Dual-Task Gait Assessment in a Clinical Sample: Implications for Improved Detection of Mild Cognitive Impairment

A detection model of cognitive impairment via the integrated gait and eye movement analysis from a large Chinese community cohort

INTRODUCTION

Whether the integration of eye-tracking, gait, and corresponding dual-task analysis can distinguish cognitive impairment (CI) patients from controls remains unclear.

METHODS

One thousand four hundred eighty-one participants, including 724 CI and 757 controls, were enrolled in this study. Eye movement and gait, combined with dual-task patterns, were measured. The LightGBM machine learning models were constructed.

RESULTS

A total of 105 gait and eye-tracking features were extracted. Forty-six parameters, including 32 gait and 14 eye-tracking features, showed significant differences between two groups (P < 0.05). Of these, the Gait_3Back-TurnTime and Dual-task cost-TurnTime patterns were significantly correlated with plasma phosphorylated tau 181 (p-tau181) level. A model based on dual-task gait, dual-task smooth pursuit, prosaccade, and anti-saccade achieved the best area under the receiver operating characteristics curve (AUC) of 0.987 for CI detection, while combined with p-tau181, the model discriminated mild cognitive impairment from controls with an AUC of 0.824.

DISCUSSION

Combining dual-task gait and dual-task eye-tracking analysis is feasible for the detection of CI.

HIGHLIGHTS

This is the first study to report the efficiency of integrated parameters of dual-task gait and eye-tracking for cognitive impairment (CI) detection in a large cohort. We identified 46 gait and eye-tracking features associated with CI, and two were correlated to plasma phosphorylated tau 181. We constructed the model based on dual-task gait, smooth pursuit, prosaccade, and anti-saccade, achieving the best area under the curve of 0.987 for CI detection.

A Study of Assisted Screening for Alzheimer's Disease Based on Handwriting and Gait Analysis

Background

Alzheimer's disease (AD) is a progressive neurodegenerative disease that is not easily detected in the early stage. Handwriting and walking have been shown to be potential indicators of cognitive decline and are often affected by AD.

Objective

This study proposes an assisted screening framework for AD based on multimodal analysis of handwriting and gait and explores whether using a combination of multiple modalities can improve the accuracy of single modality classification.

Methods

We recruited 90 participants (38 AD patients and 52 healthy controls). The handwriting data was collected under four handwriting tasks using dot-matrix digital pens, and the gait data was collected using an electronic trail. The two kinds of features were fused as inputs for several different machine learning models (Logistic Regression, SVM, XGBoost, Adaboost, LightGBM), and the model performance was compared.

Results

The accuracy of each model ranged from 71.95% to 96.17%. Among them, the model constructed by LightGBM had the best performance, with an accuracy of 96.17%, sensitivity of 95.32%, specificity of 96.78%, PPV of 95.94%, NPV of 96.74%, and AUC of 0.991. However, the highest accuracy of a single modality was 93.53%, which was achieved by XGBoost in gait features.

Conclusions

The research results show that the combination of handwriting features and gait features can achieve better classification results than a single modality. In addition, the assisted screening model proposed in this study can achieve effective classification of AD, which has development and application prospects.

Cognitive-motor dual-task interference in Alzheimer's disease, Parkinson's disease, and prodromal neurodegeneration: A scoping review

BACKGROUND

Cognitive-motor interference (CMI) is a common deficit in Alzheimer's (AD) disease and Parkinson's disease (PD) and may have utility in identification of prodromal neurodegeneration. There is lack of consensus regarding measurement of CMI resulting from dual task paradigms.

RESEARCH QUESTION

How are individuals with AD, PD, and prodromal neurodegeneration impacted by CMI as measured by dual-task (DT) performance?

METHODS

A systematic literature search was performed in six datasets using the PRISMA guidelines. Studies were included if they had samples of participants with AD, PD, or prodromal neurodegeneration and reported at least one measure of cognitive-motor DT performance.

RESULTS

4741 articles were screened and 95 included as part of this scoping review. Articles were divided into three non-mutually exclusive groups based on diagnoses, with 26 articles in AD, 56 articles in PD, and 29 articles in prodromal neurodegeneration, and results presented accordingly.

SIGNIFICANCE

Individuals with AD and PD are both impacted by CMI, though the impact is likely different for each disease. We found a robust body of evidence regarding the utility of measures of DT performance in the detection of subtle deficits in prodromal AD and some signals of utility in prodromal PD. There are several key methodological challenges related to DT paradigms for the measurement of CMI in neurodegeneration. Overall, DT paradigms show good potential as a clinical method to probe specific brain regions, networks, and function; however, task selection and effect measurement should be carefully considered.

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).

Mindfulness stress-buffering model of health: implications for successful aging

OBJECTIVES

Age-related variations in emotional, physical, and cognitive health are poorly understood. This multimethod study extends previous work by investigating mechanistic models by which trait mindfulness, perceived stress, and negative affect (NA) influence health outcomes in adults aged 57-87 years old.

METHOD

In this cross-sectional study, 119 adults completed clinical interviews, cognitive and gait assessments, the Mindful Attention and Awareness Scale, Positive and Negative Affect Schedule, and Perceived Stress Scale. Gait velocity and executive function (Flanker test of inhibitory control), which are important predictors of global health and functioning in older adults, served as objective health outcome measures.

RESULTS

Correlational analyses found that trait mindfulness is positively associated with age, gait velocity, and inhibitory control and negatively associated with NA and perceived stress. NA but not perceived stress was associated with slower gait velocity. PROCESS mediation analyses suggested that those higher in trait mindfulness showed lower NA as a result of less perceived stress, while moderation analyses indicated the relationship between gait velocity and age varied by levels of trait mindfulness.

