Author(s): Luka Dimitrijevic, Bryson Fossati
Mentor(s): Bing Jiang
Institution UTech
Navigating the modern world presents significant challenges and dangers for individuals with visual impairments. A low-profile wearable device with sensory feedback could greatly enhance their safety and mobility, potentially preventing injuries and even saving lives. Traditionally, canes have been widely used as a reliable, low-cost tool for navigation. Recent innovations include smartphone applications that provide audio navigation and real-time instructions using cameras, assisting users in navigating unfamiliar environments. Despite their utility, canes and apps have limitations. In confined spaces or when encountering structural gaps—like those at bus stops—a traditional cane may struggle to detect certain obstacles, such as overhead advertisement boards or sudden drops in elevation, potentially leading to injury. Camera systems face limitations such as dependency on lighting conditions, limited field of view, challenges in depth perception, and complexity in processing, making them less reliable for navigation, particularly for visually impaired individuals. We are developing a smart cane system that provides distance-informative sensory feedback. The system consists of an ultrasonic sensor array, a vibration module, an Arduino Nano microcontroller, and an obstacle and depth detection algorithm. By processing data from multiple sensors, the algorithm provides precise and timely sensory feedback to users. Vibrations at different locations on the user's palm will be provided when an object is detected nearby or when there's a drop in elevation ahead. The intensity of the vibrations will vary based on the distance to the object or the depth of the drop, allowing for a more intuitive understanding of their surroundings. To assess the effectiveness of the system, participants will be blindfolded and will navigate through environments containing obstacles while wearing the device on their hand with and without vibrotactile feedback. The system's effectiveness will be measured through task completion time, navigation accuracy, number of hits, and reaction time in detecting obstacles and gaps, the result will be compared with those of the no feedback group. These metrics will be used to assess the overall functionality and responsiveness of the sensory feedback system. We hypothesize that incorporating sensory feedback will increase the system’s accuracy in detecting obstacles, providing more effective and intuitive navigation support.