HaptiRead

Mid-air haptic (MAH) feedback is an interesting means to provide augmented haptic feedback for gesture-based technology as it enables a sense of touch without physical contact with an actuator. Although quite some work already investigated the user experience (UX) of MAH feedback during initial encounter, we are not aware of studies testing the UX after repeated use, with regard to both pragmatic and hedonic UX, as well as emotional reactions. In this article, we tested how the UX of MAH feedback changed over the course of five weeks by collecting both questionnaire as well as interview data of 31 participants. Our results showed that MAH feedback significantly increased the enjoyment, engagement, valence and arousal of the emotional response. However, the added value of valence was due to a novelty effect as it was only significantly elevated during initial use, and not after repeated use. Interestingly, the added value of MAH feedback in terms of enjoyment, engagement and arousal remained elevated over the course of five weeks. Moreover, the interview data hinted at substantial individual differences underlying the global trends from the questionnaire data, showing the importance of combining quantitative and qualitative data when testing the UX of MAH feedback.

The objective of this article is to provide a thorough examination of the current state of haptic information feedback in minimally invasive surgery (MIS), including research conducted between 1985 and the present. Despite the fact that haptic information input in MIS is currently scarce, the comprehensive analysis emphasises that it represents a potential option. Surgeons might potentially get substantial benefits from receiving more input about force information, which would therefore enhance their surgical accuracy and control. The extant literature highlights a significant knowledge deficit regarding the intricate ramifications of haptic feedback, specifically with regard to the sense of slip and gripping forces. It is crucial to investigate the possible advantages of incorporating supplementary haptic information in order to protect against tissue damage when performing manipulation treatments. It is of the utmost importance to fill this void, since doing so might revolutionise the field of MIS via the mitigation of unintended tissue injury and the improvement of surgical results. By capitalising on technology progress to provide more extensive haptic feedback, surgeons have the ability to enhance their tactile perception, optimise the application of force, and reduce the likelihood of tissue injuries when performing complex surgical procedures.

Mid-air haptic feedback technology produces tactile sensations that are felt without the need for physical interactions. However, mid-air haptic experiences need to be congruent with visual cues to reflect user expectations. To overcome this, we investigate how to visually present properties of objects, so that what one feels is a more accurate prediction of what one sees. Specifically, this paper investigates the relationship between 8 visual parameters of a point-cloud representation of a surface (particle color, size, distribution, etc.) and 4 mid-air haptic spatial modulation frequencies (20, 40, 60 and 80Hz). Our results and analysis reveal a statistical significance between low and high-frequency modulations and particle density, particle bumpiness (depth) and particle arrangement (randomness).

Non-contact, mid-air haptic devices have been utilized for a wide variety of experiences, including those in extended reality, public displays, medical, and automotive domains. In this work, we explore the use of synthetic jets as a promising and under-explored mid-air haptic feedback method. We show how synthetic jets can scale from compact, low-powered devices, all the way to large, long-range, and steerable devices (Figure 1 ). We built seven functional prototypes targeting different application domains to illustrate the broad applicability of our approach. These example devices are capable of rendering complex haptic effects, varying in both time and space. We quantify the physical performance of our designs using spatial pressure and wind flow measurements and validate their compelling effect on users with stimuli recognition and qualitative studies.

ABSTRACTGesture control systems based on mid-air haptics are increasingly used in infotainment systems in cars, where they can provide rich haptic feedback to improve human-computer interactions. Laboratory studies show that mid-air haptic feedback reduces drivers’ distractions and improve safety. However, it is unclear how the perception of mid-air ultrasound stimuli is affected by prolonged exposure to vibrational noise, e.g., from the steering wheel of a moving vehicle. Studies on vibrotactile adaptation show that perception of mechanical vibration is impaired by prior exposure to stimuli of the same frequency. Here, we investigated the effect of mechanical adaptation on the perception of mid-air ultrasound stimuli. We measured participants’ detection threshold for ultrasound stimuli of different frequencies both before and after exposure to 30 s mechanical vibrations. Across two experiments, we systematically manipulated the frequency and amplitude of the adapting stimulus. We found that exposure to low-frequency mechanical vibrations significantly impaired the detection of low-frequency ultrasound stimuli. In contrast, exposure to high-frequency mechanical vibrations equally impaired perception of both low- and high-frequency ultrasound stimuli. This effect was mediated by the amplitude of the adapting stimulus, with stronger mechanical vibrations producing a larger increase in participants’ detection threshold. Overall, these findings show that perception of mid-air ultrasound stimuli is affected by specific sources of mechanical noise. Crucially, frequency-specificity in the low-frequency band also points toward possible mitigating solutions that could help minimising unwanted desensitization of mechanoreceptor channels during mid-air haptic interactions.

