BackgroundFew data are available on the prevalence of cognitive impairment (CI) in Spain, and the existing information shows important variations depending on the geographical setting and the methodology employed. The aim of this study was to determine the prevalence of CI in individuals aged over 65 in an urban area, and to analyze its associated risk factors.MethodsDesign: A descriptive, cross-sectional, home questionnaire-based study; Setting: Populational, urban setting. Participants: The reference population comprised over-65s living in the city of Salamanca (Spain) in 2009. Randomized sampling stratified according to health district was carried out, and a total of 480 people were selected. In all, 327 patients were interviewed (68.10%), with a mean age of 76.35 years (SD: 7.33). Women accounted for 64.5% of the total. Measurements: A home health questionnaire was used to obtain the following data: age, sex, educational level, family structure, morbidity and functionality. All participants completed a neuropsychological test battery. The prevalence data were compared with those of the European population, with direct adjustment for age and sex. Diagnoses were divided into three general categories: normal cognitive function, cognitive impairment - no dementia (CIND), and dementia.ResultsThe prevalence of CI among these over-65s was 19% (14.7% CIND and 4.3% dementia). The age-and sex-adjusted global prevalence of CI was 14.9%. CI increased with age (p < 0.001) and decreased with increasing educational level (p < 0.001). Significant risk factors were found with the multivariate analyses: age (OR = 1.08, 95%CI: 1.03-1.12), anxiety-depression (OR = 3.47, 95%CI: 1.61-7.51) and diabetes (OR = 2.07, 95%CI: 1.02-4.18). In turn, years of education was found to be a protective factor (OR = 0.79, 95%CI: 0.70-0.90). Although CI was more frequent among women and in people living without a partner, these characteristics were not significantly associated with CI risk.ConclusionsThe observed raw prevalence of CI was 19% (14.9% after adjusting for age and sex). Older age and the presence of diabetes and anxiety-depression increased the risk of CI, while higher educational level reduced the risk.

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Objective: The aim of this paper was to compare the performance of a group of patients with early Alzheimer’s disease (EAD) against a control group of healthy control (HC) subjects in the Clock Drawing Test (CDT), i.e. verbal command versus copying of a clock model presented to the subject. Patients and Methods: The authors have studied 140 subjects; 70 patients with probable EAD, with a mean age of 76.4 ± 7.64 years and a clinical dementia rating stage 1 (mild dementia), and70 HC with a mean age of 75.16 ± 6.34 years. Results: Patients in the EAD group obtained significantly higher scores on the copy command mode than on the verbal command mode (Z = –7.129, p < 0.001) – improvement pattern of the CDT – whereas no statistically significant differences were found in the HC group (Z = –2.001, p < 0.080). Within the group of EAD patients, we have noticed that there is a correlation between the copy command mode and the visual-constructive functions of the Cambridge Cognitive Examination (CAMCOG) (r = 0.607, p < 0.01), while the memory functions of the CAMCOG correlate with the verbal command mode (r = 0.704, p < 0.01). Conclusions: In our study, the EAD patients show an improvement pattern in the execution of the CDT copy command in comparison with the execution of the CDT verbal command, which we did not observe in the HC group. Such results might be associated with a greater deterioration of the memory functions when compared with the visual-constructive ones in the patients with EAD.

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This paper describes a method for estimating the vehicle global position in a network of roads by means of visual odometry. To do so, the ego-motion of the vehicle relative to the road is computed using a stereo-vision system mounted next to the rear view mirror of the car. Feature points are matched between pairs of frames and linked into 3D trajectories. Vehicle motion is estimated using the non-linear, photogrametric approach based on RANSAC. This iterative technique enables the formulation of a robust method that can ignore large numbers of outliers as encountered in real traffic scenes. The resulting method is defined as visual odometry and can be used in conjunction with other sensors, such as GPS, to produce accurate estimates of the vehicle global position. The obvious application of the method is to provide on-board driver assistance in navigation tasks, or to provide a means for autonomously navigating a vehicle. The method has been tested in real traffic conditions without using prior knowledge about the scene nor the vehicle motion. We provide examples of estimated vehicle trajectories using the proposed method and discuss the key issues for further improvement.