DeepLabCut increases markerless tracking efficiency in X-ray video analysis of rodent locomotion.

Despite the prevalence of rat models to study human disease and injury, existing methods for quantifying behavior through skeletal movements are problematic owing to skin movement inaccuracies associated with optical video analysis, or require invasive implanted markers or time-consuming manual rotoscoping for X-ray video approaches. We examined the use of a machine learning tool, DeepLabCut, to perform automated, markerless tracking in bi-planar X-ray videos of locomoting rats. Models were trained on 590 pairs of video frames to identify 19 unique skeletal landmarks of the pelvic limb.

Acoustic Emissions as a Non-invasive Biomarker of the Structural Health of the Knee.

The longitudinal assessment of joint health is a long-standing issue in the management of musculoskeletal injuries. The acoustic emissions (AEs) produced by joint articulation could serve as a biomarker for joint health assessment, but their use has been limited by a lack of mechanistic understanding of their creation. In this paper, we investigate that mechanism using an injury model in human lower-limb cadavers, and relate AEs to joint kinematics.

Evidence for startle as a measurable behavioral indicator of motor learning.

The ability of the classic startle reflex to evoke voluntarily prepared movement involuntarily has captured the attention of neuroscientists for its wide-ranging functional utility and potential uses in patient populations. To date, there is only one documented task resistant to the startReact phenomenon-index finger abduction. Previous reports have suggested the lack of startReact is due to different neural mechanisms driving individuated finger movement and more proximal joint control (e.