An open-source low-cost wireless sensor system for acquisition of human movement data.

Several fields of research such as medicine, robotics, sports, informatics, etc., require the analysis of human movement. Traditional systems for acquisition and analysis of human movement data are based on video cameras or active sensors. However, those systems are limited to high-resource settings. Wearable devices allow monitoring subjects outside typical clinical or research environments. Here, we present an open source low-cost wireless sensor system for acquisition of human movement data. Our system consists of two main parts: a server that stores data and, one or more wearable sensor modules that collect movement data through Inertial Measurement Units (IMUs) and transmit them wirelessly to the server. As a proof of concept, we measured human gait activity. Our results show that our system with IMUs can acquire quantifiable movement data. Characteristics such as open source code and its low-cost, make our system a viable alternative for clinical or research.

Analixity: An open source, low-cost analysis system for the elevated plus maze test, based on computer vision techniques.

Manual analysis of behavioral tests in rodents involves inspection of video recordings by a researcher that assesses rodent movements to quantify parameters related with a behavior of interest. The assessment of the researcher during the quantification of such parameters can introduce variability among experimental conditions or among sessions of analysis. Here, we introduce Analixity, a video processing software for the elevated plus maze test (EPM), in which quantification of behavioral parameters is automatic, reducing the time spent in analysis and solving the variability problem. Analixity is an adaptable multiplatform open-source system. Analixity generates an Excel file with the quantified behavioral variables, such as time spent in open and closed arms and in the center zone, number of entries to each zone and total distance traveled during the test. For validation, we compared results obtained by Analixity with results obtained by manual analysis. We did not find statistically significant differences. In addition, we compared the results obtained by Analixity with results obtained by the commercial software ANY-maze. We did not find statistically significant differences in the quantification of parameters such as time spent in open arms, time spent in closed arms, time spent in center zone, number of closed arms, open arms entries, and anxiety index. We concluded that Analixity is an open-source software as reliable and effective as a commercial software.