Gait characteristics under different walking conditions: Association with the presence of cognitive impairment in community-dwelling older people

Evaluation of mild-to-moderate COVID-19 through dual-task paradigm: a longitudinal case-controlled study

INTRODUCTION

Coronavirus disease (COVID-19) was associated with cognitive alterations affecting everyday life activities. These need input integration of both motor and cognitive systems. The study aim is to evaluate cognitive-motor interference phenomenon in previously independent patients with mild-to-moderate COVID-19 (PwMCOVID-19) compared with healthy controls (HC), through dual-task (DT) paradigm.

METHODS

PwMCOVID-19 were included if being independent at home, had no previous referred cognitive impairment, mechanical ventilation or oxygen need. They were assessed at admission and after 6 months with a motor-cognitive DT test (counting backward by twos while walking 2 min). HC were enrolled as control group. Differences between single-task (ST) and DT performance, DT effect (DTE) and task prioritization amongst groups and during time points were analyzed.

RESULTS

One-hundred PwMCOVID-19 [mean age=67.32(12.08) years; 53 M/47 F] and 39 HC [mean age=63.11(9.90) years; 20 M/19 F] were recruited. Upon T0, PwMCOVID-19 showed lower cognitive and motor DT performances than ST and HC. Mutual interference pattern was predominant in PwMCOVID-19. At T1, 41 PwMCOVID-19 were examined [mean age=64.85(10.75); 22 M/19 F]. They had a worse DT performance compared to ST, although DT improved at T1. A stronger cognitive ST-DT difference was present at T0, compared to ST-DT difference at T1, while motor ST-DT difference was unchanged over time in PwCOVID-19.

CONCLUSION

In PwMCOVID-19, there is an impairment of DT counting while walking at baseline and after 6 months from hospitalization, with a more pronounced DT mutual interference pattern at T0. After 6 months, the motor and cognitive ST and DT performances ameliorated, not reaching the HC level.

Minding your steps: a cross-sectional pilot study using foot-worn inertial sensors and dual-task gait analysis to assess the cognitive status of older adults with mobility limitations

BACKGROUND

Cognitive impairment is a critical aspect of our aging society. Yet, it receives inadequate intervention due to delayed or missed detection. Dual-task gait analysis is currently considered a solution to improve the early detection of cognitive impairment in clinical settings. Recently, our group proposed a new approach for the gait analysis resorting to inertial sensors placed on the shoes. This pilot study aimed to investigate the potential of this system to capture and differentiate gait performance in the presence of cognitive impairment based on single- and dual-task gait assessments.

METHODS

We analyzed demographic and medical data, cognitive tests scores, physical tests scores, and gait metrics acquired from 29 older adults with mobility limitations. Gait metrics were extracted using the newly developed gait analysis approach and recorded in single- and dual-task conditions. Participants were stratified into two groups based on their Montreal Cognitive Assessment (MoCA) global cognitive scores. Statistical analysis was performed to assess differences between groups, discrimination ability, and association of gait metrics with cognitive performance.

RESULTS

The addition of the cognitive task influenced gait performance of both groups, but the effect was higher in the group with cognitive impairment. Multiple dual-task costs, dual-task variability, and dual-task asymmetry metrics presented significant differences between groups. Also, several of these metrics provided acceptable discrimination ability and had a significant association with MoCA scores. The dual-task effect on gait speed explained the highest percentage of the variance in MoCA scores. None of the single-task gait metrics presented significant differences between groups.

CONCLUSIONS

Our preliminary results show that the newly developed gait analysis solution based on foot-worn inertial sensors is a pertinent tool to evaluate gait metrics affected by the cognitive status of older adults relying on single- and dual-task gait assessments. Further evaluation with a larger and more diverse group is required to establish system feasibility and reliability in clinical practice.

TRIAL REGISTRATION

ClinicalTrials.gov (identifier: NCT04587895).

The association between cognitive impairment, gait speed, and Walk ratio

Background

Gait speed has been found to be associated with cognitive function. However, gait speed is an unspecific measure that may not be informative about gait patterns. The Walk ratio (step length divided by step frequency) can be measured without specialized equipment, and has been suggested as an indicator of central gait control. However, the association with cognitive function is unknown.

