Obstructive sleep apnea is a globally prevalent concern with significant health impacts, especially when coupled with comorbidities. Accurate detection and localization of airway obstructions are crucial for effective diagnosis and treatment, which remains a challenge for traditional sleep monitoring methods. Here, we report a catheter-based flexible pressure sensor array that continuously monitors soft tissue pressure in the upper airway and facilitates at the millimeter level. The sensor’s design and versatile 3D femtosecond laser fabrication process enable adaptation to diverse materials and applications. In vitro testing demonstrates high sensitivity (38.1 Ω/mmHg) and excellent stability. The sensor array effectively monitors distributed airway pressure and accurately identifies obstructions in an obstructive sleep apnea animal model. In this work, we highlight the potential of this catheter-based sensor array for long-term, continuous upper airway pressure monitoring and its prospective applications in other medical devices for pressure measurement in human body cavities.

Human motion recognition with high accuracy and fast response speed has long been considered an essential component in human-machine interactive activities such as assistive robotics, medical prosthesis, and wearable electronics. The force myography (FMG) signal has been the focus of much investigation in the search for a reliable and efficient muscular locomotion recognition system. However, the effect of the sensing system on FMG-based locomotion classification accuracy has yet to be understood. This study proposed a novel FMG sensing strategy for human lower limb locomotion classification based on flexible supercapacitive iontronic sensors. Benefiting from the ultrahigh sensitivity (up to 1 nF/mmHg) and low activation pressure (less than 5 mmHg) of the supercapacitive iontronic pressure sensor, FMG signal can be acquired accurately from 5 iontronic sensors strapped to the thigh. In the experiment with 12 subjects, the real-time classification strategy based on sliding window and SVM model gave an average locomotion classification accuracy of 99% for seven categories, including sitting, standing, walking on level ground, ramp ascent, ramp descent, stair ascent, stair descent. Compared with traditional FSR sensors, the result showed that iontronic sensors improved the classification accuracy by up to 10 percentage points in the case of short time window. The implementation of the high sensitivity flexible iontronic sensors in the wearable system brings a valuable tool for detecting small human body pressure signals and has great potential to improve the performance of the human-machine interface in rehabilitation and medical applications.

Flexible respiratory monitoring devices have become available for outside-hospital application scenarios attributable to their improved system wearability. However, the complex fabrication process of such flexible devices results in high prices, limiting their applications in real-life scenarios. This study proposes a flexible, low-cost, and easy-processing paper-based humidity sensor for sleep respiratory monitoring. A paper humidity sensing model was established and sensors under different design parameters were processed and tested, achieving high sensitivity of 5.45 kΩ/%RH and good repeatability with a matching rate of over 85.7%. Furthermore, the sensor patch with a dual-channel 3D structure was designed to distinguish between oral and nasal breathing from origin signals proved in the simulated breathing signal monitoring test. The sensor patch was applied in the sleep respiratory monitoring of a healthy volunteer and an obstruct sleep apnea patient, demonstrating its ability to distinguish between different respiratory patterns as well as various breathing modes.

An organocatalytic enantio- and diastereoselective synthesis of trifluoro-ethylamine allenoate derivatives containing axial and central chiralities has been achieved.