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

Intersession reliability of center of pressure measurement during bipedal standing with different count-back orders

INTRODUCTION

Dual-task assessments can identify changes in postural control during balance assessments. Static standing with backward counting is frequently used to evaluate postural control while dual-tasking. The most reliable countdown method for standing postural stability has not yet been defined.

RESEARCH OBJECTIVE

to investigate postural stability's intra- and inter-day reliability while backward counting in different steps.

METHOD

Thirty-nine healthy adults (20 females, 26.94 ± 7.55 years) completed 70 s trials of stability tests with no dual-task, counting backward under five conditions (in ones, tows, threes, fours, and fives) while standing on a force-plate in three sessions: two sessions were on the same day, and the third session was one-week apart. The repeatability of measurements was tested using repeated-measure analysis of variance, interclass correlation, and standard error of measurements.

RESULTS

The interclass correlation scores ranged from 0.67 to 0.92, and the standard error of measurements ranged from 2.9% to 13.4%. No significant systematic changes (p < 0.05) occurred between the testing sessions for any backward counting.

DISCUSSION

The backward counting showed higher reliability when performed in condition 5 (counting backward in five's). The inter-day reliability scores were greater than intera-day reliability.

CONCLUSIONS

Dual-tasking with most backward counting (in ones to fives) is reliable, and a quantitative assessment of the center of pressure could be used to monitor the changes in postural stability between sessions.

An 18-month multimodal intervention trial for preventing dementia: J-MINT PRIME Tamba

BACKGROUND

The number of people with dementia is increasing in Japan, and establishing evidence for preventing dementia is necessary.

METHODS

This study was a randomized controlled trial in cognitively normal community-dwelling older adults aged 65 to 85 with diabetes and/or hypertension. Participants were randomly assigned in a 1:1 ratio. The intervention group underwent 90 min of group-based weekly physical exercise, cognitive training, nutritional counseling, and vascular risk management for 18 months. The primary endpoint was the change in a cognitive composite score calculated by averaging the z-scores of seven neuropsychological tests from baseline to 18 months.

RESULTS

We randomly assigned 203 participants to two groups, and 178 (87.7%) completed the 18-month follow-up. There was a significant group difference in the cognitive composite score change at 18 months (mean difference 0.16, 95% confidence interval: 0.04 to 0.27; p = 0.009).

DISCUSSION

An 18-month multimodal intervention for older adults at risk of dementia could improve their cognitive function. The trial was registered in the Clinical Trial Registration System (UMIN000041938).

HIGHLIGHTS

Japan-Multimodal Intervention Trial for Prevention of Dementia (J-MINT) PRIME Tamba was a randomized controlled trial to prevent dementia. We provided a multifactorial intervention based on the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) trial methodology. The primary outcome, the cognitive composite score, improved with our intervention. Executive function/processing speed and memory improved in the intervention group. Intervention adherence was high, and no serious adverse events occurred.

The Efficacy of a Home-Based, Augmented Reality Dual-Task Platform for Cognitive-Motor Training in Elderly Patients: A Pilot Observational Study

OBJECTIVE

This study introduces a novel home-based dual-task platform incorporating augmented reality (AR), COGNIMO, aimed at simultaneously enhancing cognition and physical abilities. The purpose of this study was to assess the effectiveness of this intervention in enhancing cognitive and physical abilities in elderly individuals with subjective cognitive decline, mild cognitive impairment (MCI), and mild Alzheimer's dementia.

METHODS

A 12-week observational study enrolled 57 participants aged 60-85 years. Primary outcomes included changes in cognitive scores (Korean Mini-Mental State Examination, 2nd edition [K-MMSE-2] and Korean-Montreal Cognitive Assessment [K-MoCA]), while secondary outcomes measured physical parameters and depression scores between baseline and week 12 in the active and the control groups.

RESULTS

Of 57 participants, 49 completed the study. The active group (≥12 sessions) exhibited significant improvement in K-MoCA compared to the control group (<12 sessions) (p=0.004), while K-MMSE-2 score changes showed no significant difference (p=0.579). Positive correlations between training sessions and K-MoCA changes were observed (r=0.31, p=0.038), emphasizing a dose-response relationship. Subgroup analyses revealed a distinction in cognitive changes, particularly in the MCI group.

