Gait variability is associated with frailty in community-dwelling older adults

A Wrist-Worn Wearable Device Can Identify Frailty in Middle-Aged and Older Adults: The UK Biobank Study

OBJECTIVES

Digital gait biomarkers collected from body-worn devices can remotely and continuously collect movement types, quantity, and quality in real life. This study assessed whether digital gait biomarkers from a wrist-worn device could identify people with frailty in a large sample of middle-aged and older adults.

DESIGN

Cross-sectional study.

SETTING AND PARTICIPANTS

A total of 5822 middle-aged (43-64 years) and 4344 older adults (65-81 years) who participated in the UK Biobank study.

MEASURES

Frailty was assessed using a modified Fried's frailty assessment and was defined as having ≥3 of the 5 frailty criteria (weakness, low activity levels, slowness, exhaustion, and weight loss). Fourteen digital gait biomarkers were extracted from accelerometry data collected from wrist-worn sensors worn continuously by participants for up to 7 days.

RESULTS

A total of 238 (4.1%) of the middle-aged group and 196 (4.5%) of the older group were categorized as frail. Multivariable logistic regression analysis revealed that less daily walking (as assessed by step counts), slower maximum walking speed, and increased step time variability best-identified people with frailty in the middle-aged group [area under the curve (95% CI): 0.70 (0.66-0.73)]. Less daily walking, slower maximum walking speed, increased step time variability, and a lower proportion of walks undertaken with a manual task best-identified people with frailty in the older group [0.73 (0.69-0.76)].

CONCLUSIONS AND IMPLICATIONS

Our findings indicate that measures obtained from wrist-worn wearable devices worn in everyday life can identify individuals with frailty in both middle-aged and older people. These digital gait biomarkers may facilitate screening programs and the timely implementation of frailty-prevention interventions.

Force-sensing treadmill gait analysis system can detect gait abnormalities in haemophilia patients without arthropathy

BACKGROUND

Joint damage in patients with haemophilia (PwH) is commonly assessed by imaging, but few reports have described how structural changes in joints, for example, haemophilic arthropathy (HA)-affect gait ability.

OBJECTIVES

We evaluated gait function among PwH with HA, PwH without HA, and people without haemophilia (non-PwH) using a Zebris FDM-T treadmill (FDM-T), an easy-to-use gait assessment instrument with a force sensor matrix.

METHODS

The following gait parameters were collected: centre of pressure trajectory intersection (COPi) anterior/posterior variability, COPi lateral variability, COPi anterior/posterior symmetry, COPi lateral symmetry, single-limb support line (SLSL) length, and SLSL variability. Participants walked at their typical gait speed. The physical function of the PwH was assessed by the Hemophilia Joint Health Score (HJHS). Parameters were compared among the three groups.

RESULTS

Twelve PwH with HA, 28 PwH without HA, and 12 non-PwH were enrolled. Gait speed significantly differed between groups (non-PwH, 3.1 ± 0.7; PwH without HA, 2.0 ± 0.7; PwH with HA; 1.5 ± 0.4). The COPi anterior/posterior variability, COPi lateral variability, SLSL length, and SLSL variability were greater in the PwH groups than in the non-PwH group. The COPi lateral symmetry differed between PwH with HA and the other groups. The HJHS was not correlated with gait parameters among PwH with HA.

CONCLUSIONS

Gait parameters and speed were abnormal in both PwH with HA and PwH without HA. The FDM-T can be used to identify early stages of physical dysfunction that cannot be detected by conventional functional assessments such as the HJHS.

Interactive boxing-cycling on frailty and activity limitations in frail and prefrail older adults: A randomized controlled trial

BACKGROUND

Frailty is common among older adults, often associated with activity limitations during physical and walking tasks. The interactive boxing-cycling combination has the potential to be an innovative and efficient training method, and our hypothesis was that interactive boxing-cycling would be superior to stationary cycling in improving frailty and activity limitations in frail and prefrail older adults.

OBJECTIVE

To examine the impact of interactive boxing-cycling on frailty and activity limitations in frail and prefrail older adults compared to stationary cycling.

MATERIALS AND METHODS

A single-blinded randomized controlled trial. Forty-five participants who met at least one frailty phenotype criteria were randomly assigned to receive either interactive boxing-cycling (n = 23) or stationary-cycling (n = 22) for 36 sessions over 12 weeks. The interactive boxing-cycling was performed on a cycle boxer bike with an interactive boxing panel fixed in front of the bike. The primary outcomes were frailty status, including score and phenotypes. Secondary outcomes included activity limitations during physical and walking tasks. The pre- and post-intervention data of both groups were analyzed using a repeated measures two-way ANOVA.

RESULTS

Both types of cycling significantly improved frailty scores (p<0.001). Interactive boxing-cycling was more effective than stationary cycling in reversing the frailty phenotype of muscle weakness (p = 0.03, odds ratio 9.19) and demonstrated greater improvements than stationary cycling in arm curl (p = 0.002, η2=0.20), functional reach (p = 0.001, η2=0.22), and grip strength (p = 0.02, η2=0.12) tests. Additionally, interactive boxing-cycling exhibited a greater effect on gait speed (p = 0.02, η2=0.13) and gait variability (p = 0.01, η2=0.14) during dual-task walking.

CONCLUSION

In frail and prefrail older adults, interactive boxing-cycling effectively improves frailty but is not superior to stationary cycling. However, it is more effective at improving certain activity limitations.

REGISTRATION NUMBER

TCTR20220328001.

Frailty and Other Factors Associated With Early Outcomes in Middle-to Older Age Trauma Patients: A Prospective Cohort Study

OBJECTIVES

To prospectively investigate associations of frailty and other predictor variables with functional recovery and health outcomes in middle-aged and older patients with trauma.

DESIGN

Single-center prospective cohort study.

SETTING

Emergency department of Wan Fang Hospital in Taiwan.

PARTICIPANTS

Trauma patients aged 45 and older.

MEASUREMENTS

Frailty was assessed with the Clinical Frailty Scale (CFS). Injury mechanisms, pre-existing diseases, and fracture locations were recorded at baseline. The primary outcome was functional recovery assessed using the Barthel Index (BI). Secondary outcomes were new care needs, unscheduled return visits, and falls 3 months postinjury.

RESULTS

A total of 588 participants were included in the final analysis. For every one-point increase in the CFS, the multivariable-adjusted odds ratio (OR, 95% confidence interval [CI]) of failure to retain the preinjury BI was 1.34 (1.16-1.55); associations were consistent across levels of age and injury severities. Significant joint associations of frailty and age with poor functional recovery were observed. CFS was also associated with new care needs (OR for every one-point increase, 1.36, 95% CI, 1.17-1.58), unscheduled return visits (OR 1.26, 95% CI, 1.04-1.51), and falls (OR 1.23, 95% CI, 1.01-1.51). Other variables associated with failure to retain preinjury BI included road traffic accident and presence of hip fracture.

CONCLUSION

Frailty was significantly associated with poor functional and health outcomes regardless of injury severity in middle-aged and older patients with trauma. Injury mechanisms and fracture locations were also significant predictors of functional recovery postinjury.

Novel attentional gait index reveals a cognitive ability-related decline in gait automaticity during dual-task walking

Introduction

Gait automaticity refers to the ability to walk with minimal recruitment of attentional networks typically mediated through the prefrontal cortex (PFC). Reduced gait automaticity (i.e., greater use of attentional resources during walking) is common with aging, contributing to an increased risk of falls and reduced quality of life. A common assessment of gait automaticity involves examining PFC activation using near-infrared spectroscopy (fNIRS) during dual-task (DT) paradigms, such as walking while performing a cognitive task. However, neither PFC activity nor task performance in isolation measures automaticity accurately. For example, greater PFC activation could be interpreted as worse gait automaticity when accompanied by poorer DT performance, but when accompanied by better DT performance, it could be seen as successful compensation. Thus, there is a need to incorporate behavioral performance and PFC measurements for a more comprehensive evaluation of gait automaticity. To address this need, we propose a novel attentional gait index as an analytical approach that combines changes in PFC activity with changes in DT performance to quantify automaticity, where a reduction in automaticity will be reflected as an increased need for attentional gait control (i.e., larger index).

