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Hands play an important role in human life. We use our hands to do day-to-day tasks as well as to work. Unfortunately, there are those who lose their hands or arms due to accidents or diseases. It is estimated that at least 1.5 million people are living with an absence of upper limbs. Moreover, recently there has been the emergence of remote control of arms/hands to do dangerous tasks or work in places where humans can not reach. The progress of Prosthetic arms and human-like robot hands research and development have been improved incessantly. There are many approaches to realize a prosthetic hand. The most recent approaches have been using electromyographic (EMG) signals as a source to control the prosthetic hands. With the help of machine learning, the numbers of controls and movements have been increasing compared to only close and open movements in the past.
With EMG a biological data taken from the human body as the input source, Spiking Neural Network (SNN) has become a favorable solution.
To develop a neuroprosthetic hand control based on Spiking Neural Network.
| Date | Task |
| May 1~31 2021 | Survey the available 3D printed hand models and robot/prosthetic hand research |
| June 1~30 2021 | Study about the control mechanism of a hand model |
| July 1~31 2021 | Survey the approaches used to control the robot hand |
| August 1~31 2021 | Implement a chosen control approach |
