Projects

Problem exPLORATION

Inefficient Diagnostic Process

‍

Traditionally, medical professionals rely on observational gait analyses, which uses checklist forms that are limited in accuracy and vulnerable to observer bias. Current tools often suffer from excessive complexity or lack user-friendly interfaces, leading to time-consuming workflows and potential diagnostic errors.

‍

_{Examples of data report from motion tracking software}

‍

Audience

To further clarify our goals, I also narrowed down two types of future users:

Experienced Healthcare Professionals

Motivated to understand comprehensive patient deviations quickly to faster diagnose gait problems and track improvement.
Interested in concise and easy-to-read data with emphasis on the most useful features for diagnosis, visual comparison of various data forms, and easy toggle of patient reports of different dates.

Less Experienced Users:

Motivated to use the application to generate accurate diagnosis and treatment plans
Interested in more detailed diagnoses, suggestions for treatment, informational diagrams, and links to more resources.

I needed to make a design that emphasized with both user groups, to maximize the functionality of this interface.

Design Solution

Ideation / Planning

After researching about the diagnostic process, I created this flow comparison with feedback iterations from my mentor which gave more insights on what features were crucial and which were not. I narrowed them down to the following:

ROM Data: Visually displays the raw numerical ROM data from motion tracking reports (across patient’s gait cycle), to compare to normal ROM. This allows users to directly refer to the raw data in a simple way. Together with the deviations tables, they allow for a comprehensive comparison between data and diagnosis.
Stick figure graph: imported raw data from the report to help users visualize joint angles and positions at each major gait stage.

3D Muscle Diagram: To better display location and connections of mentioned muscle systems for visual reference.

Toggle of different reports (same patient): Enable easy switching to see progress over time.

Deviations Table: Display the abnormal joint angle deviations throughout the patient’s gait cycle, categorized by body part involved and colored by severity. This immediately gives users a complete overview of all the patient's deviation data.

Diagnoses Table: Analysis of the causes or corresponding symptoms of the patient’s major deviations to better aid user diagnosis.

Future Treatment: Suggestions on personalized treatment options for diagnoses such as weak muscle areas, with links to resources.

‍

With those insights, I began sketching possible UI orientations, focusing on the features that needed to be presented together for user comparison.

‍

Prototypes

The first prototype draft above was focused on the deviations mapping feature concept and had an overall simplistic layout.

Through discussions with my mentors, features were moved around and refined. For example, the colored deviation graph was too cluttered and ineffective for multiple deviations to be represented. In response, I simplified the presentation to lower the cognitive load of users.