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Advisor(s)
Abstract(s)
The independence and autonomy of both elderly and dis abled people have been a growing concern of today’s society. Conse quently, the increase in life expectancy combined with the ageing of the population has created the ideal conditions for the introduction of Intelli gent Wheelchairs (IWs). For this purpose, several adapted sensors should be used to optimize the control of a wheelchair. During this work, the Leap Motion sensor was analyzed to convert the user’s will into one of four fundamental driving commands, move forward, turn right, left, or stop. Leap Motion aims to determine the direction to follow according to the hand gesture identified. For this task, data was collected from volunteers while they were performing certain gestures. Thereby it was possible to produce a data set that after being processed and extracted some features enabled the classification of the data with an F1-Score higher than 0.97. Additionally, when tested in a real-time application, this sensor reinforced its high performance.
Description
Keywords
Hand gestures Leap motion Intelligent wheelchair
Pedagogical Context
Citation
Almeida, P., Faria, B.M., Reis, L.P. (2023). Hand Gestures Recognition for an Intelligent Wheelchair Steering Command. In: Tardioli, D., Matellán, V., Heredia, G., Silva, M.F., Marques, L. (eds) ROBOT2022: Fifth Iberian Robotics Conference. ROBOT 2022. Lecture Notes in Networks and Systems, vol 590. Springer, Cham. https://doi.org/10.1007/978-3-031-21062-4_4
Publisher
Springer