CONCLUSION

The COGNIMO platform showed positive effects on cognitive function in MCI patients, suggesting potential benefits for this population. The study highlights the potential of AR-integrated home-based interventions for cognitive enhancement in elderly individuals, underlining the need for further trials in the future.

Feasibility of Using a Novel, Multimodal Motor Function Assessment Platform With Machine Learning to Identify Individuals With Mild Cognitive Impairment

INTRODUCTION

Early identification of clinical conditions associated with Alzheimer disease and related dementias (ADRD) is vital for intervention. One promising early detection method is the use of instrumented assessment to identify subtle motor declines associated with ADRD. This pilot study sought to establish the feasibility of building a machine learning model to identify individuals with mild cognitive impairment (MCI) using motor function data obtained from an inexpensive, portable device.

METHODS

Our novel, multimodal motor function assessment platform integrates a depth camera, forceplate, and interface board. Healthy older adults (n=28) and older adults with MCI (n=19) were assessed during static balance, gait, and sit-to-stand activities in both single- and dual-task conditions. Three machine learning models (ie, support vector machine, decision trees, and logistic regression) were trained and tested with the goal of classification of MCI.

RESULTS

Our best model was decision trees, which demonstrated an accuracy of 83%, a sensitivity of 0.83, a specificity of 1.00, and an F1 score of 0.83. The top features were extracted and ranked on importance.

DISCUSSION

This study demonstrates the feasibility of building a machine learning model capable of identifying individuals with mild cognitive impairment using motor function data obtained with a portable, inexpensive, multimodal device.

Stroke rehabilitation: from diagnosis to therapy

Stroke remains a significant global health burden, necessitating comprehensive and innovative approaches in rehabilitation to optimize recovery outcomes. This paper provides a thorough exploration of rehabilitation strategies in stroke management, focusing on diagnostic methods, acute management, and diverse modalities encompassing physical, occupational, speech, and cognitive therapies. Emphasizing the importance of early identification of rehabilitation needs and leveraging technological advancements, including neurostimulation techniques and assistive technologies, this manuscript highlights the challenges and opportunities in stroke rehabilitation. Additionally, it discusses future directions, such as personalized rehabilitation approaches, neuroplasticity concepts, and advancements in assistive technologies, which hold promise in reshaping the landscape of stroke rehabilitation. By delineating these multifaceted aspects, this manuscript aims to provide insights and directions for optimizing stroke rehabilitation practices and enhancing the quality of life for stroke survivors.

Effects of divided attention on movement-related cortical potential in community-dwelling elderly adults: A preliminary study

Dual-tasking is defined as performing two or more tasks concurrently. This study aimed to investigate the effect of divided attention on movement-related cortical potential (MRCP) during dual-task performance in 11 community-dwelling elderly individuals while the load of the secondary task was altered. MRCP was recorded during a single task (ST), simple dual task (S-DT), and complex dual task (C-DT) as no-, low-, and high-load divided attention tasks, respectively. The ST involved self-paced tapping with an extended right index finger. In the S-DT and C-DT, the subjects simultaneously performed the ST and a visual number counting task with different levels of load. The coefficient of variation of movement frequency was significantly more variable in the C-DT than in the ST. The MRCP amplitude from electroencephalography electrode C3, contralateral to the moving hand, was significantly higher in the C-DT than in the ST. Higher attention diversion led to a significant reduction in MRCP amplitude in the participants. These results suggest that attention division in dual-task situations plays an important role in movement preparation and execution. We propose that MRCP can serve as a marker for screening the ability of older individuals to perform dual-tasks.

