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We explore the association between quality of diet and food security status among older persons. Cross-sectional survey of large national samples, from the National Health & Nutrition Examination Surveys (1988Surveys ( -1994Surveys ( & 2001Surveys ( -2002, in the United States. A total of 5,039 and 2,040 men and women aged 60 and older, respectively. The dependent variable was the healthy eating index (HEI; as a measure of diet quality. The independent variable of interest was food security status and was categorized as food secure, food insecurity receiving food stamps and food insecurity not receiving food stamps. In multivariate analyses, food insecure individuals not receiving food stamps had lower total HEI-2000 scores compared to food secure individuals (b=-3.91, SE=1.81, P=0.0310). Factors independently associated with high HEI (2000 or 2005) scores were female gender, being married, highly educated or wealthy, with very good/ excellent perceived health, or without functional limitations. Food secure individuals had better quality of diet than food insecure individuals. Among food insecure individuals, receiving food stamps was not associated with diet quality. Food insecure families with older individuals may need new methods of dissemination of food and nutrition programs -methods that yield positive and promising changes in the health status of this special population group.

Balance disorders can have substantial adverse implications on the performance of daily activities and lead to an increased risk of falls, which often have severe negative consequences for older adults. Quantitative assessment through computerized force plate-based posturography enables objective assessment of postural control but could not successfully represent specific abilities required during daily activities. The use of virtual reality (VR) could improve the representative design of functional activities and increase the ecological validity of posturographic tests, which would enhance the transferability of results to the real world. In this work, we investigate the feasibility of a simulated bus ride experienced in a surround-screen VR system to assess balance with increased ecological validity. Participants were first evaluated with a posturography test, and then with the VR-based bus ride test while the reactions of their centre of pressure were registered. Lastly, participants provided self-reported measures of the elicited sense of presence during the test. A total of 16 healthy young adults completed the study. Results showed that the simulation could elicit significant medial-lateral excursions of the centre of pressure in response to variations in the optical flow. Furthermore, these responses' amplitude negatively correlated with the participants' posturography excursions when fixating a target. Although the sense of presence was moderate, likely due to the passive nature of the test, the results support the feasibility of our proposed paradigm, based in the context of a meaningful daily living activity, in assessing balance control components.

paper presents the evaluation and cross-validation of four pattern recognition classifiers, with the objective of finding the best one for classify surface electromyography (sEMG) signals combined with information extracted from videogame’s variables. The classifiers, a linear classifier, a quadratic classifier, a k-nearest-neighbor classifier, and a support vector machine, were computed on a data matrix created with the recorder signal collected from 12 subjects in a body interaction videogame that used a sEMG as a control strategy for upper limbs virtual rehabilitation. Although the classifiers of sEMG signal had a widespread study, there is not evidence of how to deal with the information of sEMG signals combined with game variables. The classification task is related with discern each subject as “good player” or “bad player”, looking to following the performance of the videogame’s users through the game sessions. A cross-validation of 10 iterations was computed, PCA and Relieff were used as feature extraction and selection methods. The evaluation was developed using the percentage of accuracy, defined as the well-predicted points. The best accuracy in the classification task was found using an SVM with a misclassification parameter of 400 and an RBF kernel regularization parameter of 60. Base on this result, the SVMs showed to be the appropriate classifier to be used on sEMG signal combined with videogame variables and should be implemented to follow the user’s performance.

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