Research question

Is there a relationship between Walk ratio and cognitive function, and gait speed and cognitive function?

Methods

This was a systematic literature review of studies where spatiotemporal gait parameters was reported in populations with cognitive impairment. The search was performed through PubMed, PEDro, AMED, Cochrane, Embase, MEDLINE, and PsycINFO. The studies had to contain either the Walk ratio, or report average step length and average step frequency. In the latter case, the average step length was divided by the average step frequency. The studies also had to report gait speed and the minimal mental state examination (MMSE). Studies testing patients on treadmills or that did not state the exclusion of patients with neurologic or orthopedic diseases, possible affecting gait ability, were excluded.

Results

A total of 24 studies were included, consisting of 909 patients with cognitive impairment and 4,108 healthy controls. The patient group had a lower Walk ratio (mean difference 0.07, p ≤ 0.001) and gait speed (mean difference 0.26, p ≤ 0.001) than the healthy controls. Using linear regression models, we found an association between the MMSE and the Walk ratio (R² = 0.29, p < 0.001) and gait speed (R² = 0.41, p < 0.001) in separate, unadjusted models. In a final model with Walk ratio, gait speed and age, Walk ratio was not significantly associated with MMSE, while gait speed was.

Significance

Our results suggest that preferred gait speed may be preferable to the Walk ratio when assessing older adults with cognitive impairment.

Comparison of spatio-temporal gait parameters between the GAITRite® platinum plus classic and the GAITRite® CIRFACE among older adults: a retrospective observational study

BACKGROUND

The GAITRite® system is one of the gold standards for gait electronic analysis, especially for older adults. Previous GAITRite® systems were composed of an electronic roll-up walkway. Recently, a new GAITRite® electronic walkway, named CIRFACE, was commercialized. It is composed of a changeable association of stiff plates, unlike previous models. Are the gait parameters measured similar between these two walkways among older adults and according to the cognitive status, the history of falls, and the use of walking aids?

METHODS

In this retrospective observational study, 95 older ambulatory participants (mean, 82.6 ± 5.8 years) were included. Ten spatio-temporal gait parameters were measured simultaneously with the two GAITRite® systems in older adults while walking at comfortable self-selected pace. The GAITRite® Platinum Plus Classic (26') was superimposed on the GAITRite® CIRFACE (VI). Comparisons between the parameters of the two walkways were performed using Bravais-Pearson correlation, between-method differences (corresponding to bias), percentage errors and Intraclass Correlation Coefficients (ICC_2,1). Subgroup analyses were performed according to the cognitive status, the history of falls in the last 12 months and the use of walking aids.

RESULTS

The whole walk parameters recorded by the two walkways were extremely correlated with a Bravais-Pearson correlation coefficient ranging from 0.968 to 0.999, P < .001, indicating a very high correlation. According to the ICC_2,1 calculated for absolute agreement, all gait parameters had excellent reliability (ranging from 0.938 to 0.999). Mean bias for 9 parameters out of 10 were ranged from - 0.27 to 0.54, with clinically acceptable percentage errors (1.2-10.1%). Step length showed a substantially higher bias (1.4 ± 1.2 cm), nevertheless the percentage errors remained clinically acceptable (5%).

CONCLUSION

When walking at comfortable self-selected pace, the standard spatio-temporal walk parameters provided by both the GAITRite® PPC and the GAITRite® CIRFACE seem similar and very highly correlated in older adults with various cognitive or motor status. The data of studies using these systems can be compared and mixed with a very low risk of bias in a meta-analytic process. Also, the geriatric care units can choose the most ergonomic system according to their infrastructure without affecting their gait data.

TRIAL REGISTRATION

NCT04557592 (21/09/2020).

