Tactile Feedback Exceeds Visual Feedback to Display Tissue Slippage in a Laparoscopic Grasper

This research evaluated visual and haptic feedback for enhancing operator situational awareness during multitasking drone operations, investigating how task complexity influenced feedback effectiveness. Two virtual reality experiments were conducted: Study 1 assessed three types of visual feedback (Static, Blink, and Shake), while Study 2 compared visual, haptic, and visual-haptic multimodal feedback across varying task complexity levels determined by target density. Participants performed drone operation tasks requiring simultaneous obstacle avoidance and target counting. Results revealed that dynamic visual feedback (Shake) significantly improved primary task accuracy, reduced cognitive load, and was the preferred visual feedback type. Furthermore, haptic and visual-haptic feedback significantly shortened obstacle avoidance reaction times and decreased cognitive workload compared to visual feedback. Task complexity proved to be a critical factor: while visual feedback sufficed for low complexity scenarios, visual-haptic feedback offered distinct advantages in medium and high complexity tasks, providing insights for complexity-responsive drone interface design.

In this study we compared tactile and visual feedbacks for the motor imagery-based brain–computer interface (BCI) in five healthy subjects. A vertical green bar from the center of the fixing cross to the edge of the screen was used as visual feedback. Vibration motors that were placed on the forearms of the right and the left hands and on the back of the subject’s neck were used as tactile feedback. A vibration signal was used to confirm the correct classification of the EEG patterns of the motor imagery of right and left hand movements and the rest task. The accuracy of recognition in the classification of the three states (right hand movement, left hand movement, and rest) in the BCI without feedback exceeded the random level (33% for the three states) for all the subjects and was rather high (67.8% ± 13.4% (mean ± standard deviation)). Including the visual and tactile feedback in the BCI did not significantly change the mean accuracy of recognition of mental states for all the subjects (70.5% ± 14.8% for the visual feedback and 65.9% ± 12.4% for the tactile feedback). The analysis of the dynamics of the movement imagery skill in BCI users with the tactile and visual feedback showed no significant differences between these types of feedback. Thus, it has been found that the tactile feedback can be used in the motor imagery-based BCI instead of the commonly used visual feedback, which greatly expands the possibilities of the practical application of the BCI.

We routinely have physical interactions with others, whether it be handing someone a glass of water or jointly moving a heavy object together. These sensorimotor interactions between humans typically rely on visual feedback and haptic feedback. Recent single-participant studies have highlighted that the unique noise and time delays of each sense must be considered to estimate the state, such as the position and velocity, of one's own movement. However, we know little about how visual feedback and haptic feedback are used to estimate the state of another person. Here, we tested how humans utilize visual feedback and haptic feedback to estimate the state of their partner during a collaborative sensorimotor task. Across two experiments, we show that visual feedback dominated haptic feedback during collaboration. Specifically, we found that visual feedback led to comparatively lower task-relevant movement variability, smoother collaborative movements, and faster trial completion times. We also developed an optimal feedback controller that considered the noise and time delays of both visual feedback and haptic feedback to estimate the state of a partner. This model was able to capture both lower task-relevant movement variability and smoother collaborative movements. Taken together, our empirical and modeling results support the idea that visual accuracy is more important than haptic speed to perform state estimation of a partner during collaboration.NEW & NOTEWORTHY Physical collaboration between two or more individuals involves both visual and haptic feedback. Here, we investigated how visual and haptic feedback is used to estimate the movements of a partner during a collaboration task. Our experimental and computational modeling results parsimoniously support the notion that greater visual accuracy is more important than faster yet noisier haptic feedback when estimating the state of a partner.

Virtual environments are often used in pre-wearing training and assessment of prosthetic control abilities. Here, we developed a virtual prosthetic hand training platform for evaluation of closed-loop control of grasp force. Biorealistic controllers emulated a pair of antagonistic muscles that actuated the thumb and index fingers of the hand. Surface electromyographic (sEMG) signals from a pair of antagonistic residual muscles drove the biorealistic controllers. Tactile forces from fingertip sensors were conveyed to amputees through evoked tactile sensations (ETS) elicited at the projected finger map (PFM) areas of the stump. A forearm amputee subject participated in force tracking or holding tasks using the virtual hand with residual muscle EMGs, or the contralateral intact hand. Root-mean-square error (RMSE) was used as outcome measure of motor performance. Results in this subject showed that the biorealistic controller enabled the virtual hand to track and maintain grasping forces. The best performance in both tasks was achieved by the contralateral intact hand with visual feedback. The roles of visual or tactile feedback in force tracking or maintaining were also assessed with the virtual hand. For force holding task, hybrid tactile and visual feedback with biorealistic control had a better performance than single visual or tactile feedback in terms of RMSE, success rate, and force variability. While in the force pursuing task, tactile feedback did not seem to add visual feedback in following the target force. The study suggests that training may be required for a novel virtual hand user to perceive and integrate multiple modalities of feedback information, so as to optimize the closed-loop control ability.

