The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Iulian Iordachita - One of the best experts on this subject based on the ideXlab platform.
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sclera force control in robot assisted eye surgery adaptive force control vs auditory feedback
International Symposium Medical Robotics, 2019Co-Authors: Ali Ebrahimi, Peter L Gehlbach, Niravkumar Patel, Marin Kobilarov, Iulian IordachitaAbstract:Surgeon Hand Tremor limits human capability during microsurgical procedures such as those that treat the eye. In contrast, elimination of Hand Tremor through the introduction of microsurgical robots diminishes the surgeons tactile perception of useful and familiar tool-to-sclera forces. While the large mass and inertia of eye surgical robot prevents surgeon microTremor, loss of perception of small scleral forces may put the sclera at risk of injury. In this paper, we have applied and compared two different methods to assure the safety of sclera tissue during robot-assisted eye surgery. In the active control method, an adaptive force control strategy is implemented on the Steady-Hand Eye Robot in order to control the magnitude of scleral forces when they exceed safe boundaries. This autonomous force compensation is then compared to a passive force control method in which the surgeon performs manual adjustments in response to the provided audio feedback proportional to the magnitude of sclera force. A pilot study with three users indicate that the active control method is potentially more efficient.
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user behavior evaluation in robot assisted retinal surgery
Robot and Human Interactive Communication, 2018Co-Authors: Ali Ebrahimi, Peter L Gehlbach, Niravkumar Patel, Marina Roizenblatt, Yang Yang, Iulian IordachitaAbstract:Retinal microsurgery is technically demanding and requires high surgical skill with very little room for manipulation error. The introduction of robotic assistance has the potential to enhance and expand a surgeon's manipulation capabilities during retinal surgery, i.e., improve precision, cancel physiological Hand Tremor, and provide sensing information. However, surgeon performance may also be negatively impacted by robotic assistance due to robot structural stiffness and nonintuitive controls. In complying with robotic constraints, the surgeon loses the dexterity of the human Hand. In this paper, we present a preliminary experimental study to evaluate user behavior when affected by robotic assistance during mock retinal surgery. In these experiments user behavior is characterized by measuring the forces applied by the user to the sclera, the tool insertion/retraction speed, the tool insertion depth relative to the scleral entry point, and the duration of surgery. The users' behavior data is collected during three mock retinal surgery tasks with four users. Each task is conducted using both freeHand and robot-assisted techniques. The univariate user behavior and the correlations of multiple parameters of user behavior are analyzed. The results show that robot assistance prolongs the duration of the surgery and increases the manipulation forces applied to sclera, but refines the insertion velocity and eliminates Hand Tremor.
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a comparative study for robot assisted vitreoretinal surgery micron vs the steady Hand robot
International Conference on Robotics and Automation, 2013Co-Authors: Berk Gonenc, Peter L Gehlbach, James T Handa, Russell H Taylor, Iulian IordachitaAbstract:In vitreoretinal surgery, application of excessive forces and unintentional motion due to Hand-Tremor can easily result in serious complications. Robotic assistance when combined with tool-to-tissue force sensing capabilities has significant potential to improve such practice. In this paper, we evaluate the membrane peeling performance of a single user for two distinct robotic systems with integrated force sensing capabilities: Micron and the Steady-Hand Robot. We show that these systems provide promising performance improvement with similar impact on peeling forces and comparable Tremor cancellation trends.
Peter L Gehlbach - One of the best experts on this subject based on the ideXlab platform.
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sclera force control in robot assisted eye surgery adaptive force control vs auditory feedback
International Symposium Medical Robotics, 2019Co-Authors: Ali Ebrahimi, Peter L Gehlbach, Niravkumar Patel, Marin Kobilarov, Iulian IordachitaAbstract:Surgeon Hand Tremor limits human capability during microsurgical procedures such as those that treat the eye. In contrast, elimination of Hand Tremor through the introduction of microsurgical robots diminishes the surgeons tactile perception of useful and familiar tool-to-sclera forces. While the large mass and inertia of eye surgical robot prevents surgeon microTremor, loss of perception of small scleral forces may put the sclera at risk of injury. In this paper, we have applied and compared two different methods to assure the safety of sclera tissue during robot-assisted eye surgery. In the active control method, an adaptive force control strategy is implemented on the Steady-Hand Eye Robot in order to control the magnitude of scleral forces when they exceed safe boundaries. This autonomous force compensation is then compared to a passive force control method in which the surgeon performs manual adjustments in response to the provided audio feedback proportional to the magnitude of sclera force. A pilot study with three users indicate that the active control method is potentially more efficient.
