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Eyebot x Tufts

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Final Presentation

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Picture yourself behind the frames of a first time Eyebot user

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You make it past the first letter test without any problems,

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Then you have to take your glasses off,

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–leaving you vulnerable and confused.

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To figure out what is happening, you have to lean in to read instructions, adding extra strain.

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Problem Statement

People struggle with the current Eyebot kiosk because the guidance is different from what an eye doctor would provide, and aren’t able to complete the test.

We want to

  • Create a more intuitive instructional experience
  • Facilitate trust in the machine

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Human Factors Opportunity

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Users could be supported with non-invasive, multimodal guidance.

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Hypothesis

If we add sound and light guidance to the Eyebot eye scan test,

Users will have faster

  • Screen-to-screen reaction times
  • Prompted action reaction times
  • Error recovery times

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The Process

Research

Prototyping & Testing

Findings

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Initial Ideation

Recommendations

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Research:

Understanding the problem space

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04/30/2025jkui,ol;’/[]/

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Task Analysis

Self-ethnography

Background Research

Competitive Analysis

Interviews

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Key Insights

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    • Not everyone shares a common mental model

    • Many don’t fully understand or need to understand functionality of tests

    • Extra information should be succinct and optional
    • Reading becomes more strenuous without glasses

    • Error correction is confusing without glasses

    • Multi-modal guidance (i.e. audio) helps provide a sense of ease and direction.
    • People care about their privacy

    • Results should feel “medically official,” rather than like an ad.

It is hard and disorienting to do things without glasses.

Eye exams are complicated!

A health kiosk

shouldn’t be invasive.

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Ideating:

How might we incorporate sound and light communication?

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Where to Make Changes

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We identified areas of opportunity based on our task analysis and feedback from Riley on multimodal communication

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Adding Sound and Light

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Pairing with segmented lights

Testing potential sounds

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Testing Iterations:

How do we design a test to investigate our hypothesis?

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Prototyping

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At a Glance

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Light and Sound

Physical

Methods

Interface

V1

n=7

2 different sound combos: 14/100 and 2/7, same lights

Top screen visible, angles and distance between screens not accurate.

Each participant completes flow 4 times in a randomized order, notified of forced errors.

Original Figma with tutorial videos and color.

V2

n=28

14 for error, 100 for verification, and 2 for test complete, same lights

Top screen set back behind clear window, measurements corrected

Each participant goes through flow once: either with control or light/sound, not notified of forced errors.

Grayscale Figma with pre-test questions, removed arrows.

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Light and Sound

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Light and Sound

V1

n=7

2 different sound combos: 14/1 and 2/7, same lights

V2

n=28

14 for error, 1 for verification, and 2 for test complete, same lights

Sound 1:

Sound 7:

Sound 14:

Sound 2:

Verification

Error

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Physical

Making a higher fidelity prototype was necessary to get accurate results

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Physical

Methods

Interface

V1

n=7

Top screen visible, angles and distance between screens not accurate.

Each participant completes flow 4 times in a randomized order, notified of forced errors.

Original Figma with tutorial videos and color.

V2

n=28

Top screen set back behind clear window, measurements corrected

Each participant goes through flow once: either with control or light/sound, not notified of forced errors.

Grayscale Figma with pre-test questions, removed arrows.

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Testing Methods

Methods

Methods

Interface

V1

n=7

Each participant completes flow 4 times in a randomized order, notified of forced errors.

Each participant completes flow 4 times in a randomized order, notified of forced errors.

Original Figma with tutorial videos and color.

V2

n=28

Each participant goes through flow once: either with control or light/sound, not notified of forced errors.

Each participant goes through flow once: either with control or light/sound, not notified of forced errors.

Grayscale Figma with pre-test questions, removed arrows.

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Avoided repeated exposure which increased perceived usability

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Interface

Found ways to isolate the function of light and sound

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Interface

Methods

Interface

V1

n=7

Original Figma with tutorial videos and color.

Each participant completes flow 4 times in a randomized order, notified of forced errors.

Original Figma with tutorial videos and color.

V2

n=28

Grayscale Figma with pre-test questions, removed arrows.

Each participant goes through flow once: either with control or light/sound, not notified of forced errors.

Grayscale Figma with pre-test questions, removed arrows.

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FINAL PRESENTATION

Returning to the eye scan after taking off your glasses,

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At this point, you are vulnerable and confused.

