Impairments of gait and balance often progress through the course of dementia, and are associated with increased risk of falls.
This systematic review provides a critical analysis of the evidence ...linking quantitative measures of gait and balance to fall risk in older adults with dementia. Various instrumented measures of gait and postural stability including gait speed and non-instrumented performance measures including Timed Up and Go were shown to be capable of distinguishing fallers from non-fallers. Key Messages: Existing reviews indicate that impairments of gait and balance are associated with increased risk of falls in cognitively intact older people. There are inconsistencies, however, regarding the characteristics most predictive of a fall. In order to advance fall prevention efforts, there is an important need to understand the relationship between gait, balance, and fall risk, particularly in high-risk populations such as individuals with dementia.
To identify components of postural control included in standardized balance measures for adult populations.
Electronic searches of MEDLINE, EMBASE, and CINAHL databases using keyword combinations of ...postural balance/equilibrium, psychometrics/reproducibility of results/predictive value of tests/validation studies, instrument construction/instrument validation, geriatric assessment/disability evaluation, gray literature, and hand searches.
Inclusion criteria were measures with a stated objective to assess balance, adult populations (18y and older), at least 1 psychometric evaluation, 1 standing task, a standardized protocol and evaluation criteria, and published in English. Two reviewers independently identified studies for inclusion. Sixty-six measures were included.
A research assistant extracted descriptive characteristics and 2 reviewers independently coded components of balance in each measure using the Systems Framework for Postural Control, a widely recognized model of balance.
Components of balance evaluated in these measures were underlying motor systems (100% of measures), anticipatory postural control (71%), dynamic stability (67%), static stability (64%), sensory integration (48%), functional stability limits (27%), reactive postural control (23%), cognitive influences (17%), and verticality (8%). Thirty-four measures evaluated 3 or fewer components of balance, and 1 measure—the Balance Evaluation Systems Test—evaluated all components of balance.
Several standardized balance measures provide only partial information on postural control and omit important components of balance related to avoiding falls. As such, the choice of measure(s) may limit the overall interpretation of an individual's balance ability. Continued work is necessary to increase the implementation of comprehensive balance assessment in research and practice.
Measures of gait center of pressure (COP) can be recorded using simple available technologies in clinical settings and thus can be used to characterize gait quality in older adults and its ...relationship to falls. The aim of this systematic review was to investigate the association between measures of gait COP and aging and falls. A comprehensive search of electronic databases including MEDLINE, Embase, Cochrane Central Register of Controlled Trials, CINAHL (EBSCO), Ageline (EBSCO) and Scopus was performed. The initial search yielded 2809 papers. After removing duplicates and applying study inclusion/exclusion criteria, 34 papers were included in the review. Gait COP has been examined during three tasks: normal walking, gait initiation, and obstacle negotiation. The majority of studies examined mean COP position and velocity as outcome measures. Overall, gait in older adults was characterized by more medial COP trajectory in normal walking and lower average anterior-posterior and medio-lateral COP displacements and velocity in both gait initiation and obstacle crossing. Moreover, findings suggest that Tai chi training can enhance older adults' balance control during gait initiation as demonstrated by greater COP backward, medial and forward shift in all three phases of gait initiation. These findings should be interpreted cautiously due to inadequacy of evidence as well as methodological limitations of the studies such as small sample size, limited numbers of ‘fallers’, lack of a control group, and lack of interpretation of COP outcomes with respect to fall risk. COP measures can be adopted to assess fall-related gait changes in older adults but more complex measures of COP that reveal the dynamic nature of COP behavior in step-to-step variations are needed to adequately characterize gait changes in older adults.
•A review was done to examine how COP was characterized in older adults' walking.•Gait COP is examined during normal walking, gait initiation, and obstacle crossing.•Mean COP position and velocity were the most common COP measures.
Advances in our understanding of postural control have highlighted the need to examine the influence of higher brain centers in the modulation of this complex function. There is strong evidence of a ...link between emotional state, autonomic nervous system (ANS) activity and somatic nervous system (somatic NS) activity in postural control. For example, relationships have been demonstrated between postural threat, anxiety, fear of falling, balance confidence, and physiological arousal. Behaviorally, increased arousal has been associated with changes in velocity and amplitude of postural sway during quiet standing. The potential links between ANS and somatic NS, observed in control of posture, are associated with shared neuroanatomical connections within the central nervous system (CNS). The influence of emotional state on postural control likely reflects the important influence the limbic system has on these ANS/somatic NS control networks. This narrative review will highlight several examples of behaviors which routinely require coordination between the ANS and somatic NS, highlighting the importance of the neurofunctional link between these systems. Furthermore, we will extend beyond the more historical focus on threat models and examine how disordered/altered emotional state and ANS processing may influence postural control and assessment. Finally, this paper will discuss studies that have been important in uncovering the modulatory effect of emotional state on postural control including links that may inform our understanding of disordered control, such as that observed in individuals living with Parkinson’s disease and discuss methodological tools that have the potential to advance understanding of this complex relationship.