The Influence of Separate and Combined Exercise and Foreign Language Acquisition on Learning and Cognition

Aging contributes significantly to cognitive decline. Aerobic exercise (AE) has been shown to induce substantial neuroplasticity changes, enhancing cognitive and brain health. Likewise, recent research underscores the cognitive benefits of foreign language learning (FLL), indicating improvements in brain structure and function across age groups. However, the lack of a comprehensive paradigm integrating language learning with exercise limits research on combined effects in older adults. In order to address this gap, we devised a novel approach using a virtual world tourism scenario for auditory-based language learning combined with aerobic cycling. Our study examines the impact of simultaneous AE and FLL integration on cognitive and language learning outcomes compared to FLL alone. A total of 20 older adults were randomly assigned to AE + FLL and FLL-only groups. The results revealed significantly improved Spanish language learning outcomes in both combined and language learning-only groups. Additionally, significant cognitive function improvement was observed in the FLL group following short-term language learning.

Benefits of a Dual-Task Training on Motor and Cognitive Functions in Community-Dwelling Older Adults: A Controlled Clinical Trial

OBJECTIVE

The aim of the study is to verify the effects of a 3-mo dual-task training on motor and cognitive functions in community-dwelling older adults.

DESIGN

In this prospective, single-blinded, controlled clinical trial, a total of 40 participants were allocated to either the experimental or the control (no-exercise) group. The intervention program consisted of a combination of motor and cognitive exercises conducted twice a week on nonconsecutive days. The main outcome measures were postural stability, mobility, fear of falling, and cognitive functions. Multiple analyses of variance were used to assess the impact of the dual-task training. Effect sizes (η 2 p) were reported. Significance was set at 5%.

RESULTS

Compared with the control group, participants who underwent the dual-task training showed positive outcomes in terms of postural stability (η 2 p = 0.298, P = 0.020), mobility (η 2 p = 0.285, P = 0.003), and cognitive functions (η 2 p = 0.536, P = 0.001). No significant differences were observed between the groups in terms of the fear of falling ( P = 0.566).

CONCLUSIONS

Three-month dual-task training was beneficial for postural control, mobility, and cognitive functions in community-dwelling older adults. Based on the present findings, healthcare professionals should consider incorporating dual-task training into clinical practice.

Dual-task turn velocity - a novel digital biomarker for mild cognitive impairment and dementia

Background

Disorders associated with cognitive impairment impose a significant burden on both families and society. Previous studies have indicated that gait characteristics under dual-task as reliable markers of early cognitive impairment. Therefore, digital gait detection has great potential for future cognitive screening. However, research on digital biomarkers based on smart devices to identify cognitive impairment remains limited. The aim of this study is to explore digital gait biomarkers by utilizing intelligent wearable devices for discriminating mild cognitive impairment and dementia.

Methods

This study included 122 subjects (age: 74.7 ± 7.7 years) diagnosed with normal cognition (NC, n = 38), mild cognitive impairment (MCI, n = 42), or dementia (n = 42). All subjects underwent comprehensive neuropsychological assessments and cranial Magnetic Resonance Imaging (MRI). Gait parameters were collected using validated wearable devices in both single-task and dual-task (DT). We analyzed the ability of gait variables to predict MCI and dementia, and examined the correlations between specific DT-gait parameters and sub-cognitive functions as well as hippocampal atrophy.

Results

Our results demonstrated that dual-task could significantly improve the ability to predict cognitive impairment based on gait parameters such as gait speed (GS) and stride length (SL). Additionally, we discovered that turn velocity (TV and DT-TV) can be a valuable novel digital marker for predicting MCI and dementia, for identifying MCI (DT-TV: AUC = 0.801, sensitivity 0.738, specificity 0.842), and dementia (DT-TV: AUC = 0.923, sensitivity 0.857, specificity 0.842). The correlation analysis and linear regression analysis revealed a robust association between DT-TV and memory function, as well as the hippocampus atrophy.

Conclusion

This study presents a novel finding that DT-TV could accurately identify varying degrees of cognitive impairment. DT-TV is strongly correlated with memory function and hippocampus shrinkage, suggests that it can accurately reflect changes in cognitive function. Therefore, DT-TV could serve as a novel and effective digital biomarker for discriminating cognitive impairment.

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.

