Spatio-temporal and kinematic gait analysis in patients with Frontotemporal dementia and Alzheimer's disease through 3D motion capture

The Impact of Dual-Tasks and Disease Severity on Posture, Gait, and Functional Mobility among People Living with Dementia in Residential Care Facilities: A Pilot Study

Gait speed and timed-up-and-go (TUG) predict cognitive decline, falls, and mortality. Dual-tasks may be useful in cognitive screening among people living with dementia (PWD), but more evidence is needed. This cross-sectional study aimed to compare single- and dual-task performance and determine the influence of dementia severity on dual-task performance and interference. Thirty PWD in two residential care facilities (Age: 81.3 ± 7.1 years; Montreal Cognitive Assessment: 10.4 ± 6.0 points) completed two trials of single- (feet apart) and dual-task posture (feet apart while counting backward), single- (walk 4 m) and dual-task gait (walk 4m while naming words), and single- (timed-up-and-go (TUG)), and dual-task functional mobility (TUG while completing a category task) with APDM inertial sensors. Dual-tasks resulted in greater sway frequency, jerk, and sway area; slower gait speed; greater double limb support; shorter stride length; reduced mid-swing elevation; longer TUG duration; reduced turn angle; and slower turn velocity than single-tasks (ps < 0.05). Dual-task performance was impacted (reduced double limb support, greater mid-swing elevation), and dual-task interference (greater jerk, faster gait speed) was related to moderate-to-severe compared to mild PWD. Moderate-to-severe PWD had poorer dynamic stability and a reduced ability to appropriately select a cautious gait during dual-tasks than those with mild PWD, indicating the usefulness of dual-tasks for cognitive screening.

Medial Temporal Lobe Atrophy in Older Adults With Subjective Cognitive Impairments Affects Gait Parameters in the Spatial Navigation Task

Both navigation abilities and gait can be affected by the atrophy in the medial temporal cortex. This study aimed to determine whether navigation abilities could differentiate seniors with and without medial temporal lobe atrophy who complained about their cognitive status. The participants, classified to either the medial temporal atrophy group (n = 23) or the control group (n = 22) underwent neuropsychological assessment and performed a spatial navigation task while their gait parameters were recorded. The study showed no significant differences between the two groups in memory, fluency, and semantic knowledge or typical measures of navigating abilities. However, gait parameters, particularly the propulsion index during certain phases of the navigation task, distinguished between seniors with and without medial temporal lobe lesions. These findings suggest that the gait parameters in the navigation task may be a valuable tool for identifying seniors with cognitive complaints and subtle medial temporal atrophy.

Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning

Gait abnormalities are frequent in children and can be caused by different pathologies, such as cerebral palsy, neuromuscular disease, toe walker syndrome, etc. Analysis of the "gait pattern" (i.e., the way the person walks) using 3D analysis provides highly relevant clinical information. This information is used to guide therapeutic choices; however, it is underused in diagnostic processes, probably because of the lack of standardization of data collection methods. Therefore, 3D gait analysis is currently used as an assessment rather than a diagnostic tool. In this work, we aimed to determine if deep learning could be combined with 3D gait analysis data to diagnose gait disorders in children. We tested the diagnostic accuracy of deep learning methods combined with 3D gait analysis data from 371 children (148 with unilateral cerebral palsy, 60 with neuromuscular disease, 19 toe walkers, 60 with bilateral cerebral palsy, 25 stroke, and 59 typically developing children), with a total of 6400 gait cycles. We evaluated the accuracy, sensitivity, specificity, F1 score, Area Under the Curve (AUC) score, and confusion matrix of the predictions by ResNet, LSTM, and InceptionTime deep learning architectures for time series data. The deep learning-based models had good to excellent diagnostic accuracy (ranging from 0.77 to 0.99) for discrimination between healthy and pathological gait, discrimination between different etiologies of pathological gait (binary and multi-classification); and determining stroke onset time. LSTM performed best overall. This study revealed that the gait pattern contains specific, pathology-related information. These results open the way for an extension of 3D gait analysis from evaluation to diagnosis. Furthermore, the method we propose is a data-driven diagnostic model that can be trained and used without human intervention or expert knowledge. Furthermore, the method could be used to distinguish gait-related pathologies and their onset times beyond those studied in this research.

