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• W4386092617 abstract "Tremor is the repetitive movement of some part of the body. It disturbs the daily routine activities of humans like eating, grasping objects, etc. Physiological tremor is a big concern during surgery as the tremor in surgeon’s hand may lead to harmful results. Robotic surgery makes it possible to filter out the tremor before it is passed on to the surgical arms of the robot actually performing the surgery. In order to eliminate the effect of tremor, it is to be sensed and measured well before time. The research work reported in this chapter pertains to characterization and sensing of tremor by different methods in general and by electromyography (sEMG) in particular. SEMG signal was picked up from the tremor arm, processed, and applied to a classifier to detect the tremor and remove it. Total 14 subjects belonging to different age groups were included in the study. Seven features viz Mean, Standard Deviation, Skewness, Kurtosis, Mean Absolute Value, Zero-Crossing, and Slope Sign Change were extracted and fed to the classifier. Four classifier models viz Support Vector Machine, Logistic Regression, K-Nearest Neighbor, and Random Forest were compared. A decrease in median frequency and increase in power during tremor were observed. Classification accuracy was found as 99.5% with Random Forest model." @default.
• W4386092617 created "2023-08-24" @default.
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• W4386092617 date "2023-01-01" @default.
• W4386092617 modified "2023-09-26" @default.
• W4386092617 title "Assessment and Elimination of Surgeon Hand Tremor During Robotic Surgery" @default.
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• W4386092617 doi "https://doi.org/10.1007/978-981-99-2074-7_97" @default.
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