| dc.description.abstract | Maintaining balance is essential for daily activities and overall health. However, balance capability often declines with age or due to health conditions such as stroke, increasing fall risk. Falls among older adults are a major public health concern, affecting 14 million older adults annually in the US and directly causing over 40,000 deaths. Timely and accurate assessment of balance impairment is crucial to prevent falls and promote independence. Current assessments rely heavily on subjective therapist evaluations, underscoring the need for objective, quantitative methods. With the growing strain on healthcare systems due to an aging population, continuous at-home balance monitoring is also increasingly important. Additionally, a comprehensive understanding of the motor control mechanisms that deteriorate with aging or disease is crucial for informing therapy methods and technologies.
The goal of this thesis was to develop and validate methods that quantify quiet balance ability and control in unimpaired and impaired human participants. The first part focuses on assessing balance ability, the capacity to maintain upright posture during quiet stance that is currently often quantified by measures of body sway. A review of the strengths and limitations of current clinical and instrumented balance assessments highlighted a critical need for continuous assessment methods that enable objective monitoring of balance function outside of clinical settings. Addressing this need, a novel algorithm that quantifies balance ability using only force and motion sensors embedded in an instrumented cane was developed. Well-established balance measures were successfully estimated in both younger and older adults, demonstrating the proposed method's potential to facilitate continuous balance monitoring in real-world environments.
The next part focuses on identifying balance control strategies. The novel intersection-point analysis, based on foot-force direction and point of application, was used in conjunction with a simple biomechanical model and an optimal controller to quantify balance control. The first study demonstrated that unimpaired quiet balance in a challenging environment was best described by a controller that maintained minimal effort by adjusting relative ankle and hip joint torques. Applying this method to aging populations in a subsequent study revealed that older adults rely more on neural feedback, possibly to compensate for muscle strength deficiency. This study also quantified individual balance controllers, highlighting the method's potential as a diagnostic tool for aging populations. Finally, the model was extended to describe balance control after stroke. The results suggest that the non-paretic limb compensated for the paretic limb's abnormal coordination pattern by strongly favoring neural feedback. As one of the first studies to model quiet balance after stroke, this work lays the foundation for future efforts on studying balance impairments. The contributions of this thesis are instrumental to enhancing at-home monitoring, advancing clinical practices, and reducing fall-related injuries, ultimately improving quality of life for aging and neurologically impaired populations. | |
