Effect of Aging on Human Postural Control and the Interaction with Attention

The ability to stand upright and walk is generally taken for granted, yet control of balance utilizes many processes involving the neuromuscular and sensory systems. As we age, balance function begins to decline and can become problematic for many older adults. In particular, adults 65 years of age and older exhibit a higher incidence of falls than younger adults, and falls are a leading cause of injury in older adults, contributing to significant medical costs. Without better understanding of the impact of aging on balance and means to ameliorate those effects, this problem is expected to grow as life expectancy continues to increase. In addition to sensori-motor declines with age that impact balance, another factor known to affect balance, particularly in older adults, is attention, meaning the amount of cognitive resources utilized for a particular task. When two or more tasks vie for cognitive resources, performance in one or more tasks can be compromised (a common example today is driving while talking on a cell phone). Attention has been observed to be a critical factor in many falls reported by older adults. However, it is still not fully understood how aging and attentional demand affect balance and how they interact with each other. In this dissertation, we conducted dual-task experiments and model-based analyses to study upright standing and the interaction of the effects of age and attention on postural control. The effect of age was investigated by testing two age groups (young and older adults) with no iv evident balance and cognitive impairment and by comparing results of the two groups. The effect of attention and its interaction with age was studied by comparing body sway in the two age groups in response to a moving platform, while either concurrently performing a cognitive task (dual-task) or not (single-task). Our findings highlight postural control differences between young and older adults, as quantified by experimental measures of body motion as well as by model parameter values, such as stiffness, damping and processing delay. Table 1. Summary of anthropometric data from the subjects included in the study. – ML sway 21