Physical Activity, Central Adiposity, and Functional Limitations in Community-Dwelling Older Adults.

BACKGROUND AND PURPOSE: Obesity and physical inactivity are independently associated with physical and functional limitations in older adults. The current study examines the impact of physical activity on odds of physical and functional limitations in older adults with central and general obesity. METHODS: Data from 6279 community-dwelling adults aged 60 years or more from the Health and Retirement Study 2006 and 2008 waves were used to calculate prevalence and odds of physical and functional limitation among obese older adults with high waist circumference (waist circumference ≥88 cm in females and ≥102 cm in males) who were physically active versus inactive (engaging in moderate/vigorous activity less than once per week). Logistic regression models were adjusted for age, sex, race/ethnicity, education, smoking status, body mass index, and number of comorbidities. RESULTS: Physical activity was associated with lower odds of physical and functional limitations among older adults with high waist circumference (odds ratio [OR], 0.59; confidence interval [CI], 0.52-0.68, for physical limitations; OR, 0.52; CI, 0.44-0.62, for activities of daily living; and OR, 0.44; CI, 0.39-0.50, for instrumental activities of daily living). CONCLUSIONS: Physical activity is associated with significantly lower odds of physical and functional limitations in obese older adults regardless of how obesity is classified. Additional research is needed to determine whether physical activity moderates long-term physical and functional limitations.

Adaptive Brain-Computer Interface Systems For Communication in People with Severe Neuromuscular Disabilities

Brain-computer interfaces (BCI) have the potential to restore communication or control abilities in individuals with severe neuromuscular limitations, such as those with amyotrophic lateral sclerosis (ALS). The role of a BCI is to extract and decode relevant information that conveys a user's intent directly from brain electro-physiological signals and translate this information into executable commands to control external devices. However, the BCI decision-making process is error-prone due to noisy electro-physiological data, representing the classic problem of efficiently transmitting and receiving information via a noisy communication channel.

This research focuses on P300-based BCIs which rely predominantly on event-related potentials (ERP) that are elicited as a function of a user's uncertainty regarding stimulus events, in either an acoustic or a visual oddball recognition task. The P300-based BCI system enables users to communicate messages from a set of choices by selecting a target character or icon that conveys a desired intent or action. P300-based BCIs have been widely researched as a communication alternative, especially in individuals with ALS who represent a target BCI user population. For the P300-based BCI, repeated data measurements are required to enhance the low signal-to-noise ratio of the elicited ERPs embedded in electroencephalography (EEG) data, in order to improve the accuracy of the target character estimation process. As a result, BCIs have relatively slower speeds when compared to other commercial assistive communication devices, and this limits BCI adoption by their target user population. The goal of this research is to develop algorithms that take into account the physical limitations of the target BCI population to improve the efficiency of ERP-based spellers for real-world communication.

In this work, it is hypothesised that building adaptive capabilities into the BCI framework can potentially give the BCI system the flexibility to improve performance by adjusting system parameters in response to changing user inputs. The research in this work addresses three potential areas for improvement within the P300 speller framework: information optimisation, target character estimation and error correction. The visual interface and its operation control the method by which the ERPs are elicited through the presentation of stimulus events. The parameters of the stimulus presentation paradigm can be modified to modulate and enhance the elicited ERPs. A new stimulus presentation paradigm is developed in order to maximise the information content that is presented to the user by tuning stimulus paradigm parameters to positively affect performance. Internally, the BCI system determines the amount of data to collect and the method by which these data are processed to estimate the user's target character. Algorithms that exploit language information are developed to enhance the target character estimation process and to correct erroneous BCI selections. In addition, a new model-based method to predict BCI performance is developed, an approach which is independent of stimulus presentation paradigm and accounts for dynamic data collection. The studies presented in this work provide evidence that the proposed methods for incorporating adaptive strategies in the three areas have the potential to significantly improve BCI communication rates, and the proposed method for predicting BCI performance provides a reliable means to pre-assess BCI performance without extensive online testing.

Migration and Perception of Health Status: a Qualitative Study in Kazakh Chinese

This qualitative study explored the rural to urban migration’s effect and its related factors on later life health status and health perception among Kazakh Chinese. The participants were same sex sibling pairs, of which one moved from rural to urban areas in early life and the other stayed in rural areas. Rural participants tend to have more selected chronic diseases conditions and other self-reported conditions than urban participants but less physical limitations in older age. There is no clear difference on the health perceptions between rural and urban participants. Health care access and environmental factors are the major differences that may affect health in later life for rural participants.