Smart Shoes for Obstacle Detection
Objective To develop Smart Shoes with obstacle detection system for visually impaired people. Method The obstacle detection system adopts a triple-axis accelerometer to collect feet’s acceleration data, and uses an ultrasonic sensor to detect obstacles. T
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Abstract. Objective To develop Smart Shoes with obstacle detection system for visually impaired people. Method The obstacle detection system adopts a triple-axis accelerometer to collect feet’s acceleration data, and uses an ultrasonic sensor to detect obstacles. The system is controlled by STM32L432KC (a microcontroller from STMicroelectronics), and powered by a Lithium-ion battery that can be recharged either by a charger or by walking. A gait events recognition algorithm is proposed to detect the motion state of feet. Obstacles are detected only when users are walking with foot in stance (ST) phase. Moreover if a fall is detected, the Smart Shoes will connect to the cellphone and call the emergency contacts. Results The overall recognition ratio of the gait events was 90.9%, the ratio of walking, jiggling and fall (simulated) were 91%, 88.5% and 100% respectively. The detection resolution of Smart Shoes depends on the ultrasonic sensor. User’s average obstacles detection distance are all above 50 mm, and for each user the detection distance is proportional to the obstacles’ dimension. Conclusion Experimental results indicate that the Smart Shoes performs stably in real-time, and has high detection accuracy with low false-alarm rate. Keywords: Smart shoes Obstacle detection Visually impaired people Gait events recognition
1 Introduction Globally, at least 2.2 billion people have a vision impairment or blindness [1], and the number keeps on increasing. China accounts for at least 20% of world’s blind population. Vision loss will limit this group of people’s mobility severely. On the other hand, falls are the number one cause of injury and injury-related deaths in people over the age of 65. In China, falls caused injury makes up to 34.84% injury-related deaths in elderly people over 65 [2]. In a study of influencing factors of falls in Chinese elderly, vision loss and improper light condition counts for 2.52% and 2.38%; while uneven ground and obstacles counts for 2.45%, 2.28% in the factors of falls respectively [3]. Fall prevention is essential. To overcome the limitation caused by visual impairment, the elderly and visual impaired people turn towards assistive devices to get more independent mobility. Currently, the assistive mobility aid devices can be divided into four categories [4–9]: (1) guide crutches, (2) Electronic Travel Aids (ETA), (3) movable guiding robots, (4) wearable aid devices; every device has a certain value of popularization and application. However, most obstacle avoidance and guide devices cannot automatically switch the obstacle detection state according to the user’s gait. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 Q. Liu et al. (Eds.): CENet 2020, AISC 1274, pp. 1319–1326, 2021. https://doi.org/10.1007/978-981-15-8462-6_151
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When a user is talking with others face to face, or is stationary in a closed space (such as in a room or in a vehicle), the obstacle detection system need to be tu
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