Methods

The index was validated in 173 participants (≥65 y/o) who completed DTs with two levels of difficulty while PFC activation was recorded with fNIRS. The two DTs consisted of reciting every other letter of the alphabet while walking over either an even or uneven surface.

Results

As DT difficulty increases, more participants showed the anticipated increase in the attentional control of gait (i.e., less automaticity) as measured by the novel index compared to PFC activation. Furthermore, when comparing across individuals, lower cognitive function was related to higher attentional gait index, but not PFC activation or DT performance.

Conclusion

The proposed index better quantified the differences in attentional control of gait between tasks and individuals by providing a unified measure that includes both brain activation and performance. This new approach opens exciting possibilities to assess participant-specific deficits and compare rehabilitation outcomes from gait automaticity interventions.

Step length is associated with comprehensive frailty status in community-dwelling older people

AIM

To examine spatial-temporal gait parameters associated with comprehensive frailty status in community-dwelling, independent older people.

METHODS

This cross-sectional study included 225 older people (≥65 years) living independently in the community. The Kihon Checklist was used to assess comprehensive frailty status, and participants were classified as robust, pre-frailty, or frailty. A sheet-type plantar pressure sensor was used to evaluate the following gait parameters, which were extracted at the usual and fast pace: gait speed, cadence, stride time, step length-to-height ratio (step length/height), step width, stance duration, double-support time, and variability of each gait parameter. Ordinal logistic regression analysis adjusted for confounding factors was performed to determine the association between gait parameters and frailty status. In addition, the ability to discriminate frailty status was evaluated by receiver operating characteristic (ROC) curve analysis for gait parameters that were significantly associated with frailty status.

RESULTS

Frailty status was pre-frailty in 79 (35.1%) and frailty in 30 (13.3%) participants. Ordinal logistic regression analysis showed a significant association of step length/height (%) at both usual and fast pace with frailty status, even after adjustment for confounding factors (usual pace: odds ratio [OR] = 0.93 [95% confidence interval, CI: 0.86-0.99]; fast pace: OR = 0.93 [95% CI: 0.87-0.99]). ROC curve analysis identified step length/height at fast pace in women as the best discriminator between frailty and non-frailty (area under the curve 0.69, cut-off value 43.4%, sensitivity 50%, specificity 82%).

CONCLUSIONS

Step length appears to be a useful gait parameter for discriminating frailty status in community-dwelling, independent older people. Geriatr Gerontol Int 2024; 24: 18-24.

Monitoring Gait and Physical Activity of Elderly Frail Individuals in Free-Living Environment: A Feasibility Study

INTRODUCTION

Frailty is conventionally diagnosed using clinical tests and self-reported assessments. However, digital health technologies (DHTs), such as wearable accelerometers, can capture physical activity and gait during daily life, enabling more objective assessments. In this study, we assess the feasibility of deploying DHTs in community-dwelling older individuals, and investigate the relationship between digital measurements of physical activity and gait in naturalistic environments and participants' frailty status, as measured by conventional assessments.

METHODS

Fried Frailty Score (FFS) was used to classify fifty healthy individuals as non-frail (FFS = 0, n/female = 21/11, mean ± SD age: 71.10 ± 3.59 years), pre-frail (FFS = 1-2, n/female = 23/9, age: 73.74 ± 5.52 years), or frail (FFS = 3+, n/female = 6/6, age: 70.70 ± 6.53 years). Participants wore wrist-worn and lumbar-worn GENEActiv accelerometers (Activinsights Ltd., Kimbolton, UK) during three in-laboratory visits, and at-home for 2 weeks, to measure physical activity and gait. After this period, they completed a comfort and usability questionnaire. Compliant days at-home were defined as follows: those with ≥18 h of wear time, for the wrist-worn accelerometer, and those with ≥1 detected walking bout, for the lumbar-worn accelerometer. For each at-home measurement, a group analysis was performed using a linear regression model followed by ANOVA, to investigate the effect of frailty on physical activity and gait. Correlation between at-home digital measurements and conventional in-laboratory assessments was also investigated.

RESULTS

Participants were highly compliant in wearing the accelerometers, as 94% indicated willingness to wear the wrist device, and 66% the lumbar device, for at least 1 week. Time spent in sedentary activity and time spent in moderate activity as measured from the wrist device, as well as average gait speed and its 95th percentile from the lumbar device were significantly different between frailty groups. Moderate correlations between digital measurements and self-reported physical activity were found.

CONCLUSIONS

This work highlights the feasibility of deploying DHTs in studies involving older individuals. The potential of digital measurements in distinguishing frailty phenotypes, while unobtrusively collecting unbiased data, thus minimizing participants' travels to sites, will be further assessed in a follow-up study.

Implementation and Core Components of a Multimodal Program including Exercise and Nutrition in Prevention and Treatment of Frailty in Community-Dwelling Older Adults: A Narrative Review

Increasing disability-free life expectancy is a crucial issue to optimize active ageing and to reduce the burden of evitable medical costs. One of the main challenges is to develop pragmatic and personalized prevention strategies in order to prevent frailty, counteract adverse outcomes such as falls and mobility disability, and to improve quality of life. Strong evidence reports the effectiveness of exercise interventions to improve various physical parameters and muscle function that are cornerstones of frailty. Other findings also suggest that the interactions between nutrition and physical exercise with or without health behavior promotion prevent the development of frailty. Multimodal programs, including structured exercise, adequate dietary intervention and health behavior promotion, appear increasingly consensual. However, in order for implementation in real-life settings, some pitfalls need to be addressed. In this perspective, structuring and tailoring feasible, acceptable and sustainable interventions to optimize exercise training responses are essential conditions to warrant short, medium and long-term individual benefits. The different components of exercise programs appear to be fairly consensual and effective. However, specific composition of the programs proposed (frequency, intensity, type, time, volume and progressiveness) have to be tailored to individual characteristics and objectives in order to improve exercise responses. The intervention approaches, behavioral strategies and indications for these programs also need to be refined and framed. The main objective of this work is to guide the actions of healthcare professionals and enable them to widely and effectively implement multimodal programs including exercise, nutrition and behavioral strategies in real-life settings.

Relationship between gait parameters and cognitive indexes in adult aging

PURPOSE

This study aimed to identify the most effective summary cognitive index predicted from spatio-temporal gait features (STGF) extracted from gait patterns.

METHODS

The study involved 125 participants, including 40 young (mean age: 27.65 years, 50% women), and 85 older adults (mean age: 73.25 years, 62.35% women). The group of older adults included both healthy adults and those with Mild Cognitive Impairment (MCI). Participant´s performance in various cognitive domains was evaluated using 12 cognitive measures from five neuropsychological tests. Four summary cognitive indexes were calculated for each case: 1) the z-score of Mini-Mental State Examination (MMSE) from a population norm (MMSE z-score); 2) the sum of the absolute z-scores of the patients' neuropsychological measures from a population norm (ZSum); 3) the first principal component scores obtained from the individual cognitive variables z-scores (PCCog); and 4) the Mahalanobis distance between the vector that represents the subject's cognitive state (defined by the 12 cognitive variables) and the vector corresponding to a population norm (MDCog). The gait patterns were recorded using a body-fixed Inertial Measurement Unit while participants executed four walking tasks (normal, fast, easy- and hard-dual tasks). Sixteen STGF for each walking task, and the dual-task costs for the dual tasks (when a subject performs an attention-demanding task and walks at the same time) were computed. After applied Principal Component Analysis to gait measures (96 features), a robust regression was used to predict each cognitive index and individual cognitive variable. The adjusted proportion of variance (adjusted-R2) coefficients were reported, and confidence intervals were estimated using the bootstrap procedure.

RESULTS

The mean values of adjusted-R2 for the summary cognitive indexes were as follows: 0.0248 for MMSE z-score, 0.0080 for ZSum, 0.0033 for PCCog, and 0.4445 for MDCog. The mean adjusted-R2 values for the z-scores of individual cognitive variables ranged between 0.0009 and 0.0693. Multiple linear regression was only statistically significant for MDCog, with the highest estimated adjusted-R2 value.