Age and beta amyloid deposition impact gait speed, stride length, and gait smoothness while transitioning from an even to an uneven walking surface in older adults

BACKGROUND

Capturing a measure of movement quality during a complex walking task may indicate the earliest signs of detrimental changes to the brain due to beta amyloid (Aβ) deposition and be a potential differentiator of older adults at elevated and low risk of developing Alzheimer's disease. This study aimed to determine: 1) age-related differences in gait speed, stride length, and gait smoothness while transitioning from an even to an uneven walking surface, by comparing young adults (YA) and older adults (OA), and 2) if gait speed, stride length, and gait smoothness in OA while transitioning from an even to an uneven walking surface is influenced by the amount of Aβ deposition present in an OA's brain.

METHODS

Participants included 56 OA (>70 years of age) and 29 YA (25-35 years of age). In OA, Aβ deposition in the brain was quantified by PET imaging. All participants completed a series of cognitive assessments, a functional mobility assessment, and self-report questionnaires. Then participants performed two sets of walking trials on a custom-built walkway containing a mixture of even and uneven surface sections, including three trials with a grass uneven surface and three trials with a rocks uneven surface. Gait data were recorded using a wireless inertial measurement unit system. Stride length, gait speed, and gait smoothness (i.e., log dimensionless lumbar jerk) in the anteroposterior (AP), mediolateral (ML), and vertical (VT) directions were calculated for each stride. Outcomes were retained for five stride locations immediately surrounding the surface transition.

RESULTS

OA exhibited slower gait (Grass: p < 0.001; Rocks: p = 0.006), shorter strides (Grass: p < 0.001; Rocks: p = 0.008), and smoother gait (Grass AP: p < 0.001; Rocks AP: p = 0.002; Rocks ML: p = 0.02) than YA, but they also exhibited greater reductions in gait speed and stride length than YA while transitioning to the uneven grass and rocks surfaces. Within the OA group, those with greater Aβ deposition exhibited decreases in smoothness with age (Grass AP: p = 0.02; Rocks AP: p = 0.03; Grass ML: p = 0.04; Rocks ML: p = 0.03), while those with lower Aβ deposition exhibited increasing smoothness with age (Grass AP: p = 0.01; Rocks AP: p = 0.02; Grass ML: p = 0.08; Rocks ML: p = 0.07). Better functional mobility was associated with less smooth gait (Grass ML: p = 0.02; Rocks ML: p = 0.05) and with less variable gait smoothness (Grass and Rocks AP: both p = 0.04) in the OA group.

CONCLUSION

These results suggest that, relative to YA, OA may be adopting more cautious, compensatory gait strategies to maintain smoothness when approaching surface transitions. However, OA with greater Aβ deposition may have limited ability to adopt compensatory gait strategies to increase the smoothness of their walking as they get older because of neuropathological changes altering the sensory integration process and causing worse dynamic balance (i.e., jerkier gait). Functional mobility, in addition to age and Aβ deposition, may be an important factor of whether or not an OA chooses to employ compensatory strategies to prioritize smoothness while walking and what type of compensatory strategy an OA chooses.

Gait variability-based classification of the stages of the cognitive decline using partial least squares-discriminant analysis

