Gait and dementia

Walking fingerprinting

We consider the problem of predicting an individual's identity from accelerometry data collected during walking. In a previous paper, we transformed the accelerometry time series into an image by constructing the joint distribution of the acceleration and lagged acceleration for a vector of lags. Predictors derived by partitioning this image into grid cells were used in logistic regression to predict individuals. Here, we (a) implement machine learning methods for prediction using the grid cell-derived predictors; (b) derive inferential methods to screen for the most predictive grid cells while adjusting for correlation and multiple comparisons; and (c) develop a novel multivariate functional regression model that avoids partitioning the predictor space. Prediction methods are compared on two open source acceleometry data sets collected from: (a) 32 individuals walking on a 1.06 km path; and (b) six repetitions of walking on a 20 m path on two occasions at least 1 week apart for 153 study participants. In the 32-individual study, all methods achieve at least 95% rank-1 accuracy, while in the 153-individual study, accuracy varies from 41% to 98%, depending on the method and prediction task. Methods provide insights into why some individuals are easier to predict than others.

Alzheimer's Disease: Understanding Motor Impairments

Alzheimer's disease (AD), the most prevalent neurodegenerative disorder and the leading cause of dementia worldwide, profoundly impacts health and quality of life. While cognitive impairments-such as memory loss, attention deficits, and disorientation-predominate in AD, motor symptoms, though common, remain underexplored. These motor symptoms, including gait disturbances, reduced cardiorespiratory fitness, muscle weakness, sarcopenia, and impaired balance, are often associated with advanced stages of AD and contribute to increased mortality. Emerging evidence, however, suggests that motor symptoms may be present in earlier stages and can serve as predictive markers for AD in older adults. Despite a limited understanding of the underlying mechanisms driving these motor symptoms, several key pathways have been identified, offering avenues for further investigation. This review provides an in-depth analysis of motor symptoms in AD, discussing its progression, potential mechanisms, and therapeutic strategies. Addressing motor symptoms alongside cognitive decline may enhance patient functionality, improve quality of life, and support more comprehensive disease management strategies.

Linking Dementia Pathology and Alteration in Brain Activation to Complex Daily Functional Decline During the Preclinical Dementia Stages: Protocol for a Prospective Observational Cohort Study

BACKGROUND

Progressive difficulty in performing everyday functional activities is a key diagnostic feature of dementia syndromes. However, not much is known about the neural signature of functional decline, particularly during the very early stages of dementia. Early intervention before overt impairment is observed offers the best hope of reducing the burdens of Alzheimer disease (AD) and other dementias. However, to justify early intervention, those at risk need to be detected earlier and more accurately. The decline in complex daily function (CdF) such as managing medications has been reported to precede impairment in basic activities of daily living (eg, eating and dressing).

OBJECTIVE

Our goal is to establish the neural signature of decline in CdF during the preclinical dementia period.

METHODS

Gait is central to many CdF and community-based activities. Hence, to elucidate the neural signature of CdF, we validated a novel electroencephalographic approach to measuring gait-related brain activation while participants perform complex gait-based functional tasks. We hypothesize that dementia-related pathology during the preclinical period activates a unique gait-related electroencephalographic (grEEG) pattern that predicts a subsequent decline in CdF.

RESULTS

We provide preliminary findings showing that older adults reporting CdF limitations can be characterized by a unique gait-related neural signature: weaker sensorimotor and stronger motor control activation. This subsample also had smaller brain volume and white matter hyperintensities in regions affected early by dementia and engaged in less physical exercise. We propose a prospective observational cohort study in cognitively unimpaired older adults with and without subclinical AD (plasma amyloid-β) and vascular (white matter hyperintensities) pathologies. We aim to (1) establish the unique grEEG activation as the neural signature and predictor of decline in CdF during the preclinical dementia period; (2) determine associations between dementia-related pathologies and incidence of the neural signature of CdF; and (3) establish associations between a dementia risk factor, physical inactivity, and the neural signature of CdF.

CONCLUSIONS

By establishing the clinical relevance and biological basis of the neural signature of CdF decline, we aim to improve prediction during the preclinical stages of ADs and other dementias. Our approach has important research and translational implications because grEEG protocols are relatively inexpensive and portable, and predicting CdF decline may have real-world benefits.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56726.

Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study

Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, β, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and β bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, β ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.

Machine Learning Approaches for Dementia Detection Through Speech and Gait Analysis: A Systematic Literature Review

Background

Dementia is a general term for several progressive neurodegenerative disorders including Alzheimer's disease. Timely and accurate detection is crucial for early intervention. Advancements in artificial intelligence present significant potential for using machine learning to aid in early detection.

Objective

Summarize the state-of-the-art machine learning-based approaches for dementia prediction, focusing on non-invasive methods, as the burden on the patients is lower. Specifically, the analysis of gait and speech performance can offer insights into cognitive health through clinically cost-effective screening methods.

Methods

A systematic literature review was conducted following the PRISMA protocol (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The search was performed on three electronic databases (Scopus, Web of Science, and PubMed) to identify the relevant studies published between 2017 to 2022. A total of 40 papers were selected for review.

