Utilizing Sensor Data to perform Gait and Posture Analysis for Rehabilitation

Team: Clara Shu Qi Lim (IEOR), Emma Leiner (IEOR), Kenneth Lim (IEOR), Minsoo Kang (IEOR), Ziyu Li (IEOR)

Advisors: Coleman Fung (Blue Goji), Gabriel Gomes (ME)

“A growing number of older adults fear falling and, as a result, limit their activities and social engagements.” – National Council on Aging

One in four Americans aged 65+ falls each year. Falls are a leading cause of fatal injury among elderly individuals. A fall and subsequent injury reduces elderly individuals’ confidence in walking and increases their fear of falling. This can severely limit their mobility and quality of life. Team Infinity aims to build confidence in elderly individuals’ abilities to maintain an active lifestyle. By using sensors on Blue Goji’s Infinity Treadmill, we build data-driven models which characterizes gait and posture that are associated with mobility. By integrating our models with the treadmill and tracking these metrics over time, we can measure the rehabilitative intervention effects, helping elderly users regain control in their everyday lives.

Problem

Every 11 seconds in the United States, an elderly individual is treated in the emergency room for a fall. A fall and subsequent fear of injury greatly reduces elderly individuals’ confidence in walking. This limits their mobility and quality of life.

Solution

The Infinity Treadmill by Blue Goji currently supports eSport games in an immersive virtual reality environment. The result of our work for elderly rehabilitation adds complementary features for Blue Goji to develop a more robust system combining both gaming and health monitoring for future eSport games.

Process

Using the sensors integrated in the Infinity Treadmill, our team builds data models to quantify gait and motion. In gait analysis, the balance and symmetry of the user is determined through computing the symmetry index1 from step and stride information. We built a machine learning model to identify the leaning direction of the user based on data from the tension sensors, while visualizing the data from the Inertial Measurement Unit to verify the orientation of the user. By tracking these metrics over time, we can rehabilitate mobility in our users and rebuild their walking confidence, ultimately enriching people’s lifestyle