Serious games for rehabilitation using head-mounted display and haptic devices

In the health domain, the field of rehabilitation suffers from a lack specialized staff while hospital costs only increase. Worse, almost no tools are dedicated to motivate patients or help the personnel to carry out monitoring of therapeutic exercises. This paper demonstrates the high potential that can bring the virtual reality with a platform of serious games for the rehabilitation of the legs involving a head-mounted display and haptic robot devices. We first introduce SG principles and the current context regarding rehabilitation interventions followed by the description of an original haptic device called Lambda Health System. The architecture of the model is then detailed, including communication specifications showing that lag is imperceptible for user (60Hz). Finally, four serious games for rehabilitation using haptic robots and/or HMD were tested by 33 health specialists.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.