Results

The most common machine learning methods employed were support vector machine followed by deep learning. Studies suggested the use of multimodal approaches as they can provide comprehensive and better prediction performance. Deep learning application in gait studies is still in the early stages as few studies have applied it. Moreover, including features of whole body movement contribute to better classification accuracy. Regarding speech studies, the combination of different parameters (acoustic, linguistic, cognitive testing) produced better results.

Conclusions

The review highlights the potential of machine learning, particularly non-invasive approaches, in the early prediction of dementia. The comparable prediction accuracies of manual and automatic speech analysis indicate an imminent fully automated approach for dementia detection.

Using dual-task gait to recognize Alzheimer's disease and mild cognitive impairment: a cross-sectional study

Background

Gait is a potential diagnostic tool for detecting mild cognitive impairment (MCI) and Alzheimer's disease (AD). Nevertheless, little attention has been paid to arm movements during walking, and there is currently no consensus on gait asymmetry. Therefore, in this study, we aimed to determine whether arm motion and gait asymmetry could be utilized for identifying MCI and AD.

Methods

In total, 102 middle-aged and elderly individuals were included in the final analysis and were assigned to the following three groups: AD (n = 27), MCI (n = 35), and a normal control group (n = 40). Gait and cognitive assessments were conducted for all participants. Gait detection included a single-task gait with free-speed walking and a dual-task gait with adding a cognitive task of successive minus seven to walking. Original gait parameters were collected using a wearable device featuring the MATRIX system 2.0. Gait parameters were shortened to several main gait domains through factor analysis using principal component extraction with varimax rotation. Subsequently, the extracted gait domains were used to differentiate the three groups, and the area under the receiver operating characteristic curve was calculated.

Results

Factor analysis of single-task gait identified five independent gait domains: rhythm symmetry, rhythm, pace asymmetry, arm motion, and variability. Factor analysis of the dual-task gait identified four gait domains: rhythm, variability, symmetry, and arm motion. During single-task walking, pace asymmetry was negatively correlated with MoCA scores and could distinguish between the AD group and the other two groups. Arm motion was not associated with MoCA scores, and did not exhibit adequate discrimination in either task.

Conclusion

Currently, there is no reliable evidence suggesting that arm motion can be used to recognize AD or MCI. Gait asymmetry can serve as a potential gait marker for the auxiliary diagnosis of AD but not for MCI.

Multimodal learning of clinically accessible tests to aid diagnosis of neurodegenerative disorders: a scoping review

With ageing populations around the world, there is a rapid rise in the number of people with Alzheimer's disease (AD) and Parkinson's disease (PD), the two most common types of neurodegenerative disorders. There is an urgent need to find new ways of aiding early diagnosis of these conditions. Multimodal learning of clinically accessible data is a relatively new approach that holds great potential to support early precise diagnosis. This scoping review follows the PRSIMA guidelines and we analysed 46 papers, comprising 11,750 participants, 3569 with AD, 978 with PD, and 2482 healthy controls; the recency of this topic was highlighted by nearly all papers being published in the last 5 years. It highlights the effectiveness of combining different types of data, such as brain scans, cognitive scores, speech and language, gait, hand and eye movements, and genetic assessments for the early detection of AD and PD. The review also outlines the AI methods and the model used in each study, which includes feature extraction, feature selection, feature fusion, and using multi-source discriminative features for classification. The review identifies knowledge gaps around the need to validate findings and address limitations such as small sample sizes. Applying multimodal learning of clinically accessible tests holds strong potential to aid the development of low-cost, reliable, and non-invasive methods for early detection of AD and PD.

Artificial Intelligence Distinguishes Pathological Gait: The Analysis of Markerless Motion Capture Gait Data Acquired by an iOS Application (TDPT-GT)

Distinguishing pathological gait is challenging in neurology because of the difficulty of capturing total body movement and its analysis. We aimed to obtain a convenient recording with an iPhone and establish an algorithm based on deep learning. From May 2021 to November 2022 at Yamagata University Hospital, Shiga University, and Takahata Town, patients with idiopathic normal pressure hydrocephalus (n = 48), Parkinson's disease (n = 21), and other neuromuscular diseases (n = 45) comprised the pathological gait group (n = 114), and the control group consisted of 160 healthy volunteers. iPhone application TDPT-GT captured the subjects walking in a circular path of about 1 meter in diameter, a markerless motion capture system, with an iPhone camera, which generated the three-axis 30 frames per second (fps) relative coordinates of 27 body points. A light gradient boosting machine (Light GBM) with stratified k-fold cross-validation (k = 5) was applied for gait collection for about 1 min per person. The median ability model tested 200 frames of each person's data for its distinction capability, which resulted in the area under a curve of 0.719. The pathological gait captured by the iPhone could be distinguished by artificial intelligence.

Embodied decision biases: individually stable across different tasks?