CONCLUSIONS

The association between individual cognitive variables and most of the summary cognitive indexes with gait parameters was weak. However, the MDCog index showed a stronger and significant association with the STGF, exhibiting the highest value of the proportion of the variance that can be explained by the predictor variables. These findings suggest that the MDCog index may be a useful tool in studying the relationship between gait patterns and cognition.

Effect of automaticity induced by treadmill walking on prefrontal cortex activation and dual-task performance in older adults

As individuals age, they may experience a decline in gait automaticity, which requires increased attentional resources for the control of gait. This age-related decline in gait automaticity has been shown to contribute to higher prefrontal cortex (PFC) activation and lower dual-task performance during dual-task walking in older adults. This study is to investigate the effect of treadmill walking on PFC activation and dual-task performance in older adults. A total of 20 older adults (mean age, 64.35 ± 2.74 years) and 20 younger adults (mean age, 30.00 ± 3.15 years) performed single- and dual-task walking in overground and treadmill conditions. A wearable functional near-infrared spectroscopy and gait analyzer were used to analyze PFC activation and dual-task performance, respectively. To determine the dual-task (gait and cognitive) performance, the dual-task cost (DTC) was calculated using the following formula: (single-task - dual-task)/single-task × 100. In both groups, dual-task treadmill walking led to reduced PFC activation and reduced DTC compared to dual-task overground walking. Furthermore, despite a higher DTC in gait variability, correct response, total response, response index and a higher error score in older adults than in younger adults during overground walking, there was no difference in treadmill walking. The difference in PFC activation between single- and dual-tasks was also observed only in overground walking. Performing dual-task walking on a treadmill compared to overground walking results in different levels of dual-task performance and PFC activity. Specifically, older adults are able to maintain similar levels of dual-task performance as younger adults while walking on a treadmill, with reduced PFC activation due to the automaticity induced by the treadmill. Therefore, older adults who exhibit low dual-task performance during overground walking may be able to improve their performance while walking on a treadmill with fewer attentional resources.

Frailty Syndrome as a Transition from Compensation to Decompensation: Application to the Biomechanical Regulation of Gait

Most gait parameters decrease with age and are even more importantly reduced with frailty. However, other gait parameters exhibit different or even opposite trends for aging and frailty, and the underlying reason is unclear. Literature focuses either on aging, or on frailty, and a comprehensive understanding of how biomechanical gait regulation evolves with aging and with frailty seems to be lacking. We monitored gait dynamics in young adults (19-29 years, n = 27, 59% women), middle-aged adults (30-59 years, n = 16, 62% women), and non-frail (>60 years, n = 15, 33% women) and frail older adults (>60 years, n = 31, 71% women) during a 160 m walking test using the triaxial accelerometer of the Zephyr Bioharness 3.0 device (Zephyr Technology, Annapolis, MD, USA). Frailty was evaluated using the Frail Scale (FS) and the Clinical Frailty Scale (CFS). We found that in non-frail older adults, certain gait parameters, such as cadence, were increased, whereas other parameters, such as step length, were decreased, and gait speed is maintained. Conversely, in frail older adults, all gait parameters, including gait speed, were decreased. Our interpretation is that non-frail older adults compensate for a decreased step length with an increased cadence to maintain a functional gait speed, whereas frail older adults decompensate and consequently walk with a characteristic decreased gait speed. We quantified compensation and decompensation on a continuous scale using ratios of the compensated parameter with respect to the corresponding compensating parameter. Compensation and decompensation are general medical concepts that can be applied and quantified for many, if not all, biomechanical and physiological regulatory mechanisms of the human body. This may allow for a new research strategy to quantify both aging and frailty in a systemic and dynamic way.

Age-related changes in gait domains: Results from the LonGenity study

BACKGROUND

Impairment in gait domains such as pace, rhythm, and variability are associated with falls, cognitive decline, and dementia. However, the longitudinal changes in these gait domains are poorly understood. The aim of this study was to examine age-related changes in gait domains overall and in those with cognitive impairment and mobility disability.

METHODS

Participants were from the LonGenity study (n = 797; M Age=75.1 SD 6.5 years; 58.2% female) and were followed up to 12 years (Median=3.3; IQR: 1.1; 6.3). Gait speed and absolute values of step length, step time, cadence and, variability (standard deviation) of step length and step time during usual pace walking were assessed. Principal components analysis was used to obtain weighted combinations of three gait domains: pace (velocity, step length), variability (step length variability, step time variability) and rhythm (step time). Linear mixed effect models were used to examine age-related changes in gait domains overall, and in those with cognitive impairment and mobility disability at baseline.

RESULTS

Pace declined, and rhythm increased (worsened) in an accelerating non-linear fashion. Variability gradually increased with age. Those with cognitive impairment had faster rates of change in pace and rhythm. Those with mobility disability had faster increases in rhythm.

CONCLUSIONS

Age-related changes in gait domains are not uniform. Individuals with cognitive and mobility impairments are particularly vulnerable to accelerated change in pace and or rhythm.

Intercorrelated variability in blood and hemodynamic biomarkers reveals physiological network in hemodialysis patients

Increased intra-individual variability of a variety of biomarkers is generally associated with poor health and reflects physiological dysregulation. Correlations among these biomarker variabilities should then represent interactions among heterogeneous biomarker regulatory systems. Herein, in an attempt to elucidate the network structure of physiological systems, we probed the inter-variability correlations of 22 biomarkers. Time series data on 19 blood-based and 3 hemodynamic biomarkers were collected over a one-year period for 334 hemodialysis patients, and their variabilities were evaluated by coefficients of variation. The network diagram exhibited six clusters in the physiological systems, corresponding to the regulatory domains for metabolism, inflammation, circulation, liver, salt, and protein. These domains were captured as latent factors in exploratory and confirmatory factor analyses (CFA). The 6-factor CFA model indicates that dysregulation in each of the domains manifests itself as increased variability in a specific set of biomarkers. Comparison of a diabetic and non-diabetic group within the cohort by multi-group CFA revealed that the diabetic cohort showed reduced capacities in the metabolism and salt domains and higher variabilities of the biomarkers belonging to these domains. The variability-based network analysis visualizes the concept of homeostasis and could be a valuable tool for exploring both healthy and pathological conditions.

Effect of frailty on kinematic characteristics of walking in community-dwelling elders

OBJECTIVE

Frailty has a high prevalence in elders and impairs motor ability. This study aimed to investigate the influence caused by frailty in kinematic characteristics of walking and walking strategy adjustment from static standing to stable walking.

METHODS

In this study, 80 community-dwelling elders performed tests. The Kihon checklist (KCL) was used to assess frailty. The timed up and go test (TUGT) and the 30-s chair stand test (30-s CST) were used to assess balance and muscle strength. The Xsens MVN BIOMECH Awinda was used to collect walking kinematic data.

RESULTS

This study included 25 robust, 30 prefrail, and 25 frail elders. The TUGT completed time (P < 0.001) and the 30-s CST completed number (P = 0.002) had statistical differences among groups. The maximum peak of knee internal rotation showed an interaction between the frailty and the walking phase (P = 0.015). The peak angle of hip adduction, hip and knee flexion, and knee and ankle internal rotation were significantly lower in frail elders than others (P < 0.05).

CONCLUSION

Frailty affects the kinematic characteristics of walking, resulting in the hip, knee, and ankle flexion, hip adduction, knee and ankle internal rotation reduced. Besides, frailty has a specific negative effect on the walking strategy adjustment from static standing to stable walking.

Machine learning-based muscle mass estimation using gait parameters in community-dwelling older adults: A cross-sectional study

BACKGROUND

Loss of skeletal muscle mass is associated with numerous factors such as metabolic diseases, lack of independence, and mortality in older adults. Therefore, developing simple, safe, and reliable tools for assessing skeletal muscle mass is needed. Some studies recently reported that the risks of the incidence of geriatric conditions could be estimated by analyzing older adults' gait; however, no studies have assessed the association between gait parameters and skeletal muscle loss in older adults. In this study, we applied machine learning approach to the gait parameters derived from three-dimensional skeletal models to distinguish older adults' low skeletal muscle mass. We also identified the most important gait parameters for detecting low muscle mass.

