Integrated care has been an important model for caring the elderly. In China, it is still at its very early stage. We proposed a new model to develop a smart mobile system, taking the CARE instrument as the base and composed of apps for stakeholders. We did an usability study using the TAMM tool and, from a convenience sample of 11 elderly and 18 nurses, the results indicated the system was well appreciated.
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JMIR AI
January 2025
Human-Computer Interaction and Human-Centered AI Systems Lab, AI for Healthcare Lab, Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology, Hoboken, NJ, United States.
Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect acute marijuana intoxication in real time.
Objective: This study aims to explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, like Fitbit, can enhance the detection of acute marijuana intoxication in naturalistic settings.
Eur J Cancer
December 2024
Division of Digital Prevention, Diagnostics and Therapy Guidance, German Cancer Research Center (DKFZ), Heidelberg, Germany. Electronic address:
Front Public Health
December 2024
Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China.
Introduction: Ensuring effective measures against the spread of the virus is paramount for educational institutions and workplaces as they resume operations amidst the ongoing public health crisis. A touchless and privacy-conscious check-in procedure for visitor assessment is critical to safeguarding venues against potential virus transmission.
Methods: In our study, we developed an interaction-free entry system featuring anonymous visitors who voluntarily provide data.
J Med Eng Technol
December 2024
Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran.
Nowadays, photoplethysmograph (PPG) technology is being used more often in smart devices and mobile phones due to advancements in information and communication technology in the health field, particularly in monitoring cardiac activities. Developing generative models to generate synthetic PPG signals requires overcoming challenges like data diversity and limited data available for training deep learning models. This paper proposes a generative model by adopting a genetic programming (GP) approach to generate increasingly diversified and accurate data using an initial PPG signal sample.
View Article and Find Full Text PDFSci Rep
December 2024
Computer Engineering Department, Umm Al-Qura University, Mecca, 24381, Saudi Arabia.
Efficient traffic management solutions in 6G communication systems face challenges as the scale of the Internet of Things (IoT) grows. This paper aims to yield an all-inclusive framework ensuring reliable air pollution monitoring throughout smart cities, capitalizing on leading-edge techniques to encourage large coverage, high-accuracy data, and scalability. Dynamic sensors deployed to mobile ad-hoc pieces of fire networking sensors adapt to ambient changes.
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