Deep Learning Based Tremor Signal Recognition Method for a Vascular Interventional Surgery Robot

Hand tremor seriously reduce the accuracy and safety of robot-assisted vascular interventional surgery. However, the existing methods have some deficiencies, such as phase delay and distortion of operation signal. Therefore, a more accurate and universal method for tremor signal recognition is needed. This paper proposes a recognition method based on residual neural networks. And we use a Geomagic TouchX to collect tremor signal. The sliding window algorithm is used to process the data and make the dataset. Finally, the validation results indicate that the method can recognize normal operation signal and tremor signal, and ensure that the normal operation signal of the surgeon is not affected.