Wireless wearable insoles are interesting tools to collect gait parameters during daily life activities. However, studies have to be performed specifically for each type of insoles on a big data set to validate the measurement in ecological situations. This study aims to assess the criterion validity and test-retest reliability of gait parameters from wearable insoles compared to motion capture system. Gait of 30 healthy participants was recorded using DSPro^® insoles and a motion capture system during overground and treadmill walking at three different speeds. Criterion validity and test-retest reliability of spatio-temporal parameters were estimated with an intraclass correlation coefficient (ICC). For both systems, reliability was found higher than 0.70 for all variables (p < 0.001) except for minimum toe clearance (ICC < 0.50) with motion capture system during overground walking. Regardless of speed and condition of walking, Speed, Cadence, Stride Length, Stride Time and Stance Time variables were validated (ICC > 0.90; p < 0.001). During walking on treadmill, loading time was not validated during slow speed (ICC < 0.70). This study highlights good criterion validity and test-retest reliability of spatiotemporal gait parameters measurement using wearable insoles and opens a new possibility to improve care management of patients using clinical gait analysis in daily life activities.

Used on clinical and sportive context, three-dimensional motion analysis is considered as the gold standard in the biomechanics field. The proposed dataset has been established on 30 asymptomatic young participants. Volunteers were asked to walk at slow, comfortable and fast speeds, and to run at comfortable and fast speeds on overground and treadmill using shoes. Three dimensional trajectories of 63 reflective markers, 3D ground reaction forces and moments were simultaneously recorded. A total of 4840 and 18159 gait cycles were measured for overground and treadmill walking, respectively. Additionally, 2931 and 18945 cycles were measured for overground and treadmill running, respectively. The dataset is presented in C3D and CSV files either in raw or pre-processed format. The aim of this dataset is to provide a complete set of data that will help for the gait characterization during clinical gait analysis and in a sportive context. This data could be used for the creation of a baseline database for clinical purposes to research activities exploring the gait and the run.

Running is the basis of many sports and has highly beneficial effects on health. To increase the understanding of running, DSPro^® insoles were developed to collect running parameters during tasks. However, no validation has been carried out for running gait analysis. The aims of this study were to assess the test–retest reliability and criterion validity of running gait parameters from DSPro^® insoles compared to a motion-capture system. Equipped with DSPro^® insoles, a running gait analysis was performed on 30 healthy participants during overground and treadmill running using a motion-capture system. Using an intraclass correlation coefficient (ICC), the criterion validity and test–retest reliability of spatiotemporal parameters were calculated. The test–retest reliability shows moderate to excellent ICC values (ICC > 0.50) except for propulsion time during overground running at a fast speed with the motion-capture system. The criterion validity highlights a validation of running parameters regardless of speeds (ICC > 0.70). This present study validates the good criterion validity and test–retest reliability of DSPro^® insoles for measuring spatiotemporal running gait parameters. Without the constraints of a 3D motion-capture system, such insoles seem to be helpful and relevant for improving the care management of active patients or following running performance in sports contexts.

The potential synergistic effects of the combination of Platelet Rich Plasma with hyaluronic acid remain insufficiently evaluated in randomized controlled

Early and effective rehabilitation is essential to optimize functional recovery and preserve patient autonomy in individuals with motor impairments. Among emerging gait rehabilitation approaches, Virtual Reality (VR) enables the simulation and control of ecologically valid environments and can reproduce complex situations from daily life. However, despite its increasing use for walking, it remains unclear how progressive increase in virtual environment complexity affects locomotor performance. Addressing this gap is essential to improve clinical understanding and ultimately optimize patient rehabilitation and care by understanding the influence of environmental constraints in walking. The aim of this study is to evaluate how increasing the complexity of virtual environments is tolerated by healthy subjects and affects locomotor performance and user immersion. Forty-five healthy volunteers performed flat and slope walking under two real conditions and three immersive VR conditions with increasing complexity. Locomotor parameters were recorded using inertial measurement units. Participants completed tolerance, incarnation and presence questionnaires and performed stability measurements using a baropodometric platform. Tolerance rate was 97.8% and 100%, without falls. No significant differences were observed in the overall questionnaire scores. Walking speed, cadence and stride length decreased significantly in immersions compared with real conditions for flat and sloped walk (p < 0.001). A significant increase in cadence between the virtual laboratory compared to the complex virtual environment was found (+ 2.1 step/min, p = 0.042) during flat walk only. Increasing VR environmental complexity appears to modulate locomotor performance in healthy individuals. Further studies in patient populations are needed to support clinical translation.