Walking Speed Classification from Marker-Free Video Images in Two-Dimension Using Optimum Data and a Deep Learning Method

Walking speed is considered a reliable assessment tool for any movement-related functional activities of an individual (i.e., patients and healthy controls) by caregivers and clinicians. Traditional video surveillance gait monitoring in clinics and aged care homes may employ modern artificial intelligence techniques to utilize walking speed as a screening indicator of various physical outcomes or accidents in individuals. Specifically, ratio-based body measurements of walking individuals are extracted from marker-free and two-dimensional video images to create a walk pattern suitable for walking speed classification using deep learning based artificial intelligence techniques. However, the development of successful and highly predictive deep learning architecture depends on the optimal use of extracted data because redundant data may overburden the deep learning architecture and hinder the classification performance. The aim of this study was to investigate the optimal combination of ratio-based body measurements needed for presenting potential information to define and predict a walk pattern in terms of speed with high classification accuracy using a deep learning-based walking speed classification model. To this end, the performance of different combinations of five ratio-based body measurements was evaluated through a correlation analysis and a deep learning-based walking speed classification test. The results show that a combination of three ratio-based body measurements can potentially define and predict a walk pattern in terms of speed with classification accuracies greater than 92% using a bidirectional long short-term memory deep learning method.

Cognitive, psychological and social factors associated with older adults' mobility: a scoping review of self-report and performance-based measures

Although many factors have been associated with mobility among older adults, there is paucity of research that explores the complexity of factors that influence mobility. This review aims to synthesise the available evidence for factors comprising the cognitive, psychological, and social mobility determinants and their associations with mobility self-reported and performance-based outcomes in older adults (60 years). We followed Arksey and O'Malley's five stages of a scoping review and searched PubMed, EMBASE, PsychINFO, Web of Science, AgeLine, Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature and Sociological Abstract databases. Reviewers in pairs independently conducted title, abstract, full-text screening and data extraction. We reported associations by analyses rather than articles because articles reported multiple associations for factors and several mobility outcomes. Associations were categorised as significantly positive, negative, or not significant. We included 183 peer-reviewed articles published in 27 countries, most of which were cross-sectional studies and conducted among community-dwelling older adults. The 183 articles reported 630 analyses, of which 381 (60.5%) were significantly associated with mobility outcomes in the expected direction. For example, older adults with higher cognitive functioning such as better executive functioning had better mobility outcomes (e.g., faster gait speed), and those with poor psychological outcomes, such as depressive symptoms, or social outcomes such as reduced social network, had poorer mobility outcomes (e.g., slower gait speed) compared to their counterparts. Studies exploring the association between cognitive factors, personality (a psychological factor) and self-reported mobility outcomes (e.g., walking for transportation or driving), and social factors and performance-based mobility outcomes in older adults are limited. Understanding the additive relationships between cognitive, psychological, and social factors highlights the complexity of older adults' mobility across different forms of mobility, including independence, use of assistive devices, transportation, and driving.

Foot-to-Ground Phases Detection: A Comparison of Data Representation Formatting Methods with Respect to Adaption of Deep Learning Architectures

Identifying the foot stance and foot swing phases, also known as foot-to-ground (FTG) detection, is a branch of Human Activity Recognition (HAR). Our study aims to detect two main phases of the gait (i.e., foot-off and foot-contact) corresponding to the moments when each foot is in contact with the ground or not. This will allow the medical professionals to characterize and identify the different phases of the human gait and their respective patterns. This detection process is paramount for extracting gait features (e.g., step width, stride width, gait speed, cadence, etc.) used by medical experts to highlight gait anomalies, stance issues, or any other walking irregularities. It will be used to assist health practitioners with patient monitoring, in addition to developing a full pipeline for FTG detection that would help compute gait indicators. In this paper, a comparison of different training configurations, including model architectures, data formatting, and pre-processing, was conducted to select the parameters leading to the highest detection accuracy. This binary classification provides a label for each timestamp informing whether the foot is in contact with the ground or not. Models such as CNN, LSTM, and ConvLSTM were the best fits for this study. Yet, we did not exclude DNNs and Machine Learning models, such as Random Forest and XGBoost from our work in order to have a wide range of possible comparisons. As a result of our experiments, which included 27 senior participants who had a stroke in the past wearing IMU sensors on their ankles, the ConvLSTM model achieved a high accuracy of 97.01% for raw windowed data with a size of 3 frames per window, and each window was formatted to have two superimposed channels (accelerometer and gyroscope channels). The model was trained to have the best detection without any knowledge of the participants’ personal information including age, gender, health condition, the type of activity, or the used foot. In other words, the model’s input data only originated from IMU sensors. Overall, in terms of FTG detection, the combination of the ConvLSTM model and the data representation had an important impact in outperforming other start-of-the-art configurations; in addition, the compromise between the model’s complexity and its accuracy is a major asset for deploying this model and developing real-time solutions.

