Despite decades of research, behavior change technologies remain limited in effectiveness because they mainly focus on offering information. Immersive technologies, such as extended, virtual, and augmented reality, promise to address this limitation by shifting from information-centric to experience-centric interventions. However, we do not know which technical and psychological components of immersive technologies make interventions effective. This scoping review of 53 articles analyzes how immersive technology components are linked to theory-informed behavior change techniques, summarizes their effectiveness, and synthesizes their unique advantages for experience-based immersive behavior change interventions. We offer both a formalization of the impact of immersive technology components on behavior change, and summarize practical suggestions for designing and systematically evaluating immersive behavior change interventions in a framework toward theory-driven Extended Reality behavior change interventions.

With the increasing demand for human-computer interaction (HCI), flexible wearable gloves have emerged as a promising solution in virtual reality, medical rehabilitation, and industrial automation. However, the current technology still has problems like insufficient sensitivity and limited durability, which hinder its wide application. This paper presents a highly sensitive, modular, and flexible capacitive sensor based on line-shaped electrodes and liquid metal (EGaIn), integrated into a sensor module tailored to the human hand’s anatomy. The proposed system independently captures bending information from each finger joint, while additional measurements between adjacent fingers enable the recording of subtle variations in inter-finger spacing. This design enables accurate gesture recognition and dynamic hand morphological reconstruction of complex movements using point clouds. Experimental results demonstrate that our classifier based on Convolution Neural Network (CNN) and Multilayer Perceptron (MLP) achieves an accuracy of 99.15% across 30 gestures. Meanwhile, a transformer-based Deep Neural Network (DNN) accurately reconstructs dynamic hand shapes with an Average Distance (AD) of 2.076±3.231 mm, with the reconstruction accuracy at individual key points surpassing SOTA benchmarks by 9.7% to 64.9%. The proposed glove shows excellent accuracy, robustness and scalability in gesture recognition and hand reconstruction, making it a promising solution for next-generation HCI systems.

A novel dual-rotor transverse flux permanent magnet machine is proposed in this paper. The key to this proposed machine is to add the dual-rotor structure based on the conventional transverse flux permanent magnet machine. The main contribution of this design is to generate a high frequency air-gap flux field with two rotors that rotate at low contra-rotating speeds through flux modulation effect, which increase the speed of the whole system. Moreover, the stator structure is modified based on C-type stator in conventional transverse flux permanent magnet machine. The optimized stator is beneficial to reduce the flux leakage and the machining difficulty. In this paper, flux field modulation principle in dual-rotor structure is first analyzed. And then, The C-type stator is designed and further optimized. Finally, the overall structural design is selected and make the comparison with the conventional transverse flux permanent magnet machine through finite element method.

a novel dual-rotor permanent magnet multiport machine with C-type stator is proposed in this paper. The key point of this proposed machine is using the C-type stator to separate the magnetic and electric load. It is contributed to decrease the air-gap length to improve the torque density. For the conventional multiport machine, the main flux path flows across six-layer air-gaps because of the dual-rotor, dual stator structures. Compared with the conventional multiport machine, the proposed machine with C-type stator just across three-layer air-gaps. Moreover, the outer and inner rotor of the proposed machine rotates based on flux field modulation principle at the contra-rotating speed to generate the high frequency air-gap flux field. In this paper, the overall structure of this machine is first introduced. Second, the flux field modulation principle in dual-rotor structure and the flux circuit in C-type stator is analyzed. Finally, the prototype of the proposed machine is selected and compares with the conventional dual-rotor permanent magnet multiport machine through finite element analysis method.