METHODS

Sixty-six community-dwelling older adults were recruited. Thirty-two gait parameters were created using a three-dimensional skeletal model involving 10-meter comfortable walking. After skeletal muscle mass measurement using a bioimpedance analyzer, low muscle mass was judged in accordance with the guideline of the Asia Working Group for Sarcopenia. The eXtreme gradient boosting (XGBoost) model was applied to discriminate between low and high skeletal muscle mass.

RESULTS

Eleven subjects had a low muscle mass. The c-statistics, sensitivity, specificity, precision of the final model were 0.7, 59.5%, 81.4%, and 70.5%, respectively. The top three dominant gait parameters were, in order of strongest effect, stride length, hip dynamic range of motion, and trunk rotation variability.

CONCLUSION

Machine learning-based gait analysis is a useful approach to determine the low skeletal muscle mass of community-dwelling older adults.

A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults

Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling.

Stable Sparse Classifiers predict cognitive impairment from gait patterns

Background

Although gait patterns disturbances are known to be related to cognitive decline, there is no consensus on the possibility of predicting one from the other. It is necessary to find the optimal gait features, experimental protocols, and computational algorithms to achieve this purpose.

Purposes

To assess the efficacy of the Stable Sparse Classifiers procedure (SSC) for discriminating young and healthy older adults (YA vs. HE), as well as healthy and cognitively impaired elderly groups (HE vs. MCI-E) from their gait patterns. To identify the walking tasks or combinations of tasks and specific spatio-temporal gait features (STGF) that allow the best prediction with SSC.

Methods

A sample of 125 participants (40 young- and 85 older-adults) was studied. They underwent assessment with five neuropsychological tests that explore different cognitive domains. A summarized cognitive index (MDCog), based on the Mahalanobis distance from normative data, was calculated. The sample was divided into three groups (young adults, healthy and cognitively impaired elderly adults) using k-means clustering of MDCog in addition to Age. The participants executed four walking tasks (normal, fast, easy- and hard-dual tasks) and their gait patterns, measured with a body-fixed Inertial Measurement Unit, were used to calculate 16 STGF and dual-task costs. SSC was then employed to predict which group the participants belonged to. The classification's performance was assessed using the area under the receiver operating curves (AUC) and the stable biomarkers were identified.

Results

The discrimination HE vs. MCI-E revealed that the combination of the easy dual-task and the fast walking task had the best prediction performance (AUC = 0.86, sensitivity: 90.1%, specificity: 96.9%, accuracy: 95.8%). The features related to gait variability and to the amplitude of vertical acceleration had the largest predictive power. SSC prediction accuracy was better than the accuracies obtained with linear discriminant analysis and support vector machine classifiers.

Conclusions

The study corroborated that the changes in gait patterns can be used to discriminate between young and healthy older adults and more importantly between healthy and cognitively impaired adults. A subset of gait tasks and STGF optimal for achieving this goal with SSC were identified, with the latter method superior to other classification techniques.

Association of Muscle Mass, Muscle Strength, and Muscle Function with Gait Ability Assessed Using Inertial Measurement Unit Sensors in Older Women

Aging-related muscle atrophy is associated with decreased muscle mass (MM), muscle strength (MS), and muscle function (MF) and may cause motor control, balance, and gait pattern impairments. This study determined associations of three speed-based gait variables with loss of MM, MS, and MF in older women. Overall, 432 older women aged ≥65 performed appendicular skeletal muscle, handgrip strength, and five times sit-to-stand test to evaluate MM, MS, and MF. A gait test was performed at three speeds by modifying the preferred walking speed (PWS; slower walking speed (SWS); faster-walking speed (FWS)) on a straight 19 m walkway. Stride length (SL) at PWS was significantly associated with MM. FWS and coefficient of variance (CV) of double support phase (DSP) and DSP at PWS showed significant associations with MS. CV of step time and stride time at SWS, FWS, and single support phase (SSP) at PWS showed significant associations with MF. SL at PWS, DSP at FWS, CV of DSP at PWS, stride time at SWS, and CV of SSP at PWS showed significant associations with composite MM, MS, and MF variables. Our study indicated that gait tasks under continuous and various speed conditions are useful for evaluating MM, MS, and MF.

Walking Speed Assessed by 4-Meter Walk Test in the Community-Dwelling Oldest Old Population in Vietnam

This study aims to provide data on usual walking speed in individuals aged 80 years or older and determine the association between walking speed and related factors in community-dwelling older adults. A cross-sectional study design was conducted to measure walking speed on community-dwelling elders aged 80 years or older in Soc Son district, Vietnam. Walking speed was assessed by a 4-Meter Walk Test with a usual-pace walking mode. Health-related characteristics of participants including risk of falls (The Timed Up and Go test, activities of daily living (ADL), instrumental activities of daily living (IADLs), cognitive impairment (Mini-Cog test) and frailty syndrome (The Reported Edmonton Frail Scale (REFS)). Multiple logistic regression was used to analyze the association between a slow walking speed and selected factors. A total of 364 older people were recruited, and the majority were female (65.4%). The overall average walking speed was 0.83 ± 0.27 m/s. The proportion of participants with a slow walking speed (<0.8 m/s) was 40.4%. Multiple logistic regression analyses showed that age, female, high fall risk (assessed by TUG test), ADL/IADL dependence and frailty syndrome had a negative effect on slow walking speed in this population. The results could provide useful reference data for further investigations and measures in clinical practice.

Wearable-Based Assessment of Frailty Trajectories During Cardiac Rehabilitation After Open-Heart Surgery

Frailty in patients after open-heart surgery influences the type and intensity of a cardiac rehabilitation program. The response to tailored exercise training can be different, requiring convenient tools to assess the effectiveness of a training program routinely. The study aims to investigate whether kinematic measures extracted from the acceleration signals can provide information about frailty trajectories during rehabilitation. One hundred patients after open-heart surgery, assigned to the equal-sized intervention and control groups, participated in exercise training during inpatient rehabilitation. After rehabilitation, the intervention group continued exercise training at home, whereas the control group was asked to maintain the usual physical activity regimen. Stride time, cadence, movement vigor, gait asymmetry, Lissajous index, and postural sway were estimated during the clinical walk and stair-climbing tests before and after inpatient rehabilitation as well as after home-based exercise training. Frailty was assessed using the Edmonton frail scale. Most kinematic measures estimated during walking improved after rehabilitation along with the improvement in frailty status, i.e., stride time, cadence, postural sway, and movement vigor improved in 71%, 77%, 81%, and 83% of patients, respectively. Meanwhile, kinematic measures during stair-climbing improved to a lesser extent compared to walking. Home-based exercise training did not result in a notable change in kinematic measures which agrees well with only a negligible deterioration in frailty status. The study demonstrates the feasibility to follow frailty trajectories during inpatient rehabilitation after open-heart surgery based on kinematic measures extracted using a single wearable sensor.

Motor control of landing in an unsteady environment

BACKGROUND

When landing from a jump or a drop, muscles contract before touchdown to anticipate imminent collision with the ground, soften ground contact and allow to return to a stable standing position without stepping or rebounding.

RESEARCH QUESTION

This study assesses the effect of the unsteadiness of the environment on the motor control of landing. The 'unsteady environment' was induced by asking participants to perform drop landings inside an aircraft that underwent trajectories parallel to Earth's surface. The participants also performed the same task in a 'steady environment' in our laboratory.

METHODS

Ground reaction forces, lower limb joints' movements and the activity of lower limb muscles were recorded. The stability of the landing was assessed by the vertical and anterior-posterior stability indexes, center of pressure measures and by the coefficient of variation of kinetic and kinematic parameters.