Components of gait in people with and without mild cognitive impairment

BACKGROUND

Several objective gait parameters are associated with cognitive impairment, but there is limited knowledge of gait models in people with mild cognitive impairment (MCI).

RESEARCH QUESTION

How can 18 objective gait characteristics be used to define different components of gait in people with MCI (with suspected incipient neurocognitive disorder) and cognitively unimpaired people (CU), respectively?

METHODS

Spatiotemporal gait data were collected by using an electronic walkway (GAITRite®), i.e. assessments in comfortable gait speed. Using cross-sectional gait data, two principal component analyses (PCA) were performed (varimax rotation) to define different components of gait in people with MCI (n = 114) and CU (n = 219), respectively, from the BioFINDER-2 study.

RESULTS

Both PCAs produced four components, here called Variability, Pace/Stability, Rhythm and Asymmetry. Total variance explained was 81.0% (MCI) versus 80.3% (CU). The Variability component explained the largest amount of variance (about 25%) in both groups. The highest loading gait parameter was the same for both groups in three out of four components, i.e. step velocity variability (Variability), mean step length (Pace/Stability) and mean step time (Rhythm). In the asymmetry component, stance time asymmetry (MCI) and swing time asymmetry (CU) loaded the highest.

SIGNIFICANCE

The gait components seem similar in people with and without MCI, although there were some differences. This study may aid the identification of gait variables that represent different components of gait. Gait parameters such as step velocity variability, mean step length, mean step time as well as swing and stance time asymmetry could serve as interesting core variables of different gait components in future research in people with MCI (with suspected incipient neurocognitive disorder) and CU. However, the selection of gait variables depends on the purpose. It needs to be noted that assessment of variability measures requires more advanced technology than is usually used in the clinic.

Muscular Function as an Alternative to Identify Cognitive Impairment: A Secondary Analysis From SABE Colombia

BACKGROUND

Identification of cognitive impairment is based traditionally on the neuropsychological tests and biomarkers that are not available widely. This study aimed to establish the association between motor function (gait speed and handgrip strength) and cognitive performance in the Mini-Mental State Examination, globally and by domains. A secondary goal was calculating a cut-off point for gait speed and handgrip strength to classify older adults as cognitively impaired.

METHODS

This is a secondary analysis of SABE Colombia (Salud, Bienestar & Envejecimiento), a survey that was conducted in 2015 on health, wellbeing, and aging in Colombia. This study used linear regression models to search for an association between motor function and cognitive performance. The accuracy of motor function measurements in identifying cognitive impairment was assessed with receiver operating characteristic (ROC) curves. This study also analyzed other clinical and sociodemographical variables.

RESULTS

Gait speed was associated with orientation (r 2 = 0.16), language (r 2 = 0.15), recall memory (r 2 = 0.14), and counting (r 2 = 0.08). Similarly, handgrip strength was associated with orientation (r 2 = 0.175), language (r 2 = 0.164), recall memory (r 2 = 0.137), and counting (r 2 = 0.08). To differentiate older adults with and without cognitive impairment, a gait speed cut-off point of 0.59 m/s had an area under the curve (AUC) of 0.629 (0.613-0.646), and a weak handgrip (strength below 17.5 kg) had an AUC of 0.653 (0.645-0.661). The cut-off points for handgrip strength and gait speed were significantly higher in male participants.

CONCLUSIONS

Gait speed and handgrip strength are similarly associated with the cognitive performance, exhibiting the most extensive association with orientation and language domains of the Mini-Mental State Examination. Gait speed and handgrip strength can easily be measured by any clinician, and they prove to be useful screening tools to detect cognitive impairment.

Effects of curved path walking compared to straight path walking in older adults with cognitive deficits: A systematic review and network meta-analysis

OBJECTIVE

To determine whether the existing literature provides evidence that curved path walking time can be a reliable marker of cognitive impairment among older adults using a network meta-analysis (NMA).