•We examine learning for postural responses critical to fall avoidance.•Learning is demonstrated using rates and retention of performance improvements.•Impaired posture control does not preclude ...learning of automatic postural responses.•A shift from feedback toward anticipatory control drives performance improvements.
Although balance training is considered the most effective treatment for balance impairments in Parkinson’s disease (PD), few studies have examined if learning for balance control remains intact with PD. This study aimed to determine if learning for automatic postural responses is preserved in people with PD.
Eleven participants with moderate PD (68±6.4years; H&Y: 2–3) on their usual medication maintained balance on a platform that oscillated forward and backward with variable amplitude and constant frequency. Participants completed 42 trials during one training session, and retention and transfer tests following a 24-h delay. Performance was measured by comparing spatial and temporal measures of whole-body centre of mass (COM) with platform displacements. Learning was compared between participants with PD and previously reported, age-matched older adults (Van Ooteghem et al., 2010).
Although postural responses in participants with PD were impaired compared to control participants, a majority of PD participants improved their postural responses with practice as revealed by reduced COM displacements and improved phase relationships between COM and platform motion. Rates of improvement were comparable between groups demonstrating preserved adaptive capacity for participants with PD. Similar to control participants, the PD group moved toward anticipatory COM control as a strategy for improving stability, exhibited short-term retention of performance improvements, and demonstrated generalizability of the learned responses. Rate of improvement with practice, but not retention, was related to severity of motor impairments.
Patients with moderate PD on medication demonstrate retention of improvements in automatic postural responses with practice suggesting that intrinsic postural motor learning is preserved in this group.
Background and purpose
The pathophysiology of Parkinson's disease (PD) negatively affects brain network connectivity, and in the presence of brain white matter hyperintensities (WMHs) cognitive and ...motor impairments seem to be aggravated. However, the role of WMHs in predicting accelerating symptom worsening remains controversial. The objective was to investigate whether location and segmental brain WMH burden at baseline predict cognitive and motor declines in PD after 2 years.
Methods
Ninety‐eight older adults followed longitudinally from Ontario Neurodegenerative Diseases Research Initiative with PD of 3–8 years in duration were included. Percentages of WMH volumes at baseline were calculated by location (deep and periventricular) and by brain region (frontal, temporal, parietal, occipital lobes and basal ganglia + thalamus). Cognitive and motor changes were assessed from baseline to 2‐year follow‐up. Specifically, global cognition, attention, executive function, memory, visuospatial abilities and language were assessed as were motor symptoms evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III, spatial–temporal gait variables, Freezing of Gait Questionnaire and Activities Specific Balance Confidence Scale.
Results
Regression analysis adjusted for potential confounders showed that total and periventricular WMHs at baseline predicted decline in global cognition (p < 0.05). Also, total WMH burden predicted the decline of executive function (p < 0.05). Occipital WMH volumes also predicted decline in global cognition, visuomotor attention and visuospatial memory declines (p < 0.05). WMH volumes at baseline did not predict motor decline.
Conclusion
White matter hyperintensity burden at baseline predicted cognitive but not motor decline in early to mid‐stage PD. The motor decline observed after 2 years in these older adults with PD is probably related to the primary neurodegenerative process than comorbid white matter pathology.
Background
Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear ...may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD).
Methods
Thirty-nine participants with CVD, Alzheimer’s disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson’s disease, or amyotrophic lateral sclerosis (median age 68 (45–83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance.
Results
Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17–22 min/day), with significant differences between some locations (
p
= 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (
p
< 0.001) and there was a small but significant increase in non-wear over the collection period (
p
= 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners.
Conclusion
A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.
Accelerometery is commonly used to estimate physical activity, sleep, and sedentary behavior. In free-living conditions, periods of device removal (non-wear) can lead to misclassification of behavior ...with consequences for research outcomes and clinical decision making. Common methods for non-wear detection are limited by data transformations (e.g., activity counts) or algorithm parameters such as minimum durations or absolute temperature thresholds that risk over- or under-estimating non-wear time. This study aimed to advance non-wear detection methods by integrating a 'rate-of-change' criterion for temperature into a combined temperature-acceleration algorithm.