The purpose of the present study was to examine the differences in gait variability in terms of spatiotemporal, sub-gait cycle, ground reaction force, and the joint profiles of kinematics and kinetics between older individuals with and without risk of potential cognitive impairment, and to derive the crucial features to discriminating the older adults with future risk cognitive decline by using partial least squares-discriminant analysis. A total of 90 community-dwelling older adults aged over 65 years underwent cognitive function assessment and were divided into three groups depending on cognitive assessment score. The participants' level-walking was analyzed by using three-dimensional instrumented gait analysis. The coefficient of variation was extracted and then comparatively analyzed depending on the stages of the cognitive decline. To identify the most important contributor when differentiating the older adults with a risk of future cognitive decline, partial least squares-discriminant analysis was applied, and the discriminative power of the coefficients confirmed as features of great importance were investigated via the receiver operating characteristic area under the curve. The differences in gait variability were found mainly between the suspected dementia groups and other groups, especially in joint dynamics variables. Through the partial least squares-discriminant analysis, the discriminative features were found as follows: the mid-stance, the moments, and the power in the hip, knee, and ankle joints. In addition, the discrimination model was found to differentiate well between the three groups. The classification accuracy of intact cognition, diminished cognition, and suspected dementia was 0.857, 0.710, and 0.857, respectively. These findings mean that gait variability changes according to continuous cognitive decline, especially in sub-gait cycles and joint biomechanics, and suggest that measures of variation can be used as predictors to identify older individuals with a risk of potential cognitive impairment.

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.

Neuroimaging modalities in the detection of Alzheimer's disease-associated biomarkers

Alzheimer's disease (AD) is the most common cause of dementia. Neuropathological changes in AD patients occur up to 10-20 years before the emergence of clinical symptoms. Specific diagnosis and appropriate intervention strategies are crucial during the phase of mild cognitive impairment (MCI) and AD. The detection of biomarkers has emerged as a promising tool for tracking the efficacy of potential therapies, making an early disease diagnosis, and prejudging treatment prognosis. Specifically, multiple neuroimaging modalities, including magnetic resonance imaging (MRI), positron emission tomography, optical imaging, and single photon emission-computed tomography, have provided a few potential biomarkers for clinical application. The MRI modalities described in this review include structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, and arterial spin labelling. These techniques allow the detection of presymptomatic diagnostic biomarkers in the brains of cognitively normal elderly people and might also be used to monitor AD disease progression after the onset of clinical symptoms. This review highlights potential biomarkers, merits, and demerits of different neuroimaging modalities and their clinical value in MCI and AD patients. Further studies are necessary to explore more biomarkers and overcome the limitations of multiple neuroimaging modalities for inclusion in diagnostic criteria for AD.

Cortical thickness is related to cognitive-motor automaticity and attention allocation in individuals with Alzheimer's disease: a regions of interest study

Alzheimer's disease (AD) is characterized by a distinct pattern of cortical thinning and resultant changes in cognition and function. These result in prominent deficits in cognitive-motor automaticity. The relationship between AD-related cortical thinning and decreased automaticity is not well-understood. We aimed to investigate the relationship between cortical thickness regions-of-interest (ROI) and automaticity and attention allocation in AD using hypothesis-driven and exploratory approaches. We performed an ROI analysis of 46 patients with AD. Data regarding MR images, demographic characteristics, cognitive-motor dual task performance, and cognition were extracted from medical records. Cortical thickness was calculated from MR T1 images using FreeSurfer. Data from the dual task assessment was used to calculate the combined dual task effect (cDTE), a measure of cognitive-motor automaticity, and the modified attention allocation index (mAAI). Four hierarchical multiple linear regression models were conducted regressing cDTE and mAAI separately on (1) hypothesis-generated ROIs and (2) exploratory ROIs. For cDTE, cortical thicknesses explained 20.5% (p = 0.014) and 25.9% (p = 0.002) variability in automaticity in the hypothesized ROI and exploratory models, respectively. The dorsal lateral prefrontal cortex (DLPFC) (β =  - 0.479, p = 0.018) and superior parietal cortex (SPC) (β = 0.467, p = 0.003), and were predictors of automaticity. For mAAI, cortical thicknesses explained 20.7% (p = 0.025) and 28.3% (p = 0.003) variability in attention allocation in the hypothesized ROI and exploratory models, respectively. Thinning of SPC and fusiform gyrus were associated with motor prioritization (β =  - 0.405, p = 0.013 and β =  - 0.632, p = 0.004, respectively), whereas thinning of the DLPFC was associated with cognitive prioritization (β = 0.523, p = 0.022). Cortical thinning in AD was related to cognitive-motor automaticity and task prioritization, particularly in the DLPFC and SPC. This suggests that these regions may play a primary role in automaticity and attentional strategy during dual-tasking.