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Luckily, Eyebot is here to support you along every step of the way.

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We will now do a demo of a multimodal Eyebot kiosk!

Reading doesn’t have to be the only way to figure out what to do.

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Lights

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Split by groups of six LEDs

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Sounds

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Screens

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Lower Fidelity Screens

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Hardware

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Mimicking Hidden Scanner and Screen

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Metrics:

What did we actually test?

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Our version of Eyebot

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Blue changing to green to communicate the step was completed

Pulsing lights to indicate action needed

Verification noise plays at the end to signify moving on

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Testing Metric A

Prompted action reaction time

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Metric A: Time from prompt (Place Glasses Here) to state (Glasses in, Hands off)

Light and sound condition

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Testing Metric A

Prompted action reaction time

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Metric A: Time from prompt (Place Glasses Here) to state (Glasses in, Hands off)

Control condition

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Our version of Eyebot

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Blue to signify “look here,” a neutral color with a health focus

Lights segmented to surround the screen to focus on

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Testing Metrics

Screen-to-screen reaction time

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Metric B: Time from prompt (Look at top screen) to state (Stabilized head, Constantly looking)

Light and sound condition

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Testing Metric B

Screen-to-screen reaction time

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Metric B: Time from prompt (Look at top screen) to state (Stabilized head, Constantly looking)

Control condition

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Our version of Eyebot

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Red to indicate an error, something went wrong in the surrounded section

Lights segmented by screen, communicating different things in each section

Blue to signify “look here,” a neutral color with a health focus

Error noise would play to alert people

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Testing Metric C

Error recovery time

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Metric C: Time from prompt (Error Message) to state (Looking down at the bottom screen)

Light and sound condition

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Testing Metric C

Error recovery time

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Metric C: Time from prompt (Error Message) to state (Looking down at the bottom screen)

Control condition

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Our version of Eyebot

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Red to indicate an error, something went wrong in the surrounded section

Lights segmented to surround the screen to focus on

Error noise would play to alert people

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Testing Metric D

Error recovery time

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Metric D: Time from prompt (Error Message) to state (Looking down at the bottom screen)

Light and sound condition

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Testing Metric D

Error recovery time

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Metric D: Time from prompt (Error Message) to state (Looking down at the bottom screen)

Control condition

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Our version of Eyebot

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Green to indicate complete

Lights segmented to surround the screen where the step was completed

Verification noise plays to signify moving on

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Testing Metrics

Screen-to-screen reaction time

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Metric E: Time from prompt (Scan Done) to state (Looking down at the bottom screen)

Light and sound condition

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Testing Metrics

Screen-to-screen reaction time

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Metric E: Time from prompt (Scan Done) to state (Looking down at the bottom screen)

Control condition

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Testing Results: Did our changes impact the user experience?

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Participant Overview

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33

5

67.7%

total number of version 2 testing participants

of participants wear glasses or contacts regularly

Non-Native English Speakers

[-4.25, +7]

Range of user prescriptions

60.6%

Number of participants aged 21-22

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Findings

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Majority of users found the instructions easy to understand.

“Straightforward and clearly worded!”

“I knew what to do after I got that error- it was clear”

“I wondered what the error was, after reading it, it became obvious what’s next”

“It felt intuitive”

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Findings

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Users felt uncertain when switching their gaze and wanted more communication.

“I wish there was an arrow down like the arrow up”

"Whoops you stopped looking - it would've helped to tell me how long"

“You could add ‘don't look away until a check mark appears’"

“counterintuitive for having more text and instructions after looking up”

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Findings

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Users thought the light and sound choices were intuitive, but…

“one was positive, sound was not stressful or jarring”

"(Light was) good indicator of when to look down"

“when something happens- I'm used to that with phones”

“good chime, bah nah when something bad happened- it’s universal”

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Findings

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…most users tended not to notice the lights or sounds.

“I didn’t see light when everything was going fine, but I noticed when it changed color to red or green”

“I didn’t notice (sound)- that means it was good- wasn't distracting, but good at guiding you”

“I didn't notice at all- except red (?) when I had done something wrong”

“I noticed they (lights) were on but I didn't notice the purpose of them”

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Findings

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No statistically significant differences when comparing the control group to the light/sound groups during glasses prompt, errors, or scan finished prompt.

