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

Jintao Luo1; Shuxiang Guo1,2; Yonggan Yan1; Duohao Zhao1; Chuqiao Lyu1; Zhijun Lin1; Bin Wang3; Mingchao Ding3

10.1109/ICMA61710.2024.10633144

2024-08-07

2152-7431

979-8-3503-8808-4

2024 IEEE International Conference on Mechatronics and Automation (ICMA)

4-7 Aug. 2024

Tianjin, China

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.

其他

1.The Aerospace Center Hospital, School of Life Science and the Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China
2.The Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
3.The Department of Peripheral Vascular Intervention, Aerospace Center Hospital, School of Life Science, Beijing Institute of Technology, Beijing, China

Jintao Luo,Shuxiang Guo,Yonggan Yan,et al. Deep Learning Based Tremor Signal Recognition Method for a Vascular Interventional Surgery Robot[C],2024.