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Improving Sensor Alignment, with user feedback
Problem
To complete onboarding, users must connect, attach, and align their sensors. During the alignment flow, users are guided to step onto an alignment block (yoga block) to create flexion, after which the app records the sensor angle.
A study with representative users identified several issues with the existing Sensor Alignment workflow, which is a critical step in ensuring the overall success of the product.
Brief
Using study data, propose a new concept design to the replace the existing MS 2.0 Sensor Alignment workflow.
Analysis of the Problem
Current Flow
At the end of the alignment workflow, the app prompts the user to test the sensor accuracy. This assessment allows users to evaluate how accurately the sensors are aligned. Sensors that are correctly aligned should record an angle close to 0 degrees when the leg is fully straight.
(1) SENSOR ALIGNMENT
The app records the sensor angle while the user holds the alignment position on the block.
(2) SENSOR ACCURACY CHECK SCREEN/INSTRUCTIONS
The user is then instructed to step off the block and straighten their leg. Once the leg is confirmed to be straight, the user is introduced to an avatar.
(3) SENSOR ACCURACY CHECK SCREEN/LIVE SCREEN
On the live screen, the avatar is displayed, showing an arc that mirrors the live sensor reading. The user is prompted to confirm whether the avatar’s leg position matches their own.
(4) ALIGNMENT COMPLETE
If the user confirms that the avatar's leg position matches theirs, the sensor alignment is considered complete.
Study Data - Check Angle Accuracy Screen
Observations from 22 Participants:
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5 participants incorrectly confirmed that the avatar matched their leg position, even when it did not
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3 participants were unsure or unaware of the acceptable accuracy tolerance
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1 participant did not move their leg to properly test sensor accuracy
Study participant doing sensor alignment in study (left). Moderator performing goniometer reading (right)
Problems Identified
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When the avatar displays an angle close to zero, users generally understand the feedback and confirm alignment accurately. However, there is a grey area, typically when the sensor is off by 10–15 degrees, where confusion arises
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In these cases, users often assume that any avatar movement indicates a correct match, without verifying whether the avatar's leg truly aligns with their own straight leg
Action
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Revisit the sensor accuracy confirmation screen and the broader alignment flow to explore ways to improve user success and confidence when choosing between: ‘Yes, her leg matches’ and ‘No, it looks different
Constraints
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Not all users are able to fully straighten their leg during the accuracy check—particularly those recovering from or preparing for surgery. Some may only be able to achieve a partially extended position, such as 30 degrees of flexion
Design Concept
The updated proposal removes the live avatar screen and refines the sensor accuracy check by automating the sensor reading once the user selects “I have straightened my leg.” Based on the sensor’s reading, the app responds with one of four tailored feedback scenarios:
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SCENARIO 1
Sensor records 0-15 degrees -
SCENARIO 2
Sensor records 15 degrees to goniometer reading* -
SCENARIO 3
Sensor records greater than goniometer angle (obviously wrong as the user in this case would be flexing, not straightening) -
SCENARIO 4
Sensor records hyperextension
*The goniometer reading is taken by the clinician during the user's first appointment, while the user stands on the block and flexes their leg following the same positioning instructions used during sensor alignment.
Scenario 1 - Sensor Records 0-15 Degrees
The app automatically completes the alignment process if the sensor records a value between 0–15 degrees. In this case, the user does not need to verify accuracy against the system, as the alignment is assumed to be within an acceptable range.
Why this is an Improvement?
The user no longer needs to test sensor accuracy using a live screen.
Scenario 2 - Sensor Records 15 Degrees to Goniometer Reading
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Static Avatar Comparison
The app displays a static image of an avatar leg representing the sensor's recorded angle. The user is asked:
“Does the leg in the image below match your leg when you straightened it as far as you could?”
Response options:-
'Yes, her leg matches' → progresses the user
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'No, my leg was straighter'
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'No, my leg was more bent'
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Progression on Match
If the user selects 'Yes, her leg matches', the alignment process is completed. -
Prompt to Recheck
If the user selects either 'my leg was straighter' or 'more bent', the app prompts them to recheck their position and repeat the straight-leg check. This step verifies whether the user followed the alignment instructions correctly. -
Repeat Error Handling
If the same mismatch is reported more than twice, the app suggests redoing the full sensor alignment workflow, indicating potential misunderstanding of the alignment instructions. -
Escalation to Support
If the mismatch persists more than five times, the app advises the user to contact Technical Support for further assistance.
Why this is an Improvement?
With this updated flow, the user no longer sees a moving arc which previously caused confusion and the ambiguity .
If the static image does not match the user’s leg position, the app can more reliably infer what may have gone wrong, whether it’s a positioning error or a misunderstanding of the alignment instructions.
Scenario 3 - Sensor Records Greater than Goniometer Angle (Obviously Wrong)
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Since displaying the still leg image in Scenario 2 did not add value, the app now shows a modal with the following suggestions before prompting the user to check alignment again:
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'Make sure you are straightening your leg and not bending'
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'Make sure you are standing straight'
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If this issue occurs more than twice, the app will ask the user to redo the sensor alignment. This ensures that the user has followed the alignment instructions correctly (i.e., standing as straight as possible).
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If the problem persists after 5 attempts, the app will advise the user to contact their practitioner to arrange a new goniometer reading.
Why this is an Improvement?
This approach allows the app to identify the root cause more quickly, streamlining the troubleshooting process for the user.
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Scenario 4 - Sensor Records Hyperextension
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The app gives the user two opportunities to redo the sensor alignment, as rechecking sensor accuracy would not yield a different result in this scenario
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If the error persists after these attempts, the app directs the user to contact their physical therapist for further assistance
Why this is an Improvement?
Once again, the app is better at focusing on the root cause and can rule out issues related to sensor alignment before instructing the user to contact their physical therapist.
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What Came Next?
Given the time constraints before an upcoming study, I needed to propose a solution with a lower developer cost. I came up with three suggestions:
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Current Implementation (minus the live arc, plus a static arrow):
This approach retains the existing workflow but simplifies it by removing the live arc and adding a static arrow for clearer guidance. -
Proposed Solution Above:
The updated solution that incorporates the modal suggestions and streamlined error handling. -
Simplified Option, No Feedback:
Ask the user to straighten their leg, capture the sensor reading, and provide no further feedback. The issue with this option is that it wouldn't give us valuable insight into how users are making mistakes.
Final Design
We agreed to implement Concept 1 with the following enhancements:
- Straighten Leg Instruction Screen
- Copy Update: The copy was updated to instruct the user to straighten their leg as far as they can.
- Visual Update: The visual was revised to better emphasize the action of straightening the leg.
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Live Feedback Screen
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Removal of Live Arc: The live arc was removed to simplify the process. However, the avatar would still move, providing real-time feedback on alignment.
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Arrow Inclusion: An arrow was added to indicate the correct direction, guiding the user on how to adjust their leg position.
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Why this is an Improvement?
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Clearer Instructions:
The app now clearly tells users to straighten their leg as much as possible, reducing confusion. -
Simplified Feedback:
Replacing the live arc with a static arrow gives direct, easy-to-follow guidance on leg position. -
Accuracy Tolerance:
While this solution doesn’t fully address accuracy tolerance (as much as the earlier concept), it still simplifies the alignment process and reduces ambiguity.
