Deep learning biomechanical models perform optimally when trained with large datasets, however these can be challenging to collect in gait labs, while limited augmentation techniques are available. This study presents a data augmentation approach bas...
Gait analysis is used in research and clinical environments; yet several limitations exist in current methodologies. Markerless systems, utilizing high-speed video and artificial intelligence, eliminate most limitations encountered in marker-, depth-...
Dance interventions hold promise for improving gait and balance in people with neurological conditions. It is possible that synchronization of movement to the music is one of the mechanisms through which dance bestows physical benefits. This technica...
Observations from laboratory-based gait analysis are difficult to extrapolate to real-world environments where gait behavior is modulated in response to complex environmental conditions and surface profiles. Inertial measurement units (IMUs) permit r...
Upper-limb rehabilitation therapy sessions for post-stroke people generally contain rhythmic hand movements in a tiresome manner to rebuild the injured neural circuits. Fatigue formation causes breaks in the training and limits the therapy duration. ...
This study's purpose was to develop a direct MRI-based, deep-learning semantic segmentation approach for computing global longitudinal strain (GLS), a known metric for detecting left-ventricular (LV) cardiotoxicity in breast cancer. Displacement Enco...
Human body center of mass location plays an essential role in physical therapy, especially in investigating a subject's capability to maintain balance. However, its estimation can be a very complex, costly, and time-consuming process. To overcome the...
Challenging trunk neuromuscular control maximally using a seated balancing task is useful for unmasking impairments that may go unnoticed with traditional postural sway measures and appears to be safe to assess in healthy individuals. This study inve...
Kinematic analysis is often performed in a lab using optical cameras combined with reflective markers. With the advent of artificial intelligence techniques such as deep neural networks, it is now possible to perform such analyses without markers, ma...
Spatiotemporal parameters can characterize the gait patterns of individuals, allowing assessment of their health status and detection of clinically meaningful changes in their gait. Video-based markerless motion capture is a user-friendly, inexpensiv...