Implementation of multi-modal interface for VR application

Machidori, Yushi; Takayama, Ko; Sugita, Kenichiro

doi:10.1109/icawst.2019.8923551

Cited by 2 publications

(1 citation statement)

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“…However, these interface devices must minimize the gap between the target content and the RWD reproduced in the HMD to provide a smooth immersion experience. VR interface devices connect the VWD and the RWD, and users can use natural user interfaces (NUI) such as voice, touch, motion, and even brain waves to operate these devices [ 9 ]. Researchers are exploring different technologies such as Leap Motion, and Ultra-Leap Motion to provide virtual immersion [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Low-Latency Haptic Open Glove for Immersive Virtual Reality Interaction

Sim

Baek

Cho

et al. 2021

Sensors

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Recent advancements in telecommunications and the tactile Internet have paved the way for studying human senses through haptic technology. Haptic technology enables tactile sensations and control using virtual reality (VR) over a network. Researchers are developing various haptic devices to allow for real-time tactile sensation, which can be used in various industries, telesurgery, and other mission-critical operations. One of the main criteria of such devices is extremely low latency, as low as 1 ms. Although researchers are attempting to develop haptic devices with low latency, there remains a need to improve latency and robustness to hand sizes. In this paper, a low-latency haptic open glove (LLHOG) based on a rotary position sensor and min-max scaling (MMS) filter is proposed to realize immersive VR interaction. The proposed device detects finger flexion/extension and adduction/abduction motions using two position sensors located in the metacarpophalangeal (MCP) joint. The sensor data are processed using an MMS filter to enable low latency and ensure high accuracy. Moreover, the MMS filter is used to process object handling control data to enable hand motion-tracking. Its performance is evaluated in terms of accuracy, latency, and robustness to finger length variations. We achieved a very low processing delay of 145.37 s per finger and overall hand motion-tracking latency of 4ms. Moreover, we tested the proposed glove with 10 subjects and achieved an average mean absolute error (MAE) of 3.091∘ for flexion/extension, and 2.068∘ for adduction/abduction. The proposed method is therefore superior to the existing methods in terms of the above factors for immersive VR interaction.

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Section: Introductionmentioning

confidence: 99%