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Study of Sensor-Data-Fusion in Robotic Hand Prosthetic

NeuroSys progress meetings†

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Background and Motivation†

Combining measurements of different sensors are a crucial step to achieve better precision in many applications, such as gesture recognition, etc.

Sensor fusion is an efficient estimation method, which is used in several disciplines.

Using sensor fusion, the information from many sensors and the characteristics of each sensor can be used together to improve the estimate and decrease the error.

(A Kalman filter has been used previously for the fusion of the measurements of the different sensors.)

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Research Goal†

The goal of this thesis is to Study Sensor-Fusion on EMG Signal Processing and Classification towards the Development of Adaptive Robot-Arm (i.e. artificial/prosthetic hand).

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Research Schedule†

DateTask
☑Nov 1 ~ Dec 7, 2020Resize MNIST dataset
Dec 21 ~ TBDUpdate paper "Hand Gesture Processing with Sensor Fusion based on Neuromorphic System"
☑Dec 24 ~ Jan 8, 2021EMG dataset collection using Myo
☑Jan 9 ~ 20, 2021Implementing signal processing part in Matlab
Jan 20 ~ Feb 28, 2021Converting EMG signal to spike
☑Jan 17 ~ 31, 2021Help to revise ETLTC20210 papers
☑Feb 20 ~ 26, 2021Test 3D printer
Mar 1~ Apr 1, 2020Implementation of EMG classification with traditional neuromorphic processor
Apr 2 ~ May 1, 2021Implement new classification algorithms
May 2 ~ June 1, 2021Evaluate new classification algorithms
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References†

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