CONCLUSION

Our findings are consistent with a mindfulness stress-buffering model of health. It is plausible that trait mindfulness, which has both mediating and moderating effects on health, might help to promote more successful aging and provide resilience to age-related declines in physical health.

Gait Characteristics and Cognitive Function in Middle-Aged Adults with and without Type 2 Diabetes Mellitus: Data from ENBIND

Type 2 Diabetes Mellitus (T2DM) in midlife is associated with a greater risk of dementia in later life. Both gait speed and spatiotemporal gait characteristics have been associated with later cognitive decline in community-dwelling older adults. Thus, the assessment of gait characteristics in uncomplicated midlife T2DM may be important in selecting-out those with T2DM at greatest risk of later cognitive decline. We assessed the relationship between Inertial Motion Unit (IMUs)-derived gait characteristics and cognitive function assessed via Montreal Cognitive Assessment (MoCA)/detailed neuropsychological assessment battery (CANTAB) in middle-aged adults with and without uncomplicated T2DM using both multivariate linear regression and a neural network approach. Gait was assessed under (i) normal walking, (ii) fast (maximal) walking and (iii) cognitive dual-task walking (reciting alternate letters of the alphabet) conditions. Overall, 138 individuals were recruited (n = 94 with T2DM; 53% female, 52.8 ± 8.3 years; n = 44 healthy controls, 43% female, 51.9 ± 8.1 years). Midlife T2DM was associated with significantly slower gait velocity on both slow and fast walks (both p < 0.01) in addition to a longer stride time and greater gait complexity during normal walk (both p < 0.05). Findings persisted following covariate adjustment. In analyzing cognitive performance, the strongest association was observed between gait velocity and global cognitive function (MoCA). Significant associations were also observed between immediate/delayed memory performance and gait velocity. Analysis using a neural network approach did not outperform multivariate linear regression in predicting cognitive function (MoCA) from gait velocity. Our study demonstrates the impact of uncomplicated T2DM on gait speed and gait characteristics in midlife, in addition to the striking relationship between gait characteristics and global cognitive function/memory performance in midlife. Further studies are needed to evaluate the longitudinal relationship between midlife gait characteristics and later cognitive decline, which may aid in selecting-out those with T2DM at greatest-risk for preventative interventions.

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.

Dual-task performance in old adults: cognitive, functional, psychosocial and socio-demographic variables

Background

Dual tasking, or the ability to executing two tasks simultaneously, has been used in recent research to predict cognitive impairments, physical frailty, and has been linked with cognitive frailty in old adults.

Aim

This study aimed to determine age-related variables can predict dual-task (DT) performance in the older population.

Methods

A total of 258 healthy community-dwelling participants + 60 years were assessed in relation to their functional capacity, health, well-being, social support and years of education. Performance of a cognitive (Fluency) task and a cognitive–motor (Tracking) task was recorded under single and DT conditions. Multiple linear regression analysis was carried out for each dependent variable, in separate models including cognitive, functional and psychosocial variables.

Results

Performance in Fluency in DT conditions was predicted by cognitive variables, whereas performance in Tracking DT conditions was predicted by positive interaction, health status, age and motor variables.

Discussion

The findings suggest that a wide range of cognitive, psychological, social, physical and functional variables influence cognitive and motor performance in aging.

Conclusion

DT methodology is sensitive to different age-related changes and could be related to frailty conditions in aging.

Slower gait speed increases risk of falling in older adults with depression and cognitive complaints

Slowed gait is one of the strongest predictors of fall risk in older adults. The present study investigated whether gait speed mediated the relationship between depression and fall history in 147 older adults presenting to a memory clinic for cognitive complaints. Depression, cognitive status, gait speed, and number of falls within the last year were the primary measures. Results revealed fallers, relative to non-fallers, had slower gait speed and higher depression scores. As hypothesized, analyses using the PROCESS macro found that gait mediated the relationship between depression and fall history. Additionally, the combination of depression and mild cognitive impairments (MCI) associated with a significantly greater likelihood of falling. Our findings indicate that combined depression and MCI have additive effects on fall risk, likely through the destabilizing effect of slowed gait on balance. Better understanding the underlying pathophysiology involved in MCI and depression-related gait disturbances may lead to improved intervention targets for fall risk prevention.

Brain volumes and dual-task performance correlates among individuals with cognitive impairment: a retrospective analysis

Cognitive impairment (CI) is a prevalent condition characterized by loss of brain volume and changes in cognition, motor function, and dual-tasking ability. To examine associations between brain volumes, dual-task performance, and gait and balance in those with CI to elucidate the mechanisms underlying loss of function. We performed a retrospective analysis of medical records of patients with CI and compared brain volumes, dual-task performance, and measures of gait and balance. Greater cognitive and combined dual-task effects (DTE) are associated with smaller brain volumes. In contrast, motor DTE is not associated with distinct pattern of brain volumes. As brain volumes decrease, dual-task performance becomes more motor prioritized. Cognitive DTE is more strongly associated with decreased performance on measures of gait and balance than motor DTE. Decreased gait and balance performance are also associated with increased motor task prioritization. Cognitive DTE appears to be more strongly associated with decreased automaticity and gait and balance ability than motor DTE and should be utilized as a clinical and research outcome measure in this population. The increased motor task prioritization associated with decreased brain volume and function indicates a potential for accommodative strategies to maximize function in those with CI. Counterintuitive correlations between motor brain volumes and motor DTE in our study suggest a complicated interaction between brain pathology and function.