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

Neural underpinnings of fine motor skills under stress and anxiety: A review

This review offers a comprehensive examination of how stress and anxiety affect motor behavior, particularly focusing on fine motor skills and gait adaptability. We explore the role of several neurochemicals, including brain-derived neurotrophic factor (BDNF) and dopamine, in modulating neural plasticity and motor control under these affective states. The review highlights the importance of developing therapeutic strategies that enhance motor performance by leveraging the interactions between key neurochemicals. Additionally, we investigate the complex interplay between emotional-cognitive states and sensorimotor behaviors, showing how stress and anxiety disrupt neural integration, leading to impairments in skilled movements and negatively impacting quality of life. Synthesizing evidence from human and rodent studies, we provide a detailed understanding of the relationships among stress, anxiety, and motor behavior. Our findings reveal neurophysiological pathways, behavioral outcomes, and potential therapeutic targets, emphasizing the intricate connections between neurobiological mechanisms, environmental factors, and motor performance.

Development and External Validation of a Gait Test Based Diagnostic Model for Detecting Mild Cognitive Impairment

OBJECTIVE

To address the lack of large-scale screening tools for mild cognitive impairment (MCI), this study aimed to assess the discriminatory ability of several gait tests for MCI and develop a screening tool based on gait test for MCI.

DESIGN

A diagnostic case-control test.

SETTING

The general community.

PARTICIPANTS

We recruited 134 older adults (≥65 years) for the derivation sample, comprising -69 individuals in the cognitively normal group and -65 in the MCI group (N=134). An additional 70 participants were enrolled for the validation sample.

INTERVENTIONS

All participants completed gait tests consisting of a single task (ST) and 3 dual tasks (DTs): counting backwards, serial subtractions 7, and naming animals.

MAIN OUTCOME MEASURES

Binary logistic regression analyses were used to develop models, and the efficacy of each model was assessed using receiver operating characteristic (ROC) curve and area under the curve (AUC). The best effective model was the final diagnostic model and validated using ROC curve and calibration curve.

RESULTS

The DT gait test incorporating serial subtractions 7 as the cognitive task demonstrated the highest efficacy with the AUC of 0.906 and the accuracy of 0.831 in detecting MCI with "years of education" being adjusted. Furthermore, the model exhibited consistent performance across different age and sex groups. In external validation, the model displayed robust discrimination (AUC=0.913) and calibration (calibrated intercept=-0.062, slope=1.039).

CONCLUSIONS

The DT gait test incorporating serial subtractions 7 as the cognitive task demonstrated robust discriminate ability for MCI. This test holds the potential to serve as a large-scale screening tool for MCI, aids in the early detection and intervention of cognitive impairment in older adults.

Development of a smartphone screening test for preclinical Alzheimer's disease and validation across the dementia continuum

BACKGROUND

Dementia prevalence is predicted to triple to 152 million globally by 2050. Alzheimer's disease (AD) constitutes 70% of cases. There is an urgent need to identify individuals with preclinical AD, a 10-20-year period of progressive brain pathology without noticeable cognitive symptoms, for targeted risk reduction. Current tests of AD pathology are either too invasive, specialised or expensive for population-level assessments. Cognitive tests are normal in preclinical AD. Emerging evidence demonstrates that movement analysis is sensitive to AD across the disease continuum, including preclinical AD. Our new smartphone test, TapTalk, combines analysis of hand and speech-like movements to detect AD risk. This study aims to [1] determine which combinations of hand-speech movement data most accurately predict preclinical AD [2], determine usability, reliability, and validity of TapTalk in cognitively asymptomatic older adults and [3], prospectively validate TapTalk in older adults who have cognitive symptoms against cognitive tests and clinical diagnoses of Mild Cognitive Impairment and AD dementia.

