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Depth information is important for postural stability and is generated by two visual systems: binocular and motion parallax. The effect of each type of parallax on postural stability remains unclear. We investigated the effects of binocular and motion parallax loss on static postural stability using a virtual reality (VR) system with a head-mounted display (HMD). A total of 24 healthy young adults were asked to stand still on a foam surface fixed on a force plate. They wore an HMD and faced a visual background in the VR system under four visual test conditions: normal vision (Control), absence of motion parallax (Non-MP)/binocular parallax (Non-BP), and absence of both motion and binocular parallax (Non-P). The sway area and velocity in the anteroposterior and mediolateral directions of the center-of-pressure displacements were measured. All postural stability measurements were significantly higher under the Non-MP and Non-P conditions than those under the Control and Non-BP conditions, with no significant differences in the postural stability measurements between the Control and Non-BP conditions. In conclusion, motion parallax has a more prominent effect on static postural stability than binocular parallax, which clarifies the underlying mechanisms of postural instability and informs the development of rehabilitation methods for people with visual impairments. [ABSTRACT FROM AUTHOR]

Background: People with from Parkinson's disease (PD) and freezing of gait (FoG) have more frequent falls compared to those who do not freeze but there is no consensus on which, specific objective measures of postural instability are worse in freezers (PD + FoG) than non-freezers (PD-FoG).Research Question: Are functional limits of stability (fLoS) or postural sway during stance measured with wearable inertial sensors different between PD + FoG versus PD-FoG, as well as between PD versus healthy control subjects (HC)?Methods: Sixty-four PD subjects with FoG (MDS-UPDRS Part III: 45.9 ± 12.5) and 80 PD subjects without FoG (MDS-UPDRS Part III: 36.2 ± 10.9) were tested Off medication and compared with 79 HC. Balance was quantified with inertial sensors worn on the lumbar spine while performing the following balance tasks: 1) fLoS as defined by the maximum displacement in the forward and backward directions and 2) postural sway area while standing with eyes open on a firm and foam surface. An ANOVA, controlling for disease duration, compared postural control between groups.Results: PD + FoG had significantly smaller fLoS compared to PD-FoG (p =  0.004) and to healthy controls (p <  0.001). However, PD-FoG showed similar fLoS compared to healthy controls (p =  0.48). Both PD+FoG and PD-FoG showed larger postural sway on a foam surface compared to healthy controls (p =  0.001) but there was no significant difference in postural sway between PD+FoG and PD-FoG.Significance: People with PD and FoG showed task-specific, postural impairments with smaller fLoS compared to non-freezers, even when controlling for disease duration. However, individuals with PD with or without FoG had similar difficulties standing quietly on an unreliable surface compared to healthy controls. Wearable inertial sensors can reveal worse fLoS in freezers than non-freezers that may contribute to FoG and help explain their more frequent falls. [ABSTRACT FROM AUTHOR]

Background: Balance deficits in people with Parkinson's disease (PD) are often not helped by pharmacological or surgical treatment. Although balance exercise intervention has been shown to improve clinical measures of balance, the efficacy of exercise on different, objective balance domains is still unknown. Objective: To compare the sensitivity to change in objective and clinical measures of several different domains of balance and gait following an Agility Boot Camp with Cognitive Challenges (ABC-C) intervention. Methods: In this cross-over, randomized design, 86 individuals with PD participated in 6-week (3×/week) ABC-C exercise classes and 6-week education classes, consisting of 3–6 individuals. Blinded examiners tested people in their practical off state. Objective outcome measures from wearable sensors quantified four domains of balance: sway in standing balance, anticipatory postural adjustments (APAs) during step initiation, postural responses to the push-and-release test, and a 2-min natural speed walk with and without a cognitive task. Clinical outcome measures included the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III, the Mini Balance Evaluation Systems Test (Mini-BESTest), the Activities of Balance Confidence (ABC), and the Parkinson's Disease Questionnaire (PDQ-39). The standardized response means (SRM) of the differences between before and after each intervention compared responsiveness of outcomes to intervention. A linear mixed model compared effects of exercise with the active control—education intervention. Results: The most responsive outcome measures to exercise intervention with an SRM > 0.5 were objective measures of gait and APAs, specifically arm range of motion, gait speed during a dual-task walk, trunk coronal range of motion, foot strike angle, and first-step length at step initiation. The most responsive clinical outcome measure was the patient-reported PDQ-39 activities daily living subscore, but all clinical measures had SRMs <0.5. Conclusions: The objective measures were more sensitive to change after exercise intervention compared to the clinical measures. Spatiotemporal parameters of gait, including gait speed with a dual task, and APAs were the most sensitive objective measures, and perceived functional independence was the most sensitive clinical measure to change after the ABC-C exercise intervention. Future exercise intervention to improve gait and balance in PD should include objective outcome measures. [ABSTRACT FROM AUTHOR]

This study aimed to determine the most sensitive objective measures of balance dysfunction that differ between people with Parkinson's Disease (PD) and healthy controls. One-hundred and forty-four people with PD and 79 age-matched healthy controls wore eight inertial sensors while performing tasks to measure five domains of balance: standing posture (Sway), anticipatory postural adjustments (APAs), automatic postural responses (APRs), dynamic posture (Gait) and limits of stability (LOS). To reduce the initial 93 measures, we selected uncorrelated measures that were most sensitive to PD. After applying a threshold on the Standardized Mean Difference between PD and healthy controls, 44 measures remained; and after reducing highly correlated measures, 24 measures remained. The four most sensitive measures were from APAs and Gait domains. The random forest with 10-fold cross-validation on the remaining measures (n = 24) showed an accuracy to separate PD from healthy controls of 82.4%—identical to result for all measures. Measures from the most sensitive domains, APAs and Gait, were significantly correlated with the severity of disease and with patient-related outcomes. This method greatly reduced the objective measures of balance to the most sensitive for PD, while still capturing four of the five domains of balance. [ABSTRACT FROM AUTHOR]