RESULTS

On one hand, participants slowdown their joint movements and reduce the knee joint excursion during landing, probably to avoid excessive movements that may induce imbalance. On the other hand, the stability of the landing is reduced while the variability of the movement is increased, illustrating a less stable and less consistent landing. In addition, whatever the environment, landing parameters associated with increased stiffness (i.e., increased impact forces and decreased joint range of motion) are correlated with decreased landing stability.

SIGNIFICANCE

Overall, landings in the'unsteady environment' appear to be more cautious but less stable and less finely tuned. Since the stability of the landing is not directly influenced by the steadiness of the environment, this more cautious behavior could be, at least in part, related to the fear/apprehension induced by sudden acceleration variations of the frame of the aircraft.

Effects of Remotely Supervised Physical Activity on Health Profile in Frail Older Adults: A Randomized Controlled Trial Protocol

Background

Frailty is considered a major public health challenge of the 21st century, characterized by the decline of multiform body functions. Physical activity may be the most effective intervention to delay frailty. This study aims to verify the effect of remotely supervised physical activity on health profile in community-dwelling frail older adults.

Design

This is a multicenter, three-blind, two-arm, and cohort randomized controlled study.

Methods

The intelligent exercise rehabilitation management system (IERMS) is an integrated digital platform that involves evaluation, guidance, monitoring, and feedback. A total of 120 participants aged ≥ 65 years and diagnosed as frailty on the FRAIL scale will be recruited and randomly divided into two groups. Group 1 will receive a 12-week IERMS-based intervention, and Group 2 will receive the usual care. Data will be collected at baseline, 12 and 24 weeks. The primary outcome is the physical function, and secondary outcomes include gait parameters, psychology, and cognition measurements. Analyses will be performed using DSS statistics, version 25. P < 0.05 will be considered statistically significant.

Conclusion

We believe that intervention plays a positive role in delaying the frailty. If our program is effective, we will provide a viable means to promote healthy aging in primary healthcare.

Trial registration number

ChiCTR2100052286; Pre-results.

Impact of walking states, self-reported daily walking amount and age on the gait of older adults measured with a smart-phone app: a pilot study

BACKGROUND

Smartphones provide a cost-effective avenue for gait assessment among older adults in the community. The purpose of this study is to explore the impact of walking state, self-reported daily walking amount, and age on gait quality, using a smartphone application.

METHODS

One hundred older adult individuals from North China, aged 73.0 ± 7.7 years, voluntarily participated in this study. They performed three walking tests: normal walking, fast walking, and visually impaired walking. Three-dimensional acceleration data for gait were obtained using the smartphone app Pocket Gait. This study used multivariate analysis of variance (MANOVA) to explore the effects of the walking state, self-reported daily walking amount, and age on the step frequency, root mean square (RMS) acceleration, step time variability, regularity, and symmetry.

RESULTS

The walking state, self-reported daily walking amount, and age had statistically significant effects on gait quality. Compared with normal walking, the step frequency, RMS acceleration, variability, and regularity were greater in the fast-walking state, and simulated visually impaired walking did not significantly affect gait quality. Relatively older individuals had a significant decline in gait quality compared to (relatively) younger older adult individuals. Compared with older adults who walked less than 1 km a day, older adults who walked more had better gait quality.

CONCLUSIONS

The walking state, self-reported daily walking amount, and age have a significant effect on the gait quality of older adults. Walking with pigmented sunglasses can be used as a training intervention to improve gait performance. Older adult people who walk less than 1 km/day have worse gait quality compared with their counterparts.

Kinematic characteristics during gait in frail older women identified by principal component analysis

Frailty is associated with gait variability in several quantitative parameters, including high stride time variability. However, the associations between joint kinematics during walking and increased gait variability with frailty remain unclear. In the current study, principal component analysis was used to identify the key joint kinematics characteristics of gait related to frailty. We analyzed whole kinematic waveforms during the entire gait cycle obtained from the pelvis and lower limb joint angle in 30 older women (frail/prefrail: 15 participants; non-frail: 15 participants). Principal component analysis was conducted using a 60 × 1224 input matrix constructed from participants’ time-normalized pelvic and lower-limb-joint angles along three axes (each leg of 30 participants, 51 time points, four angles, three axes, and two variables). Statistical analyses revealed that only principal component vectors 6 and 9 were related to frailty. Recombining the joint kinematics corresponding to these principal component vectors revealed that frail older women tended to exhibit greater variability of knee- and ankle-joint angles in the sagittal plane while walking compared with non-frail older women. We concluded that greater variability of knee- and ankle-joint angles in the sagittal plane are joint kinematic characteristics of gait related to frailty.

Gait-based Frailty Assessment using Image Representation of IMU Signals and Deep CNN

Frailty is a common and critical condition in elderly adults, which may lead to further deterioration of health. However, difficulties and complexities exist in traditional frailty assessments based on activity-related questionnaires. These can be overcome by monitoring the effects of frailty on the gait. In this paper, it is shown that by encoding gait signals as images, deep learning-based models can be utilized for the classification of gait type. Two deep learning models (a) SS-CNN, based on single stride input images, and (b) MS-CNN, based on 3 consecutive strides were proposed. It was shown that MS-CNN performs best with an accuracy of 85.1%, while SS-CNN achieved an accuracy of 77.3%. This is because MS-CNN can observe more features corresponding to stride-to-stride variations which is one of the key symptoms of frailty. Gait signals were encoded as images using STFT, CWT, and GAF. While the MS-CNN model using GAF images achieved the best overall accuracy and precision, CWT has a slightly better recall. This study demonstrates how image encoded gait data can be used to exploit the full potential of deep learning CNN models for the assessment of frailty.

Short- and long-term effects of different exercise programs on the gait performance of older adults with subjective cognitive decline: A randomized controlled trial

BACKGROUND

Older adults, especially those with cognitive decline, often have poor gait performance, which results in poor clinical outcomes due to falls or decreased daily physical activity. The effects of various exercises on gait performance have been studied, whereas the short-term and long-term effects of different exercise modalities remain unknown.

OBJECTIVE

To compare the short- and long-term effects of aerobic training (AT), resistance training (RT), and combined training (CT) on the gait performance of community-dwelling older adults with subjective cognitive decline (SCD).

DESIGN

A four-arm, randomized controlled trial.

SETTING AND SUBJECTS

388 community-dwelling older adults with SCD (mean age, 72.3 years).

METHODS

Participants attended an exercise or education class twice a week for 26 weeks. 10 gait performance parameters were examined at baseline, post-intervention (Week 26), and after 26 weeks of follow-up (Week 52) using an electronic walkway system.

RESULTS

The mean adherence of exercise sessions was 82.5 to 85.9%. All exercise intervention induced an improvement in gait speed, stride time, cadence, stride length, and double-support time at Week 26 (p < .05), without significant intergroup differences among exercise interventions. However, only RT showed a significant effect on some spatiotemporal gait parameters at Week 52. The analyses for the gait variability parameters showed mild effects of all exercise interventions.

CONCLUSION

All of the exercise programs examined had a positive short-term effect on spatiotemporal gait parameters of older adults with SCD, despite no effect on gait variability parameters. RT are most recommended when long-lasting effects are the primary aim.

[Women over 65 years of age performing supervised physical exercise: Differences in physical capacity, physical activity and quality of life according to walking speed]

INTRODUCTION

Walking speed (WS) is an easy, quick and inexpensive measure that could be used to discern between older people with greater and lesser function and thus individualize physical exercise programs.

OBJECTIVES

To analyze the differences in physical capacity, physical activity, and quality of life in people over 65years of age who attended a physical exercise program according to their WS and age.

METHODS

55 women (mean age: 76.67±6.66years) were divided into groups based on their WS (low WS: ≤1.59m/s and high WS: >1.59m/s) and age (older-younger: ≤76years and older-older: >76years). The following parameters were compared: 10Meters Walk Test (10MWT), Arm Curl Test, Handgrip, Chair Stand Test, 8Foot Up and Go Test (8FUG), 6Minute Walk Test (6MWT), and the Minnesota and The Short Form-36 Health Survey (SF-36) questionnaires.