METHODS

Aim 1 will be addressed in a cross-sectional study of at least 500 cognitively asymptomatic older adults who will complete computerised tests comprising measures of hand motor control (finger tapping) and oro-motor control (syllabic diadochokinesis). So far, 1382 adults, mean (SD) age 66.20 (7.65) years, range 50-92 (72.07% female) have been recruited. Motor measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 to develop an algorithm that classifies preclinical AD risk. Aim 2 comprises three sub-studies in cognitively asymptomatic adults: (i) a cross-sectional study of 30-40 adults to determine the validity of data collection from different types of smartphones, (ii) a prospective cohort study of 50-100 adults ≥ 50 years old to determine usability and test-retest reliability, and (iii) a prospective cohort study of ~1,000 adults ≥ 50 years old to validate against cognitive measures. Aim 3 will be addressed in a cross-sectional study of ~200 participants with cognitive symptoms to validate TapTalk against Montreal Cognitive Assessment and interdisciplinary consensus diagnosis.

DISCUSSION

This study will establish the precision of TapTalk to identify preclinical AD and estimate risk of cognitive decline. If accurate, this innovative smartphone app will enable low-cost, accessible screening of individuals for AD risk. This will have wide applications in public health initiatives and clinical trials.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT06114914, 29 October 2023. Retrospectively registered.

Investigating the associations between upper limb motor function and cognitive impairment: a scoping review

Upper limb motor function is a potential new biomarker of cognitive impairment and may aid discrimination from healthy ageing. However, it remains unclear which assessments to use. This study aimed to explore what methods have been used and to describe associations between upper limb function and cognitive impairment. A scoping review was conducted using PubMed, CINAHL and Web of Science. A systematic search was undertaken, including synonyms for key concepts 'upper limb', 'motor function' and 'cognitive impairment'. Selection criteria included tests of upper limb motor function and impaired cognition in adults. Analysis was by narrative synthesis. Sixty papers published between 1998 and 2022, comprising 41,800 participants, were included. The most common assessment tasks were finger tapping, Purdue Pegboard Test and functional tasks such as writing. Protocols were diverse in terms of equipment used and recording duration. Most participants were recruited from clinical settings. Alzheimer's Disease was the most common cause of cognitive impairment. Results were mixed but, generally, slower speed, more errors, and greater variability in upper limb movement variables was associated with cognitive impairment. This review maps the upper limb motor function assessments used and summarises the available evidence on how these associate with cognitive impairment. It identifies research gaps and may help guide protocols for future research. There is potential for upper limb motor function to be used in assessments of cognitive impairment.

Ecological Fall Prediction Sensitivity, Specificity, and Accuracy in Patients with Mild Cognitive Impairment at a High Risk of Falls

While falls among patients with mild cognitive impairment (MCI) have been closely associated with an increased postural sway during ecological activities of daily living, there is a dearth of postural sway detection (PSD) research in ecological environments. The present study aimed to investigate the fall sensitivity, specificity, and accuracy of our PSD system. Forty healthy young and older adults with MCI at a high risk of falls underwent the sensitivity, specificity, and accuracy tests for PSD by simultaneously recording the Berg Balance Scale and Timed Up and Go in ecological environments, and the data were analyzed using the receiver operating characteristic curve and area under the curve. The fall prediction sensitivity ranged from 0.82 to 0.99, specificity ranged from 0.69 to 0.90, and accuracy ranged from 0.53 to 0.81. The PSD system's fall prediction sensitivity, specificity, and accuracy data suggest a reasonable discriminative capacity for distinguishing between fallers and non-fallers as well as predicting falls in older adults with MCI in ecological testing environments.

Mild cognitive impairment identification based on motor and cognitive dual-task pooled indices

OBJECTIVE

This study investigates the possibility of adopting motor and cognitive dual-task (MCDT) approaches to identify subjects with mild cognitive impairment (MCI) and subjective cognitive impairment (SCI).

METHODS

The upper and lower motor performances of 44 older adults were assessed using the SensHand and SensFoot wearable system during three MCDTs: forefinger tapping (FTAP), toe-tapping heel pin (TTHP), and walking 10 m (GAIT). We developed five pooled indices (PIs) based on these MCDTs, and we included them, along with demographic data (age) and clinical scores (Frontal Assessment Battery (FAB) scores), in five logistic regression models.

RESULTS

Models which consider cognitively normal adult (CNA) vs MCI subjects have accuracies that range from 67% to 78%. The addition of clinical scores stabilised the accuracies, which ranged from 85% to 89%. For models which consider CNA vs SCI vs MCI subjects, there are great benefits to considering all three regressors (age, FAB score, and PIs); the overall accuracies of the three-class models range between 50% and 59% when just PIs and age are considered, whereas the overall accuracy increases by 18% when all three regressors are utilised.

