Increasing Access to Trainer-led Aerobic Exercise for People with Visual Impairments through a Sensor Mat System

Abstract

People with visual impairments (PVIs) are less likely to participate in physical activity than their sighted peers. One barrier is the lack of accessible group-based aerobic exercise classes, often due to instructors not giving accessible verbal instructions. While there is research in exercise tracking, these tools often require vision or familiarity with the exercise. There are accessible solutions that give personalized verbal feedback in slower-paced exercises, not generalizing to aerobics. In response, we have developed an algorithm that detects shoeprints on a sensor mat using computer vision and a CNN. We can infer whether a person is following along with a step aerobics workout and are designing reactive verbal feedback to guide the person to rejoin the class. Future work will include finishing development and conducting a user study to assess the effectiveness of the reactive verbal feedback.