DATA SOURCES

PubMed, Web of Science, ScienceDirect, Scopus, and Korean Studies Information Service System (KSISS) electronic databases were searched in December 2019.

STUDY SELECTION

Studies that included the following variables were selected: (P): patients with cognitive impairment, (I): straight path versus curved path walking, (C): control group without cognitive impairment, (O): walking time, and (S): cross-sectional or longitudinal study design. In total, 21 studies were selected for the NMA, which was performed to compare the standardized mean difference (SMD) of walking time on curved and straight paths.

RESULTS

Older adults with dementia had significantly longer walking times than older adults with mild cognitive impairment (MCI) for both straight path walking and curved path walking. The SMD of straight path walking time was 0.59 (95% credible interval [CrI]: 0.39, 0.81) for older adults with MCI and 0.90 (95% CrI: 0.65, 1.16) for older adults with dementia. The SMD of walking time on a curved path was 0.52 (95% CrI: -0.22, 1.26) for older adults with MCI and 1.98 (95% CrI: 1.20, 2.92) for those with dementia. In older adults with dementia, the correlation coefficient of the Fisher's z value was higher for curved path walking than for straight path walking.

CONCLUSION

The way people with dementia walk exhibits signs of cognitive impairments. NMA confirmed that older adults with dementia requires significantly longer time to walk the same distance than healthy controls or older adults with MCI for both curved and straight path walking.

Combining Transcranial Direct Current Stimulation With Tai Chi to Improve Dual-Task Gait Performance in Older Adults With Mild Cognitive Impairment: A Randomized Controlled Trial

Introduction: Engaging in a secondary task while walking increases motor-cognitive interference and exacerbates fall risk in older adults with mild cognitive impairment (MCI). Previous studies have demonstrated that Tai Chi (TC) may improve cognitive function and dual-task gait performance. Intriguingly, with emerging studies also indicating the potential of transcranial direct current stimulation (tDCS) in enhancing such motor-cognitive performance, whether combining tDCS with TC might be superior to TC alone is still unclear. The purpose of this study was to investigate the effects of combining tDCS with TC on dual-task gait in patients with MCI.

Materials and Methods: Twenty patients with MCI were randomly assigned to receive either anodal or sham tDCS, both combined with TC, for 36 sessions over 12 weeks. Subjects received 40 min of TC training in each session. During the first 20 min, they simultaneously received either anodal or sham tDCS over the left dorsolateral prefrontal cortex. Outcome measures included dual-task gait performance and other cognitive functions.

Results: There were significant interaction effects between groups on the cognitive dual task walking. Compared to sham, the anodal tDCS group demonstrated a greater improvement on cadence and dual task cost of speed.

Conclusion: Combining tDCS with TC may offer additional benefits over TC alone in enhancing dual-task gait performance in patients with MCI.

Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [TCTR20201201007].

Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification

Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a simple approach for estimating human body measurement data which could be used in walking speed-related health assessment. Conventional body measurement data of 2D images are dependent on body-worn garments (used as segmental markers) and are susceptible to changes in the distance between the participant and camera in indoor and outdoor settings. In this study, we propose five ratio-based body measurement data that can be extracted from 2D images and can be used to classify three walking speeds (i.e., slow, normal, and fast) using a deep learning-based bidirectional long short-term memory classification model. The results showed that average classification accuracies of 88.08% and 79.18% could be achieved in indoor and outdoor environments, respectively. Additionally, the proposed ratio-based body measurement data are independent of body-worn garments and not susceptible to changes in the distance between the walking individual and camera. As a simple but efficient technique, the proposed walking speed classification has great potential to be employed in clinics and aged care homes.

