Stroke is currently the world’s second cause of disability. It can cause deficits such as postural control, and telerehabilitation could improve the therapeutic dose as well as functional results. The aim of this work is to determine the effectiveness and usability of a low-cost telerehabilitation system in patients with stroke. We developed a telerehabilitation system based on exergames on smartphones, inertial sensors, and a cloud database. We trained the balance of six participants (three men and three women) in early subacute stroke (seven weeks of progress). In addition to their conventional treatment, these participants trained for a total of nine sessions of 30 min per week, for four weeks. The telerehabilitation group was compared with a control group of four clinically similar participants (three men and one woman). Clinical and usability measurements were made before and after the training. The results show a significant improvement of 11.3 ± 3.5 points in the Berg Balance Scale, 8.3 ± 3.01 points in the Mini-BESTest, and 17.5 ± 9.87 points in the Barthel scale for the telerehabilitation group. However, only the improvements of Berg and Barthel scales were statistically higher for the telerehabilitation group compared to the control group. The proposed system achieved excellent usability on the System Usability Scale (87.5 ± 11.61). Our results demonstrate that a complementary low-cost telemedicine approach is feasible, and that it can significantly improve the balance of stroke patients; therefore, the proposed clinical strategy could potentially improve dosage and overall treatment effectiveness.

Motivation Quantitative descriptions of multi-cellular structures from optical microscopy imaging are prime to understand the variety of three-dimensional (3D) shapes in living organisms. Experimental models of vertebrates, invertebrates and plants, such as zebrafish, killifish, Drosophila or Marchantia, mainly comprise multilayer tissues, and even if microscopes can reach the needed depth, their geometry hinders the selection and subsequent analysis of the optical volumes of interest. Computational tools to “peel” tissues by removing specific layers and reducing 3D volume into planar images, can critically improve visualization and analysis. Results We developed VolumePeeler, a versatile FIJI plugin for virtual 3D “peeling” of image stacks. The plugin implements spherical and spline surface projections. We applied VolumePeeler to perform peeling in 3D images of spherical embryos, as well as non-spherical tissue layers. The produced images improve the 3D volume visualization and enable analysis and quantification of geometrically challenging microscopy datasets. Availability ImageJ/FIJI software, source code, examples, and tutorials are openly available in https://cimt.uchile.cl/mcerda