RESULTS

The level of physical activity was higher than 3000METs/week in all groups. The high WS group had better results in the Arm Curl Test, 10MWT, 8FUG and 6MWT and in the Physical Role and Vitality dimensions of the SF-36 (P<.05). The older-older group had lower weight, BMI and Handgrip (P<.01).

CONCLUSIONS

The best results in physical capacity and quality of life are in those women with higher WS, suggesting that WS could be useful to individualize physical exercise programs.

Gait Variability Is Associated With the Strength of Functional Connectivity Between the Default and Dorsal Attention Brain Networks: Evidence From Multiple Cohorts

BACKGROUND

In older adults, elevated gait variability when walking has been associated with both cognitive impairment and future falls. This study leveraged 3 existing data sets to determine relationships between gait variability and the strength of functional connectivity within and between large-scale brain networks in healthy older adults, those with mild-to-moderate functional impairment, and those with Parkinson's disease (PD).

METHOD

Gait and resting-state functional magnetic resonance imaging data were extracted from existing data sets on: (i) 12 older adults without overt disease yet with slow gait and mild executive dysfunction; (ii) 12 older adults with intact cognitive-motor function and age- and sex-matched to the first cohort; and (iii) 15 individuals with PD. Gait variability (%, coefficient of variation of stride time) during preferred walking speed was measured and correlated with the degree of functional connectivity within and between 7 established large-scale functional brain networks.

RESULTS

Regression models adjusted for age and sex revealed that in each cohort, those with less gait variability exhibited greater negative correlation between fluctuations in resting-state brain activity between the default network and the dorsal attention network (functionally limited older: β = 4.38, p = .027; healthy older: β = 1.66, p = .032; PD: β = 1.65, p = .005). No other within- or between-network connectivity outcomes were consistently related to gait variability across all 3 cohorts.

CONCLUSION

These results provide strong evidence that gait variability is uniquely related to functional connectivity between the default network and the dorsal attention network, and that this relationship may be independent of both functional status and underlying brain disease.

Frailty Assessment Using Temporal Gait Characteristics and a Long Short-Term Memory Network

Faced with the rapidly aging world population, frailty has emerged as a major health burden among the elderly. This study aimed to investigate the feasibility of using temporal gait characteristics and a long short-term memory network for assessing frailty. Seventy-four community-dwelling elderly individuals participated in this study. The participants were categorized into three groups by their FRAIL scale: robust, pre-frail, and frail groups. The participants completed a 7-meter walking at the self-selected pace with a gyroscope on each foot. Analyzing the gyroscopic data produced seven temporal gait parameters per each gait cycle. Enumerating six consecutive values of each gait parameter produced the gait sequence features which were used as frailty predictors along with the demographic features. Five-fold cross-validation was applied to 70% of the data, and the remaining 30% were used as test data. An F1-score of 0.931 was achieved in classifying the robust, pre-frail, and frail groups by the random forest model trained with age, sex, and the outputs of the long short-term memory network-based classifier that used the initial and terminal double-limb support, step, and stride times as inputs. The proposed approach of assessing frailty using the arrhythmic gait pattern of the elderly and machine learning technique is novel and promising. Pioneering a way that self-monitor frailty at home without any help from experts, the study can contribute toearly diagnosis of frailty and make timely medical intervention possible.

Towards automated assessment of frailty status using a wrist-worn device

Wearable sensors potentially enable monitoring the users physical activity in daily life. Therefore, they are particularly appealing for the evaluation of older subjects in their environment, to capture early signs of frailty and mobility-related problems. This study explores the use of body-worn accelerometers for automated assessment of frailty during walking activity. Experiments involved 34 volunteers aged 70+, who were initially screened by geriatricians for the presence of frailty according to Frieds criteria. After screening, the volunteers were asked to walk 60 m at preferred speed, while wearing two accelerometers, one positioned on the lower back and the other on the wrist. Sensor-derived signals were analyzed independently to compare the ability of the two signals (wrist vs. lower back) in frailty status assessment. A gait detection technique was applied to identify segments made of four gait cycles. These segments were then used as input to compute 25 features in time and time-frequency domains, the latter by means of the Wavelet Transform. Finally, five machine learning models were trained and evaluated to classify subjects as robust or non-robust (i.e., pre-frail or frail). Gaussian naive Bayes applied to the features derived from the wrist sensor signal identified non-robust subjects with 91% sensitivity and 82% specificity, compared to 87% sensitivity and 64% specificity achieved with the lower back sensor. Results demonstrate that a wrist-worn accelerometer provides valuable information for the recognition of frailty in older adults, and could represent an effective tool to enable automated and unobtrusive assessment of frailty.

Visit-to-Visit Blood Pressure Variability and Incident Frailty in Older Adults

This study aimed to determine whether visit-to-visit blood pressure (BP) variability (BPV) is associated with incident frailty. We included 1 394 nonfrail community-dwelling participants aged ≥70 years from the Multidomain Alzheimer Preventive Trial (MAPT) who underwent repeated clinical examinations, including BP and frailty, over a 5-year follow-up period. Systolic BPV (SBPV), diastolic BPV (DBPV), mean arterial pressure variability (MAPV), and pulse pressure variability (PPV) were evaluated using standard deviation (SD), coefficient of variation (CV), average real variability, successive variation, variation independent of mean, and residual SD. Incident frailty was assessed using the Fried phenotype. Cox proportional hazards models were used for the analyses. Higher SBPV was significantly associated with greater risk of frailty (1-SD increase of CV: hazard ratio [HR] = 1.18, 95% confidence interval [CI]: 1.02-1.36) after adjustment for demographics, systolic BP, antihypertensive drugs, body mass index, diabetes, ischemic heart disease, congestive heart failure, stroke, atrial fibrillation, MAPT randomization group, and frailty status. Similar results were observed with all indicators of variability. Higher PPV was associated with a greater risk of developing frailty over time (1-SD increase of CV: HR = 1.17, 95% CI: 1.01-1.35). DBPV and MAPV were not significantly associated with incident frailty. Higher SBPV and PPV were associated with greater risk of incident frailty. Our findings support the concept of BP physiological dysregulation underlying the frail state and suggest that BP instability could be an early marker of frailty.

[Group-based exercise to prevent falls in community-dwelling older adults : Update of the 2009 recommendations of the German Federal Initiative to Prevent Falls]

Dieser Beitrag stellt eine Aktualisierung des Empfehlungspapiers der Bundesinitiative Sturzprävention für das körperliche Gruppentraining zur Sturzprävention bei älteren, zu Hause lebenden Menschen aus dem Jahre 2009 unter Berücksichtigung aktueller Evidenz dar. Das aktualisierte Empfehlungspapier zielt darauf ab, die Umsetzung ambulanter Sturzpräventionsgruppen zu fördern sowie konkrete Empfehlungen für deren Einrichtung und Durchführung auszusprechen. Die Empfehlungen beziehen sich auf die Identifikation und Ansprache der Zielgruppe für gruppenbasierte Sturzpräventionsprogramme sowie auf die Programmgestaltung und Qualitätssicherung. Hintergründe zu Finanzierung und Trainer*innen-Ausbildung werden samt einer Auflistung der in Deutschland etablierten Programme ebenfalls dargelegt.

How gait influences frailty models and health-related outcomes in clinical-based and population-based studies: a systematic review

Aging is often associated with a decline in physical function that eventually leads to loss of autonomy in activities of daily living (ADL). Walking is a very common ADL, important for main determinants of quality of life in older age, and it requires the integration of many physiological systems. Gait speed has been described as the 'sixth vital sign' because it is a core indicator of health and function in aging and disease. We reviewed original studies up to June 2020 that assessed frailty in both longitudinal and cross-sectional observational studies, paying particular attention to how gait is measured in older population and how the gait parameter adopted may influence the estimated frailty models and the health-related outcomes of the various studies (i.e. clinical, cognitive, physical, and nutritional outcomes). Eighty-five studies met the search strategy and were included in the present systematic review. According to the frailty tools, more than 60% of the studies used the physical phenotype model proposed by Fried and colleagues, while one-third referred to multi-domain indexes or models and only 5% referred to other single-domain frailty models (social or cognitive). The great heterogeneity observed in gait measurements and protocols limited the possibility to directly compare the results of the studies and it could represent an important issue causing variability in the different outcome measures in both clinical-and population-based settings. Gait appeared to be an indicator of health and function also in frail older adults, and different gait parameters appeared to predict adverse health-related outcomes in clinical, cognitive, and physical domains and, to a lesser extent, in nutritional domain. Gait has the potential to elucidate the common basic mechanisms of cognitive and motor decline. Advances in technology may extend the validity of gait in different clinical settings also in frail older adults, and technology-based assessment should be encouraged. Combining various gait parameters may enhance frailty prediction and classification of different frailty phenotypes.

