This paper proposes a comprehensive investigation of the automatic classification of functional gait disorders (GDs) based solely on ground reaction force (GRF) measurements. The aim of this study is twofold: first, to investigate the suitability of the state-of-the-art GRF parameterization techniques (representations) for the discrimination of functional GDs; and second, to provide a first performance baseline for the automated classification of functional GDs for a large-scale dataset. The utilized database comprises GRF measurements from 279 patients with GDs and data from 161 healthy controls (N). Patients were manually classified into four classes with different functional impairments associated with the "hip", "knee", "ankle", and "calcaneus". Different parameterizations are investigated: GRF parameters, global principal component analysis (PCA) based representations, and a combined representation applying PCA on GRF parameters. The discriminative power of each parameterization for different classes is investigated by linear discriminant analysis. Based on this analysis, two classification experiments are pursued: distinction between healthy and impaired gait (N versus GD) and multiclass classification between healthy gait and all four GD classes. Experiments show promising results and reveal among others that several factors, such as imbalanced class cardinalities and varying numbers of measurement sessions per patient, have a strong impact on the classification accuracy and therefore need to be taken into account. The results represent a promising first step toward the automated classification of GDs and a first performance baseline for future developments in this direction.

The treatment of gait disorders and impairments are major challenges in physical therapy. The broad and fast development in low-cost, miniaturized, and wireless sensing technologies supports the development of embedded and unobtrusive systems for robust gait-related data acquisition and analysis. Next to their applications as portable and lowcost diagnostic tools, such systems are also capable of use as feedback devices for retraining gait. The approach described within this article applies movement-based sonification of gait to foster motor learning. This article aims at presenting and evaluating a prototype of a pair of instrumented insoles for real-time sonification of gait (SONIGait) and to assess its immediate effects on spatio-temporal gait parameters. For this purpose, a convenience sample of six healthy males (age 35 ± 5 years, height 178 ± 4 cm, mass 78 ± 12 kg) and six healthy females (age 38 ± 7 years, height 166 ± 5 cm, mass: 63±8 kg) was recruited. They walked at a self-selected walking speed across a force distribution measurement system (FDM) to quantify spatio-temporal gait parameters during walking without and with five different types of sonification. The primary results from this pilot study revealed that participants exhibited decreased cadence (p < 0.01) and differences Results suggest that sonification has an effect on gait parameters, however further investigation and development is needed to understand its role as a tool for gait rehabilitation.

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Background and Purpose People with multiple sclerosis (PwMS) commonly have mobility impairments that may lead to falls and limitations in activities. Physiotherapy interventions that might improve mobility typically take several weeks. Balance-based torso-weighting (BBTW), a system of strategically placing light weights to improve response to balance perturbations, has resulted in immediate small improvements in clinical measures in PwMS, but changes in spatio-temporal gait parameters are unknown. The purpose was to investigate the effects of BBTW on gait parameters in PwMS and healthy controls. Methods Design: non-randomized controlled experiment Participants 20 PwMS and 20 matched healthy controls Procedures PwMS walked on an instrumented mat at their fastest speed for three trials each in two conditions: without BBTW then with BBTW. Healthy controls walked in both conditions at two speeds: their fastest speed, and at velocities equivalent to their matched PwMS. Results Averaged gait trials showed that, with BBTW, PwMS had significantly increased velocity (p=.002), cadence (p=.007), and time spent in single-limb support (p=.014), with decreased time in double-limb support (p=.004). Healthy controls increased velocity (p=.012) and cadence (p=.015) and decreased support base (p=.014) in fast trials with BBTW; at matched velocities, step length (p=.028) and support base (p=.006) were significantly different from PwMS. All gait variables in healthy controls at fast speeds were significantly different from PwMS walking at their fastest speeds. Discussion All participants showed increases in gait velocity and cadence during fast walk with BBTW. Improvements in time spent in single- and double-limb support by PwMS with BBTW may reflect greater stability in gait. Future research might ascertain if these immediate improvements could enhance effectiveness of longer-term physiotherapy on functional mobility in PwMS.

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