Foot

BackgroundGait instability is a common and disabling symptom of Parkinson's disease (PD), contributing to frequent falls and reduced quality of life. While clinical balance tests and spatiotemporal gait measures can predict fall risk, they do not fully explain the underlying control mechanisms. In healthy individuals, foot placement is actively adjusted based on an estimate of the Center of Mass (CoM) state to maintain gait stability, known as foot placement control. This estimation relies on the integration of multisensory information, which has been shown to be impaired in PD, potentially disrupting the control of gait stability through foot placement. This study aimed to investigate whether foot placement coordination during overground walking is impaired in people with PD.MethodsFifty people with PD and 51 healthy older adults walked overground for 10 min at self-selected walking speed. Foot placement errors were quantified as the deviation between the actual foot placement and the predicted placement derived from the CoM kinematic state during the preceding swing phase.ResultsFoot placement errors were significantly higher in people with PD than in healthy older adults in both mediolateral (p ConclusionWe provide first evidence of impaired coordination between the CoM and foot placement in PD. Future work should investigate a causal relationship between impaired foot placement control, sensorimotor integration and gait instability.

Animals navigate their environment stably without inefficient course corrections despite unavoidable errors. In humans, this stability is achieved by modulating the placement of the foot on each step such that recent errors are corrected. However, it is unknown whether animals with diverse nervous systems and body mechanics use such foot placement control; foot trajectories of many-legged animals are considered to be stereotypical velocity-driven patterns, as opposed to error-driven. Here, we put forth a unified "feedforward-feedback" control structure for stable locomotion that combines velocity-driven and body state error-driven foot placement. We provide empirical support for this control structure across flies, mice, and humans by mining their natural locomotor variability, finding that a competing control structure with purely velocity-driven foot placement is not supported by the data. This work finds shared behavioral signatures of foot placement control in flies, mice, and humans. We find that key characteristics of these signatures, such as their urgency and centralization, vary with neuromechanical embodiment across species. For example, more inherently stable multilegged animals exhibit less urgent control with a lower control magnitude and a slower correction timescale compared to humans. Furthermore, many-legged animals display modular, direction-, and leg-specific control signatures, whereas humans exhibit common signatures across both legs. Overall, our findings provide insight into stable locomotion across species, revealing how species with diverse neuromechanics achieve a shared functional goal: foot placement control.

Diabetic foot Ulceration (DFU) is a severe complication of diabetic foot syndrome, often leading to amputation. In patients with neuropathy, ulcer formation is facilitated by elevated plantar tissue stress under insensate feet. This study presents a plantar pressure distribution analysis method to predict diabetic peripheral neuropathy. The Win-Track platform was used to gather clinical and plantar pressure data from 86 diabetic patients with different degrees of neuropathy. An automated image processing algorithm segmented plantar pressure images into forefoot and hindfoot regions for precise pressure distribution measurement. Comparative analysis of static and dynamic assessment showed that static analysis consistently outperformed dynamic methods. Gradient Boosting achieved the highest accuracy (88% dynamic, 100% static), with Random Forest and Decision Tree also performing well. Explainable AI techniques (SHAP, Eli5, Anchor Explanations) provided insights into feature importance, enhancing model interpretability. Additionally, a foot classification system based on the forefoot-hindfoot pressure ratio categorized feet as flat, regular, or arched. These findings support the development of improved diagnostic tools for early neuropathy detection, aiding risk stratification and prevention strategies. Enhanced screening can help reduce DFU incidence, lower amputation rates, and ultimately decrease diabetes-related mortality.

PurposeThe aetiology of tarsal tunnel syndrome is not always clear. Treatment commonly involves a single release of the flexor retinaculum, but post-operative outcomes are not always successful. This may be due to the lack of understanding the tissues that may compress the neurovasculature. The aim of this study was to define the tissues that separate the contents of the tarsal tunnel.MethodsFeet from embalmed body donors (n = 15; mean age = 83.9 ± 10.2 years; female = 9, male = 6) were examined. One underwent magnetic resonance imaging. All were dissected and modelled in virtual three-dimensional space.ResultsThe tarsal tunnel was divided into at least five spaces by a fibrous skeleton, formed by septae that were much thicker than previously understood.ConclusionThese data strongly suggest that the fibrous skeleton may compress the neurovasculature and may need to be considered in the diagnosis and management of tarsal tunnel syndrome. Surgically, this may more precisely inform which tissues need to be targeted for tarsal tunnel release.