Researchers explored wearable technology combined with machine learning to predict migraine attacks by analyzing physiological signals during sleep. The study found that shorter analysis frames effectively identified pre-migraine changes, highlighting the potential for personalized migraine management.
A novel depth-sensing system accurately tracks chest morphology changes in children with cerebral palsy.
In a recent article published in the journal Advanced Science, researchers presented a novel Multi-Sensor Origami Platform (MSOP) that integrates multiple sensors into a customizable origami structure, allowing for preci...
Researchers developed innovative pH-responsive antibodies by incorporating tyrosine derivatives, enhancing their binding affinity in acidic tumor microenvironments.
A wearable microneedle patch integrates real-time glucose monitoring and automated insulin delivery, offering a minimally invasive and efficient solution for diabetes management.
Researchers at ACS Central Science demonstrate how to package fluorescent sensors for simple passage across the BBB in mice, allowing for better brain imaging.
A new electrochemical biosensor that is 100 times more sensitive than traditional tests for detecting cortisol levels (the "stress hormone") in human saliva has been created.
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.
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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