Mechanisms of Change in Cognitive Function Domains Among Older Adults in Cognitive Deterioration and Improvement Groups: Evidence From Phenotypic Network Structure

OBJECTIVE

To investigate how cognitive function domains change in phenotypic networks in cognitive deterioration and improvement groups.

DESIGN

Secondary data analysis.

SETTING AND PARTICIPANTS

Respondents in the Aging, Demographics, and Memory Study (ADAMS) who were 70 years or older at the time of the data collection in 2000 or 2002.

METHODS

This study used data from the ADAMS in Wave A and Wave B. We assessed 12 cognitive function domains. Latent profile transition analysis (LPTA) and the cross-lagged panel network model were used to the dynamic interactions of the 12 cognitive function domains over time in both the deterioration and improvement groups.

RESULTS

A total of 252 participants were included in the final analysis. LPTA identified 5 subgroups and categorized all samples into 3 main categories: improvement group (n = 61), deterioration group (n = 54), and no change group (n = 137). "D9: psychomotor processing" showed the largest value of out-strength in the deterioration group (r = 0.941) and improvement group (r = 0.969). The strongest direct positive effect in the deterioration group was "C9: psychomotor processing" -> "C8: attention" [β = 0.39 (0.00, 1.13)]. In the improvement group, the strongest direct positive effect was "C9 = psychomotor processing" -> "C7 = visual memory" [β = 0.69 (0.07, 1.30)].

CONCLUSION AND IMPLICATIONS

Psychomotor processing affected other cognitive domains, and it played a crucial role in changes of cognitive function. The paths of psychomotor processing to attention and visual memory were found to be major factors in cognitive deterioration and improvement. Targeting psychomotor processing may lead to the development of more effective and precise interventions.

Postural Control of Patients with Low Back Pain Under Dual-Task Conditions

Low back pain is a major global public health problem, but the current intervention effect is not ideal. A large body of previous literature suggests that patients with chronic low back pain may have abnormal postural control, which is more evident in the dual task situation. In recent years, research on postural control in patients with low back pain under dual-task conditions has gradually become a hot topic. However, the results obtained from these studies were not entirely consistent. In this review, we summarized relevant studies on the performance of postural control in patients with low back pain under dual-task conditions, analyze it from the perspective of the theoretical model of dual-task interaction, the specific research paradigm of dual task, the performance of postural control, and the related factors affecting postural control performance, etc. It was reasonable to assume that patients with low back pain might have a certain degree of abnormal postural control, and this abnormality was affected by comprehensive factors such as age, cognitive resource capacity, attention needs, complex sensorimotor integration, external environment, etc. Furthermore, postural control performance in low back pain patients under dual-task conditions was further influenced by the nature and complexity of the different tasks. In general, the more attention resources were needed, the external environmental conditions were worse, and the age-related functions were degenerate, etc., the weaker posture control ability was. In short, a deeper understanding of postural control in patients with low back pain under dual-task conditions may shed light on more references for the rehabilitation and management of low back pain, as well as some new ideas for scientific research on cognition and postural control.

A novel dual-task paradigm with story recall shows significant differences in the gait kinematics in older adults with cognitive impairment: A cross-sectional study

Objective

Cognitive and motor dysfunctions in older people become more evident while dual-tasking. Several dual-task paradigms have been used to identify older individuals at the risk of developing Alzheimer's disease and dementia. This study evaluated gait kinematic parameters for dual-task (DT) conditions in older adults with mild cognitive impairment (MCI), subjective cognitive decline (SCD), and normal cognition (NC).

Method

This is a cross-sectional, clinical-based study carried out at the Zhongshan Rehabilitation Branch of First Affiliated Hospital of Nanjing Medical University, China.

Participants

We recruited 83 community-dwelling participants and sorted them into MCI (n = 24), SCD (n = 33), and NC (n = 26) groups based on neuropsychological tests. Their mean age was 72.0 (5.55) years, and male-female ratio was 42/41 (p = 0.112). Each participant performed one single-task walk and four DT walks: DT calculation with subtracting serial sevens; DT naming animals; DT story recall; and DT words recall.