CONCLUSION

Logistic regression models that consider MCDT PIs and age have been effective in distinguishing between CNA and MCI subjects. The inclusion of clinical scores increased the models' accuracy. Particularly high performances in distinguishing among CNA, SCI, and MCI subjects were obtained by the TTHP PI. This study suggests that a broader framework for MCDTs, which should encompass a greater selection of motor tasks, could provide clinicians with new appropriate tools.

The Value of Handgrip Strength and Self-Rated Squat Ability in Predicting Mild Cognitive Impairment: Development and Validation of a Prediction Model

Early identification of individuals with mild cognitive impairment (MCI) is essential to combat worldwide dementia threats. Physical function indicators might be low-cost early markers for cognitive decline. To establish an early identification tool for MCI by combining physical function indicators (upper and lower limb function) via a clinical prediction modeling strategy. A total of 5393 participants aged 60 or older were included in the model. The variables selected for the model included sociodemographic characteristics, behavioral factors, mental status and chronic conditions, upper limb function (handgrip strength), and lower limb function (self-rated squat ability). Two models were developed to test the predictive value of handgrip strength (Model 1) or self-rated squat ability (Model 2) separately, and Model 3 was developed by combining handgrip strength and self-rated squat ability. The 3 models all yielded good discrimination performance (area under the curve values ranged from 0.719 to 0.732). The estimated net reclassification improvement values were 0.3279 and 0.1862 in Model 3 when comparing Model 3 to Model 1 and Model 2, respectively. The integrated discrimination improvement values were estimated as 0.0139 and 0.0128 when comparing Model 3 with Model 1 and Model 2, respectively. The model that contains both upper and lower limb function has better performance in predicting MCI. The final prediction model is expected to assist health workers in early identification of MCI, thus supporting early interventions to reduce future risk of AD, particularly in socioeconomically deprived communities.

Prefrontal Cerebral Oxygenated Hemoglobin Concentration during the Category Fluency and Finger-Tapping Tasks in Adults with and without Mild Cognitive Impairment: A Near-Infrared Spectroscopy Study

Mild cognitive impairment (MCI) is considered to be the limit between the cognitive changes of aging and early dementia; thus, discriminating between participants with and without MCI is important. In the present study, we aimed to examine the differences in the cerebral oxyhemoglobin signal between individuals with and without MCI. The cerebral oxyhemoglobin signal was measured when the participants (young and elderly controls as well as patients with MCI) performed category fluency, finger tapping, and dual tasks using head-mounted near-infrared spectroscopy; the results were compared between the groups. The cerebral oxyhemoglobin signal trended toward the highest values during the category fluency task in young participants and during the finger-tapping task in elderly participants regardless of the MCI status. The area under the curve was approximately 0.5, indicating a low discrimination ability between elderly participants with and without MCI. The measurement of the blood flow in the prefrontal cortex may not accurately quantify cognitive and motor performance to detect MCI. Finger tapping may increase cerebral blood flow in individuals with and without MCI during the task.

Mental arithmetic modulates temporal variabilities of finger-tapping tasks in a tempo-dependent manner

Background

Several psychiatric diseases impair temporal processing. Temporal processing is thought to be based on two domains: supra-second intervals and sub-second intervals. Studies show that temporal processing in sub-second intervals is mainly an automated process. However, the brain functions involved in temporal processing at each time scale remain unclear. We hypothesized that temporal processing in supra-second intervals requires several brain areas, such as the ventrolateral prefrontal cortex, intraparietal sulcus (IPS), and inferior parietal lobe, corresponding to various cognitions in a time scale-dependent manner. We focused on a dual-task paradigm (DTP) involving simultaneous performance of cognitive and motor tasks, which is an effective method for screening psychomotor functions; we then designed a DTP comprising finger tapping at various tempi as the temporal processing task and two cognitive tasks (mental arithmetic and reading) that might affect temporal processing. We hoped to determine whether task-dependent interferences on temporal processing in supra-second intervals differed depending on the cognitive tasks involved.