For Metric B (time in seconds from “look up” prompt to constantly looking at top screen), Wilcoxon Rank-Sum test returned with p-value = 0.01628.

Light design aided users when switching between the bottom to the top screen.

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Notable: Color-Blind Participants

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  • 2 participants with Red-Green Color Blindness
    • (6.5-8% of Men and 0.4% of Women1)
  • Like many other participants, both did not initially notice light design
  • “If both colors are present, then it's really hard to tell the difference. But if only one is on at a time, then I can see the change.”

1 Birch J. Worldwide prevalence of red-green color deficiency. J Opt Soc Am A Opt Image Sci Vis. 2012 Mar 1;29(3):313-20. doi: 10.1364/JOSAA.29.000313. PMID: 22472762.

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Recommendations

Multimodal Feedback

  • Integrate both light and sound cues to guide users, accommodating different sensory preferences.

  • Design simple, peripheral light indicators that are noticeable without distracting the user, especially when glasses are removed.

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Verification:

Error:

Test Complete:

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Recommendations

Clarify User Instructions:

  • Clarify how long users should focus on the balloon, either through audio prompts or visual countdown indicators.

  • Include more on-screen explanation of errors, helping users understand what went wrong and what to do next.

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Recommendations

Revised Onboarding:

  • Introduce brief training or onboarding screens that explain the light and sound components users will encounter during the exam.

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Recommendations

Amount of Information:

  • Add succinct, optional information to provide more details about steps of the process

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Future Directions

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Implement multimodal options in current Eyebot locations - gain insights on a more diverse user group.

Test different “families” of sounds - is one more attention-grabbing?

Test different decibels of sounds – what is the optimal volume in a mall?

More metrics with accurate measurements- look away errors, time to look up, etc.

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Thanks! Questions?

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Appendix A:

Research

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Self-Ethnography Initial Impressions

  • Cool that the product could accurately measure– especially for contacts!
  • Average of 5 minutes 48 seconds. (One contacts, three glasses)
  • Missing sense of privacy & cleanliness.
  • Confusion, especially for people who may not have a mental model from past experiences with an optometrist.
  • Lack of trust:
    • Four-letter choice.
    • Feeling of being out in public.
  • Clear need for increasing intuitiveness – Michelle stated that she never saw anyone make errors because she completed the entire workflow for every user.
  • Lots of words/reading– a potential for user fatigue.
  • Subtle/unclear messaging on the physical kiosk and on the cards.

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(Working) Task Analysis

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(Working) Task Analysis

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(Working) Task Analysis

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(Working) Task Analysis

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(Working) Task Analysis

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(Working) Task Analysis

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(Working) Task Analysis

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Interview Notes

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Interview Notes

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Takeaway #1: Understanding and Awareness of Procedures

  • Limited knowledge about specific procedures for vision correction.
  • Several users wish for better explanations of the tests, but only if provided efficiently.
    • Optional information, short videos, or a brief explanation before each step.
  • Users with a history of medical conditions are more concerned about eye health beyond prescription updates.
    • Clarify position of the kiosk in relation to an eye doctor
      • Emphasis that it is not a replacement for an eye doctor
    • We noticed different needs based on age/health, is current UI/UX meant to address a certain group? Did you have certain personas in mind when designing?
  • Users consistently and correctly identify Snellen Chart and lens switching.
    • Including these steps could help to match the kiosk with doctor experiences.
    • A level of difficulty/challenge is expected in the acuity section (Competitive Analysis)

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Takeaway #2: Result Delivery Preferences

  • Prescription information is the most valued result.
    • (US-specific) Need to update prescription each year for contact orders.
    • Many ignore other data unless explicitly told something is wrong.
  • Digital result preference: Email, Text, Attached PDF Copy.
    • Should feel “medically official” rather than an advertisement for glasses.
    • Was helpful to see side-by-side comparison pictures
  • Confusion on how to interpret their prescription.
    • Dependent on previous eye exam experiences and mental models.
    • Users were unsure what to do next after receiving their results.
  • Users expressed low interest in age percentile comparison data.

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Takeaway #3: Attitudes Toward Automated/Kiosk-Based Eye Exams

  • Privacy Concerns
    • Especially when displaying results on a public screen.
    • Preference for email or private result viewing options.
  • Health-Focused Design and Location
    • Ideal locations for kiosks include health-focused spaces (e.g., pharmacies, campus centers, health fairs) rather than malls.
    • “When I’m in a setting where I’m already in a health setting… associating it with health”
  • Concerns about Test Accuracy
    • Preference for a kiosk as a preliminary test rather than a replacement for a doctor.