Outcome and measures

Kinematic gait parameters of speed, knee peak extension angle, and dual-task cost (DTC) were obtained using the Vicon Nexus motion capture system and calculated by Visual 3D software. A mixed-effect linear regression model was used to analyze the data.

Results

The difference in gait speed under DT story recall and DT calculation was -0.099 m/s and - 0.119 m/s (p = 0.04, p = 0.013) between MCI and SCD, respectively. Knee peak extension angle under DT story recall, words recall, and single task was bigger in the MCI group compared to the NC group, respectively (p = 0.001, p = 0.001, p = 0.004). DTC was higher in the DT story recall test than all other DT conditions (p < 0.001).

Conclusion

Kinematic gait parameters of knee peak extension angle for the DT story recall were found to be sensitive enough to discriminate MCI individuals from NC group. DTC under DT story recall was higher than the other DT conditions.

Do the dual-task "8-foot up and go" tests provide additional predictive value for early detection of cognitive decline in community-dwelling older women?

BACKGROUND

The 8-Foot Up and Go (8UG) test is a widely used mobility assessment. Some dual-task mobility assessments have been developed to help detect cognitive decline.

AIMS

This study developed a dual-task version of 8UG test to investigate the dual-task 8UG performance and to evaluate the ability of dual-task 8UG test in detecting cognitive decline.

METHODS

A total of 101 eligible community-dwelling women aged 60-74 years were grouped into the mild cognitive impairment group (MCI, n = 49) and the non-cognitive impairment group (NCI, n = 52). The 8UG tests under single-task (ST), manual dual-task (MT), and cognitive dual-task (CT) conditions were performed respectively. The dual-task cost (DTC) and the correct response rate (CRR) were calculated to quantify the dual-task interference.

RESULTS

Participants spent more time in performing the 8UG test under dual-task conditions. No differences were observed between NCI and MCI groups for 8UG parameters under ST and MT conditions (p > 0.05). When executing CT, significant differences were found in the number of correct answers and CRR (p < 0.05). CRR showed the strongest ability to predict MCI with a cut-off point of 0.50 (71.2% sensitivity and 61.2% specificity).

DISCUSSION

Both manual and cognitive dual-task were found to interfere with the 8UG performance. CRR with cutoff point of 0.50 could be a potential predictor of MCI in community-dwelling older women.

CONCLUSIONS

The CRR of the cognitive dual-task 8UG test could be recommended as a potential predictor for the early detection of MCI in community-dwelling older women.

The Performance of Dual-Task Tests Can Be a Combined Neuro-Psychological and Motor Marker of Mild Cognitive Impairment, Depression and Dementia in Geriatric Patients-A Cross-Sectional Study

The study aims to assess the performance of dual-task tests in the geriatric population and their association with the cognitive status of the patients.

METHODS

Patients admitted to the Department of Geriatrics, Hospital of the Ministry of Interior and Administration on Bialystok, Poland, in 2019 and 2020 were enrolled in the study. Data on the patients' clinical, functional, and cognitive status were collected based on the comprehensive geriatric assessment. Dual-task tests included Timed Up and Go (TUG) test while counting backward (CB7), enumerating animals (EA), and holding a cup (TUG M).

RESULTS

250 patients were included in the study, with a median age of 81.5 years (IQR 76-86) and most above 75 years of age (80.8%). Only 29 (11.6%) of study participants had no cognitive or mood disorders. Depression was diagnosed in 30.4%, MCI in 12%, and dementia in 38.4% of cases with median Mini-Mental Score Evaluation (MMSE) 17 (12-20) points. Dual-task TUG CB7 results did not differ between cognitive conditions of patients. TUG EA differed between healthy controls and other cognitive groups and TUG between healthy controls and depression and dementia, but not mild cognitive impairment (MCI). The performance of all dual-task tests differed in patients with and without dementia. Ability to finish TUG CB7 was low even in the group without dementia. There were statistically significant differences in median scores of MMSE and Clock Drawing Test (CDT) between patients who were able or not to finish single and dual-task gait tests.

CONCLUSION

Dual-task test results and the performance of these tasks can differentiate patients with depression, MCI and dementia compared to healthy controls in the geriatric population.

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.