StepCheck | Wearable Gait Trainer

My Role:

Designed and simulated a wearable system concept for foot pronation tracking. I developed the sensing architecture, processed biomechanical gait data in MATLAB, and created an Android application prototype for real-time visualization and guided exercises

Project Type:

Personal Project

Impact:

Excessive foot pronation can cause musculoskeletal imbalances and increase the risk of injury. StepCheck presents an innovative wearable device that tracks foot pronation angle and pressure distribution using accessible sensors by providing interactive feedback to promote foot health. It demonstrates an affordable and engaging method to monitor gait dynamics and correct excessive pronation through guided exercises.

Techniques:

CAD modelling, Hardware Design, Signal Processing & Analysis, Biomechanical Modeling, Mobile App Development (Android Studio, Java, real-time data visualization, user interface design)

Problem

Excessive foot pronation can lead to musculoskeletal issues. Accurate analysis is needed for better foot health and performance.

Objectives

Design of an innovative wearable device that can track foot pronation and collects relevant data using accessible sensors.
Biomechanical analysis of scientific dataset that includes measurements of individual with gait impairments.
Development of android application that receives and visualizes gait information (real-time pronation angle data and pressure distribution) and interactive guided exercise for pronation.

Design

The proposed design includes three force sensors and two IMU sensors for accurately measuring foot pronation. The sensors are integrated inside eco-flex silicone polymer. By doing so, comfortable daily use and accurate measurement can be achieved.

Pronation angle calculation [1].

System Design

Gait Analysis Data

To simulate the force and IMU sensor measurement, a Nature Scientific Data [2] of gait analysis measurements is used. The 3D motion data was processed using the Mokka app. The time series pronation angle is calculated in MATLAB.

Mobile App

The mobile app is developed on Android Studio using Java programming language. The application integrates the Arduino Bluetooth module's sensor data and pronation measurements. User can connect the device to the app via Bluetooth.

Interactive Tracking and Guiding Exercises

The app provides the visualization of time series pronation angle and force measurements. The user can do guided foot pronation exercises with real-time feedback on his foot position. This aims to increase the exercise efficiency and makes it enjoyable. Users can track their gait performance and progress.

https://video.wixstatic.com/video/8662fb_0a3bfb3816084264aef3892acf3a16e1/720p/mp4/file.mp4

References

1-Genova, J. M., & Gross, M. T. (2000). Effect of foot orthotics on calcaneal eversion during standing and treadmill walking for subjects with abnormal pronation [PMID: 11104377]. Journal of Orthopaedic & Sports Physical Therapy, 30(11), 664–675.https://doi.org/10.2519/jospt.2000.30.11.664

2- Nature Scientific Data: Grouvel, G., Carcreff, L., Moissenet, F. et al. A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates. Sci Data 10, 180 (2023). https://doi.org/10.1038/s41597-023-02077-3