With the explosive development of smart wearable devices, a serious situation that a large amount of energy waste and environmental pollution caused by electronic discarding needs to be solved urgently. Here, as a throwaway waste material, a chewed g...
Falls are dangerous for the elderly, often causing serious injuries especially when the fallen person stays on the ground for a long time without assistance. This paper extends our previous work on the development of a Fall Detection System (FDS) usi...
In this study, a self-sorting sensor was developed with the ability to distinguish between different pressure regimes and translate the pressure to electrical signals. Specifically, the self-sorting sensor can distinguish between soft and hard pressu...
BACKGROUND: Multimodal wearable technologies have brought forward wide possibilities in human activity recognition, and more specifically personalized monitoring of eating habits. The emerging challenge now is the selection of most discriminative inf...
IEEE reviews in biomedical engineering
Jan 26, 2021
Sign language is used as a primary form of communication by many people who are Deaf, deafened, hard of hearing, and non-verbal. Communication barriers exist for members of these populations during daily interactions with those who are unable to unde...
This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was...
With the rapid growth of artificial intelligence, wearable electronic devices have caught intensive research interest recently. Flexible sensors, as the significant part of them, have become the focus of research. Particularly, flexible microstructur...
Motion intention detection is fundamental in the implementation of human-machine interfaces applied to assistive robots. In this paper, multiple machine learning techniques have been explored for creating upper limb motion prediction models, which ge...
This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offerin...
BACKGROUND: Recent studies have demonstrated that passive smartphone and wearable sensor data collected throughout daily life can predict anxiety symptoms cross-sectionally. However, to date, no research has demonstrated the capacity for these digita...
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