In 3D gesture interaction, people engage in contactless interaction with computers through arm and palm movements. The aim of this study was to develop and verify a reasonable evaluation scheme for 3D gesture usability through empirical methods and finally form an efficient, natural, and standard gesture library for 3D interaction. Two experiments were performed. In the first experiment, an evaluation scheme for 3D gestures with different weighted indexes of usability was developed, and then the ratings of the usability dimensions of 30 gestures within 10 operations in the 3D interaction were compared with one another. The purpose of this comparison was to summarize a set of 3D gestures with the highest usability. In the second experiment, the validity of the gesture set acquired in the first experiment was verified by comparing the usability differences between the high- and low-rated 3D gestures. An optimal set of 3D gestures was obtained by comparing the usability ratings of the different gestures and then verifying the superiority of the operation performance and users’ satisfaction of this 3D gesture set in a real operation task.

We propose a haptic scanner that records vibrotactile and pressure stimulations as audio signals. Most of exiting the haptic sensors sense physical properties of real objects. However, haptic sensation is an integration of a considerable amount of sensory information and therefore, these methods require complex algorithms for converting properties to haptic stimulations. To simplify recreating haptic stimulations, we use recorded vibration sounds as the vibrotactile stimulations. Additionally, we sense contact forces by observing the amplitude modulations caused by change of resistance. Audio signals are preferable for record, edit and share. Especially, our proposed method can use haptic information as general stereo audio signal. Therefore, users can introduce haptic information to a variety of existing media and design new haptic media easily.

The use of robotic devices to provide active motor support and sensory feedback of ongoing motor intention, by means of a Brain Computer Interface (BCI), has received growing support by recent literature, with particular focus on neurorehabilitation therapies. At the same time, performance in the use of the BCI has become a more critical factor, since it directly influences congruency and consistency of the provided sensory feedback. As motor imagery is the mental simulation of a given movement without depending on residual function, training of patients in the use of motor imagery BCI can be extended beyond each rehabilitation session, and practiced by using simpler devices than rehabilitation robots available in the hospital. In this work, we investigated the use of haptic stimulation provided by vibrating electromagnetic motors to enhance BCI system training. The BCI is based on motor imagery of hand grasping and designed to operate a hand exoskeleton. We investigated whether haptic stimulation at fingerpads proves to be more effective than stimulation at wrist, already experimented in literature, due to the higher density of mechano-receptors. Our results did not show significant differences between the two body locations in BCI performance, yet a wider and more stable event-relateddesynchronization appeared for the finger-located stimulation. Future investigations will put in relation training with haptic feedback at fingerpads with BCI performance using the handexoskeleton, in grasping tasks that naturally involve haptic feedback at fingerpads.

This article gives an overview of research performed in the field of haptic information feedback during minimally invasive surgery (MIS). Literature has been consulted from 1985 to present. The studies show that currently, haptic information feedback is rare, but promising, in MIS. Surgeons benefit from additional feedback about force information. When it comes to grasping forces and perceiving slip, little is known about the advantages additional haptic information can give to prevent tissue trauma during manipulation. Improvement of haptic perception through augmented haptic information feedback in MIS might be promising.

This study investigates the influence of shoe type (sneakers and safety boots), age, and gender on the perception of haptic pulse feedback provided by a prototype accelerator pedal in a running stationary vehicle. Haptic feedback can be a less distracting alternative to traditionally visual and auditory in-vehicle feedback. However, to be effective, the device delivering the haptic feedback needs to be in contact with the person. Factors such as shoe type vary naturally over the season and could render feedback that is perceived well in one situation, unnoticeable in another. In this study, we evaluate factors that can influence the subjective perception of haptic feedback in a stationary but running car: shoe type, age, and gender. Thirty-six drivers within three age groups (≤39, 40-59, and ≥60) took part. For each haptic feedback, participants rated intensity, urgency, and comfort via a questionnaire. The perception of the haptic feedback is significantly influenced by the interaction between the pulse's duration and force amplitude and the participant's age and gender but not shoe type. The results indicate that it is important to consider different age groups and gender in the evaluation of haptic feedback. Future research might also look into approaches to adapt haptic feedback to the individual driver's preferences. Findings from this study can be applied to the design of an accelerator pedal in a car, for example, for a nonvisual in-vehicle warning, but also to plan user studies with a haptic pedal in general.