In everyday life, action and decision-making often run in parallel. Action-based models argue that action and decision-making strongly interact and, more specifically, that action can bias decision-making. This embodied decision bias is thought to originate from changes in motor costs and/or cognitive crosstalk. Recent research confirmed embodied decision biases for different tasks including walking and manual movements. Yet, whether such biases generalize within individuals across different tasks remains to be determined. To test this, we used two different decision-making tasks that have independently been shown to reliably produce embodied decision biases. In a within-participant design, participants performed two tasks in a counterbalanced fashion: (i) a walking paradigm for which it is known that motor costs systematically influence reward decisions, and (ii) a manual movement task in which motor costs and cognitive crosstalk have been shown to impact reward decisions. In both tasks, we successfully replicated the predicted embodied decision biases. However, there was no evidence that the strength of the biases correlated between tasks. Hence, our findings do not confirm that embodied decision biases transfer between tasks. Future research is needed to examine whether this lack of transfer may be due to different causes underlying the impact of motor costs on decisions and the impact of cognitive crosstalk or task-specific differences.

Health Conditions Associated with Alzheimer's Disease and Vascular Dementia

OBJECTIVE

We examined medical records to determine health conditions associated with dementia at varied intervals prior to dementia diagnosis in participants from the Baltimore Longitudinal Study of Aging (BLSA).

METHODS

Data were available for 347 Alzheimer's disease (AD), 76 vascular dementia (VaD), and 811 control participants without dementia. Logistic regressions were performed associating International Classification of Diseases, 9th Revision (ICD-9) health codes with dementia status across all time points, at 5 and 1 year(s) prior to dementia diagnosis, and at the year of diagnosis, controlling for age, sex, and follow-up length of the medical record.

RESULTS

In AD, the earliest and most consistent associations across all time points included depression, erectile dysfunction, gait abnormalities, hearing loss, and nervous and musculoskeletal symptoms. Cardiomegaly, urinary incontinence, non-epithelial skin cancer, and pneumonia were not significant until 1 year before dementia diagnosis. In VaD, the earliest and most consistent associations across all time points included abnormal electrocardiogram (EKG), cardiac dysrhythmias, cerebrovascular disease, non-epithelial skin cancer, depression, and hearing loss. Atrial fibrillation, occlusion of cerebral arteries, essential tremor, and abnormal reflexes were not significant until 1 year before dementia diagnosis.

INTERPRETATION

These findings suggest that some health conditions are associated with future dementia beginning at least 5 years before dementia diagnosis and are consistently seen over time, while others only reach significance closer to the date of diagnosis. These results also show that there are both shared and distinctive health conditions associated with AD and VaD. These results reinforce the need for medical intervention and treatment to lessen the impact of health comorbidities in the aging population. ANN NEUROL 2023;93:805-818.

Clinical and MRI features of gait and balance disorders in neurodegenerative diseases

Gait and balance disorders are common signs in several neurodegenerative diseases such as Parkinson's disease, atypical parkinsonism, idiopathic normal pressure hydrocephalus, cerebrovascular disease, dementing disorders and multiple sclerosis. According to each condition, patients present with different gait and balance alterations depending on the structural and functional brain changes through the disease course. In this review, we will summarize the main clinical characteristics of gait and balance disorders in the major neurodegenerative conditions, providing an overview of the significant structural and functional MRI brain alterations underlying these deficits. We also will discuss the role of neurorehabilitation strategies in promoting brain plasticity and gait/balance improvements in these patients.

Effects of Dementia on Outcomes after Cervical Spine Injuries in Elderly Patients: Evaluation of 1512 Cases in a Nationwide Multicenter Study in Japan

We aimed to retrospectively investigate the demographic characteristics and short-term outcomes of traumatic cervical spine injuries in patients with dementia. We enrolled 1512 patients aged ≥ 65 years with traumatic cervical injuries registered in a multicenter study database. Patients were divided into two groups according to the presence of dementia, and 95 patients (6.3%) had dementia. Univariate analysis revealed that the dementia group comprised patients who were older and predominantly female and had lower body mass index, higher modified 5-item frailty index (mFI-5), lower pre-injury activities of daily living (ADLs), and a larger number of comorbidities than patients without dementia. Furthermore, 61 patient pairs were selected through propensity score matching with adjustments for age, sex, pre-injury ADLs, American Spinal Injury Association Impairment Scale score at the time of injury, and the administration of surgical treatment. In the univariate analysis of the matched groups, patients with dementia had significantly lower ADLs at 6 months and a higher incidence of dysphagia up to 6 months than patients without dementia. Kaplan-Meier analysis revealed that patients with dementia had a higher mortality than those without dementia until the last follow-up. Dementia was associated with poor ADLs and higher mortality rates after traumatic cervical spine injuries in elderly patients.