For educational purposes, virtual reality (VR) is often used to produce life-like experiences. However, the use of haptic feedback in educational practices for science and mathematics remained under-studied. Haptically-enabled science simulations (HESSs) enable students to physically experience the concepts being taught via haptic feedback. We present a study on the effect of a buoyancy HESS designed to aid in the understanding of basic physics concepts. We hypothesize that introducing both visual and haptic feedback of the underlying simulated forces will improve participants understanding. We investigate this hypothesis with a 2 (haptics: yes, no) × 2 (visuals: yes, no) between subjects design user study, where all participants were randomly assigned to one of the four conditions. Participants were given a pretest of buoyancy knowledge, then instructed to interact with the buoyancy simulation, then given a post-test of buoyancy knowledge. The present study is still in the process of data collection, with 40 out of 60 participants. Preliminary results highlight a significant improvement in performance of participants in the haptic-and-visual condition, while no significant differences were observed in other conditions.

Fitts’ law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts’ law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts’ law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts’ law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts’ law (average r2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts’ law for explicit targets with vision (r2 = 0.96) and implicit targets (r2 = 0.89), but not as well-described for explicit targets without vision (r2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts’ law to quantify the relative speed-accuracy relationship of any given grasper.

This paper describes development of an activity based, multimodal balance rehabilitation training device. Various sensors can be used, including a force plate, inertial sensors, and depth sensing cameras, and various combinations of visual, auditory and tactile feedback can be configured depending on the rehabilitation task and activity. Tactile feedback is presented via a lightweight belt that is worn on the torso. Generally, visual feedback is only needed at the start of rehabilitation training (task orientation) while tactile feedback may be used to augment balance control. Tactile feedback can be configured as a cue that certain movement targets or limits have been reached or as an immediate indicator of the variance in postural sway. Tactile feedback allows the subject to naturally concentrate on the functional rehabilitation task, and is less reliant on visual or verbal cues.

Most prosthetic hand users are limited to visual feedback of movement performance. To characterize the benefit of vibrotactile feedback for a task that lacks haptic feedback, a virtual environment was used to experimentally manipulate visual, task-relevant haptic, and remote vibrotactile feedback on simple object manipulation for unimpaired subjects. The combination of visual and remote vibrotactile feedback was compared to visual feedback alone, and to simultaneous visual and direct haptic feedback to represent ideal performance. Visual and vibrotactile feedback resulted in improvement of most performance variables including difficulty ratings relative to visual feedback alone. However addition of sensory cues to visual feedback increased trial times and the increase was steeper for vibrotactile than for haptic feedback. Specifically, during vibrotactile feedback the velocity did not change, but the duration of execution increased due to improved performance, resulting in increased trial times. This result suggests future exploration of performance improvement and execution speed for augmented sensory feedback.

Haptic technologies and applications have received enormous attention in the last decade. The incorporation of haptic modality into multimedia applications adds excitement and enjoyment to an application. It also adds a more natural feel to multimedia applications, that otherwise would be limited to vision and audition, by engaging as well the user's sense of touch, giving a more intrinsic feel essential for ambient intelligent applications. However, the improvement of an application's Quality of Experience (QoE) by the addition of haptic feedback is still not completely understood. The research presented in this paper focuses on the effect of haptic feedback and what it potentially adds to the experience of the user as opposed to the traditional visual and auditory feedback. In essence, it investigates certain issues regarding stylus-based haptic education applications and haptic-enhanced entertainment videos. To this end, we used two haptic applications: the haptic handwriting learning tool to experiment with force feedback haptic interaction and the tactile YouTube application for tactile haptic feedback. In both applications, our analysis shows that the addition of haptic feedback will increase the QoE in the absence of fatigue or discomfort for this category of applications. This implies that the incorporation of haptic modality (both force feedback as well as tactile feedback) has positively contributed to the overall QoE for the users.

Spinal cord injury (SCI) impairs motor function and requires rigorous rehabilitative therapy, motivating the development of approaches that are engaging and customizable. Virtual reality (VR) motor training with augmented sensory feedback (ASF) offers a promising pathway to enhance functional outcomes, yet it remains unclear how ASF modalities affect performance and underlying psychophysiological states in persons with SCI. Five participants with chronic incomplete cervical-level SCI controlled a virtual robotic arm with semi-isometric upper-body contractions while undergoing ASF training with either visual feedback (VF) or combined visual plus haptic feedback (VHF). Motor performance (pathlength, completion time), psychophysiological measures (EEG, EMG, EDA, HR), and perceptual ratings (agency, motivation, utility) were assessed before and after ASF training. VF significantly reduced pathlength (−12.5%, p = 0.0011) and lowered EMG amplitude (−32.5%, p = 0.0063), suggesting the potential for improved motor performance and neuromuscular efficiency. VHF did not significantly improve performance, but trended toward higher cortical engagement. EEG analyses showed VF significantly decreased alpha and beta activity after training, whereas VHF trended toward mild increases. Regression revealed improved performance was significantly (p < 0.05) associated with changes in alpha power, EMG, EDA, and self-reported motivation. ASF type may differentially shape performance and psychophysiological responses in SCI participants. These preliminary findings suggest VR-based ASF as a potent multidimensional tool for personalizing rehabilitation.

