Researchers have developed a novel wearable system for non-invasive, continuous monitoring of bulbar muscle function in ALS animal models.
This study quantifies soft tissue desiccation during decomposition using custom sensors in the Western Cape, South Africa.
Researchers developed a microfluidic platform using surface-enhanced Raman spectroscopy (SERS) to detect single pancreatic cancer cells. The platform successfully differentiated between cancer stages, offering a promising tool for early cancer diagnosis through molecular analysis of individual cells.
Researchers developed an ultraflexible energy harvesting-storage system that combines organic photovoltaics (OPVs) with zinc-ion batteries, achieving high efficiency and adaptability for wearable devices. The system, featuring a power conversion efficiency of up to 16.18%, offers a lightweight, safe, and flexible energy solution
Researchers developed a smart silicone belt integrating wearable sensors for monitoring motion and harvesting energy from body movements. Utilizing triboelectric nanogenerators, the belt enhances self-powered wearables, demonstrating effective energy generation and physical activity tracking with optimized design features.
Researchers developed a flexible wearable sensor to monitor cortisol levels in sweat, providing real-time feedback for stress management. This non-invasive device utilizes molecularly imprinted polymers and carbon nanotubes to enhance sensitivity, offering a practical solution for everyday stress monitoring.
A review article highlights the growing importance of electronic tongues (e-tongues) in evaluating the bitterness of oral medications. These advanced taste sensors offer objective and reliable measurements, improving pharmaceutical formulations and patient compliance.
A review article in Sensors outlines how wearable and portable devices are transforming sports biomechanics and training science. The studies reviewed demonstrate how these devices enable real-time data collection in natural settings, providing valuable insights for athletes and coaches.
Researchers have introduced a cutting-edge system that merges wearable ECG sensors with machine learning to enable real-time monitoring and early detection of cardiorespiratory problems. Utilizing convolutional neural networks, this innovative approach promises to enhance patient care through timely insights and proactive intervention.
Researchers in Turkey have developed a real-time sign language recognition (SLR) system using wearable sensors, as detailed in the journal Sensors. Combining surface electromyography (sEMG) and inertial measurement units (IMUs), the system translates sign language into text or speech, achieving a high accuracy rate and promising to improve communication for those with hearing impairments.
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