Geriatric Care Management System Powered by the IoT and Computer Vision Techniques

The digitalisation of geriatric care refers to the use of emerging technologies to manage and provide person-centered care to the elderly by collecting patients' data electronically and using them to streamline the care process, which improves the overall quality, accuracy, and efficiency of healthcare. In many countries, healthcare providers still rely on the manual measurement of bioparameters, inconsistent monitoring, and paper-based care plans to manage and deliver care to elderly patients. This can lead to a number of problems, including incomplete and inaccurate record-keeping, errors, and delays in identifying and resolving health problems. The purpose of this study is to develop a geriatric care management system that combines signals from various wearable sensors, noncontact measurement devices, and image recognition techniques to monitor and detect changes in the health status of a person. The system relies on deep learning algorithms and the Internet of Things (IoT) to identify the patient and their six most pertinent poses. In addition, the algorithm has been developed to monitor changes in the patient's position over a longer period of time, which could be important for detecting health problems in a timely manner and taking appropriate measures. Finally, based on expert knowledge and a priori rules integrated in a decision tree-based model, the automated final decision on the status of nursing care plan is generated to support nursing staff.

A double-channel multiscale depthwise separable convolutional neural network for abnormal gait recognition

Abnormal gait recognition is important for detecting body part weakness and diagnosing diseases. The abnormal gait hides a considerable amount of information. In order to extract the fine, spatial feature information in the abnormal gait and reduce the computational cost arising from excessive network parameters, this paper proposes a double-channel multiscale depthwise separable convolutional neural network (DCMSDSCNN) for abnormal gait recognition. The method designs a multiscale depthwise feature extraction block (MDB), uses depthwise separable convolution (DSC) instead of standard convolution in the module and introduces the Bottleneck (BK) structure to optimize the MDB. The module achieves the extraction of effective features of abnormal gaits at different scales, and reduces the computational cost of the network. Experimental results show that the gait recognition accuracy is up to 99.60%, while the memory size of the model is reduced 4.21 times than before optimization.

Motor and cognitive deficits limit the ability to flexibly modulate spatiotemporal gait features in older adults with mild cognitive impairment

Introduction: Dance-based therapies are an emerging form of movement therapy aiming to improve motor and cognitive function in older adults with mild cognitive impairments (MCIs). Despite the promising effects of dance-based therapies on function, it remains unclear how age-related declines in motor and cognitive function affect movement capacity and influence which movements and rhythms maximize dance therapy efficacy. Here, we evaluated the effects of age and MCI on the ability to accurately modulate spatial (i.e., joint kinematics), temporal (i.e., step timing), and spatiotemporal features of gait to achieve spatial and temporal targets during walking. Methods: We developed novel rhythmic movement sequences-nine spatial, nine temporal, and four spatiotemporal-that deviated from typical spatial and temporal features of walking. Healthy young adults (HYA), healthy older adults (HOA), and adults with MCI were trained on each gait modification before performing the modification overground, with kinematic data recorded using wearable sensors. Results: HOA performed spatial (p = 0.010) and spatiotemporal (p = 0.048) gait modifications less accurately than HYA. Individuals with MCI performed spatiotemporal gait modifications less accurately than HOA (p = 0.017). Spatial modifications to the swing phase of gait (p = 0.006, Cohen's d = -1.3), and four- and six-step Duple rhythms during temporal modifications (p ≤ 0.030, Cohen's d ≤ 0.9) elicited the largest differences in gait performance in HYA vs. HOA and HOA vs. MCI, respectively. Discussion: These findings suggest that age-related declines in strength and balance reduce the ability to accurately modulate spatial gait features, while declines in working memory in individuals with MCI may reduce the ability to perform longer temporal gait modification sequences. Differences in rhythmic movement sequence performance highlight motor and cognitive factors potentially underlying deficits in gait modulation capacity, which may guide therapy personalization and provide more sensitive indices to track intervention efficacy.

