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Depth-Based Intervention Detection in the Neonatal Intensive Care Unit Using Vision Transformers.
Sensors (Basel)
December 2024
Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.
Depth cameras can provide an effective, noncontact, and privacy-preserving means to monitor patients in the Neonatal Intensive Care Unit (NICU). Clinical interventions and routine care events can disrupt video-based patient monitoring. Automatically detecting these periods can decrease the time required for hand-annotating recordings, which is needed for system development.
View Article and Find Full Text PDFRF sensing enabled tracking of human facial expressions using machine learning algorithms.
Sci Rep
November 2024
University of Glasgow, James Watt School of Engineering, G12 8QQ, Glasgow, UK.
Automatic analysis of facial expressions has emerged as a prominent research area in the past decade. Facial expressions serve as crucial indicators for understanding human behavior, enabling the identification and assessment of positive and negative emotions. Moreover, facial expressions provide insights into various aspects of mental activities, social connections, and physiological information.
View Article and Find Full Text PDFAdvanced Camera-Based Scoliosis Screening via Deep Learning Detection and Fusion of Trunk, Limb, and Skeleton Features.
IEEE J Biomed Health Inform
November 2024
Scoliosis significantly impacts quality of life, highlighting the need for effective early scoliosis screening (SS) and intervention. However, current SS methods often involve physical contact, undressing, or radiation exposure. This study introduces an innovative, non-invasive SS approach utilizing a monocular RGB camera that eliminates the need for undressing, sensor attachment, and radiation exposure.
View Article and Find Full Text PDFOff-Body Sleep Analysis for Predicting Adverse Behavior in Individuals With Autism Spectrum Disorder.
IEEE J Biomed Health Inform
November 2024
Poor sleep quality in Autism Spectrum Disorder (ASD) individuals is linked to severe daytime behaviors. This study explores the relationship between a prior night's sleep structure and its predictive power for next-day behavior in ASD individuals. The motion was extracted using a low-cost near-infrared camera in a privacy-preserving way.
View Article and Find Full Text PDFBackground: In the Healthcare (HC) sector, the usage of Wireless Sensor Healthcare Networks (WSHN) is attaining specific importance. The sensor device is implanted into the patient's body, and the sensed health information of patients is transformed via data aggregating devices like mobile devices, cameras, and so on, to the doctors. Thus, the early signs of diseases are identified, and remote monitoring of the patient's health is carried out by the physician on time.
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