Fast gait spatiotemporal parameters in adults and association with muscle strength - The Yishun study

BACKGROUND

There is limited data on fast gait speed and spatial-temporal parameters across age groups among Asian adults, and the associations between upper and lower extremity muscle strength with gait.

RESEARCH QUESTION

What values characterise fast gait spatiotemporal parameters across the age groups of an Asian population? Are hand grip strength (HGS) and knee extension strength (KES) associated with fast gait speed and spatiotemporal parameters?

METHODS

Healthy community-living adults between 21-90 years (n = 487) were recruited. Fast gait was assessed using a 6 m instrumented walkway, and spatiotemporal parameters including variability for fast gait speed, stride length, stride width, stride time, stance time, swing time, single support time and double support time were analysed. Maximum HGS and KES were also assessed. Linear regression modelling was used to explore the association of HGS and KES with fast gait speed, spatiotemporal parameters and their variability.

RESULTS

Age reduced fast gait speed and stride length, but increased stride width, stance time, stride time and double support time. Age increased all investigated gait variabilities except stride width variability. Gender differences were observed for all gait features except for fast gait speed and double support time. Both HGS and KES were positively associated with fast gait speed in both young and old adults. KES was positively associated with spatiotemporal variations in stride length, stride time, stance time and double support time. HGS was also significantly associated with two additional temporal parameters - positively with swing time and negatively with double support time variability.

SIGNIFICANCE

The data from this study contributes to reference values database for the use of fast gait assessments in adults.

Normative Data for Gait Speed and Height Norm Speed in ≥ 60-Year-Old Men and Women

Purpose

To determine normative data for gait speed and height-normalized gait speed in community-dwelling older men and women.

Materials and Methods

In this cross-sectional study, we recruited 565 men and women aged ≥60 years old. Age was calculated from the date of birth and further classified into four categories: (1) 60-65 years, (2) 66-70 years, (3) 71-75 years and (4) ≥76 years. Gait speed was assessed by a pressure platform (ZEBRIS, Munich, Germany) in meters per second (m/s). Height and weight were objectively measured. Height-normalized gait speed was calculated by dividing gait speed by height. We created the 20th, 40th, 60th and 80th percentile curves for both outcome measures using Cole's Lambda (L), Mu (M) and Sigma (S) method.

Results

Mean gait speed and height-normalized gait speed was 1.24 (standard deviation 0.28) and 0.75 (0.17). Significant age-related decline in gait speed for both sexes was observed (p < 0.001). Being a woman (β = - 0.09, p < 0.001), being older (β = - 0.02, p < 0.001) and having higher body mass index values (β = - 0.02, p < 0.001) were significantly associated with slower gait speed.

Conclusion

Gait speed significantly declines with age in both older men and women. Providing normative data can be used in screening and monitoring "slow" walkers to prevent from foot pain and higher risk of falls.

When Will My Patient Fall? Sensor-Based In-Home Walking Speed Identifies Future Falls in Older Adults

BACKGROUND

Although there are known clinical measures that may be associated with risk of future falls in older adults, we are still unable to predict when the fall will happen. Our objective was to determine whether unobtrusive in-home assessment of walking speed can detect a future fall.

METHOD

In both ISAAC and ORCATECH Living Laboratory studies, a sensor-based monitoring system has been deployed in the homes of older adults. Longitudinal mixed-effects regression models were used to explore trajectories of sensor-based walking speed metrics in those destined to fall versus controls over time. Falls were captured during a 3-year period.

RESULTS

We observed no major differences between those destined to fall (n = 55) and controls (n = 70) at baseline in clinical functional tests. There was a longitudinal decline in median daily walking speed over the 3 months before a fall in those destined to fall when compared with controls, p < .01 (ie, mean walking speed declined 0.1 cm s-1 per week). We also found prefall differences in sensor-based walking speed metrics in individuals who experienced a fall: walking speed variability was lower the month and the week just before the fall compared with 3 months before the fall, both p < .01.

CONCLUSIONS

While basic clinical tests were not able to differentiate who will prospectively fall, we found that significant variations in walking speed metrics before a fall were measurable. These results provide evidence of a potential sensor-based risk biomarker of prospective falls in community living older adults.

Current Perspectives on the Assessment and Management of Gait Disorders in Parkinson's Disease

Gait dysfunction is a key defining feature of Parkinson's disease (PD), and is associated with symptoms of freezing and an increased risk of falls. In this narrative review, we cover the putative mechanisms of gait dysfunction in PD, the assessment of gait abnormalities, and the management of symptoms caused by the inherent difficulty in walking. Our understanding of the causes of gait problems in PD has progressed in recent times, moving from neurocognitive theory to correlates of affected neuronal pathways. In particular, this can be shown to correspond with abnormalities in responses to dual-task paradigms and dysfunction in cholinergic signaling. Great progress has been made in the sophistication and precision of gait assessment; however, it has firmly remained in the research domain. There is significant momentum behind wearable technologies that can be used by patients in their own environment, acting as digital biomarkers that can not only reflect progression but also independently discriminate PD from non-PD individuals. The treatment of gait dysfunction has historically relied on physical therapies and training combined with a view to mitigating the impact of such consequences as falls. Pharmacological therapies that are the mainstay of treatment in PD have tended to address symptoms like bradykinesia; however, optimization of dopaminergic therapies likely has a positive effect on quality of gait. Other targets have been assessed with the goal of improving gait, of which medications that improve cholinergic signaling appear most promising. Neuromodulation techniques are increasingly used in the form of deep-brain stimulation; however, standard targets, such as the globus pallidus interna, have a modest effect on gait. Considerable benefit has been seen through targeting the pedunculopontine nucleus, and a dual-target approach may be warranted. Stimulation of the spinal cord and brain through direct or magnetic approaches has been assessed, but requires further evidence.

Wearable Sensors Technology as a Tool for Discriminating Frailty Levels During Instrumented Gait Analysis

Background and objectives: One of the greatest challenges facing the healthcare of the aging population is frailty. There is growing scientific evidence that gait assessment using wearable sensors could be used for prefrailty and frailty screening. The purpose of this study was to examine the ability of a wearable sensor-based assessment of gait to discriminate between frailty levels (robust, prefrail, and frail). Materials and methods: 133 participants (≥60 years) were recruited and frailty was assessed using the Fried criteria. Gait was assessed using wireless inertial sensors attached by straps on the thighs, shins, and feet. Between-group differences in frailty were assessed using analysis of variance. Associations between frailty and gait parameters were assessed using multinomial logistic models with frailty as the dependent variable. We used receiver operating characteristic (ROC) curves to calculate the area under the curve (AUC) to estimate the predictive validity of each parameter. The cut-off values were calculated based on the Youden index. Results: Frailty was identified in 37 (28%) participants, prefrailty in 66 (50%), and no Fried criteria were found in 30 (23%) participants. Gait speed, stance phase time, swing phase time, stride time, double support time, and cadence were able to discriminate frailty from robust, and prefrail from robust. Stride time (AUC = 0.915), stance phase (AUC = 0.923), and cadence (AUC = 0.930) were the most sensitive parameters to separate frail or prefrail from robust. Other gait parameters, such as double support, had poor sensitivity. We determined the value of stride time (1.19 s), stance phase time (0.68 s), and cadence (101 steps/min) to identify individuals with prefrailty or frailty with sufficient sensitivity and specificity. Conclusions: The results of our study show that gait analysis using wearable sensors could discriminate between frailty levels. We were able to identify several gait indicators apart from gait speed that distinguish frail or prefrail from robust with sufficient sensitivity and specificity. If improved and adapted for everyday use, gait assessment technologies could contribute to frailty screening and monitoring.