Innovative motor and cognitive dual-task approaches combining upper and lower limbs may improve dementia early detection

Motor and Cognitive Dual-Task (MCDT) represents an innovative chance to assess Mild Cognitive Impairment (MCI). We compare two novel MCDTs, fore-finger tapping (FTAP), toe-tapping (TTHP), to gold standards for cognitive screening (Mini-Mental State Examination-MMSE), and to a well-established MCDT (GAIT). We administered the aforementioned MCDTs to 44 subjects (MCIs and controls). Motor parameters were extracted, and correlations with MMSE investigated. Logistic regression models were built, and AUC areas computed. Spearman's correlation demonstrated that FTAP and TTHP significantly correlate with MMSE, at each cognitive load. AUC areas computed report similar (FTAP, 0.87), and even higher (TTHP, 0.97) capability to identify MCIs, if compared to GAIT (0.92). We investigated the use of novel MCDT approaches to assess MCI, aiming to enrich the clinical repertoire with objective and non-invasive tools. Our protocol shows good correlations with MMSE, and reaches high performances in identifying MCI, adopting simpler exercises.

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.

Gait Performance as an Indicator of Cognitive Deficit in Older People

Background: The purpose of this study was to analyze which gait variables are the best for detecting cognitive impairment and to determine if age and gender can influence gait variations in older people. Methods: 65 participants took part in this study (22 men and 43 women; age: 73.88 ± 9.56 years). We use the Montreal Cognitive Assessment (MoCA) to assess mild cognitive impairment (MCI). Gait speed (GS) and the complex gait test (CGT) were analyzed with photocells Witty (Microgate, Italia). The OptoGait system (Microgate, Italia) was used to analyze step length (SL) and step coefficient of variation (CV sl). Results: There was a significant association between MoCA and SL (r = 0.420; p = 0.002), CV sl (r = −0.591; p < 0.001), and CGT (r = −0.406; p = 0.001). Instrumental activities of daily living showed significant association with SL (r = 0.563; p < 0.001); CV sl (r = −0.762; p < 0.001), CGT (r = −0.622; p < 0.001), and GS (r = 0.418; p < 0.001). CV sl showed the best results with MoCA when linear regression analysis was applied (R² = 0.560; p = 0.007; Y = 23.669 − 0.320x). Participants older than 79 years showed lower MoCA scores and poorer gait parameters than people younger than 79 years. Conclusions: CV sl, SL, CGT, and GS make it possible to detect MCI in older people, especially when these variables are evaluated as a whole.

Functional objective parameters which may discriminate patients with mild cognitive impairment from cognitively healthy individuals: a systematic review and meta-analysis using an instrumented kinematic assessment

BACKGROUND

a systematic review in 2015 showed kinematic gait and balance parameters which can discriminate patients with mild cognitive impairment (MCI) from cognitively healthy individuals.

OBJECTIVE

this systematic review and meta-analysis aims to summarise and synthesise the evidence published after the previous review about the functional objective parameters obtained by an instrumented kinematic assessment which could discriminate patients with MCI from cognitively healthy individuals, as well as to assess the level of evidence per outcome.

METHODS

major electronic databases were searched from inception to August 2019 for cross-sectional studies published after 2015 examining kinematic gait and balance parameters, which may discriminate patients with MCI from cognitively healthy individuals. Meta-analysis was carried out for each parameter reported in two or more studies.

RESULTS

Ten cross-sectional studies with a total of 1,405 patients with MCI and 2,277 cognitively healthy individuals were included. Eight of the included studies reported a low risk of bias. Patients with MCI showed a slower gait speed than cognitively healthy individuals. Thus, single-task gait speed (d = -0.44, 95%CI [-0.60 to -0.28]; P < 0.001), gait speed at fast pace (d = -0.48, 95%CI [-0.72 to -0.24]; P < 0.001) and arithmetic dual-task gait speed (d = -1.20, 95%CI [-2.12 to -0.28]; P = 0.01) were the functional objective parameters which best discriminated both groups.

CONCLUSION

the present review shows kinematic gait parameters which may discriminate patients with MCI from cognitively healthy individuals. Most of the included studies reported a low risk of bias, but the grading of recommendations assessment, development and evaluation criteria showed a low level of evidence per outcome.

