOSE: People enjoy supervision during visual field assessment, although resource demands often make this difficult. We evaluated outcomes and subjective experience of methods of receiving feedback during perimetry, with specific goals to compare a humanoid robot to a computerized voice in participants with minimal prior perimetric experience. Human feedback and no feedback also were compared. METHODS: Twenty-two younger (aged 21-31 years) and 18 older (aged 52-76 years) adults participated. Visual field tests were conducted using an Octopus 900, controlled with the Open Perimetry Interface. Participants underwent four tests with the following feedback conditions: (1) human, (2) humanoid robot, (3) computer speaker, and (4) no feedback, in random order. Feedback rules for the speaker and robot were identical, with the difference being a social interaction with the robot before the test. Quantitative perimetric performance compared mean sensitivity (dB), fixation losses, and false-positives. Subjective experience was collected via survey. RESULTS: There was no significant effect of feedback type on the quantitative measures. For younger adults, the human and robot were preferred to the computer speaker (P < 0.01). For older adults, the experience rating was similar for the speaker and robot. No feedback was the least preferred option of 77% younger and 50% older adults. CONCLUSIONS: During perimetry, a social robot was preferred to a computer speaker providing the same feedback, despite the robot not being visible during the test. Making visual field testing more enjoyable for patients and operators may improve compliance and attitude to perimetry, leading to improved clinical outcomes. TRANSLATIONAL RELEVANCE: Our data suggest that humanoid robots can replace some aspects of human interaction during perimetry and are preferable to receiving no human feedback.
Entities:
Keywords:
feedback; healthcare robot; perimetry; robot; social robot
Authors: Pete R Jones; Giorgia Demaria; Iris Tigchelaar; Daniel S Asfaw; David F Edgar; Peter Campbell; Tamsin Callaghan; David P Crabb Journal: Transl Vis Sci Technol Date: 2020-07-20 Impact factor: 3.283
Authors: María Consuelo Sáiz-Manzanares; Raúl Marticorena-Sánchez; Javier Ochoa-Orihuel Journal: Int J Environ Res Public Health Date: 2020-08-04 Impact factor: 3.390