This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control.

Compared to young adults, older adults walk with smaller propulsive forces and a redistribution to more proximal leg muscles for power generation during push-off. Despite this deficit in propulsive function, older adults can increase push-off intensity when encouraged to via real-time biofeedback. However, the specific joint-level modifications used by older adults to enhance propulsive force generation has yet to be elucidated. The purpose of this study was to identify the joint-level modifications used by young and older adults to modulate propulsive forces when walking at their preferred speed. 9 young and 16 older adults walked at their preferred speed while visual biofeedback prompted them to modulate their propulsive forces using targets prescribed at ±10% and ±20% of their preferred value. Older adults were then divided into groups exhibiting relatively larger or smaller baseline redistribution to more proximal leg muscles for power generation. Neither young nor either older adult cohort modulated propulsive forces by altering their peak ankle power generation. Instead, subjects increased trailing limb extension and attenuated mechanical power demands at the hip during push-off. Older adults that had a larger baseline redistribution exhibited larger responses to enhanced push-off intensity than their peers–for example, walking with 11% less hip flexor power and 10% more trailing limb extension during push-off when exerting larger than preferred propulsive forces. Propulsive force biofeedback that elicits larger than preferred propulsive forces also increases trailing limb extension and attenuates mechanical power demands at the hip in older adults most exhibiting a distal-to-proximal redistribution. Our results suggest that considering baseline redistribution may be important in the personalized prescription of interventions aimed at enhancing walking performance by improving push-off intensity.

The Achilles tendon (AT) moment arm is an important determinant of ankle moment and power generation during locomotion. Load and depth-dependent variations in the AT moment arm are generally not considered, but may be relevant given the complex triceps surae architecture. We coupled motion analysis and ultrasound imaging to characterize AT moment arms during walking in 10 subjects. Muscle loading during push-off amplified the AT moment arm by 10% relative to heel strike. AT moment arms also varied by 14% over the tendon thickness. In walking, AT moment arms are not strictly dependent on kinematics, but exhibit important load and spatial dependencies.