Types of anomalies in two-dimensional video-based gait analysis in uncontrolled environments

Two-dimensional video-based pose estimation is a technique that can be used to estimate human skeletal coordinates from video data alone. It is also being applied to gait analysis and in particularly, due to its simplicity of measurement, it has the potential to be applied to gait analysis of large populations. However, it is considered difficult to completely homogenize the environment and settings during the measurement of large populations. Therefore, it is necessary to appropriately deal with technical errors that are not related to the biological factors of interest. In this study, by analyzing a large cohort database, we have identified four major types of anomalies that occur during gait analysis using OpenPose in uncontrolled environments: anatomical, biomechanical, and physical anomalies and errors due to estimation. We have also developed a workflow for identifying and correcting these anomalies and confirmed that this workflow is reproducible through simulation experiments. Our results will help obtain a comprehensive understanding of the anomalies to be addressed during pre-processing for 2D video-based gait analysis of large populations.

Use of electroencephalogram, gait, and their combined signals for classifying cognitive impairment and normal cognition

Background

Early identification of people at risk for cognitive decline is an important step in delaying the occurrence of cognitive impairment. This study investigated whether multimodal signals assessed using electroencephalogram (EEG) and gait kinematic parameters could be used to identify individuals at risk of cognitive impairment.

Methods

The survey was conducted at the Veterans Medical Research Institute in the Veterans Health Service Medical Center. A total of 220 individuals volunteered for this study and provided informed consent at enrollment. A cap-type wireless EEG device was used for EEG recording, with a linked-ear references based on a standard international 10/20 system. Three-dimensional motion capture equipment was used to collect kinematic gait parameters. Mild cognitive impairment (MCI) was evaluated by Seoul Neuropsychological Screening Battery-Core (SNSB-C).

Results

The mean age of the study participants was 73.5 years, and 54.7% were male. We found that specific EEG and gait parameters were significantly associated with cognitive status. Individuals with decreases in high-frequency EEG activity in high beta (25-30 Hz) and gamma (30-40 Hz) bands increased the odds ratio of MCI. There was an association between the pelvic obliquity angle and cognitive status, assessed by MCI or SNSB-C scores. Results from the ROC analysis revealed that multimodal signals combining high beta or gamma and pelvic obliquity improved the ability to discriminate MCI individuals from normal controls.

Conclusion

These findings support prior work on the association between cognitive status and EEG or gait, and offer new insights into the applicability of multimodal signals to distinguish cognitive impairment.

The effect of different dual tasks conditions on gait kinematics and spatio-temporal walking parameters in older adults

BACKGROUND

Dual-task (DT) walking has increasingly been investigated over the last decade because of its valuable role as a clinical marker of both cognitive impairment and fall risk in older adults based on cognitive and motor performance (DTEcog, DTEmotor). However, there is still a lack of information on what type of dual task to choose and which is the most adapted to the population of interest.

RESEARCH QUESTION

To evaluate the effect of different dual-tasks (DT3, DT7, FLU, STROOP) on the spatiotemporal and kinematic parameters of hip, knee, and ankle joints.

METHODS

Thirty-eight older adults were recruited (9 men, 29 women, mean age = 77.5 +/- 6.5 years, mean height = 163.6 +/- 8.6 cm, mean weight = 67.5 +/- 15.3 kg). They performed a single and dual-task walk with the 4 types of tasks during 1 min, equipped with an inertial system. Dual-task effect (DTE) on spatiotemporal and kinematic variables as well as cognitive score and speed were calculated.

RESULTS

An alteration in most of the spatiotemporal parameters was observed in each DT condition (p < 0.05), especially in arithmetic tasks (DT3, DT7), while no DT effect was noticed on kinematic parameters (RMSE<3°) except on hip and knee angular velocities (RMSE>15°). Arithmetic tasks seemed to alter more spatiotemporal and kinematic parameters than the verbal fluency or STROOP test. However, DT7 appeared to be too difficult for the population of interest.