Methods

The study included 30 participants with no history of neuromuscular disorders. Participants were asked to perform a DTP involving right index finger tapping at varying tempi (0.33, 0.5, 1, 2, 3, and 4 s inter-tapping intervals). Cognitive tasks comprised mental arithmetic (MA) involving three-digit addition, mental reading (MR) of three- to four-digit numbers, and a control (CTL) task without any cognitive loading. For comparison between tasks, we calculated the SDs of the inter-tapping intervals. Participants' MA abilities in the three-digit addition task were evaluated.

Results

The MA and MR tasks significantly increased the SDs of the inter-tapping intervals compared to those of the CTL task in 2-3 s and 3-4 s for the MA and MR tasks, respectively. Furthermore, SD peaks in the finger-tapping tasks involving MA were normalized by those in the CTL task, which were moderately correlated with the participants' MA ability (r = 0.462, P = 0.010).

Discussion

Our results established that DTP involving the temporal coordination of finger-tapping and cognitive tasks increased temporal variability in a task- and tempo-dependent manner. Based on the behavioral aspects, we believe that these modulations of temporal variability might result from the interaction between finger function, arithmetic processing, and temporal processing, especially during the "pre-semantic period". Our findings may help in understanding the temporal processing deficits in various disorders such as dementia, Parkinson's disease, and autism.

A New Motor and Cognitive Dual-Task Approach Based on Foot Tapping for The Identification of Mild Cognitive Impairment

This study investigates the adoption of innovative Motor and Cognitive Dual-Task (MCDT) based on the combination of increasing motor and cognitive tasks to discern between subjects with Mild Cognitive Impairment (MCI) and Cognitively Normal Adults (CNA). We aim to adopt new MCDT protocols and to compare their performance against the gold standard (a walking based MCDT, called GAIT). 27 older adults have been assessed through a customized wearable system during 4 MCDTs. We developed as many pooled indices (PIs), based on MCDTs perfomance, demographic data, and clinical scores. We use these parameters as regressors in 4 different logistic regression models. The regression models that encompassed features from innovative MCDT overcame the gold standard classification performance. In particular, models based on the heel tapping and the alternate heel-toe tapping reach the best outputs, namely +8% of accuracy if compared to the gold standard (a walking task). The use of logistic regression models based on MCDT PI have been effective in discerning between CNA vs MCI. Our results suggest that the gold standard MCDT may represents a too demanding exercise to highlight differences between CNA and MCI. It seems that MCDT based on an intermediate level of motor difficulty could represent the sweet spot for the identification of MCI against CNA. Clinical relevance- The combination of innovative digital devices and innovative approach on data analysis (PIs) opened a new scenarios to the early detection and prediction of dementia. Their use would standardize the assessment procedure, lightening the physician from the burden of cumbersome testing sessions. This study suggests that a broader framework for MCDT, which should encompass an ampler selection of motor tasks with different possibilities in terms of difficulties levels, could provide clinicians with a new appropriate set of tools for the early detection of dementia.

Predictive Accuracy of Digital Biomarker Technologies for Detection of Mild Cognitive Impairment and Pre-Frailty Amongst Older Adults: A Systematic Review and Meta-Analysis

Digital biomarker technologies coupled with predictive models are increasingly applied for early detection of age-related potentially reversible conditions including mild cognitive impairment (MCI) and pre-frailty (PF). We aimed to determine the predictive accuracy of digital biomarker technologies to detect MCI and PF with systematic review and meta-analysis. A computer-assisted search on major academic research databases including IEEE-Xplore was conducted. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines were adopted reporting in this study. Summary receiver operating characteristic curve based on random-effect bivariate model was used to evaluate overall sensitivity and specificity for detection of the respective age-related conditions. A total of 43 studies were selected for final systematic review and meta-analysis. 26 studies reported on detection of MCI with sensitivity and specificity of 0.48-1.00 and 0.55-1.00, respectively. On the other hand, there were 17 studies that reported on the detection of PF with reported sensitivity of 0.53-1.00 and specificity of 0.61-1.00. Meta-analysis further revealed pooled sensitivities of 0.84 (95% CI: 0.79-0.88) and 0.82 (95% CI: 0.74-0.88) for in-home detection of MCI and PF, respectively, while pooled specificities were 0.85 (95% CI: 0.80-0.89) and 0.82 (95% CI: 0.75-0.88), respectively. Besides MCI, and PF, in this work during systematic review, we also found one study which reported a sensitivity of 0.93 and a specificity of 0.57 for detection of cognitive frailty (CF). The meta-analytic result, for the first time, quantifies the predictive efficacy of digital biomarker technologies for detection of MCI and PF. Additionally, we found the number of studies for detection of CF to be notably lower, indicating possible research gaps to explore predictive models on digital biomarker technology for detection of CF.