Electroencephalogram (EEG)-based emotion recognition has demonstrated encouraging results using machine learning (ML)-based algorithms. This study compares the performance of different frequency bands using four ML-based classifiers for the recognition of multi-class human emotions from EEG signals. Initially, the raw EEG signals are divided into five frequency bands such as delta, theta, alpha, beta, and gamma bands. Secondly, the statistical, time and frequency domain features are extracted. To classify emotions into positive, negative and neutral classes from the SEED dataset, these features are fed to four ML-based classifiers. This study shows the efficacy of an ensemble ML-based classifier over traditional classifiers. The best highest average classification accuracy reported by the random forest (RF) classifier for the delta band is 95.71%. The second highest average accuracy was reported by KNN with 80.32% for the theta band. A similar trend was also followed by other frequency bands. In conclusion, our study demonstrated the value of the proposed ML-based model for multi-class emotion recognition.

Interactive 3D visualizations of geospatial data are currently available and popular through various applications such as Google EarthTM and others. Several studies have focused on user performance with 3D maps, but static 3D maps were mostly used as stimuli. The main objective of this paper was to identify differences between interactive and static 3D maps. We also explored the role of different tasks and inter-individual differences of map users. In the experimental study, we analyzed effectiveness, efficiency, and subjective preferences, when working with static and interactive 3D maps. The study included 76 participants and used a within-subjects design. Experimental testing was performed using our own testing tool 3DmoveR 2.0, which was based on a user logging method and open web technologies. We demonstrated statistically significant differences between interactive and static 3D maps in effectiveness, efficiency, and subjective preferences. Interactivity influenced the results mainly in ‘spatial understanding’ and ‘combined’ tasks. From the identified differences, we concluded that the results of the user studies with static 3D maps as stimuli could not be transferred to interactive 3D visualizations or virtual reality.

Recently a number of TV manufacturers introduced TV remotes with a touchpad which is used for indirect control of TV UI. Users can navigate the UI by moving a finger across the touch pad. However, due to the latency in visual feedback, there is a disconnection between the finger movement on the touchpad and the visual perception in the TV UI, which often causes overshooting. In this paper, we investigate how haptic feedback affects the user experience of the touchpad-based TV remote. We described two haptic prototypes built on the smartphone and Samsung 2013 TV remote respectively. We conducted two user studies with two prototypes to evaluate how the user preference and the user performance been affected. The results show that there is overwhelming support of haptic feedback in terms of subjective user preference, though we didn't find significant difference in performance between with and without haptic feedback conditions.

Haptic information such as pressure (tactile) distribution could improve the clinical outcomes significantly by helping to detect tumors within soft-tissue organs and indicating potential abnormalities. In open surgeries, fingers are used to obtain this information. However, current surgical tele-manipulators do not provide explicit haptic feedback during soft tissue palpation. This paper describes a tactile sensing and feedback system, consisting of a colored tactile information display and pneumatic multi-fingered haptic feedback. This tissue stiffness feedback system is validated by palpating two phantom organs to locate tissue tumors. The results proved that the stiffness distribution is acquirable, visible, and palpable using our method.

Dexterous manipulation remains an aspirational goal for autonomous robotic systems, particularly when learning to lift and rotate objects against gravity with intermittent finger contacts. We use model-free reinforcement learning to compare the effect of curriculum (i.e., combinations of lift and rotation tasks) and haptic information (i.e., no-tactile versus 3D-force) on learning with a simulated three-finger robotic hand. In addition, a novel curriculum-based learning rate scheduler accelerates convergence. We demonstrate that the choice of curriculum biases the progression of learning for dexterous manipulation across objects with different weights, sizes, and shapes-underscoring the robustness of our learning approach. Unexpectedly, learning is achieved even in the absence of haptic information. This challenges conventional thinking about task "complexity" and the necessity of haptic information for dexterous manipulation for this task. This work invites the analogy of curriculum learning as a malleable developmental process from a pluripotent state driven by the nature of the learning experience.