Gait dysfunction in Alzheimer disease

Alzheimer's disease (AD) is the most common cause of age-associated dementia and will exponentially rise in prevalence in the coming decades, supporting the parallel development of the early stage detection and disease-modifying strategies. While primarily considered as a cognitive disorder, AD also features motor symptoms, primarily gait dysfunction. Such gait abnormalities can be phenotyped across classic clinical syndromes as well as by quantitative kinematic assessments to address subtle dysfunction at preclinical and prodromal stages. As such, certain measures of gait can predict the future cognitive and functional decline. Moreover, cross-sectional and longitudinal studies have associated gait abnormalities with imaging, biofluid, and genetic markers of AD across all stages. This suggests that gait assessment is an important tool in the clinical assessment of patients across the AD spectrum, especially to help identify at-risk individuals.

Six-month change in gait speed to discriminate between those with and without falls history in older people with Mild Cognitive Impairment and mild Alzheimer disease

BACKGROUND AND PURPOSE

The purposes of this study were to identify differences in gait speed performance over 6 months between older people with Preserved Cognition (PrC), with Mild Cognitive Impairment (MCI) and with Alzheimer disease (AD) in mild stage; and to verify if the change in gait speed could discriminate fallers in older people with MCI and AD in a mild stage METHODS: A longitudinal study was conducted with community-dwelling older adults, including 40 with PrC, 36 with MCI and 34 with AD in the mild stage. Gait speed (in m/s) changes were captured through a 10-meter walk test. We documented the number of self-reported falls by monthly calendars that were returned after a 6-month follow-up. During this period, the participants received monthly telephone calls to remind them to fill in the calendar RESULTS: There was a significant difference in terms of sex and age between the groups: 23%, 31% and 19% were female and had a mean age of 72.8, 75.9 and 76.9 years in the PrC, MCI and AD groups respectively. During the follow-up, 45%, 52.7% and 52.9% of the PrC, MCI and AD groups fell. The MCI and AD groups presented lower gait speed compared to the PrC Group at both moments. There was no significant difference in the change of gait speed between groups. In the model adjusted by age, the change in gait speed failed to discriminate fallers in older people with MCI and with AD CONCLUSION: Older people with MCI and AD in the mild stage present lower gait speed compared to older people with PrC. Changes in gait speed over a short period of time do not discriminate fallers in older people with MCI or AD in a mild stage.

Use of the Tokyo Cognitive Assessment for mild cognitive impairment to characterize elderly people that use day care services in Japan

[Purpose] This study compared the motor skills and cognitive functions of elderly participants who required support with those who did not require support. We aimed to evaluate the characteristics of impairment in sub-items of cognitive function in patients who needed support to predict future clinical issues. [Participants and Methods] We surveyed 31 participants requiring support under the day care service insurance system for which they attended day care service centers in Japan (rehabilitation users) and 10 healthy participants who attended a university for lifelong learning (healthy elders). Data on personal attributes of the participants were collected, and the Cardio-Ankle Vascular Index and motor and cognitive functions were assessed. [Results] Although the participants undergoing rehabilitation were, on average, 6 years older than the healthy elders, we found no significant differences between the two groups in closed-eye, one-legged standing, grip strength, or quadriceps muscle strength. In terms of the Tokyo Cognitive Assessment for mild cognitive impairment, we found no significant differences between those undergoing rehabilitation and healthy elders in clock drawing performance, serial 7 task performance, or orientation; however, there were significant differences in erase character, copy of triangular pyramid, composition, read of digits, go/no-go, word recall, story reproduction, ToCA total score. [Conclusion] We believe that it is imperative for day care service centers to conduct programs that maintain cognitive function in addition to programs for improvement of physical function.

A Review of the Measurement of the Neurology of Gait in Cognitive Dysfunction or Dementia, Focusing on the Application of fNIRS during Dual-Task Gait Assessment

Poor motor function or physical performance is a predictor of cognitive decline. Additionally, slow gait speed is associated with poor cognitive performance, with gait disturbances being a risk factor for dementia. Parallel declines in muscular and cognitive performance (resulting in cognitive frailty) might be driven primarily by muscle deterioration, but bidirectional pathways involving muscle–brain crosstalk through the central and peripheral nervous systems are likely to exist. Following screening, early-stage parallel declines may be manageable and modifiable through simple interventions. Gait–brain relationships in dementia and the underlying mechanisms are not fully understood; therefore, the current authors critically reviewed the literature on the gait–brain relationship and the underlying mechanisms and the feasibility/accuracy of assessment tools in order to identify research gaps. The authors suggest that dual-task gait is involved in concurrent cognitive and motor activities, reflecting how the brain allocates resources when gait is challenged by an additional task and that poor performance on dual-task gait is a predictor of dementia onset. Thus, tools or protocols that allow the identification of subtle disease- or disorder-related changes in gait are highly desirable to improve diagnosis. Functional near-infrared spectroscopy (fNIRS) is a non-invasive, cost-effective, safe, simple, portable, and non-motion-sensitive neuroimaging technique, widely used in studies of clinical populations such as people suffering from Alzheimer’s disease, depression, and other chronic neurological disorders. If fNIRS can help researchers to better understand gait disturbance, then fNIRS could form the basis of a cost-effective means of identifying people at risk of cognitive dysfunction and dementia. The major research gap identified in this review relates to the role of the central/peripheral nervous system when performing dual tasks.