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

Background

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

Methods

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

Results

Gait speed was associated with orientation (r² = 0.16), language (r² = 0.15), recall memory (r² = 0.14), and counting (r² = 0.08). Similarly, handgrip strength was associated with orientation (r² = 0.175), language (r² = 0.164), recall memory (r² = 0.137), and counting (r² = 0.08). To differentiate older adults with and without cognitive impairment, a gait speed cut-off point of 0.59 m/s had an area under the curve (AUC) of 0.629 (0.613–0.646), and a weak handgrip (strength below 17.5 kg) had an AUC of 0.653 (0.645-0.661). The cut-off points for handgrip strength and gait speed were significantly higher in male participants.

Conclusions

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

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.

Single-Task or Dual-Task? Gait Assessment as a Potential Diagnostic Tool for Alzheimer's Dementia

Background:

A person’s gait performance requires the integration of sensorimotor and cognitive systems. Therefore, a person’s gait may be influenced by concurrent cognitive load such as simultaneous talking. Although it has been known that gait performance of people with Alzheimer’s dementia (AD) is compromised when they attempt a dual-task walking task, it is unclear if using a dual-task gait performance during an AD assessment yields higher diagnostic accuracy.

Objective:

This study was designed to compare the predictive power for AD of dual-task gait performance in an AD assessment to that of single-task gait performance.

Methods:

Participants (14 with AD and 15 healthy controls) walked across the GAITRite© Portable Walkway mat under three different cognitive load conditions: no simultaneous cognitive load, walking while counting numbers by ones, and walking while completing category naming.

Results:

Multiple logistic regression revealed that the gait performance under a dual-task condition (i.e., concurrent counting or category naming) increased the proportion of variance explained by the FAP, SL, and DST, of the incidence of AD.

Conclusion:

Dual-task walking and talking may be a more effective diagnostic feature than single-task walking in a comprehensive AD diagnostic assessment.

A wearable ring-shaped inertial system to identify action planning impairments during reach-to-grasp sequences: a pilot study

Background

The progressive ageing of the population is leading to an increasing number of people affected by cognitive decline, including disorders in executive functions (EFs), such as action planning. Current procedures to evaluate cognitive decline are based on neuropsychological tests, but novel methods and approaches start to be investigated. Reach-to-grasp (RG) protocols have shown that intentions can influence the EFs of action planning. In this work, we proposed a novel ring-shaped wearable inertial device, SensRing, to measure kinematic parameters during RG and after-grasp (AG) tasks with different end-goals. The aim is to evaluate whether SensRing can characterize the motor performances of people affected by Mild Neurocognitive Disorder (MND) with impairment in EFs.

Methods

Eight Individuals with dysexecutive MND, named d-MND, were compared to ten older healthy subjects (HC). They were asked to reach and grasp a can with three different intentions: to drink (DRINK), to place it on a target (PLACE), or to pass it to a partner (PASS). Twenty-one kinematic parameters were extracted from SensRing inertial data.

Results

Seven parameters resulted able to differentiate between HC and d-MND in the RG phase, and 8 features resulted significant in the AG phase. d-MND, indeed, had longer reaction times (in RG PLACE), slower peak velocities (in RG PLACE and PASS, in AG DRINK and PLACE), longer deceleration phases (in all RG and AG DRINK), and higher variability (in RG PLACE, in AG DRINK and PASS). Furthermore, d-MND showed no significant differences among conditions, suggesting that impairments in EFs influence their capabilities in modulating the action planning based on the end-goal.

Conclusions

Based on this explorative study, the system might have the potential for objectifying the clinical assessment of people affected by d-MND by administering an easy motor test. Although these preliminary results have to be investigated in-depth in a larger sample, the portability, wearability, accuracy, and ease-of use of the system make the SensRing potentially appliable for remote applications at home, including analysis of protocols for neuromotor rehabilitation in patients affected by MND.