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user behavior evaluation in robot assisted retinal surgery
Robot and Human Interactive Communication, 2018Co-Authors: Ali Ebrahimi, Peter L Gehlbach, Niravkumar Patel, Marina Roizenblatt, Yang Yang, Iulian IordachitaAbstract:Retinal microsurgery is technically demanding and requires high surgical skill with very little room for manipulation error. The introduction of robotic assistance has the potential to enhance and expand a surgeon's manipulation capabilities during retinal surgery, i.e., improve precision, cancel physiological Hand Tremor, and provide sensing information. However, surgeon performance may also be negatively impacted by robotic assistance due to robot structural stiffness and nonintuitive controls. In complying with robotic constraints, the surgeon loses the dexterity of the human Hand. In this paper, we present a preliminary experimental study to evaluate user behavior when affected by robotic assistance during mock retinal surgery. In these experiments user behavior is characterized by measuring the forces applied by the user to the sclera, the tool insertion/retraction speed, the tool insertion depth relative to the scleral entry point, and the duration of surgery. The users' behavior data is collected during three mock retinal surgery tasks with four users. Each task is conducted using both freeHand and robot-assisted techniques. The univariate user behavior and the correlations of multiple parameters of user behavior are analyzed. The results show that robot assistance prolongs the duration of the surgery and increases the manipulation forces applied to sclera, but refines the insertion velocity and eliminates Hand Tremor.
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dual optical coherence tomography sensor guided two motor horizontal smart micro scissors
Optics Letters, 2016Co-Authors: Hyuncheol Park, Seonjin Jang, Peter L Gehlbach, Cheol SongAbstract:In microsurgery, the physiological Hand Tremor of the surgeon remains an important factor affecting procedure efficiency, risk of complications, and ultimately, the efficacy of treatment. The micro-scissors are routinely employed to perform precise sharp dissection of delicate tissues. Here, we present a dual optical coherence tomography (OCT) distance sensor guided, two-motor, horizontal smart micromanipulation aided robotic-surgery tool (SMART) micro-scissors. It is intended to improve surgeon performance by retaining all of the attributes of the horizontal scissors while implementing proof-of-concept use of two functional motors to provide Tremor cancellation.
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a comparative study for robot assisted vitreoretinal surgery micron vs the steady Hand robot
International Conference on Robotics and Automation, 2013Co-Authors: Berk Gonenc, Peter L Gehlbach, James T Handa, Russell H Taylor, Iulian IordachitaAbstract:In vitreoretinal surgery, application of excessive forces and unintentional motion due to Hand-Tremor can easily result in serious complications. Robotic assistance when combined with tool-to-tissue force sensing capabilities has significant potential to improve such practice. In this paper, we evaluate the membrane peeling performance of a single user for two distinct robotic systems with integrated force sensing capabilities: Micron and the Steady-Hand Robot. We show that these systems provide promising performance improvement with similar impact on peeling forces and comparable Tremor cancellation trends.
Jane E Alty - One of the best experts on this subject based on the ideXlab platform.
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accuracy of smartphone video for contactless measurement of Hand Tremor frequency
Movement Disorders Clinical Practice, 2021Co-Authors: Stefan Williams, Hui Fang, Samuel D Relton, Taimour Alam, Jane E Alty, David WongAbstract:Background: Computer vision can measure movement from video without the time and access limitations of hospital accelerometry/electromyography or the requirement to hold or strap a smartphone accelerometer. Objective: To compare computer vision measurement of Hand Tremor frequency from smartphone video with a gold standard measure accelerometer. Methods: A total of 37 smartphone videos of Hands, at rest and in posture, were recorded from 15 participants with Tremor diagnoses (9 Parkinson’s disease, 5 essential Tremor, 1 functional Tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier transform and Bland-Altman analysis were applied. Tremor amplitude was scored by 2 clinicians. Results: Bland-Altman analysis of dominant Tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement −0.38 Hz to +0.35 Hz. In 36 of 37 videos (97%), there was <0.5 Hz difference between computer vision and accelerometer measurement. There was no significant correlation between the level of agreement and Tremor amplitude. Conclusion: The study suggests a potential new, contactless point-and-press measure of Tremor frequency within standard clinical settings, research studies, or telemedicine.
