A Wearable Assistive Device for Blind Pedestrians Using Real-Time Object Detection and Tactile Presentation - Shen, Junjie; Chen, Yiwen; Sawada, Hideyuki (Sensors (Basel, Switzerland), 2022)
Nowadays, improving the traffic safety of visually impaired people is a topic of widespread concern. To help avoid the risks and hazards of road traffic in their daily life, we propose a wearable device using object detection techniques and a novel tactile display made from shape-memory alloy (SMA) actuators. After detecting obstacles in real-time, the tactile display attached to a user’s hands presents different tactile sensations to show the position of the obstacles. To implement the computation-consuming object detection algorithm in a low-memory mobile device, we introduced a slimming compression method to reduce 90% of the redundant structures of the neural network. We also designed a particular driving circuit board that can efficiently drive the SMA-based tactile displays. In addition, we also conducted several experiments to verify our wearable assistive device’s performance. The results of the experiments showed that the subject was able to recognize the left or right position of a stationary obstacle with 96% accuracy and also successfully avoided collisions with moving obstacles by using the wearable assistive device.