Search

The use of Virtual Reality (VR) technology, especially in medical rehabilitation, has expanded to include tactile cues along with visual stimuli. For patients with upper limb hemiplegia, tangible handles with haptic stimuli could improve their ability to perform daily activities. Traditional VR controllers are unsuitable for patient rehabilitation in VR, necessitating the design of specialized tangible handles with integrated tracking devices. Besides, matching tactile stimulation with corresponding virtual visuals could strengthen users' embodiment (i.e., owning and controlling virtual bodies) in VR, which is crucial for patients' training with virtual hands. Haptic stimuli have been shown to amplify the embodiment in VR, whereas the effect of partial tactile stimulation from tangible handles on embodiment remains to be clarified. This research, including three experiments, aims to investigate how partial tactile feedback of tangible handles impacts users' embodiment, and we proposed a design concept called TouchMark for partial tactile stimuli that could help users quickly connect the physical and virtual worlds. To evaluate users' tactile and comfort perceptions when grasping tangible handles in a non-VR setting, various handles with three partial tactile factors were manipulated in Study 1. In Study 2, we explored the effects of partial feedback using three forms of TouchMark on the embodiment of healthy users in VR, with various tangible handles, while Study 3 focused on similar investigations with patients. These handles were utilized to complete virtual food preparation tasks. The tactile and comfort perceptions of tangible handles and users' embodiment were evaluated in this research using questionnaires and interviews. The results indicate that TouchMark with haptic line and ring forms over no stimulation would significantly enhance users' embodiment, especially for patients. The low-cost and innovative TouchMark approach may assist users, particularly those with limited VR experience, in achieving the embodiment and enhancing their virtual interactive experience.

Software-defined radio (SDR) can be used to detect human respiratory and heartbeat signals with the merits of low costs, high flexibility, and fast implementation. This paper proposes a human respiratory heartbeat detection system based on SDR micro-Doppler radar. The system can adjust radar parameters in real-time according to the detection environment, breaking the hardware limitations of traditional radar. Data pre-processing is performed on the transmit and receive baseband signals to obtain a composite signal containing human respiratory and heartbeat signals. In addressing the difficulty of detecting heartbeat signals compared to respiratory signals, an adaptive heartbeat signal enhancement detection algorithm named the one-time differential weighted step-size normalized least mean square (ODWS-NLMS) is proposed. This algorithm enhances the step size through weighted improvements utilizing the first-order differential characteristics of composite signals. Experiments were conducted in three distinct real-world environments, and the results indicate that the proposed algorithm outperforms discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD) in terms of average accuracy, root mean square error (RMSE), and signal-to-noise ratio (SNR).

Photon sensors have a lot of applications in our productive life, from inspection of steel building structures to early disease screening in preventive medicine. However, the precision of these sensors is limited by the shot-noise limit (SNL). Fortunately, previous studies have shown that quantum technology not only has better resolution than traditional sensing methods but also can achieve ultrahigh precision that breaks the SNL. Here, a new fiber salinity sensing method with quantum-limited precision is demonstrated by applying the single-photon interferometer. A novel detection method is designed and implemented by using the Fisher information analysis. Also, the precision is defined as the estimation error of the single-photon transmittance. The salinity sensitivity of the single-photon interferometer is about −0.00053/‰ with a good linearity. The salinity resolution of the proposed fiber salinity sensor is 0.062‰. Also, the detection precision is beyond the SNL. This work demonstrates that the introduction of quantum resources has opened a new door for high-performance detection technology.