Projects

Overview

At Kinetic Motion Inc. (KMI), I designed an intuitive user interface to present detailed gait analysis reports derived from advanced motion-tracking technology. The interface was developed to streamline data interpretation for medical professionals, enabling the diagnosis of muscle deficiencies and gait weaknesses for fall prevention treatment.

This project was part of a larger, federally funded initiative under the San Antonio Claude D. Pepper Center at UTHSCSA with applications in Alzheimer's disease, which is supported by the NIH. Working closely with subcontractors on this initiative, Dr. Marcus Hollis, CEO of Blue Bay Research (BBR), and Dr. Wei Liu, Associate professor at UTHSCSA, my work contributed to improving the usability of complex medical data, enabling healthcare professionals to make informed decisions.

Problem Statement

Medical professionals need a streamlined, intuitive solution to analyze patient gait patterns and diagnose related issues. Current tools often suffer from excessive complexity or lack user-friendly interfaces, leading to time-consuming workflows, potential diagnostic errors, and reduced user satisfaction. This results in inefficiencies in both the diagnostic process and overall patient care, highlighting the need for a more accessible, accurate, and effective platform tailored to the needs of healthcare professionals.

Goals

Create an easy-to-use interface for a gait analysis app.

Represent numeric data from motion-tracking technologies in simple, clear visuals like graphs and tables.

Make it easier for doctors to diagnose and treat patients by speeding up the process.

Challenges

Making complex medical data easy to understand.

Ensuring the design fits medical standards and is user-friendly for doctors.

Updating designs based on ongoing feedback from KMI.

Role

The only UI/UX Designer: Led the entire design process from research to final prototypes.

Studied gait analysis and medical design principles.

Worked closely with KMI to make sure designs met their needs.

Research

Audience

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.

features

ROM Data Graph: Visually displays the numerical ROM data from motion capture reports (across patient’s gait cycle), to compare to normal ROM.

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

Toggle of different reports: 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 ranked by severity.

Muscles Involved: diagram showing what muscles are involved in each.

Diagnoses Table: Analysis of the causes or corresponding symptoms of the patient’s major deviations.

Future Treatment: Suggestions on personalized treatment options for diagnoses such as weak muscle areas.

Feature Mapping for Deviations Table

Design

Ideation / Planning

No items found.

After researching into gait problems and diagnosis and medical ui styles, I began with a general brainstorm of main features and rough sketches of layouts.

Each main feature was organized and extended in feature mapping.

Prototypes

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

Through discussions with stakeholders, more features were added to provide a thorough report to help medical professionals with the diagnostic process. For instance, a togglable muscle diagram was added to help clarify the muscle groups involved with each deviation, and a stick figure diagram to help users visualize joint angles and positions at each major gait stage.