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  1. This work presents a scalable grayscale UV technique for fabricating spatially programmable soft actuators with diverse actuation behaviors in one actuator. The advanced programmability lays the foundation for soft robotics and adaptive devices.

     
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    Free, publicly-accessible full text available January 1, 2026
  2. Abstract

    Silent speech interfaces offer an alternative and efficient communication modality for individuals with voice disorders and when the vocalized speech communication is compromised by noisy environments. Despite the recent progress in developing silent speech interfaces, these systems face several challenges that prevent their wide acceptance, such as bulkiness, obtrusiveness, and immobility. Herein, the material optimization, structural design, deep learning algorithm, and system integration of mechanically and visually unobtrusive silent speech interfaces are presented that can realize both speaker identification and speech content identification. Conformal, transparent, and self‐adhesive electromyography electrode arrays are designed for capturing speech‐relevant muscle activities. Temporal convolutional networks are employed for recognizing speakers and converting sensing signals into spoken content. The resulting silent speech interfaces achieve a 97.5% speaker classification accuracy and 91.5% keyword classification accuracy using four electrodes. The speech interface is further integrated with an optical hand‐tracking system and a robotic manipulator for human‐robot collaboration in both assembly and disassembly processes. The integrated system achieves the control of the robot manipulator by silent speech and facilitates the hand‐over process by hand motion trajectory detection. The developed framework enables natural robot control in noisy environments and lays the ground for collaborative human‐robot tasks involving multiple human operators.

     
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    Free, publicly-accessible full text available October 1, 2025
  3. Conventional catheter- or probe-based in vivo biomedical sensing is uncomfortable, inconvenient, and sometimes infeasible for longterm monitoring. Existing implantable sensors often require an invasive procedure for sensor placement. Untethered soft robots with the capability to deliver the sensor to the desired monitoring point hold great promise for minimally invasive biomedical sensing. Inspired by the locomotion modes of snakes, we present here a soft kirigami robot for sensor deployment and real-time wireless sensing. The locomotion mechanism of the soft robot is achieved by kirigami patterns that offer asymmetric tribological properties that mimic the skin of the snake. The robot exhibits good deployability, excellent load capacity (up to 150 times its own weight), high-speed locomotion (0.25 body length per step), and wide environmental adaptability with multimodal movements (obstacle crossing, locomotion in wet and dry conditions, climbing, and inverted crawling). When integrated with passive sensors, the versatile soft robot can locomote inside the human body, deliver the passive sensor to the desired location, and hold the sensor in place for real-time monitoring in a minimally invasive manner. The proof-of-concept prototype demonstrates that the platform can perform real-time impedance monitoring for the diagnosis of gastroesophageal reflux disease. 
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  4. Abstract  
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  5. Silent speech interfaces have been pursued to restore spoken communication for individuals with voice disorders and to facilitate intuitive communications when acoustic-based speech communication is unreliable, inappropriate, or undesired. However, the current methodology for silent speech faces several challenges, including bulkiness, obtrusiveness, low accuracy, limited portability, and susceptibility to interferences. In this work, we present a wireless, unobtrusive, and robust silent speech interface for tracking and decoding speech-relevant movements of the temporomandibular joint. Our solution employs a single soft magnetic skin placed behind the ear for wireless and socially acceptable silent speech recognition. The developed system alleviates several concerns associated with existing interfaces based on face-worn sensors, including a large number of sensors, highly visible interfaces on the face, and obtrusive interconnections between sensors and data acquisition components. With machine learning-based signal processing techniques, good speech recognition accuracy is achieved (93.2% accuracy for phonemes, and 87.3% for a list of words from the same viseme groups). Moreover, the reported silent speech interface demonstrates robustness against noises from both ambient environments and users’ daily motions. Finally, its potential in assistive technology and human–machine interactions is illustrated through two demonstrations – silent speech enabled smartphone assistants and silent speech enabled drone control. 
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  6. Abstract

    Skin-integrated haptic interfaces that can relay a wealth of information from the machine to the human are of great interest. However, existing haptic devices are not yet able to produce haptic cues that are compatible with the skin. In this work, we present the stretchable soft actuators for haptic feedback, which can match the perception range, spatial resolution, and stretchability of the skin. Pressure-amplification structures are fabricated using a scalable self-assembly process to ensure an output pressure beyond the skin perception threshold. Due to the minimized device size, the actuator array can be fabricated with a sufficiently high spatial resolution, which makes the haptic device applicable for skin locations with the highest spatial acuity. A haptic feedback system is demonstrated by employing the developed soft actuators and highly sensitive pressure sensors. Two proof-of-concept applications are developed to illustrate the capability of transferring information related to surface textures and object shapes acquired at the robot side to the user side.

     
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  7. null (Ed.)