The use of Motor and Cognitive Dual-Task quantitative assessment on subjects with mild cognitive impairment: A systematic review

Dementia and Alzheimer's Disease (AD) represent a health emergency. The identification of valid and noninvasive markers to identify people with Mild Cognitive Impairment (MCI) is profoundly advocated. This review outlines the use of quantitative Motor and Cognitive Dual-Task (MCDT) on MCI, by technologies aid. We describe the framework and the most valuable researches, displaying the adopted protocols, and the available technologies. PubMed Central, Web of Science, and Scopus were inspected between January 2010 and May 2020. 1939 articles were found in the initial quest. Exclusion criteria allowed the selection of the most relevant papers; 38 papers were included. The articles, regarding four technological solutions "wearable sensors", "personal devices", "optokinetic systems", and "electronic walkways", are organized into three categories: "Quantitative MCDT", "MCDT Inspired by Neuropsychological Test", and "MCDT for MCI Stimulation". MCDT might furnish clinical landmarks, supplying aid for disease stratication, risk prediction, and intervention optimization. Such protocols could foster the use of data mining and machine learning techniques. Notwithstanding, there is still a need to standardize and harmonize such protocols.

Complex Gait Is Related to Cognitive Functioning in Older People: A Cross-Sectional Study Providing an Innovative Test

BACKGROUND

Many studies have demonstrated an inverse relationship between gait performance and cognitive impairment. The main purposes of this study were: (1) to design and validate a complex gait test (CGT) in older people, (2) to analyze the effects of age and sex on CGT, and (3) to analyze the association between CGT performance and physical functioning and cognitive measures.

METHODS

A total of 279 older people (60-97 years) were analyzed in 2019. Fitness tests, gait performance, and several cognitive measures such asthe Trail-Walking Test and Montreal Cognitive Assessment were used.

RESULTS

The CGT reported adequate reliability and validity parameters. In the test-retest analysis, the intra-class correlation coefficient was 0.868 (p < 0.001). There was a significant correlation between the CGT and Trail-Walking Test (r = 0.592; p < 0.001). The linear regression analysis showed that the CGT was associated with the Montreal Cognitive Assessment (R2 = 0.357; p =0.001). The binary logistic regression analysis revealed that a high CGT score was a risk factor for mild cognitive impairment (odds ratio 1.201, 95% CI 1.081-1.334; p = 0.001). The ROC curve of the mild cognitive impairment was predicted by the CGT performance (area under the curve = 0.768, 95% CI 0.647-0.889; p < 0.001), reaching the cut-off point at 20.25 s.

CONCLUSIONS

The CGT showed good reliability and validity and may serve as a potential biomarker in mild cognitive impairment prediction in older adults aged 60-97 years.

Comprehensive Quantitative Spatiotemporal Gait Analysis Identifies Gait Characteristics for Early Dementia Subtyping in Community Dwelling Older Adults

Background: Recent studies associated gait patterns with cognitive impairment stages. The current study examined the relation between dementia type and spatiotemporal gait characteristics under different walking conditions in pre and mild neurocognitive disorder stage.

Methods: Community-dwelling older adults (age 50+) with memory complaints consulting a memory clinic underwent, at baseline and during follow-up (every 4 months), a standard dementia assessment and a comprehensive spatiotemporal gait analysis [walking on an electronic walkway at usual pace (UP) with and without a counting-backwards (CW) or animal-reciting dual-task (AW), at fast (FP) and at slow (SP) pace]. At baseline the participants were categorized according to the Clinical Dementia Rating (CDR) scale. At the end of the study, the dementia diagnosis was used to stratify the categories in three outcome groups: developed “No-dementia,” “AD+FTD” (grouping Alzheimer's or Fronto-temporal dementia) or “VascD+LBD” dementia (grouping Vascular dementia or Lewy body dementia). The gait characteristics were compared per category in paired groups. Sub-analyzing in the ≥70-years-old participants evaluated the age effect.

Results: Five hundred and thirty-six participants, age 50-to-95-years old were followed for 31-to-41 months. In the CDR 0, no differences were seen between eventual dementia and no-dementia individuals. In the CDR 0.5, CW dual task cost (DTC) step width was larger in the imminent “AD+FTD” and AW (normalized) gait speed was slower in the future “VascD+LBD” group compared to the no-dementia participants. Slower UP (normalized) gait speed differed the future “VascD+LBD” from the “AD+FTD” individuals. In the CDR 1: Wider steps in UP, SP and CW differed the “VascD+LBD” from the “AD+FTD” group. In the ≥70-years old CDR 0 category, higher AW cycle time variability in the imminent “AD+FTD” dementia group, wider UP step width and higher AW cycle time variability in the “VascD+LBD” group differed them from the no-dementia group up to 3 years before dementia diagnosis. The distinctive gait characteristics between the no-dementia and the imminent dementia groups in CDR 0.5 and CDR 1 remained the same as in the overall group. However, no gait differences were found between “VascD+LBD” and “AD+FTD” groups in the pre-dementia stages.

