Ilana Nisky

A Regression and Boundary-Crossing-Based Model for the Perception of Delayed Stiffness

The stiffness of the environment with which we come in contact is the local derivative of a force field. The boundary of an elastic field is a singular region where local stiffness is ill-defined. We found that subjects interacting with delayed force fields tend to underestimate stiffness if they do not move across the boundary. In contrast, they tend to overestimate stiffness when they move across the elastic field boundary. We propose a unifying computational model of stiffness perception based on an active process that combines the concurrent operations of a force and of a position-control system.

Perception and Action in Teleoperated Needle Insertion

We studied the effect of delay on perception and action in contact with a force field that emulates elastic soft tissue with a rigid nonlinear boundary. Such a field is similar to forces exerted on a needle during teleoperated needle insertion. We found that delay causes motor underestimation of the stiffness of this nonlinear soft tissue, without perceptual change. These experimental results are supported by simulation of a simplified mechanical model of the arm and neural controller, and a model for perception of stiffness, which is based on regression in the force-position space. In addition, we show that changing the gain of the teleoperation channel cancels the motor effect of delay without adding perceptual distortion. We conclude that it is possible to achieve perceptual and motor transparency in virtual one-dimensional remote needle insertion task.

Toward Perceiving Robots as Humans: Three Handshake Models Face the Turing-Like Handshake Test

In the Turing test a computer model is deemed to “think intelligently” if it can generate answers that are indistinguishable from those of a human. We developed an analogous Turing-like handshake test to determine if a machine can produce similarly indistinguishable movements. The test is administered through a telerobotic system in which an interrogator holds a robotic stylus and interacts with another party - artificial or human with varying levels of noise. The interrogator is asked which party seems to be more human. Here, we compare the human-likeness levels of three different models for handshake: (1) Tit-for-Tat model, (2) λ model, and (3) Machine Learning model. The Tit-for-Tat and the Machine Learning models generated handshakes that were perceived as the most human-like among the three models that were tested. Combining the best aspects of each of the three models into a single robotic handshake algorithm might allow us to advance our understanding of the way the nervous system controls sensorimotor interactions and further improve the human-likeness of robotic handshakes.

Proximodistal gradient in the perception of delayed stiffness.

Introduction of successful telerehabilitation into the variety of techniques that are available to the therapist will forever change the field of rehabilitation. Accurate perception of the remote environments mechanical properties and of stiffness in particular is extremely important for successful telerehabilitation. In the current study we present the framework for exploring perception of delayed stiffness when probing is executed using movement with different joints, and provide experimental results supporting the existence of proximodistal gradient in the perception of delayed stiffness. We found that delayed stiffness was underestimated to a larger extent after probing with wrist than with elbow. We suggest that the observed gradient in perception reveals a proximodistal gradient in control: proximal joints are dominated by force control, whereas distal joints are dominated by position control.

Analytical Study of Perceptual and Motor Transparency in Bilateral Teleoperation

In bilateral teleoperation, a human operator manipulates a remote environment through a pair of master and slave robots. The transparency quantifies the fidelity of the teleoperation system, and is typically defined as the ability to accurately display remote environment properties to the operator. We propose a novel multidimensional measure of transparency which takes into account the human operator and consists of three components: 1) perceptual transparency, which quantifies human perception of the remote environment, 2) local motor transparency, which quantifies how far is the movement of the human operator from ideal, and 3) remote motor transparency, which describes how far is the movement of the remote device from ideal. We suggest that for many practical applications, the goal of the transparency optimization is to maintain perceptual and remote motor transparency while sacrificing local motor transparency, and that it is plausible to take advantage of the gap between perception and action in the operators sensorimotor system. We prove analytically that for a teleoperation channel with a position and force scaling and a constant transmission delay, in a palpation and perception of stiffness task, it is possible to find gains that ensure perfect perceptual and remote motor transparency while maintaining stability. We also show that stability depends on the operator that maintain sufficient arm impedance relative to environment impedance and delay.

[D67] Sensory substitution using 3-Degree-of-Freedom tangential and normal skin deformation feedback

During manual interactions, we experience both kinesthetic forces and tactile sensations. Friction and normal force between the fingerpads and the tool/interaction surfaces cause shear and normal deformation of the skin. Capitalizing on this observation, we designed a 3-degree-of-freedom (DoF) tactile device that is grasped by a user and can render both tangential skin stretch and normal deformation on the skin of the users fingerpads. Tactile feedback from the device is delivered in a manner consistent with natural tactile cues from manual interaction. An experiment assessed the accuracy with which users can locate the center of a contoured hole on a virtual surface. The task was completed under four conditions: the cases of skin deformation and force feedback, with both 3- and 1-DoF feedback in each case. With 3-DoF feedback, users located the hole faster and more accurately than with 1-DoF feedback, for both force and skin deformation feedback. These results indicated that users were able to interpret the additional DoF cues provided by our 3-DoF tactile device to improve task performance.

