Acute effects of robot-assisted body weight unloading on biomechanical movement patterns during overground walking.

Body weight unloading (BWU) is used in rehabilitation/training settings to reduce kinetic requirements, however different BWU methods may be unequally capable of preserving biomechanical movement patterns. Biomechanical analysis of both kinetic and kinematic movement trajectories rather than discrete variables has not previously been performed to describe the effect of BWU on gait patterns during horizontal walking. The aim of the present study was to investigate how robot-assisted BWU producing an dynamic unloading force on the body centre of mass, affects kinematic, kinetic, and spatiotemporal gait parameters in healthy young adults by use of time-continuous analysis. Twenty participants walked overground in a 3-D motion-capture lab at 0, 10, 20, 30, 40, and 50 % BWU at a self-selected speed. Vertical and anterior-posterior ground reaction forces (GRFs) and lower limb internal joint moments were obtained during the stance phase, while joint angles were obtained during entire strides. Time-continuous data were analysed using Statistical Parametric Mapping (SPM) and discrete data using conventional statistics to compare different BWU conditions by means of One-Way Repeated Measures Anova. With increasing BWU, corresponding reductions were observed for GRFs, internal joint moments, joint angles, walking speed, stride/step length and cadence. Observed effects were partially caused by decreased walking speed and increased BWU. While amplitude reductions were observed for kinetic and kinematic variables, trajectory shapes were largely preserved. In conclusion, dynamic robot-assisted BWU enables reduced kinetic requirements without distorting biomechanically normal gait patterns during overground walking in young healthy adults.

Data Vizualization Dashboards in Robotic Rehabilitation.

Robotic rehabilitation can offer effective solutions, facilitating physiotherapist work, and helping patients regain their strength. Visualizing results of rehabilitative training could give a better insight into the factors that contribute to progress and measure the exact progress by every session. This paper aims to present a set of prototype dashboards to analyze and visualize data from robotic rehabilitation in order to help the patients measure their exerted force progress throughout the training period. The created visualization dashboards which proved helpful and essential to present achieved measurements, the progress of the patient, and the maximum force in a timeline presentation. The proposed prototypes could give a personalized overview to each patient, fed with the corresponding datasets.