Tendon vibration can create movement illusions: vibrating the biceps tendon induces an illusion of extending the arm, while vibrating the triceps tendon induces an illusion of flexing the arm. However, it is unclear how to create and integrate such illusions shown in neuroscience to interaction techniques in virtual reality (VR). We first design a motor setup for tendon vibration. Study 1 validates that the setup induces movement illusions which on average create a 5.26 cm offset in active arm movements. Study 2 shows that tendon vibration improves the detection thresholds of visual motion gains often used in VR interaction techniques by 0.22. A model we developed in Study 2 predicts the effects of tendon vibration and is used in a biomechanical simulation to demonstrate the detection thresholds across typical reaching tasks in VR.

Low-frequency sound Heartbeat sensationsFigure 1: Heartbeat signals are modulated using low-frequency sound waves to create the perception of heartbeat sensations within the user's chest cavity.

This paper proposes a method for generating non-contact sensations using low-frequency sound waves without requiring user instrumentation. This method leverages the fundamental acoustic response of a confined space to produce predictable pressure spatial distributions at low frequencies, called modes. These modes can be used to produce sensations either throughout the body, in localized areas of the body, or within the body. We first validate the location and strength of the modes simulated by acoustic modeling. Next, a perceptual study is conducted to show how different frequencies produce qualitatively different sensations across and within the participants’ bodies. The low-frequency sound offers a new way of delivering non-contact sensations throughout the body. The results indicate a high accuracy for predicting sensations at specific body locations.

While model-mediated teleoperation (MMT) is an effective alternative for ensuring both transparency and stability, its potential in transmitting surface haptic texture is not yet explored. This paper introduces the first MMT framework capable of sharing surface haptic texture. The follower side collects physical signals contributing to haptic texture perception, e.g., high frequency acceleration, and streams them to the leader side. The leader side uses the signals to build and update a local measurement-based texture simulation model that reflects the remote surface. At the same time, the leader runs local simulation using the model, resulting in non-delayed, stable, and accurate feedback of texture. Considering that rendering haptic texture needs tougher real-time requirements, e.g., higher update rate and lower action-feedback latency, MMT can be a perfect platform for remote texture sharing. An initial proof-of-concept system supporting single and homogeneous surface is implemented and evaluated, demonstrating the potential of the approach.

This paper introduces a framework to predict multi-dimensional haptic attribute values that humans use to recognize the material by using the physical tactile signals (acceleration) generated when a textured surface is stroked. To this end, two spaces are established: a haptic attribute space and a physical signal space. A five-dimensional haptic attribute space is established through human adjective rating experiments with the 25 real texture samples. The physical space is constructed using tool-based interaction data from the same 25 samples. A mapping is modeled between the aforementioned spaces using a newly designed CNN-LSTM deep learning network. Finally, a prediction algorithm is implemented that takes acceleration data and returns coordinates in the haptic attribute space. A quantitative evaluation was conducted to inspect the reliability of the algorithm on unseen textures, showing that the model outperformed other similar models.

Recently, there has been an excessive congestion occurring in the driving environment because of the presence of modern gadgets inside the car and increased traffic on the roads, which has resulted in a higher demand for the visual and cognitive senses. This prompted the need to reduce the demand to make driving experience safer and more comfortable. Consequently, a novel steering wheel design for in-car controls is presented in this paper. The new design introduces dual ubiquitous touch panels embedded in the steering wheel for interaction with in-car controls and haptic feedback as positive reinforcement upon successful execution of an in-car control. There are eight different functionalities that can be controlled using the embedded touch panels. The proposed system is compared with a standard car regarding its efficacy using the NASA task load index (NASA-TLX) evaluation technique. The results showed that the proposed system significantly reduced the drivers’ visual, cognitive, and manual workload.

We present an interactive virtual-reality (VR) fire extinguisher that provides both realistic viewing using a head-mounted display (HMD) and kinesthetic experiences using a pneumatic muscle and vibrotactile transducer. The VR fire extinguisher is designed to train people to use a fire extinguisher skillfully in real fire situations. We seamlessly integrate three technologies: VR, object motion tracking, and haptic feedback. A fire scene is immersed in the HMD, and a motion tracker is used to replicate a real designed object into the virtual environment to realize augmented reality. In addition, when the handle of the fire extinguisher is squeezed to release the extinguishing agent, the haptic device generates both vibrotactile and air flow tactile feedback signals, providing the same experience as that obtained while using a real fire extinguisher.