Background: After mild stroke persistent balance limitations may occur, creating a risk factor for fear of falling, falls, and reduced activity levels. Objective. To investigate whether individuals in the chronic phase after mild stroke show balance and gait limitations, elevated fall risk, reduced balance confidence, and physical activity levels compared to healthy controls. Methods: An observational case-control study was performed. Main outcomes included the Mini-Balance Evaluation Systems Test (mini-BEST), Timed Up and Go (TUG), 10-m Walking Test (10-MWT), and 6-item version Activity-specific Balance Confidence (6-ABC) scale which were measured in 1 session. Objectively measured daily physical activity was measured for 7 consecutive days. Fall rate in daily life was recorded for 12 months. Individuals after a mild stroke were considered eligible when they: (1) sustained a transient ischemic attack or stroke longer than 6 months ago, resulting in motor and/or sensory loss in the contralesional leg at the time of stroke, (2) showed (near-) complete motor function, that is, ≥24 points on the Fugl-Meyer Assessment—Lower Extremity (range: 0-28). Results: Forty-seven healthy controls and 70 participants after mild stroke were included. Participants with stroke fell more than twice as often as healthy controls, had a 2 point lower median score on the mini-BEST, were 1.7 second slower on TUG, 0.6 km/h slower on the 10-MWT, and had a 12% lower 6-ABC score. Intensity for both total activity (8%) as well as walking activity (6%) was lower in the participants with stroke, while no differences were found in terms of duration. Conclusions: Individuals in the chronic phase after a mild stroke demonstrate persistent balance limitations and have an increased fall risk. Our results point at an unmet clinical need in this population.

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The contributions of the cerebral cortex to human balance control are clearly demonstrated by the profound impact of cortical lesions on the ability to maintain standing balance. The cerebral cortex is thought to regulate subcortical postural centers to maintain upright balance and posture under varying environmental conditions and task demands. However, the cortical mechanisms that support standing balance remain elusive. Here, we present an EEG-based analysis of cortical oscillatory dynamics during the preparation and execution of balance responses with distinct postural demands. In our experiment, participants responded to backward movements of the support surface either with one forward step or by keeping their feet in place. To challenge the postural control system, we applied participant-specific high accelerations of the support surface such that the postural demand was low for stepping responses and high for feet-in-place responses. We expected that postural demand modulated the power of intrinsic cortical oscillations. Independent component analysis and time-frequency domain statistics revealed stronger suppression of alpha (9–13 Hz) and low-gamma (31–34 Hz) rhythms in the supplementary motor area (SMA) when preparing for feet-in-place responses (i.e., high postural demand). Irrespective of the response condition, support-surface movements elicited broadband (3–17 Hz) power increase in the SMA and enhancement of the theta (3–7 Hz) rhythm in the anterior prefrontal cortex (PFC), anterior cingulate cortex (ACC), and bilateral sensorimotor cortices (M1/S1). Although the execution of reactive responses resulted in largely similar cortical dynamics, comparison between the bilateral M1/S1 showed that stepping responses corresponded with stronger suppression of the beta (13–17 Hz) rhythm in the M1/S1 contralateral to the support leg. Comparison between response conditions showed that feet-in-place responses corresponded with stronger enhancement of the theta (3–7 Hz) rhythm in the PFC. Our results provide novel insights into the cortical dynamics of SMA, PFC, and M1/S1 during the control of human balance.

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The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control.@en