ABSTRACT
The widespread emergence of airborne diseases has transformed our lifestyle, and respirators have become an essential part of daily life. Nevertheless, finding respirators that fit well can be challenging due to the variety of human facial sizes and shapes, potentially compromising protection. In addition, the current respirators do not inform the user of the air quality in case of continuous long-term use. Here, we introduce a smart filtering facepiece respirator incorporating a humidity sensor and pressure sensory feedback for self-fit adjusting and maintaining an adequate fit. The humidity detection sensor uses laser-induced graphene, and the pressure sensor array based on the dielectric elastomeric sponge monitors the respirator contact on the user's face, providing real-time closed-loop feedback and the wearer's fitting status. Those membrane sensors show outstanding performance, such as a low humidity hysteresis of 0.131 % and a precise pressure detection limit of 0.23 ± 0.02 kPa. As a result of the self-fit adjusting mode, the overall fit factor is increased by 10 % on average compared to the commercial respirator. This significant improvement in fit factor, coupled with the innovative design, has the potential to develop next-generation facepiece respirators as essential personal protective equipment.
ABSTRACT
Noncommunicable diseases (NCD), such as obesity, diabetes, and cardiovascular disease, are defining healthcare challenges of the 21st century. Medical infrastructure, which for decades sought to reduce the incidence and severity of communicable diseases, has proven insufficient in meeting the intensive, long-term monitoring needs of many NCD disease patient groups. In addition, existing portable devices with rigid electronics are still limited in clinical use due to unreliable data, limited functionality, and lack of continuous measurement ability. Here, a wearable system for at-home cardiovascular monitoring of postpartum women-a group with urgently unmet NCD needs in the United States-using a cloud-integrated soft sternal device with conformal nanomembrane sensors is introduced. A supporting mobile application provides device data to a custom cloud architecture for real-time waveform analytics, including medical device-grade blood pressure prediction via deep learning, and shares the results with both patient and clinician to complete a robust and highly scalable remote monitoring ecosystem. Validated in a month-long clinical study with 20 postpartum Black women, the system demonstrates its ability to remotely monitor existing disease progression, stratify patient risk, and augment clinical decision-making by informing interventions for groups whose healthcare needs otherwise remain unmet in standard clinical practice.
Subject(s)
Mobile Applications , Noncommunicable Diseases , Wearable Electronic Devices , Female , Humans , Monitoring, PhysiologicABSTRACT
Atherosclerosis is a prominent cause of coronary artery disease and broader cardiovascular diseases, the leading cause of death worldwide. Angioplasty and stenting is a common treatment, but in-stent restenosis, where the artery re-narrows, is a frequent complication. Restenosis is detected through invasive procedures and is not currently monitored frequently for patients. Here, we report an implantable vascular bioelectronic device using a newly developed miniaturized strain sensor via microneedle printing methods. A capillary-based printing system achieves high-resolution patterning of a soft, capacitive strain sensor. Ink and printing parameters are evaluated to create a fully printed sensor, while sensor design and sensing mechanism are studied to enhance sensitivity and minimize sensor size. The sensor is integrated with a wireless vascular stent, offering a biocompatible, battery-free, wireless monitoring system compatible with conventional catheterization procedures. The vascular sensing system is demonstrated in an artery model for monitoring restenosis progression. Collectively, the artery implantable bioelectronic system shows the potential for wireless, real-time monitoring of various cardiovascular diseases and stent-integrated sensing/treatments.