Conclusion: Distinctive spatiotemporal gait characteristics were associated with specific dementia types up to 3 years before diagnosis. The association is influenced by the cognitive stage and age.

The impact of cognitive impairment on the physical ageing process

BACKGROUND

Physical decline and cognitive degeneration characterise the ageing process.

AIM

Physical parameters, performance and the functional indexes were studied in relation to age in healthy and cognitively impaired older persons to understand the interactions and changes during normal ageing, cognitive decline and progression to frailty.

METHODS

Cross-sectional analysis was performed on a data registry of an ambulatory Memory Diagnosis Centre. The quantitative gait characteristics at usual pace, body composition parameters, disability scales (activity of daily living and instrumental activity of daily living) and Rockwood frailty index were compared in cognitively healthy (CHI), mild cognitively impaired, mildly and moderately demented < 80-years old and > 80-years old adults.

RESULTS

Quality of gait deteriorated with age in CHI and cognitively impaired. Skeletal muscle mass index decreased when cognitive status worsened. Disability and frailty correlated with increasing cognitive impairment. Age, gender, cognitive impairment, body composition and Rockwood's Frailty scale had a combined forecasting effect, as well as the individual effect on the gait characteristics. Disability score, Frailty index, skeletal muscle mass and skeletal muscle mass index, gait speed, normalised mean step length and swing time variability in mildly demented < 80-years old adults mirrored the parameters in the CHI > 80-years old.

CONCLUSION

Quantitative gait characteristics, muscle mass and disabilities change along with cognitive impairment, frailty and age. A more rapid physical ageing process accompanies cognitive decline. Therefore, gait characteristics should be age-referenced and studies on gait in older persons should include muscle mass, frailty and cognitive parameters.

Relations Between Exercise Habit and Visual Attentional Ability in Older Adult Community Dwellers: Evidences From the Yakumo Study

Objective:

The relation between mild everyday exercise and cognitive ability in healthy older people was examined using cohort study database.

Methods:

Individually calculated linear regression coefficients in digit cancelation task performances for 11 years age from 65 to 75 years were compared between mild exercise habit holders and non-holders.

Results:

Exercise habit holders showed significantly smaller age-related decline than non-holders, irrespective of task difficulty.

Discussion:

The results suggested that even mild exercise habit for long years possesses benefits on sustaining cognitive function in older people as well as the physical activities such as programmed in a sport gym. It also becomes clear that it is difficult for ordinary older adult to continue exercising habits for many years. Therefore, more substantial ways are required for local health officials to advertise the effectiveness of mild exercise habits and to devise the necessary work to become a habit.

The relationship between gait variability and cognitive functions differs between fallers and non-fallers in MS

The objective of the study was to determine if cognitive function is associated with step time variability in people with multiple sclerosis (PwMS). The study included 355 PwMS (218 women), average age 41.1 (SD = 13.5), disease duration 5.9 (SD = 7.3) years, and a median expanded disability status scale score of 2.5. We separately analyzed the sample group of fallers and non-fallers based on their fall history. Gait variability was measured by an electronic walkway and all participants completed a computerized cognitive test battery designed to evaluate multiple cognitive domains. Fallers (43.7%) demonstrated elevated step time variability (%CV), 5.0 (SD = 3.4) vs. 3.5 (SD = 1.6), P < 0.001 compared to the non-faller subjects. According to the regression analysis in the non-fallers' group, step time variability was found significantly associated with the global cognitive score (P = 0.001), executive function subcategory (P = 0.038), and motor skills subcategory (P < 0.001). No relationship between step time variability and any cognitive domain was demonstrated in the faller group. This study illustrated that the association between gait variability and cognition occurs only in PwMS without a fall history. From a clinical standpoint, these findings might help medical professionals to create improved assessment tests and rehabilitation strategies in the MS population.