Articles

  • 1 week ago | spectroscopyonline.com | Jerome Workman

    Wearable Sensor Brings Brain Monitoring Out of the LabIn a leap forward for portable neuroscience and real-time cognitive tracking, a team of engineers has unveiled a wearable wireless system that uses near-infrared spectroscopy (NIRS) to monitor brain activity linked to cognitive fatigue.

  • 1 week ago | spectroscopyonline.com | Jerome Workman

    Imagine a world where your shirt tracks your vital signs, your watch detects early signs of disease, and your smartphone alerts your doctor before symptoms even appear. This is no longer science fiction. In a recent review published in Advanced Materials, a team of international researchers presents an in-depth analysis of how intelligent wearable sensors—enhanced by smart materials and artificial intelligence (AI)—are poised to change global healthcare systems in a dramatic way (1,2).

  • 1 week ago | spectroscopyonline.com | Jerome Workman

    Wearable Health Monitoring Through SweatWearable health sensors are undergoing a transformative shift, thanks to the integration of advanced spectroscopic techniques like surface-enhanced Raman spectroscopy (SERS) (1,2). A recent review titled “Trends and Advances in Wearable Plasmonic Sensors Utilizing Surface-Enhanced Raman Spectroscopy (SERS): A Comprehensive Review” in Sensors by Svetlana N. Khonina and Nikolay L.

  • 2 weeks ago | spectroscopyonline.com | Jerome Workman

    S. Michael Angel, a leading expert in laser-based spectroscopy, was involved as a consultant with the technical team that designed and developed the rover instrument SuperCam, one of the most advanced instruments aboard NASA’s Perseverance Mars rover. SuperCam combines multiple technologies—including laser-induced breakdown spectroscopy (LIBS), Raman spectroscopy, and infrared (IR) spectroscopy—to explore the Martian surface remotely.

  • 2 weeks ago | spectroscopyonline.com | Jerome Workman

    In a significant advancement for environmental monitoring, researchers in China have developed a novel approach for assessing water pollution in urban rivers by fusing satellite data, land use patterns, weather variables, and machine learning models.

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