Background An incomplete spinal cord injury (SCI) refers to remaining sensorimotor function below the injury with the possibility for the patient to regain walking abilities. However, these patients often suffer from diverse gait deficits, which are not objectively assessed in the current clinical routine. Wearable inertial sensors are a promising tool to capture gait patterns objectively and started to gain ground for other neurological disorders such as stroke, multiple sclerosis, and Parkinson’s disease. In this work, we present a data-driven approach to assess walking for SCI patients based on sensor-derived outcome measures. We aimed to (i) characterize their walking pattern in more depth by identifying groups with similar walking characteristics and (ii) use sensor-derived gait parameters as predictors for future walking capacity. Methods The dataset analyzed consisted of 66 SCI patients and 20 healthy controls performing a standardized gait test, namely the 6-min walking test (6MWT), while wearing a sparse sensor setup of one sensor attached to each ankle. A data-driven approach has been followed using statistical methods and machine learning models to identify relevant and non-redundant gait parameters. Results Clustering resulted in 4 groups of patients that were compared to each other and to the healthy controls. The clusters did differ in terms of their average walking speed but also in terms of more qualitative gait parameters such as variability or parameters indicating compensatory movements. Further, using longitudinal data from a subset of patients that performed the 6MWT several times during their rehabilitation, a prediction model has been trained to estimate whether the patient’s walking speed will improve significantly in the future. Including sensor-derived gait parameters as inputs for the prediction model resulted in an accuracy of 80%, which is a considerable improvement of 10% compared to using only the days since injury, the present 6MWT distance, and the days until the next 6MWT as predictors. Conclusions In summary, the work presented proves that sensor-derived gait parameters provide additional information on walking characteristics and thus are beneficial to complement clinical walking assessments of SCI patients. This work is a step towards a more deficit-oriented therapy and paves the way for better rehabilitation outcome predictions.

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Objective: Steering-by-leaning is a promising innovation for manual wheelchairs. It may enable improved energy efficiency, one-handed manoeuvrability, and increased trunk activity during wheelchair use in daily life. To explore the feasibility of this concept, the lateral trunk function of active wheelchair users was assessed before comparing 3 preliminary dynamic backrest designs in a virtual steering exercise.Design: Repeated measures, cross-over study.Subjects: A convenience sample of 15 individuals who had been full-time users of manual wheelchair for at least 1 year.Methods: Active core strength and lateral leaning range of motion were captured while sitting freely. Participants subsequently tested 3 dynamic wheelchair backrest designs on an individually adjusted laboratory wheelchair prototype by performing a virtual steering exercise. Deviations from a target movement path were analysed using repeated measures analysis of variance and Pearson correlation coefficients.Results: Functional leaning range of motion ranged from below 10° to almost 70°, but increased significantly with use of the simplest backrest design based on a 2-dimensional hinge joint. No correlation was found between functional levels and performance parameters in the virtual steering exercise.Conclusion: Using an individually fitted and calibrated design, upper body-actuated wheelchair steering using a laterally tilting backrest is accessible to wheelchair users across a wide spectrum of physical abilities. LAY ABSTRACTManual wheelchairs not only enable mobility, but also provide postural support to users through passive seating elements. The consequences of static sitting, however, include pain, deformities, and pressure injuries. The concept of backrest steering in manual wheelchairs may improve overall energy efficiency while promoting active trunk movement, but its applicability is questionable given the varying levels of trunk control among users. In this study, active trunk function of 15 full-time users of manual wheelchairs was measured prior to testing 3 prototype dynamic backrest designs in a virtual steering exercise. The results highlight the broad spectrum of abilities in this population, but suggest that active movement can be supported by simple mechanisms. No meaningful relationship was found between trunk abilities and performance in the virtual steering exercise, indicating that upper body-actuated steering of manual wheelchairs is accessible to users across a wide spectrum of physical abilities.