Data were from 39 participants with neurodegenerative disease (36% female; age: 45-83 years) who wore a tri-axial accelerometer (GENEActiv) on their wrist 24-h per day for 7-days as part of a multi-sensor protocol. The reference dataset was derived from visual inspection conducted by two expert analysts. Linear regression was used to establish temperature rate-of-change as a criterion for non-wear detection. A classification and regression tree (CART) decision tree classifier determined optimal parameters separately for non-wear start and end detection. Classifiers were trained using data from 15 participants (38.5%). Outputs from the CART analysis were supplemented based on edge cases and published parameters.
The dataset included 186 non-wear periods (85.5% < 60 min). Temperature rate-of-change over the first five minutes of non-wear was - 0.40 ± 0.17 °C/minute and 0.36 ± 0.21 °C/minute for the first five minutes following device donning. Performance of the DETACH (DEvice Temperature and Accelerometer CHange) algorithm was improved compared to existing algorithms with recall of 0.942 (95% CI 0.883 to 1.0), precision of 0.942 (95% CI 0.844 to 1.0), F1-Score of 0.942 (95% CI 0.880 to 1.0) and accuracy of 0.996 (0.994-1.000).
The DETACH algorithm accurately detected non-wear intervals as short as five minutes; improving non-wear classification relative to current interval-based methods. Using temperature rate-of-change combined with acceleration results in a robust algorithm appropriate for use across different temperature ranges and settings. The ability to detect short non-wear periods is particularly relevant to free-living scenarios where brief but frequent removals occur, and for clinical application where misclassification of behavior may have important implications for healthcare decision-making.
To identify measures of standing balance validated in pediatric populations, and to determine the components of postural control captured in each tool.
Electronic searches of MEDLINE, Embase, and ...CINAHL databases using key word combinations of postural balance/equilibrium, psychometrics/reproducibility of results/predictive value of tests, and child/pediatrics; gray literature; and hand searches.
Inclusion criteria were measures with a stated objective to assess balance, with pediatric (≤18y) populations, with at least 1 psychometric evaluation, with at least 1 standing task, with a standardized protocol and evaluation criteria, and published in English. Two reviewers independently identified studies for inclusion. There were 21 measures included.
Two reviewers extracted descriptive characteristics, and 2 investigators independently coded components of balance in each measure using a systems perspective for postural control, an established framework for balance in pediatric populations.
Components of balance evaluated in measures were underlying motor systems (100% of measures), anticipatory postural control (72%), static stability (62%), sensory integration (52%), dynamic stability (48%), functional stability limits (24%), cognitive influences (24%), verticality (9%), and reactive postural control (0%).
Assessing children's balance with valid and comprehensive measures is important for ensuring development of safe mobility and independence with functional tasks. Balance measures validated in pediatric populations to date do not comprehensively assess standing postural control and omit some key components for safe mobility and independence. Existing balance measures, that have been validated in adult populations and address some of the existing gaps in pediatric measures, warrant consideration for validation in children.
Abstract Background Recent technological advances have led to a surge in the use of wearable devices for personal health and fitness monitoring; however, clinical uptake of wearable devices for ...remote or ‘free-living’ measurement of daily health-related behavior has lagged. To advance the field, there is need for valid and reliable outcomes across multiple health domains specific to the cohorts or patients of interest and centralized tools to build capacity for use of these data. The NiMBaLWear pipeline provides a flexible and integrated approach to wearables analytics applied to raw sensor data that considers multiple, inter-related physiological and behavioral signals to provide a holistic view of health status. Results & discussion NiMBaLWear is a modular, open-source, wearable sensor analytic pipeline that quantifies physical activity, mobility, and sleep from raw single- or multi-sensor free-living data collected over multiple days. Data captured from any device, in different possible formats, are standardized prior to processing. Data preparation includes accelerometer autocalibration, cross-device synchronization, and non-wear detection. Validated, domain-specific algorithms detect events, generate outcome measures, and output standardized tabular data and user-friendly summary collection reports. NiMBaLWear was developed in Python using an iterative and incremental software development process, which included a combination of semi-automated inspection and expert review of data collected from 286 participants across two remote-measurement studies. A comparative analysis revealed a paucity of open-source packages capable of deriving and sharing health-related behavioral outcomes across multiple domains from multi-sensor wearables data. Forthcoming improvements to the pipeline will leverage sensor fusion techniques to add new, and refine existing, domain- and disease-specific analytics, and optimize pipeline accessibility and reporting. Conclusion The NiMBaLWear pipeline transforms raw multi-sensor wearables data into accurate and relevant outcomes across multiple health domains to objectively characterize and measure an individual’s daily health-related behavior. NiMBaLWear’s focus on high-quality, clinically relevant outcomes, as well as end-user optimization, provides a foundation for innovation to improve the utility of wearables for clinical care and self-management of health .
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