SIGNIFICANCE

Arithmetic tasks seemed to be very pertinent as a clinical dual-task protocol for older adults. The use of an inertial system to retrieve kinematic variables is an improvement in these dual-task protocols.

Rivastigmine Reverses the Decrease in Synapsin and Memory Caused by Homocysteine: Is There Relation to Inflammation?

Elevated levels of homocysteine (Hcy) in the blood, called hyperhomocysteinemia (HHcy), is a prevalent risk factor for it has been shown that Hcy induces oxidative stress and increases microglial activation and neuroinflammation, as well as causes cognitive impairment, which have been linked to the neurodegenerative process. This study aimed to evaluate the effect of mild hyperhomocysteinemia with or without ibuprofen and rivastigmine treatments on the behavior and neurochemical parameters in male rats. The chronic mild HHcy model was chemically induced in Wistar rats by subcutaneous administration of Hcy (4055 mg/kg body weight) twice daily for 30 days. Ibuprofen (40 mg/kg) and rivastigmine (0.5 mg/kg) were administered intraperitoneally once daily. Motor damage (open field, balance beam, rotarod, and vertical pole test), cognitive deficits (Y-maze), neurochemical parameters (oxidative status/antioxidant enzymatic defenses, presynaptic protein synapsin 1, inflammatory profile parameters, calcium binding adapter molecule 1 (Iba1), iNOS gene expression), and cholinergic anti-inflammatory pathway were investigated. Results showed that mild HHcy caused cognitive deficits in working memory, and impaired motor coordination reduced the amount of synapsin 1 protein, altered the neuroinflammatory picture, and caused changes in the activity of catalase and acetylcholinesterase enzymes. Both rivastigmine and ibuprofen treatments were able to mitigate this damage caused by mild HHcy. Together, these neurochemical changes may be associated with the mechanisms by which Hcy has been linked to a risk factor for AD. Treatments with rivastigmine and ibuprofen can effectively reduce the damage caused by increased Hcy levels.

Sensitivity to gait improvement after levodopa intake in Parkinson's disease: A comparison study among synthetic kinematic indices

The synthetic indices are widely used to describe balance and stability during gait. Some of these are employed to describe the gait features in Parkinson's disease (PD). However, the results are sometimes inconsistent, and the same indices are rarely used to compare the individuals affected by PD before and after levodopa intake (OFF and ON condition, respectively). Our aim was to investigate which synthetic measure among Harmonic Ratio, Jerk Ratio, Golden Ratio and Trunk Displacement Index is representative of gait stability and harmony, and which of these are more sensitive to the variations between OFF and ON condition. We found that all indices, except the Jerk Ratio, significantly improve after levodopa. Only the improvement of the Trunk Displacement Index showed a direct correlation with the motor improvement measured through the clinical scale UPDRS-III (Unified Parkinson's Disease Rating Scale-part III). In conclusion, we suggest that the synthetic indices can be useful to detect motor changes induced by, but not all of them clearly correlate with the clinical changes achieved with the levodopa administration. In our analysis, only the Trunk Displacement Index was able to show a clear relationship with the PD clinical motor improvement.

Multidimensional Clinical Assessment in Frontotemporal Dementia and Its Spectrum in Latin America and the Caribbean: A Narrative Review and a Glance at Future Challenges

