Leveraging Anticipation to Investigate Proactive and Reactive Balance Responses with Clinical Applications in Aging and Dementia with Lewy Bodies

Falls pose a significant threat to our older adult population, as they are the leading cause of fatal and nonfatal injuries. Thus, falls are costly to both the individual and society, as fall-related injuries lead to reduced independence and decreased quality of life and cost roughly $80 billion annually. With our aging population rapidly growing, the rate of injurious falls is also expected to increase. Cognitive decline, such as Dementia with Lewy Bodies (DLB), only further increases these risks due to reduced executive functioning and parkinsonian symptoms affecting balance. Only by understanding the effects of aging and DLB on balance control can we better inform the design of clinical interventions, assistive devices, and wearable sensors to improve balance, monitor and detect instability, and mitigate the risk of falling in these populations. The purpose of this dissertation was to investigate age- and dementia-related differences in two aspects of multi-scale balance control – proactive adjustments and reactive responses – in the face of walking balance challenges, while also improving the clinical translation of wearable sensors to measure and detect instability in patient populations. In my first study, I found that anticipation of a balance perturbation does not affect younger adults’ whole-body balance response, suggesting that those with a healthy, intact nervous system may feel confident in their reactive balance responses. My second study quantified these younger adults’ distal leg muscle neuromechanics during walking balance challenges, alluding to direction-dependent proactive adjustments of distal agonist leg muscles, with anticipation allowing for greater force responsiveness when disrupted by a perturbation. My third study quantified age-related differences in distal leg neuromechanics and their role in governing whole-body stability in the face of balance challenges. I found that older adults fail to deploy effective proactive adjustments in anticipating a balance perturbation and deploy larger but less effective reactive responses and exhibit worsened stability during balance recovery. My fourth study demonstrates the feasibility of deploying treadmill-induced balance perturbations during walking in individuals with DLB and found that these individuals exhibit worse reactive responses, but not worse proactive adjustments, compared to matched controls. Finally, my fifth study sought to use a clinically-feasible sparse sensor set to generate synthetic data from a larger set of sensors necessary for WBAM estimation in individuals with DLB. My results suggest that a sparse sensor set may be deployed in a clinical setting and reduce the burden for both clinicians and patients. Collectively, these findings provide pivotal insights into age- and dementia-related changes in proactive and reactive walking balance while showing promise for wearable sensors to be integrated into clinical practice for monitoring and diagnosis of balance impairments in individuals with dementia.