Influence of Cardiovascular Risk Burden on Motor Function Among Older Adults: Mediating Role of Cardiovascular Diseases Accumulation and Cognitive Decline

Purpose

This study aimed to investigate the association of the cardiovascular risk burden assessed by the Framingham General Cardiovascular Risk Score (FGCRS) with the trajectories of motor function over time and to assess the mediating effects of cardiovascular diseases (CVDs) accumulation and cognitive decline in such association.

Methods

In Rush Memory and Aging Project, a total of 1,378 physical health participants (mean age: 79.3 ± 7.3 years) were followed up for up to 22 years. FGCRS at baseline was assessed and categorized into tertiles (lowest, middle, and highest). Global motor function (including dexterity, gait, and hand strength) was assessed annually with 10 motor tests. CVDs (including stroke, congestive heart failure, and other heart diseases) were ascertained at baseline and follow-ups, and the number of CVDs accumulation over time was assessed. Global cognitive function was tested annually by 19 tests. Data were analyzed using the linear mixed-effects models and mediation analysis.

Results

At baseline, FGCRS ranged from 4 to 28 (mean score: 15.6 ± 3.7). Over the follow-up (median: 5.3 years; interquartile range: 2.9-9.0 years), in multi-adjusted mixed-effects models, the highest FGCRS was associated with faster decline in global motor function (β = -0.0038; 95% confidence interval [CI]: -0.0069 to -0.0008), dexterity (β = -0.0056; 95% CI: -0.0093 to -0.0020), gait (β = -0.0039; 95% CI: -0.0077 to -0.0001), and hand strength (β = -0.0053; 95% CI: -0.0098 to -0.0008) compared with the lowest tertile. In mediation analysis, CVDs accumulation and cognitive decline mediated 8.4% and 42.9% of the association between FGCRS and global motor function over time, respectively.

Conclusion

Higher cardiovascular risk burden is associated with a faster decline in motor function including dexterity, gait, and hand strength. CVDs accumulation and cognitive decline may partially mediate the association between cardiovascular risk burden and global motor function decline.

Prediction of Disorientation by Accelerometric and Gait Features in Young and Older Adults Navigating in a Virtually Enriched Environment

Objective

To determine whether gait and accelerometric features can predict disorientation events in young and older adults.

Methods

Cognitively healthy younger (18–40 years, n = 25) and older (60–85 years, n = 28) participants navigated on a treadmill through a virtual representation of the city of Rostock featured within the Gait Real-Time Analysis Interactive Lab (GRAIL) system. We conducted Bayesian Poisson regression to determine the association of navigation performance with domain-specific cognitive functions. We determined associations of gait and accelerometric features with disorientation events in real-time data using Bayesian generalized mixed effect models. The accuracy of gait and accelerometric features to predict disorientation events was determined using cross-validated support vector machines (SVM) and Hidden Markov models (HMM).

Results

Bayesian analysis revealed strong evidence for the effect of gait and accelerometric features on disorientation. The evidence supported a relationship between executive functions but not visuospatial abilities and perspective taking with navigation performance. Despite these effects, the cross-validated percentage of correctly assigned instances of disorientation was only 72% in the SVM and 63% in the HMM analysis using gait and accelerometric features as predictors.

Conclusion

Disorientation is reflected in spatiotemporal gait features and the accelerometric signal as a potentially more easily accessible surrogate for gait features. At the same time, such measurements probably need to be enriched with other parameters to be sufficiently accurate for individual prediction of disorientation events.

Motoric Cognitive Risk Syndrome: Symptoms, Pathology, Diagnosis, and Recovery

The motoric cognitive risk (MCR) syndrome is a pre-dementia condition, marked by the enhanced risk for Alzheimer's disease (AD) and vascular dementia, together with falls, disability, and abnormal movements. The research studies revealed the distinct neurological and non-neurological clinical gait irregularities during dementia and accelerated functional decline, such as postural and balance impairments, memory loss, cognitive failure, and metabolic dysfunctions. The disabling characteristics of MCR comprise altered afferent sensory and efferent motor responses, together with disrupted visual, vestibular, and proprioceptive components. The pathological basis of MCR relates with the frontal lacunar infarcts, white matter hyperintensity (WMH), gray matter atrophy in the pre-motor and pre-frontal cortex, abnormal cholinergic functioning, inflammatory responses, and genetic factors. Further, cerebrovascular lesions and cardiovascular disorders exacerbate the disease pathology. The diagnosis of MCR is carried out through neuropsychological tests, biomarker assays, imaging studies, questionnaire-based evaluation, and motor function tests, including walking speed, dual-task gait tests, and ambulation ability. Recovery from MCR may include cognitive, physical, and social activities, exercise, diet, nutritional supplements, symptomatic drug treatment, and lifestyle habits that restrict the disease progression. Psychotherapeutic counseling, anti-depressants, and vitamins may support motor and cognitive improvement, primarily through the restorative pathways. However, an in-depth understanding of the association of immobility, dementia, and cognitive stress with MCR requires additional clinical and pre-clinical studies. They may have a significant contribution in reducing MCR syndrome and the risk for dementia. Overall, the current review informs the vital connection between gait performance and cognition in MCR and highlights the usefulness of future research in the discernment and treatment of dementiating illness.

