BackgroundPrevious evidence indicates that older people allocate more of their attentional resources toward their gait and that the attention-related changes that occur during aging increase the risk of falls. The aim of this study was to investigate whether performance and variability in sustained attention is associated with falls and falls efficacy in older adults.Methods458 community-dwelling adults aged ≥ 60 years underwent a comprehensive geriatric assessment. Mean and variability of reaction time (RT), commission errors and omission errors were recorded during a fixed version of the Sustained Attention to Response Task (SART). RT variability was decomposed using the Fast Fourier Transform (FFT) procedure, to help characterise variability associated with the arousal and vigilance aspects of sustained attention.The number of self-reported falls in the previous twelve months, and falls efficacy (Modified Falls Efficacy Scale) were also recorded.ResultsSignificant increases in the mean and variability of reaction time on the SART were significantly associated with both falls (p < 0.01) and reduced falls efficacy (p < 0.05) in older adults. An increase in omission errors was also associated with falls (p < 0.01) and reduced falls efficacy (p < 0.05). Upon controlling for age and gender affects, logistic regression modelling revealed that increasing variability associated with the vigilance (top-down) aspect of sustained attention was a retrospective predictor of falling (p < 0.01, OR = 1.14, 95% CI: 1.03 - 1.26) in the previous year and was weakly correlated with reduced falls efficacy in non-fallers (p = 0.07).ConclusionsGreater variability in sustained attention is strongly correlated with retrospective falls and to a lesser degree with reduced falls efficacy. This cognitive measure may provide a novel and valuable biomarker for falls in older adults, potentially allowing for early detection and the implementation of preventative intervention strategies.

No abstract

No abstract

Resting fluctuations in the blood oxygenation level-dependent signal have attracted considerable interest for their sensitivity to pathological brain processes. However, these analyses are susceptible to confound by nonneural physiological factors such as vasculature, breathing, and head movement which is a concern when investigating elderly or pathological groups. Here, we used simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) (EEG/fMRI) to constrain the analysis of resting state networks (RSNs) and identify aging differences. Four of 26 RSNs showed fMRI and EEG/fMRI group differences; anterior default-mode network, left frontal-parietal network, bilateral middle frontal, and postcentral gyri. Seven RSNs showed only EEG/fMRI differences suggesting the combination of these 2 methods might be more sensitive to age-related neural changes than fMRI alone. Five RSNs showed only fMRI differences and might reflect nonneural group differences. Activity within some EEG/fMRI RSNs was better explained by neuropsychological measures (Mini Mental State Examination and Stroop) than age. These results support previous studies suggesting that age-related changes in specific RSNs are neural in origin, and show that changes in some RSNs relate better to elderly cognition than age.

This work presents an overview of the main strategies that have been proposed for non-invasive monitoring of heart rate (HR) in extramural and home settings. We discuss three categories of sensing according to what physiological effect is used to measure the pulsatile activity of the heart, and we focus on an illustrative sensing modality for each of them. Therefore, electrocardiography, photoplethysmography, and mechanocardiography are presented as illustrative modalities to sense electrical activity, mechanical activity, and the peripheral effect of heart activity. In this paper, we describe the physical principles underlying the three categories and the characteristics of the different types of sensors that belong to each class, and we touch upon the most used software strategies that are currently adopted to effectively and reliably extract HR. In addition, we investigate the strengths and weaknesses of each category linked to the different applications in order to provide the reader with guidelines for selecting the most suitable solution according to the requirements and constraints of the application.