Quantitative Magnetic Resonance Imaging (MRI) can enable early diagnosis of knee cartilage damage if imaging is performed during the application of load. Mechanical loading via ropes, pulleys and suspended weights can be obstructive and require adaptations to the patient table. In this paper, a new lightweight MRI-compatible elastic loading mechanism is introduced. The new device showed sufficient linearity (|α/β| = 0.42 ± 0.25), reproducibility (CoV = 5 ± 2%), and stability (CoV = 0.5 ± 0.1%). In vivo and ex vivo scans confirmed the ability of the device to exert sufficient force to study the knee cartilage under loading conditions, inducing up to a 29% decrease in T2 of the central medial cartilage. With this device mechanical loading can become more accessible for researchers and clinicians, thus facilitating the translational use of MRI biomarkers for the detection of cartilage deterioration.

Human walking speeds can be influenced by multiple factors, from energetic considerations to the time to reach a destination. Neurological deficits or lower-limb injuries can lead to slower walking speeds, and the recovery of able-bodied gait speed and behavior from impaired gait is considered an important rehabilitation goal. Because gait studies are typically performed at faster speeds, little normative data exists for very slow speeds (less than 0.6 ms^{− 1}). The purpose of our study was to investigate healthy gait mechanics at extremely slow walking speeds. We recorded kinematic and kinetic data from eight adult subjects walking at four slow speeds from 0.1 ms^{− 1} to 0.6 ms^{− 1} and at their self-selected speed. We found that known relations for spatiotemporal and work measures are still valid at very slow speeds. Trends derived from slow speeds largely provided reasonable estimates of gait measures at self-selected speeds. Our study helps enable valuable comparisons between able-bodied and impaired gait, including which pathological behaviors can be attributed to slow speeds and which to gait deficits. We also provide a slow walking dataset, which may serve as normative data for clinical evaluations and gait rehabilitative devices.