Comprehensive Model for Physical and Cognitive Frailty: Current Organization and Unmet Needs

Aging is characterized by the decline and deterioration of functional cells and results in a wide variety of molecular damages and reduced physical and mental capacity. The knowledge on aging process is important because life expectancy is expected to rise until 2050. Aging cannot be considered a homogeneous process and includes different trajectories characterized by states of fitness, frailty, and disability. Frailty is a dynamic condition put between a normal functional state and disability, with reduced capacity to cope with stressors. This geriatric syndrome affects physical, neuropsychological, and social domains and is driven by emotional and spiritual components. Sarcopenia is considered one of the determinants and the biological substrates of physical frailty. Physical and cognitive frailty are separately approached during daily clinical practice. The concept of motoric cognitive syndrome has partially changed this scenario, opening interesting windows toward future approaches. Thus, the purpose of this manuscript is to provide an excursus on current clinical practice, enforced by aneddoctical cases. The analysis of the current state of the art seems to support the urgent need of comprehensive organizational model incorporating physical and cognitive spheres in the same umbrella.

Dual decline in gait speed and cognition is associated with future dementia: evidence for a phenotype

BACKGROUND

concurrent declines in gait speed and cognition have been associated with future dementia. However, the clinical profile of 'dual decliners', those with concomitant decline in both gait speed and cognition, has not been yet described. We aimed to describe the phenotype and the risk for incident dementia of those who present with dual decline in comparison with non-dual decliners.

METHODS

prospective cohort of community-dwelling older adults free of dementia at baseline. We evaluated participants' gait speed, cognition, medical status, functionality, incidence of adverse events and dementia, biannually over 7 years. Gait speed was assessed with a 6-m electronic walkway and global cognition using the MoCA test. We compared characteristics between dual decliners and non-dual decliners using t-test, chi-square and hierarchical regression models. We estimated incident dementia using Cox models.

RESULTS

among 144 participants (mean age 74.23 ± 6.72 years, 54% women), 17% progressed to dementia. Dual decliners had a 3-fold risk (HR: 3.12, 95%CI: 1.23-7.93, P = 0.017) of progression to dementia compared with non-dual decliners. Dual decliners were significantly older with a higher prevalence of hypertension and dyslipidemia (P = 0.002). Hierarchical regression models show that age and sex alone explained 3% of the variation in the dual decliners group. Adding hypertension and dyslipidemia increased the explained variation by 8 and 10%, respectively. The risk of becoming a dual decliner was 4-fold higher if hypertension was present.

CONCLUSION

older adults with a concurrent decline in gait speed and cognition represent a group at the highest risk of progression to dementia. Older adults with dual decline have a distinct phenotype with a higher prevalence of hypertension, a treatable condition.

The Association Between Comorbidity, Frailty, and Outdoor Mobility Loss Among Community-Dwelling Individuals 60 Years of Age and Above in Moscow

To determine the prognostic value of frailty and comorbidity for outdoor mobility loss and mortality in the elderly. The retrospective study was conducted among outpatients aged ≥60 years. Patients with ≥3 chronic illnesses were treated by doctors who had undergone a 72-hour geriatric training. The outdoor low-mobility group comprised patients who failed to visit a doctor because of decreased outdoor mobility during the 3-year follow-up period. The outdoor high-mobility group comprised participants with no outdoor mobility loss. 5678 patients with a mean age of 71.0 ± 0.1 years were included in the study. The risk of outdoor mobility loss rose by 4% per year with men developing it 30% more than women. The effect of frailty was of particular importance because it increased the risk of developing outdoor mobility loss by 70%. Comorbidity was not associated with a higher risk of outdoor mobility loss, but the investigators did not take into account all possible illnesses, or the severity of disease. The loss of outdoor mobility was associated with increase in mortality. Early detection of frailty can help predict outdoor mobility loss and could reduce mortality among older people.

Estimation of homeostatic dysregulation and frailty using biomarker variability: a principal component analysis of hemodialysis patients

Increased intraindividual variability in several biological parameters is associated with aspects of frailty and may reflect impaired physiological regulation. As frailty involves a cumulative decline in multiple physiological systems, we aimed to estimate the overall regulatory capacity by applying a principal component analysis to such variability. The variability of 20 blood-based parameters was evaluated as the log-transformed coefficient of variation (LCV) for one year’s worth of data from 580 hemodialysis patients. All the LCVs were positively correlated with each other and shared common characteristics. In a principal component analysis of 19 LCVs, the first principal component (PC1) explained 27.7% of the total variance, and the PC1 score exhibited consistent correlations with diverse negative health indicators, including diabetes, hypoalbuminemia, hyponatremia, and relative hypocreatininemia. The relationship between the PC1 score and frailty was subsequently examined in a subset of the subjects. The PC1 score was associated with the prevalence of frailty and was an independent predictor for frailty (odds ratio per SD: 2.31, P = 0.01) using a multivariate logistic regression model, which showed good discrimination (c-statistic: 0.85). Therefore, the PC1 score represents principal information shared by biomarker variabilities and is a reasonable measure of homeostatic dysregulation and frailty.

Obstacle Negotiation, Gait Variability, and Risk of Falling: Results From the "Gait and Brain Study"

BACKGROUND

Gait variability is an early fall predictor. However, it is unknown how gait variability of older adults at high risk of falls is affected by an obstacle negotiation task. We aimed to compare gait performance between older adults with significant history of falls (i.e. fallers) and nonfallers while approaching an obstacle crossing.

METHODS

A total of 137 older adults without dementia were enrolled (72.7 ± 5.1 years of age; 60.5% women) from the "Gait and Brain Study." Fallers were defined as having at least one injurious fall or at least two noninjurious falls in the previous 12 months. Participants performed gait assessments under unobstructed and obstructed conditions. During the obstructed condition, participants walked and stepped over an ad hoc obstacle set at 15% of participants' height, transversally placed on a 6-meter electronic walkway. Gait speed and step-to-step variabilities were quantified from the last six steps prior to obstacle crossing. Analysis of variance models adjusted for age, sex, fear of falling, comorbidities, and unobstructed gait were used to compare gait performance of fallers and nonfallers during an obstacle approaching.

RESULTS

In the study, 27 older adults were identified as fallers and 110 as nonfallers. Fallers had higher step time variability and step length variability when approaching an obstacle compared with nonfallers, although groups had comparable gait performance during unobstructed walking.

CONCLUSION

Gait variability of older individuals at high risk of falling is more disturbed, compared with low-risk individuals, while approaching an obstacle crossing. High gait variability prior to crossing an obstacle may be a risk factor for falls.

Relevance of sex, age and gait kinematics when predicting fall-risk and mortality in older adults

Approximately one-third of elderly people fall each year with severe consequences, including death. The aim of this study was to identify the most relevant features to be considered to maximize the accuracy of a logistic regression model designed for prediction of fall/mortality risk among older people. This study included 261 adults, aged over 65 years. Men and women were analyzed separately because sex stratification was revealed as being essential for our purposes of feature ranking and selection. Participants completed a 3-m walk test at their own gait velocity. An inertial sensor attached to their lumbar spine was used to record acceleration data in the three spatial directions. Signal processing techniques allowed the extraction of 21 features representative of gait kinematics, to be used as predictors to train and test the model. Age and gait speed data were also considered as predictors. A set of 23 features was considered. These features demonstrate to be more or less relevant depending on the sex of the cohort under analysis and the classification label (risk of falls and mortality). In each case, the minimum size subset of relevant features is provided to show the maximum accuracy prediction capability. Gait speed has been largely used as the single feature for the prediction fall risk among older adults. Nevertheless, prediction accuracy can be substantially improved, reaching 70% in some cases, if the task of training and testing the model takes into account some other features, namely, sex, age and gait kinematic parameters. Therefore we recommend considering sex, age and step regularity to predict fall-risk.