Detection of Cancer Using Advanced Computerized Analysis of Infrared Spectra of Peripheral Blood

We have developed a novel approach for detection of cancer based on biochemical analysis of peripheral blood plasma using Fourier transform infrared spectroscopy. This approach has proven to be quick, safe, minimal invasive, and effective. Our approach recognizes any signs of solid tumor presence, regardless of location in the body or cancer type by measuring a spectrum that gives information regarding the total molecular composition and structure of the peripheral blood samples. The analysis includes clinically relevant preprocessing and feature extraction with principal component analysis, and uses Fishers linear discriminant analysis to classify between cancer patients and healthy controls. We evaluated our method with leave-one-out cross validation and were able to establish sensitivity of 93.33%, specificity of 87.8%, and overall accuracy of 90.7%. Using our method for cancer detection should result in fewer unnecessary invasive procedures and yield fast detection of solid tumors.

Motor learning affects car-to-driver handover in automated vehicles

A human driver requires a period of motor adaptation to resume normal steering after taking control of an automated vehicle. Vehicles in the foreseeable future will be required to transition between autonomous driving (without human involvement) and full human control. During this transition period, the human, who has not been actively engaged in the driving process, must resume the motor control necessary to steer the car. The in-car study presented here demonstrates that when human drivers are presented with a steering behavior that is different from the last time they were in control, specifically the ratio of hand wheel angle to road wheel angle (emulating a change in vehicle speed), they undergo a significant period of adaptation before they return to their previous steering behavior. However, drivers do not require an adaptation period to return to previous driving behavior after changes in steering torque. These findings have implications for the design of vehicles that transition from automated to manual driving and for understanding of human motor control in real-world tasks.

Sensory Substitution and Augmentation Using 3-Degree-of-Freedom Skin Deformation Feedback

During tool-mediated interaction with everyday objects, we experience kinesthetic forces and tactile sensations in the form of vibration and skin deformation at the fingerpad. Fingerpad skin deformation is caused by forces applied tangentially and normally to the fingerpad skin, resulting in tangential and normal skin displacement. We designed a device to convey 3-degree-of-freedom (DoF) force information to the user via skin deformation, and conducted two experiments to determine the devices effectiveness for force-feedback substitution and augmentation. For sensory substitution, participants used 1-DoF and 3-DoF skin deformation feedback to locate a feature in a 3-DoF virtual environment. Participants showed improved precision and shorter completion time when using 3-DoF compared to 1-DoF skin deformation feedback. For sensory augmentation, participants traced a path in space from an initial to a target location, while under guidance from force and/or skin deformation feedback. When force feedback was augmented with skin deformation, participants reduced their path-following error over the cases when force or skin deformation feedback are used separately. We conclude that 3-DoF skin deformation feedback is effective in substituting or augmenting force feedback. Such substitution or augmentation could be used when force feedback is unattainable or attenuated due to device limitations or system instability.

Learning and generalization in an isometric visuomotor task.

Adaptation is a prominent feature of the human motor system and has been studied extensively in reaching movements. This study characterizes adaptation and generalization during isometric reaching in which the arm remains stationary and the participant controls a virtual cursor via force applied by the hand. We measured how learning of a visual cursor rotation generalizes across workspace 1) to determine the coordinate system that predominates visual rotation learning, and 2) to ascertain whether mapping type, namely position or velocity control, influences transfer. Participants performed virtual reaches to one of two orthogonal training targets with the applied rotation. In a new workspace, participants reached to a single target, similar to the training target in either hand or joint space. Furthermore, a control experiment measured within-workspace generalization to an orthogonal target. Across position and velocity mappings, learning transferred predominantly in intrinsic (joint) space, although the transfer was incomplete. The velocity mapping resulted in significantly larger aftereffects and broader within-workspace generalization than the position mapping, potentially due to slower peak speeds, longer trial times, greater target overshoot, or other factors. Although we cannot rule out a mixed reference frame in our task, the predominance of intrinsic coding of cursor kinematics in the isometric environment opposes the extrinsic coding of arm kinematics in real reaching but matches the intrinsic coding of dynamics found in prior work. These findings have implications for the design of isometric control systems in human-machine interaction or in rehabilitation when coordinated multi-degree-of-freedom movement is difficult to achieve.