Muscle Fatigue Induced Hand Tremor Clustering in Dynamic Laparoscopic Manipulation

Chandra, Sourav; Hayashibe, Mitsuhiro; Thondiyath, Asokan

doi:10.1109/tsmc.2018.2882957

Cited by 15 publications

(10 citation statements)

References 42 publications

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“…According to Table 4, the master manipulator could keep stationary in a balanced state after being released. Experimental data prove that the gravity balance designed master manipulator can well meet the needs of surgical tasks 27 …”

Section: Resultsmentioning

confidence: 85%

Design and experimental validation of a master manipulator with position and posture decoupling for laparoscopic surgical robot

Lei

Song

et al. 2022

Robotics Computer Surgery

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Background:The master manipulator with position and posture decoupling and force feedback can improve the immersion of the operation, and the gravity balance can reduce the fatigue of surgeons.Methods: A seven degree of freedom master manipulator is developed. The parallelogram structure and the angle conversion method contribute to the realization of decoupling position and posture. The calculating method based on the virtual work principle is adopted to achieve the passive gravity balance. The relationship between the master manipulator's joint torque and output force is established to achieve force feedback.Results: A prototype of the master manipulator was built and its performance was experimentally evaluated. The maximum value of the positioning mean absolute error is 1.2 mm. The maximum absolute error of the force-feedback is 0.32 N. Conclusion:With the functions of positioning, gravity balance, and force feedback, our manipulator shows the potential for single port laparoscopic surgery.

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Section: Resultsmentioning

confidence: 85%

Design and experimental validation of a master manipulator with position and posture decoupling for laparoscopic surgical robot

Lei

Song

et al. 2022

Robotics Computer Surgery

View full text Add to dashboard Cite

show abstract

“…Experimental protocols should also be extended, including different fatiguing tasks. Although an accelerometer can be effectively used to capture hand tremor changes in static activity, it does not assess the effect of muscle fatigue during the implementation of dynamic activities that requires measurement of surface electromyography [18]. To minimize the equipment constraints, accelerometer data could be combined with data collected by a gyroscope.…”

Section: Discussionmentioning

confidence: 99%

“…This type of tremor may disrupt the daily activities of the individual, especially those involving precision tasks, which may, in turn, negatively impact the quality of life [17]. Fatigue-induced physiological tremor can adversely affect tasks that require fine and precise movements (e.g., surgery [5,18], micropipetting [7], or teleoperation of robots [19]).…”

Section: Introductionmentioning

confidence: 99%

Classification of Fatigue Phases in Healthy and Diabetic Adults Using Wearable Sensor

Aljihmani

Kerdjidj

Zhu

et al. 2020

Sensors

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Fatigue is defined as “a loss of force-generating capacity” in a muscle that can intensify tremor. Tremor quantification can facilitate early detection of fatigue onset so that preventative or corrective controls can be taken to minimize work-related injuries and improve the performance of tasks that require high-levels of accuracy. We focused on developing a system that recognizes and classifies voluntary effort and detects phases of fatigue. The experiment was designed to extract and evaluate hand-tremor data during the performance of both rest and effort tasks. The data were collected from the wrist and finger of the participant’s dominant hand. To investigate tremor, time, frequency domain features were extracted from the accelerometer signal for segments of 45 and 90 samples/window. Analysis using advanced signal processing and machine-learning techniques such as decision tree, k-nearest neighbor, support vector machine, and ensemble classifiers were applied to discover models to classify rest and effort tasks and the phases of fatigue. Evaluation of the classifier’s performance was assessed based on various metrics using 5-fold cross-validation. The recognition of rest and effort tasks using an ensemble classifier based on the random subspace and window length of 45 samples was deemed to be the most accurate (96.1%). The highest accuracy (~98%) that distinguished between early and late fatigue phases was achieved using the same classifier and window length.

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“…The representative feature of a Hammerstein model is that its architecture consists of two blocks: a static nonlinear model followed by a linear dynamic model. The simplicity in structure makes it provide a good compromise between the accuracy of nonlinear systems and the tractability of linear systems, and thus promoting its use in different nonlinear applications such as automatic control [13][14][15], fault detection and diagnosis [16][17][18], and so on.…”

Section: Introductionmentioning

confidence: 99%

Auxiliary Model-Based Multi-Innovation Fractional Stochastic Gradient Algorithm for Hammerstein Output-Error Systems

Mao

2021

Machines

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This paper focuses on the nonlinear system identification problem, which is a basic premise of control and fault diagnosis. For Hammerstein output-error nonlinear systems, we propose an auxiliary model-based multi-innovation fractional stochastic gradient method. The scalar innovation is extended to the innovation vector for increasing the data use based on the multi-innovation identification theory. By establishing appropriate auxiliary models, the unknown variables are estimated and the improvement in the performance of parameter estimation is achieved owing to the fractional-order calculus theory. Compared with the conventional multi-innovation stochastic gradient algorithm, the proposed method is validated to obtain better estimation accuracy by the simulation results.

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Muscle Fatigue Induced Hand Tremor Clustering in Dynamic Laparoscopic Manipulation

Cited by 15 publications

References 42 publications

Design and experimental validation of a master manipulator with position and posture decoupling for laparoscopic surgical robot

Design and experimental validation of a master manipulator with position and posture decoupling for laparoscopic surgical robot

Classification of Fatigue Phases in Healthy and Diabetic Adults Using Wearable Sensor

Auxiliary Model-Based Multi-Innovation Fractional Stochastic Gradient Algorithm for Hammerstein Output-Error Systems

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