Frontotemporal dementia (FTD) is the third most common form of dementia across all age groups and is a leading cause of early-onset dementia. The Frontotemporal dementia (FTD) includes a spectrum of diseases that are classified according to their clinical presentation and patterns of neurodegeneration. There are two main types of FTD: behavioral FTD variant (bvFTD), characterized by a deterioration in social function, behavior, and personality; and primary progressive aphasias (PPA), characterized by a deficit in language skills. There are other types of FTD-related disorders that present motor impairment and/or parkinsonism, including FTD with motor neuron disease (FTD-MND), progressive supranuclear palsy (PSP), and corticobasal syndrome (CBS). The FTD and its associated disorders present great clinical heterogeneity. The diagnosis of FTD is based on the identification through clinical assessments of a specific clinical phenotype of impairments in different domains, complemented by an evaluation through instruments, i.e., tests and questionnaires, validated for the population under study, thus, achieving timely detection and treatment. While the prevalence of dementia in Latin America and the Caribbean (LAC) is increasing rapidly, there is still a lack of standardized instruments and consensus for FTD diagnosis. In this context, it is important to review the published tests and questionnaires adapted and/or validated in LAC for the assessment of cognition, behavior, functionality, and gait in FTD and its spectrum. Therefore, our paper has three main goals. First, to present a narrative review of the main tests and questionnaires published in LAC for the assessment of FTD and its spectrum in six dimensions: (i) Cognitive screening; (ii) Neuropsychological assessment divided by cognitive domain; (iii) Gait assessment; (iv) Behavioral and neuropsychiatric symptoms; (v) Functional assessment; and (vi) Global Rating Scale. Second, to propose a multidimensional clinical assessment of FTD in LAC identifying the main gaps. Lastly, it is proposed to create a LAC consortium that will discuss strategies to address the current challenges in the field.

The effects of different frequencies of rhythmic acoustic stimulation on gait stability in healthy elderly individuals: a pilot study

The efficacy of rhythmic acoustic stimulation (RAS) to improve gait and balance in healthy elderly individuals is controversial. Our aim was to investigate, through 3D gait analysis, the effect of different types of RAS (fixed frequency and based on subject-specific cadence), using conventional gait parameters and the trunk displacement as readouts. Walking at a fixed frequency of 80 bpm, the subjects showed extended duration of gait cycle and increased gait variability while the same individuals, walking at a fixed frequency of 120 bpm, showed reduced trunk sway and gait cycle duration. With regard to the RAS at subject-specific frequencies, walking at 90% of the subject-specific average cadence did not significantly modify the gait parameters, except for the speed, which was reduced. In contrast, walking at 100% and 110% of the mean cadence caused increased stride length and a slight reduction of temporal parameters and trunk sway. In conclusion, this pilot study shows that using RAS at fixed frequencies might be an inappropriate strategy, as it is not adjusted to individual gait characteristics. On the other hand, RAS frequencies equal to or slightly higher than each subject's natural cadence seem to be beneficial for gait and stability.

Gait Kinematic and Kinetic Characteristics of Older Adults With Mild Cognitive Impairment and Subjective Cognitive Decline: A Cross-Sectional Study

Background

Older adults with mild cognitive impairment (MCI) have slower gait speed and poor gait performance under dual-task conditions. However, gait kinematic and kinetic characteristics in older adults with MCI or subjective cognitive decline (SCD) remain unknown. This study was designed to explore the difference in gait kinematics and kinetics during level walking among older people with MCI, SCD, and normal cognition (NC).

Methods

This cross-sectional study recruited 181 participants from July to December 2019; only 82 met the inclusion criteria and consented to participate and only 79 completed gait analysis. Kinematic and kinetic data were obtained using three-dimensional motion capture system during level walking, and joint movements of the lower limbs in the sagittal plane were analyzed by Visual 3D software. Differences in gait kinematics and kinetics among the groups were analyzed using multivariate analysis of covariance (MANCOVA) with Bonferroni post-hoc analysis. After adjusting for multiple comparisons, the significance level was p < 0.002 for MANCOVA and p < 0.0008 for post-hoc analysis.