Relationships between Gait Regularity and Cognitive Function, including Cognitive Domains and Mild Cognitive Impairment, in Community-Dwelling Older People

The aim of this cross-sectional study was to examine the correlations between gait regularity, cognitive functions including cognitive domains, and the mild cognitive impairment (MCI) in community-dwelling older people. This study included 463 older adults (63.4% women, mean age: 74.1), and their step and stride regularity along the three-axis components was estimated from trunk acceleration, which was measured by inertial measurement units during a comfortable gait. Four aspects of cognitive function were assessed using a tablet computer: attention, executive function, processing speed, and memory, and participants were classified into those with or without MCI. The vertical component of stride and step regularity was associated with attention and executive function (r = -0.176--0.109, p ≤ 0.019), and processing speed (r = 0.152, p < 0.001), after it was adjusted for age and gait speed. The low vertical component of step regularity was related to the MCI after it was adjusted for covariates (OR 0.019; p = 0.016). The results revealed that cognitive function could affect gait regularity, and the vertical component of gait regularity, as measured by a wearable sensor, could play an important role in investigating cognitive decline in older people.

Contribution of a multicomponent intervention on functional capacity and independence on activities of daily living in individuals with neurocognitive disorder

BACKGROUND

To examine the effects of a 6-month multicomponent (MT) exercise intervention in the functional capacity and ability to independently perform activities of daily living (ADL) of individuals diagnosed with neurocognitive disorder (NCD).

METHODS

A quasi-experimental controlled trial with a parallel design study was conducted in multicentered community-based settings. Forty-three individuals (N Female: 30) were allocated to an exercise group (EG; N: 23; mean 75.09, SD = 5.54 years) or a control group (CG; N:20; mean 81.90, SD = 1.33 years). The EG engaged in a 6-month MT program (60-min sessions, twice a week). Exercise sessions were divided into a warm-up, specific training (e.g., coordination and balance, lower and upper body strength, and aerobics), and cool down. Lower body function, mobility, and gait speed were evaluated through Short Physical Performance Battery (SPPB), Timed-Up and Go test (TUG) and 6-Meter Walk test, respectively. The Barthel Index (BI) was administered to assess individuals' ADL independence. Evaluations were performed before and after the 6-month intervention.

RESULTS

Linear Mixed Models revealed a statistically significant interaction (time X group) effect factor on SPPB (B = 2.33, 95% CI: 1.39-3.28, p < 0.001), TUG (B = - 11.15, 95% CI: - 17.23 - - 5.06, p = 0.001), and 6-Meter Walk test (B = 0.17, 95% CI: 0.08-0.25, p < 0.001). No differences between groups or assessment moments were found in the ability of individuals to independently perform ADL.

CONCLUSIONS

The 6-month MT exercise intervention improves the functional capacity of older adults living with NCD.

TRIAL REGISTRATION

ClinicalTrials.gov - identifier number NCT04095962 ; retrospectively registered on 19 September 2019.

Relationship between peripheral neuropathy and cognitive performance in the elderly population

ABSTRACT

There are only a few studies that have shown an association of peripheral neuropathy with cognitive impairment in elderly individuals. Therefore, we investigated the relationship between cognitive performance and peripheral neuropathy.From the database of the National Health and Nutrition Examination Survey (NHANES, 1999-2002), each participant completed a household interview, physical performance test, questionnaire regarding personal health, and Digit Symbol Substitution Test (DSST) to evaluate cognitive performance. The severity of peripheral neuropathy was assessed based on the number of insensate areas in both feet during monofilament examination. We used the multivariate linear regression to analyze the association of the DSST findings with insensate areas of the worse foot.There were 828 participants in our study from NHANES 1999 to 2002; their mean age was 69.96 ± 7.38 years, and 51.3% were male. The β coefficients of the number of insensate areas associated with the DSST findings were all negative values, and the absolute value increased as the number of insensate areas increased. After adjustment for pertinent variables, the correlations remained significantly negative (all P for trend <.001). In addition, subgroup analysis showed no gender differences in the negative association, but this association was not significant in obese participants (P > .05).Our study provides evidence that the severity of peripheral neuropathy is significantly negatively correlated with cognitive performance.

Physical performance across the cognitive spectrum and between dementia subtypes in a population-based sample of older adults: The HUNT study

BACKGROUND

Literature on physical performance in older adults across the cognitive spectrum remains inconclusive, and knowledge on differences between dementia subtypes is lacking. We aim to identify distinct physical-performance deficits across the cognitive spectrum and between dementia subtypes.

