BACKGROUND: Inter-segment joint angles can be obtained from inertial measurement units (IMUs); however, accurate 3D joint motion measurement, which requires sensor fusion and signal processing, sensor alignment with segments and joint axis calibratio...
Artificial neural networks (ANNs) offers potential for obtaining kinetics in non-laboratory. This study compared the estimation performance for ground reaction forces (GRF) and lower-limb joint moments during sidestepping between ANNs fed with full-b...
In hospitals, timely interventions can prevent avoidable clinical deterioration. Early recognition of deterioration is vital to stopping further decline. Measuring the way patients position themselves in bed and change their positions may signal when...
BMC medical informatics and decision making
39934805
This study proposes a deep learning-based motion assessment method that integrates the pose estimation algorithm (Keypoint RCNN) with signal processing techniques, demonstrating its reliability and effectiveness.The reliability and validity of this m...
The random motion of molecules in living cells has consistently been reported to deviate from standard Brownian motion, a behavior coined as "anomalous diffusion." To study this phenomenon in living cells, fluorescence correlation spectroscopy (FCS) ...
Identifying new anti-seizure medications (ASMs) is difficult due to limitations in animal-based assays. Zebrafish (Danio rerio) serve as a model for chemical and genetic seizures, but current methods for detecting anti-seizure responses are limited b...
Control of movement is learned and uses error feedback during practice to predict actions for the next movement. We previously showed that augmenting error can enhance learning, but while such findings are encouraging, the methods need to be refined ...
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
39902572
Generative deep learning has emerged as a promising data augmentation technique in recent years. This approach becomes particularly valuable in areas such as motion analysis, where it is challenging to collect substantial amounts of data. The objecti...
. Among all BCI paradigms, motion imagery (MI) has gained favor among researchers because it allows users to control external devices by imagining movements rather than actually performing actions. This property holds important promise for clinical a...
. Deep learning tools applied to high-resolution neurophysiological data have significantly progressed, offering enhanced decoding, real-time processing, and readability for practical applications. However, the design of artificial neural networks to...