Abstract:In this paper, we develop possible realizations of pseudo-haptic feedback in teleoperation systems based on existing works for pseudo-haptic feedback in virtual reality and the intended applications. We derive four potential factors affecting the performance of haptic feedback (calculation operator, maximum displacement, offset force, and scaling factor), which are analyzed in three compliance identification experiments. First, we analyze the principle usability of pseudo-haptic feedback by comparing informati… Show more
“…Therefore, we delivered force/kinesthetic feedback and not tactile/cutaneous feedback. Thirdly, the force feedback was conveyed as a true haptic force feedback unlike visual or pseudo-haptic representation [ 30 ]. Fig.…”
Background
Most currently used surgical robots have no force feedback; the next generation displays forces visually. A novel single-port robotic surgical system called FLEXMIN has been developed. Through an outer diameter of 38 mm, two instruments are teleoperated from a surgeon’s control console including true haptic force feedback. One additional channel incorporates a telescope, another is free for special instrument functions.
Methods
This randomized cross-over study analyzed the effect of haptic feedback on the application of intracorporeal forces. In a standardized experiment setup, the subjects had to draw circles with the surgical robot as gently as possible. The applied forces, the required time spans, and predefined error rates were measured.
Results
Without haptic feedback, the maximum forces (median/IQR) were 6.43 N/2.96 N. With haptic feedback, the maximum forces were lower (3.57 N/1.94 N, p < 0.001). Also, the arithmetic means of the force progression (p < 0.001) and their standard deviations (p < 0.001) were lower. Not significant were the shorter durations and lower error rates. No sequence effect of force or duration was detected. No characteristic learning or fatigue curve was observed.
Conclusions
In the experiment setup, the true haptic force feedback can reduce the applied intracorporeal robotic force to one-half when considering the aspects maximum, means, and standard deviation. Other test tasks are needed to validate the influence of force feedback on surgical efficiency and safety.
“…Therefore, we delivered force/kinesthetic feedback and not tactile/cutaneous feedback. Thirdly, the force feedback was conveyed as a true haptic force feedback unlike visual or pseudo-haptic representation [ 30 ]. Fig.…”
Background
Most currently used surgical robots have no force feedback; the next generation displays forces visually. A novel single-port robotic surgical system called FLEXMIN has been developed. Through an outer diameter of 38 mm, two instruments are teleoperated from a surgeon’s control console including true haptic force feedback. One additional channel incorporates a telescope, another is free for special instrument functions.
Methods
This randomized cross-over study analyzed the effect of haptic feedback on the application of intracorporeal forces. In a standardized experiment setup, the subjects had to draw circles with the surgical robot as gently as possible. The applied forces, the required time spans, and predefined error rates were measured.
Results
Without haptic feedback, the maximum forces (median/IQR) were 6.43 N/2.96 N. With haptic feedback, the maximum forces were lower (3.57 N/1.94 N, p < 0.001). Also, the arithmetic means of the force progression (p < 0.001) and their standard deviations (p < 0.001) were lower. Not significant were the shorter durations and lower error rates. No sequence effect of force or duration was detected. No characteristic learning or fatigue curve was observed.
Conclusions
In the experiment setup, the true haptic force feedback can reduce the applied intracorporeal robotic force to one-half when considering the aspects maximum, means, and standard deviation. Other test tasks are needed to validate the influence of force feedback on surgical efficiency and safety.
“…In this section, a method is described for estimating the interaction force during suturing using images and tool positions to generate pseudo-tactile feedback, which has been investigated for its usefulness during teleoperation surgery [36]. Similar to experienced surgeons merging visual information and proprioception to feel a pseudotactile sensation, our method finds that the tension increases in the image even with slight changes at the end of the stitch as a result of the movement toward the direction of the knot pulling.…”
Compared to laparoscopy, robotics-assisted minimally invasive surgery has the problem of an absence of force feedback, which is important to prevent a breakage of the suture. To overcome this problem, surgeons infer the suture force from their proprioception and 2D image by comparing them to the training experience. Based on this idea, a deep-learning-based method using a single image and robot position to estimate the tensile force of the sutures without a force sensor is proposed. A neural network structure with a modified Inception Resnet-V2 and Long Short Term Memory (LSTM) networks is used to estimate the suture pulling force. The feasibility of proposed network is verified using the generated DB, recording the interaction under the condition of two different artificial skins and two different situations (in vivo and in vitro) at 13 viewing angles of the images by changing the tool positions collected from the master-slave robotic system. From the evaluation conducted to show the feasibility of the interaction force estimation, the proposed learning models successfully estimated the tensile force at 10 unseen viewing angles during training.
“…Currently, there are mainly two methods for augmenting tissue stiffness perception: pseudo-haptic feedback and haptic feedback. Pseudo-haptic feedback is based on tissue stiffness maps, which are provided by rolling mechanical imaging [6], [7], [8], [9] and do not require real haptic devices. Compared with pseudo-haptic feedback, haptic feedback augments tissue stiffness perception by using a haptic device to interact with virtual environments, which is similar to the way of human perceiving information.…”
Haptic-based tissue stiffness perception is essential for palpation training system, which can provide the surgeon haptic cues for improving the diagnostic abilities. However, current haptic devices, such as Geomagic Touch, fail to provide immersive and natural haptic interaction in virtual surgery due to the inherent mechanical friction, inertia, limited workspace and flawed haptic feedback. To tackle this issue, we design a novel magnetic levitation haptic device based on electromagnetic principles to augment the tissue stiffness perception in virtual environment. Users can naturally interact with the virtual tissue by tracking the motion of magnetic stylus using stereoscopic vision so that they can accurately sense the stiffness by the magnetic stylus, which moves in the magnetic field generated by our device. We propose the idea that the effective magnetic field (EMF) is closely related to the coil attitude for the first time. To fully harness the magnetic field and flexibly generate the specific magnetic field for obtaining required haptic perception, we adopt probability clouds to describe the requirement of interactive applications and put forward an algorithm to calculate the best coil attitude. Moreover, we design a control interface circuit and present a self-adaptive fuzzy proportion integration differentiation (PID) algorithm to precisely control the coil current. We evaluate our haptic device via a series of quantitative experiments which show the high consistency of the experimental and simulated magnetic flux density, the high accuracy (0.28 mm) of real-time 3D positioning and tracking of the magnetic stylus, the low power consumption of the adjustable coil configuration, and the tissue stiffness perception accuracy improvement by 2.38 percent with the self-adaptive fuzzy PID algorithm. We conduct a user study with 22 participants, and the results suggest most of the users can clearly and immersively perceive different tissue stiffness and easily detect the tissue abnormality. Experimental results demonstrate that our magnetic levitation haptic device can provide accurate tissue stiffness perception augmentation with natural and immersive haptic interaction.
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