METHODS

11,466 persons were included from the 70-year-and-older cohort in the fourth wave of the Trøndelag Health Study (HUNT4 70+). Physical performance was assessed with the Short Physical Performance Battery (SPPB), 4-meter gait speed, five-times-sit-to-stand (FTSS), grip strength and one-leg-standing (OLS). Clinical experts diagnosed dementia per DSM-5 criteria. Multiple linear and logistic regression were performed to analyze differences between groups. Age, sex, education, somatic comorbidity, physical activity and smoking status were used as covariates.

RESULTS

Gait speed declined across the cognitive spectrum, beginning in people with subjective cognitive decline (SCD). Participants with mild cognitive impairment (MCI) additionally showed reduced lower-limb muscle strength, balance and grip strength. Those with dementia scored lowest on all physical-performance measures. Participants with Alzheimer's disease (AD) had a higher SPPB sum score and faster gait speed than participants with vascular dementia (VaD) and Lewy body dementia (LBD); participants with VaD and LBD had lower odds of being able to perform FTSS and OLS than participants with AD.

CONCLUSIONS

Physical performance declined across the spectrum from cognitively healthy to SCD to MCI and to dementia. Participants with AD performed better on all assessments except grip strength than participants with VaD and LBD. Stage of cognitive impairment and dementia subtype should guide exercise interventions to prevent mobility decline and dependency.

Early mobility after fragility hip fracture: a mixed methods embedded case study

BACKGROUND

Following a hip fracture up to 60% of patients are unable to regain their pre-fracture level of mobility. For hospitalized older adults, the deconditioning effect of bedrest and functional decline has been identified as the most preventable cause of ambulation loss. Recent studies demonstrate that this older adult population spends greater than 80% of their time in bed during hospitalization, despite being ambulatory before their fracture. We do not fully understand why there continues to be such high rates of sedentary times, given that evidence demonstrates functional decline is preventable and early mobility recommendations have been available for over a decade.

METHODS

A descriptive mixed method embedded case study was selected to understand the phenomenon of early mobility after fragility hip fracture surgery. In this study, the main case was one post-operative unit with a history of recommendation implementation, and the embedded units were patients recovering from hip fracture repair. Data from multiple sources provided an understanding of mobility activity initiation and patient participation.

RESULTS

Activity monitor data from eighteen participants demonstrated a mean sedentary time of 23.18 h. Median upright time was 24 min, and median number of steps taken was 30. Qualitative interviews from healthcare providers and patients identified two main categories of themes; themes external to the person and themes unique to the person. We identified four factors that can influence mobility; a patient's pre-fracture functional status, cognitive status, medical unpredictability, and preconceived notions held by healthcare providers and patients.

CONCLUSIONS

There are multi-level factors that require consideration with implementation of best practice interventions, namely, systemic, healthcare provider related, and patient related. An increased risk of poor outcomes occurs with compounding multiple factors, such as a patient with low pre-fracture functional mobility, cognitive impairment, and a mismatch of expectations. The study reports several variables to be important considerations for facilitating early mobility. Communicating mobility expectations and addressing physical and psychological readiness are essential. Our findings can be used to develop meaningful healthcare provider and patient-centred interventions to address the risks of poor outcomes.

Bidirectional relationship between depressive symptoms and physical performance in community-dwelling older people with subjective memory complaints

PURPOSE

This study examined the bidirectional relationship between depressive symptoms and physical performance in community-dwelling older people with subjective memory complaints.

METHODS

Secondary analyses using data from the Multidomain Alzheimer Preventive Trial (MAPT) study were performed. The participants were 1679 subjects (female, 64.8%; mean age, 75.3 ± 4.4 years). The outcome measures were depressive symptoms assessed by the 15-item Geriatric Depression Scale (GDS) and physical performance assessed by the Short Physical Performance Battery (SPPB) and handgrip strength (HGS). All measurements were performed at baseline and at 6, 12, 24, and 36 months. The bidirectional relationships of GDS with SPPB and HGS were examined using mixed-effect regression analysis.

RESULTS

Baseline physical performance was significantly associated with a decreased GDS score (SPPB score: β = - 0.210, 95% confidence interval [CI], - 0.283 to - 0.137; HGS: β = - 0.038, 95% CI - 0.056 to - 0.019). The baseline GDS score was significantly associated with decreased physical performance (SPPB score: β = - 0.082, 95% CI - 0.107 to - 0.056; HGS: β = - 0.261, 95% CI - 0.370 to - 0.152).

CONCLUSION

Since depressive symptoms and physical performance had a bidirectional relationship, prevention or improvement of decreased physical performance could play a role in reducing depressive symptoms, and addressing depressive symptoms may play a role in improving physical performance.

TRIAL REGISTRATION NUMBER

NCT01513252.

