Abstract
Electromyography (EMG) has become an automation technique and has found its way in disciplines other than medical sciences. EMG based equipment is being used for automation of soft as well as hard robots. NAO is a humanoid robot developed by Aldebaran Robotics currently deployed in the health and education sector. In this paper we have attempted to develop an interface for controlling the NAO robot with an EMG sensor known as Myo Armband, we implemented a TCP client with the C++ Myo arm-band SDK and a corresponding sever with the Python NAO robot SDK. A Finite State Machine (FSM) architecture is incorporated at the client side to manage the network traffic rate as well as to increase efficiency of the system. The scope of this paper is limited to four different gestures instantiating four distinct actions performed by the robot using Myo Armband, this research is currently under development and in its testing phase. This technological aid supports the person who is waist down paralyzed or for an immobile patient on a hospital bed who wants to get the task done through a social robot.
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Ali, S. et al. (2020). Hand Gesture Based Control of NAO Robot Using Myo Armband. In: Ayaz, H. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2019. Advances in Intelligent Systems and Computing, vol 953. Springer, Cham. https://doi.org/10.1007/978-3-030-20473-0_44
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DOI: https://doi.org/10.1007/978-3-030-20473-0_44
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