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Accuracy of smartphone video for contactless measurement of Hand Tremor frequency
2020Co-Authors: Stefan Williams, Hui Fang, Samuel D Relton, David C Wong, Taimour Alam, Jane E AltyAbstract:Background Computer vision can measure movement from video without the time and access limitations of hospital accelerometry / electromyography, or the requirement to hold or strap a smartphone accelerometer. Objective To compare computer vision measurement of Hand Tremor frequency from smartphone video with a gold standard measure, accelerometer. Methods 37 smartphone videos of Hands at rest and in posture, were recorded from 15 participants with Tremor diagnoses (9 Parkinson’s, 5 Essential Tremor, 1 Functional Tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier Transform and Bland-Altman analysis were applied. Tremor amplitude was scored by two clinicians. Results Bland-Altman analysis of dominant Tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement -0.38 Hz to +0.35Hz. In 36 out of 37 videos (97%) there was
Ali Ebrahimi - One of the best experts on this subject based on the ideXlab platform.
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sclera force control in robot assisted eye surgery adaptive force control vs auditory feedback
International Symposium Medical Robotics, 2019Co-Authors: Ali Ebrahimi, Peter L Gehlbach, Niravkumar Patel, Marin Kobilarov, Iulian IordachitaAbstract:Surgeon Hand Tremor limits human capability during microsurgical procedures such as those that treat the eye. In contrast, elimination of Hand Tremor through the introduction of microsurgical robots diminishes the surgeons tactile perception of useful and familiar tool-to-sclera forces. While the large mass and inertia of eye surgical robot prevents surgeon microTremor, loss of perception of small scleral forces may put the sclera at risk of injury. In this paper, we have applied and compared two different methods to assure the safety of sclera tissue during robot-assisted eye surgery. In the active control method, an adaptive force control strategy is implemented on the Steady-Hand Eye Robot in order to control the magnitude of scleral forces when they exceed safe boundaries. This autonomous force compensation is then compared to a passive force control method in which the surgeon performs manual adjustments in response to the provided audio feedback proportional to the magnitude of sclera force. A pilot study with three users indicate that the active control method is potentially more efficient.
Stefan Williams - One of the best experts on this subject based on the ideXlab platform.
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accuracy of smartphone video for contactless measurement of Hand Tremor frequency
Movement Disorders Clinical Practice, 2021Co-Authors: Stefan Williams, Hui Fang, Samuel D Relton, Taimour Alam, Jane E Alty, David WongAbstract:Background: Computer vision can measure movement from video without the time and access limitations of hospital accelerometry/electromyography or the requirement to hold or strap a smartphone accelerometer. Objective: To compare computer vision measurement of Hand Tremor frequency from smartphone video with a gold standard measure accelerometer. Methods: A total of 37 smartphone videos of Hands, at rest and in posture, were recorded from 15 participants with Tremor diagnoses (9 Parkinson’s disease, 5 essential Tremor, 1 functional Tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier transform and Bland-Altman analysis were applied. Tremor amplitude was scored by 2 clinicians. Results: Bland-Altman analysis of dominant Tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement −0.38 Hz to +0.35 Hz. In 36 of 37 videos (97%), there was <0.5 Hz difference between computer vision and accelerometer measurement. There was no significant correlation between the level of agreement and Tremor amplitude. Conclusion: The study suggests a potential new, contactless point-and-press measure of Tremor frequency within standard clinical settings, research studies, or telemedicine.
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Accuracy of smartphone video for contactless measurement of Hand Tremor frequency
2020Co-Authors: Stefan Williams, Hui Fang, Samuel D Relton, David C Wong, Taimour Alam, Jane E AltyAbstract:Background Computer vision can measure movement from video without the time and access limitations of hospital accelerometry / electromyography, or the requirement to hold or strap a smartphone accelerometer. Objective To compare computer vision measurement of Hand Tremor frequency from smartphone video with a gold standard measure, accelerometer. Methods 37 smartphone videos of Hands at rest and in posture, were recorded from 15 participants with Tremor diagnoses (9 Parkinson’s, 5 Essential Tremor, 1 Functional Tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier Transform and Bland-Altman analysis were applied. Tremor amplitude was scored by two clinicians. Results Bland-Altman analysis of dominant Tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement -0.38 Hz to +0.35Hz. In 36 out of 37 videos (97%) there was