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Appendix B:

Ideation

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User Flow Improvement Suggestions

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User Flow Improvement Suggestions

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User Flow Improvement Suggestions

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Demonstration

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RESEARCH SYNTHESIS

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Opportunity Area

Reasoning

Demonstration of light and sound cues (2.b.a)

User may feel pressed for time and want to skip the video immediately leading to a misunderstanding in the steps.

User may feel relieved that there’s instruction in a different form instead of text.

�Users may feel fatigued and be distracted during the video due to its longer format.��Users may be surprised by sounds or lights if not previously introduced.

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Progress Communication

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Opportunity Area

Reasoning

During eye scan (2.b.h)

Users may feel confused about how long they need to stare at the hot air balloon. ��Users may want to know the current status of the scan.

User may look away before the process has concluded.

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Progress Communication

  • Opportunity Areas

    • During eye scan (2.b.h)

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Top Screen

Top Screen

Digital LED progress bar

Hardware LED progress bar

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Verification

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RESEARCH SYNTHESIS

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Opportunity Area

Reasoning

When user adjusts location of feet to line (assuming line stickers still being used) (2.b.c)

There are multiple ways to be misaligned (too close, too far, leaning).

When glasses are placed on scanner (2.b.e.a)

Users may be prompted to restart due to a failed scan, leading to frustration.

When machine is done adjusting (up and down) (2.b.f.c)

Calibration is confusing due to user and machine both responding at the same time.

After auto-refractor/ scanning process (2.b.i)

Glasses users have limited perception without their glasses — they may feel vulnerable and confused.

Users may be focused only on the top screen.

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Verification

  • Opportunity Areas

    • When user adjusts location of feet to line (assuming line stickers still being used) (2.b.c)

    • When glasses are placed on scanner (2.b.e.a)

    • When machine is done adjusting (up and down) (2.b.f.c)

    • After auto-refractor/ scanning process (2.b.i)

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Potential Sounds

Sound 7

Sound 8

Sound 9

Sound 1

Sound 2

Sound 3

Sound 4

Sound 5

Sound 6

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Verification

  • Opportunity Areas

    • When user adjusts location of feet to line (assuming line stickers still being used) (2.b.c)

    • When glasses are placed on scanner (2.b.e.a)

    • When machine is done adjusting (up and down) (2.b.f.c)

    • After auto-refractor/ scanning process (2.b.i)

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Potential Visual

Text specific to use step- actionable instructions

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Glasses Positioning

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Opportunity Area

Reasoning

Placing glasses into scanner (2.b.e.a)

There are many ways to misalign glasses (placed upside down, placed in the wrong area, placed with dirty lenses).

Taking glasses out of scanner (2.b.j)

User may not realize they can pick up their glasses now.

Users with limited vision may struggle to find their glasses.

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Glasses Positioning

  • Opportunity Areas

    • Placing glasses into scanner (2.b.e.a)

    • Taking glasses out of scanner (2.b.j)

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Lights around glasses slot pulsing to indicate region.

Possible change of color to denote cleaning needed.

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User Positioning

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RESEARCH SYNTHESIS

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Opportunity Area

Reasoning

When user adjusts location of feet to line (assuming line stickers still being used) (2.b.c)

There are multiple ways to be misaligned (too close, too far, leaning).

Users may want real-time guidance to reduce number of errors due to body or head misalignment.

When user needs to look at top screen (2.b.f.a)

User may not know where to look or looks at bottom screen rather than top.

When user focuses on balloon (2.b.g)

Same as above.

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User Positioning

  • Opportunity Areas

    • When user adjusts location of feet to line (assuming line stickers still being used) (2.b.c)

    • When user needs to look at top screen (2.b.f.a)

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Eye/head alignment

Hot/cold position indication

Differentiating screen to look at

Redirecting attention

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Appendix C:

Testing & Results

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Testing Design

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Sound Test (1-8).1

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Sound Test (9-16).1

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Sound Test (1-8).2

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Sound Test (9-16).2

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Sound Test (1-8).3

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Sound Test (9-16).3

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Appendix D:

Statistical Analysis

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R Code

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