Controlling the motion of a prosthetic upper limb without visual feedback is extremely difficult because the wearer does not know the prosthesis' configuration. This paper describes an experiment designed to determine the relative importance of visual and haptic position feedback during targeted force-based motion by non-amputee human subjects as an analogy to prosthetic use. Subjects control the angle of a virtual proxy through an admittance relationship by generating torque at the MCP joint of the right index finger. During successive repetitions of a target acquisition task, the proxy's state is selectively conveyed to the user through graphical display, finger motion, and tactile stimulation. Performance metrics for each feedback condition will provide insights on the role of haptic position feedback and may help guide the development of future upper-limb prostheses

Background: The purpose of this study was to determine the reaction time (RT) and movement time (MT) in Down syndrome children under two different visual feedback conditions. Methods: An observational cross-sectional study was conducted in which 30 mild to moderate Down syndrome children were allocated randomly into two groups. The full visual feedback group comprised 15 participants with an average age of 12(± 1.4) years, and the no visual feedback group comprised 15 participants with an average age of 12(± 1.7) years. All the participants repeated the same activity 20 times with the order of conditions randomized across individuals. Results: RT and MT were analyzed while participants performed the movement sequence. After 20 trials, both groups showed significant differences in their MT but no significant differences in RT. Intergroup analysis also showed that there was no statistically significant difference in either RT or MT. Conclusion: Down syndrome children exhibited longer movement and RTs than normal children regardless of vision condition. Knowledge of their performance at regular intervals and encouragement helped to improve their MT. Down syndrome children were less affected by the elimination of visual feedback and showed no significant variation in RTs.

Humans systematically adapt their strategies for closed-loop control based on visual feedback according to the dynamics of the system. Tactile feedback is a key element in many human–machine interfaces, but it is not known if and how well human control adapts to changes in system dynamics when information about the system state is provided using this type of feedback. In this study, 11 participants tracked a pseudorandom trajectory with a virtual, position- or velocity-controlled plant using a joystick. Visual or electrotactile feedback provided the instantaneous error between the target and generated trajectory. Frequency-domain system identification indicated that human control adapted in similar ways to the different control modes (i.e., position/velocity control) for both feedback modalities. For the plant dynamics modeled as gain and integrator, the human controller behaved as a low-pass filter and gain, respectively (under the assumption of quasi-linear behavior). However, while tracking quality was largely similar for both control modes with visual feedback, velocity control enabled substantially worse control with electrotactile feedback compared to position control. Furthermore, for both control modes, the crossover frequency of open-loop transfer functions was lower for electrotactile feedback (0.9 and 1.1 rad/s) than for visual feedback (1.5 and 1.7 rad/s) indicating limited control bandwidth. To summarize, closed-loop control based on electrotactile feedback enables natural adaptations in human control strategy, which is encouraging for tactile feedback-controlled human–machine interfaces, but the lower control bandwidth and lower tracking quality with velocity control may impose functional limitations.

The Simulation-Based Open Surgery Training System (SOSTS) is a virtual reality simulator designed to provide training on a simulated orthopedic bone pinning procedure. The present version of SOSTS offers five distinct combinations of multi-sensory feedback during training. The purpose of this study was to investigate the effects of visual and haptic feedback on participants' ability to place a pin through a fractured tibia on the simulator. Enhanced visual feedback resulted in a significant reduction of pin alignment error, although participants in these conditions took five times longer to achieve proficiency than those in the moderate visual feedback conditions. Any form of haptic feedback resulted in significantly greater pin placement error than no haptic feedback. The results provide partial support for the proximity compatibility principle for display design.

We introduce a novel posture guidance office chair and evaluate the effectiveness of vibrotactile and visual feedback methods for guiding seated postures. For visually dominant office work such as typing on the computer, it is possible that delivering posture feedback visually may overload the visual sense while haptic feedback may be a viable alternative. We performed two experiments to compare vibrotactile and visual feedback--posture compliance and dual-task cognitive workload assessment. In the first experiment, our results showed no statistically significant difference in effectiveness between using vibrotactile and visual feedback to obtain postural compliance to a reference posture. In the second experiment, participants experienced typing performance and response time degradations from both types of feedback. However the differences in performance degradation were not statistically significant between the two feedback methods. We conclude that vibrotactile and visual feedback are similarly effective for guiding quasistatic postures in routine tasks such as seated office work.