Gait and balance disturbances are common in young urbanites and associated with cognitive impairment. Air pollution and the historical development of Alzheimer's disease in the young

To determine whether gait and balance dysfunction are present in young urbanites exposed to fine particular matter PM2.5 ≥ annual USEPA standard, we tested gait and balance with Tinetti and Berg tests in 575 clinically healthy subjects, age 21.0 ± 5.7 y who were residents in Metropolitan Mexico City, Villahermosa and Reynosa. The Montreal Cognitive Assessment was also applied to an independent cohort n:76, age 23.3 ± 9.1 y. In the 575 cohort, 75.4% and 34.4% had abnormal total Tinetti and Berg scores and high risk of falls in 17.2% and 5.7% respectively. BMI impacted negatively Tinetti and Berg performance. Gait dysfunction worsen with age and males performed worse than females. Gait and balance dysfunction were associated with mild cognitive impairment MCI (19.73%) and dementia (55.26%) in 57/76 and 19 cognitively intact subjects had gait and balance dysfunction. Seventy-five percent of urbanites exposed to PM2.5 had gait and balance dysfunction. For MMC residents-with historical documented Alzheimer disease (AD) and CSF abnormalities, these findings suggest Alzheimer Continuum is in progress. Early development of a Motoric Cognitive Risk Syndrome ought to be considered in city dwellers with normal cognition and gait dysfunction. The AD research frame in PM2.5 exposed young urbanites should include gait and balance measurements. Multicity teens and young adult cohorts are warranted for quantitative gait and balance measurements and neuropsychological and brain imaging studies in high vs low PM2.5 exposures. Early identification of gait and balance impairment in young air pollution-exposed urbanites would facilitate multidisciplinary prevention efforts for modifying the course of AD.

Effect of Spatial Disorientation in a Virtual Environment on Gait and Vital Features in Patients with Dementia: Pilot Single-Blind Randomized Control Trial

Background

Orientation deficits are among the most devastating consequences of early dementia. Digital navigation devices could overcome these deficits if adaptable to the user’s needs (ie, provide situation-aware, proactive navigation assistance). To fulfill this task, systems need to automatically detect spatial disorientation from sensors in real time. Ideally, this would require field studies consisting of real-world navigation. However, such field studies can be challenging and are not guaranteed to cover sufficient instances of disorientation due to the large variability of real-world settings and a lack of control over the environment.

Objective

Extending a foregoing field study, we aim to evaluate the feasibility of using a sophisticated virtual reality (VR) setup, which allows a more controlled observation of disorientation states and accompanying behavioral and physiological parameters in cognitively healthy older people and people with dementia.

Methods

In this feasibility study, we described the experimental design and pilot outcomes of an ongoing study aimed at investigating the effect of disorientation on gait and selected physiological features in a virtual laboratory. We transferred a real-world navigation task to a treadmill-based virtual system for gait analysis. Disorientation was induced by deliberately manipulating landmarks in the VR projection. Associated responses in motion behavior and physiological parameters were recorded by sensors. Primary outcomes were variations in motion and physiological parameters, frequency of disorientation, and questionnaire-derived usability estimates (immersion and perceived control of the gait system) for our population of interest. At this time, the included participants were 9 cognitively healthy older participants [5/9 women, 4/9 men; mean age 70 years, SD 4.40; Mini–Mental State Examination (MMSE) mean 29, SD 0.70) and 4 participants with dementia (2/4 women, 2/4 men; mean age 78 years, SD 2.30 years; MMSE mean 20.50, SD 7.54). Recruitment is ongoing, with the aim of including 30 cognitively healthy older participants and 20 participants with dementia.

Results

All 13 participants completed the experiment. Patients’ route was adapted by shortening it relative to the original route. Average instances of disorientation were 21.40, 36.50, and 37.50 for the cognitively healthy older control, cognitively healthy older experimental participants, and participants with dementia, respectively. Questionnaire outcomes indicated that participants experienced adequate usability and immersion; 4.30 for presence, 3.73 for involvement, and 3.85 for realism of 7 possible points, indicating a good overall ability to cope with the experiment. Variations were also observed in motion and physiological parameters during instances of disorientation.

Conclusions

This study presents the first feasibility outcomes of a study investigating the viability of using a sophisticated VR setup, based on an earlier real-world navigation study, to study spatial disorientation among cognitively healthy older people and people with dementia. Preliminary outcomes give confidence to the notion that our setup can be used to assess motion and physiological markers of disorientation, even in people with cognitive decline.

Trial Registration

ClinicalTrials.gov; https://clinicaltrials.gov/ct2/show/NCT04134806

Motoric Cognitive Risk Syndrome: A Risk Factor for Cognitive Impairment and Dementia in Different Populations

Changes in gait, especially decreased gait velocity, may be a harbinger of cognitive decline in aging. Motoric cognitive risk syndrome (MCR), a pre-dementia syndrome combining slow gait and cognitive complaints, is a powerful clinical tool used to identify older adults at a high risk of developing dementia. The mean prevalence of MCR worldwide, including in a Korean cohort, was around 10%. The reported risk factors for incident MCR include older age, low education, cardiovascular disease, obesity, physical inactivity, and depression. In addition to dementia, MCR is also a risk factor for other age-related adverse conditions such as falls, disability, frailty, and mortality. The use of MCR has advantages over other pre-dementia syndromes in being much simpler to implement and requires fewer resources. Identification of mechanisms responsible for MCR may help in developing interventions to reduce the growing burden of dementia and disability worldwide.