Results

Twenty-two participants were MCI [mean ± standard deviation (SD) age, 71.23 ± 6.65 years], 33 were SCD (age, 72.73 ± 5.25 years), and 24 were NC (age, 71.96 ± 5.30 years). MANCOVA adjusted for age, gender, body mass index (BMI), gait speed, years of education, diabetes mellitus, and Geriatric Depression Scale (GDS) revealed a significant multivariate effect of group in knee peak extension angle (F = 8.77, p < 0.0001) and knee heel strike angle (F = 8.07, p = 0.001) on the right side. Post-hoc comparisons with Bonferroni correction showed a significant increase of 5.91° in knee peak extension angle (p < 0.0001) and a noticeable decrease of 6.21°in knee heel strike angle (p = 0.001) in MCI compared with NC on the right side. However, no significant intergroup difference was found in gait kinetics, including dorsiflexion, plantar flexion, knee flexion, knee extension, hip flexion, and hip extension(p > 0.002).

Conclusion

An increase of right knee peak extension angle and a decrease of right knee heel strike angle during level walking were found among older adults with MCI compared to those with NC.

Early manifestation of gait alterations in the Tg2576 mouse model of Alzheimer's disease

There is strong clinical evidence that multifaceted gait abnormalities may be manifested at early stages of Alzheimer's disease (AD), are related to cognitive decline, and can be used as an early biomarker to identify patients at risk of progressing to full-blown dementia. Despite their importance, gait abnormalities have not been investigated in mouse models of AD, which replicate important aspects of the human disease. The Tg2576 is frequently used in AD research to test therapeutic interventions targeting cellular mechanisms contributing to the genesis of AD. This transgenic mouse strain overexpresses a mutant form of the 695 amino acid isoform of human amyloid precursor protein with K670N and M671L mutations (APPK670/671L) linked to early-onset familial AD. Tg2576 mice exhibit impaired cognitive functions and increased cortical and hippocampal soluble β-amyloid levels starting from 5 months of age and increased insoluble β-amyloid levels and amyloid plaques that resemble senile plaques associated with human AD by 13 months of age. To demonstrate early manifestations of gait dysfunction in this relevant preclinical model, we characterized gait and motor performance in 10-month-old Tg2576 mice and age-matched littermate controls using the semi-automated, highly sensitive, Catwalk XT system. We found that Tg2576 mice at the pre-plaque stage exhibited significantly altered duty cycle and step patterns and decreased stride length and stride time. Base-of-support, stride time variability, stride length variability, cadence, phase dispersions and gait symmetry indices were unaltered. The presence of measurable early gait abnormalities during the pre-plaque stages of AD in this relevant preclinical mouse model has direct translational relevance and supports the view that longitudinal monitoring of gait performance could be used in addition to behavioral testing to evaluate progression of the disease and to assess treatment efficacy.

Human Gait Analysis in Neurodegenerative Diseases: a Review

This paper reviews the recent literature on technologies and methodologies for quantitative human gait analysis in the context of neurodegnerative diseases. The use of technological instruments can be of great support in both clinical diagnosis and severity assessment of these pathologies. In this paper, sensors, features and processing methodologies have been reviewed in order to provide a highly consistent work that explores the issues related to gait analysis. First, the phases of the human gait cycle are briefly explained, along with some non-normal gait patterns (gait abnormalities) typical of some neurodegenerative diseases. The work continues with a survey on the publicly available datasets principally used for comparing results. Then the paper reports the most common processing techniques for both feature selection and extraction and for classification and clustering. Finally, a conclusive discussion on current open problems and future directions is outlined.

Critical spatiotemporal gait parameters for individuals with dementia: A systematic review and meta-analysis

Instrumented gait analysis allows for the identification of walking parameters to predict cognitive decline and the worsening of dementia. The aim of this study was to perform a meta-analysis to better clarify which gait parameters are affected or modified with the progression of the dementia in a larger sample, as well as which gait assessment conditions (single-task or dual-task conditions) would be more sensitive to reflect the influence of dementia. Literature searches were conducted with the keywords "quantitative gait" OR "gait analysis" AND "dementia" AND "single-task" AND "dual-task," and for "quantitative gait" OR "gait analysis" AND "dementia" AND "fall risk" on PubMed, EMBASE, the Cochrane Library, Scopus, and Web of Science. The results were used to perform a systematic review focussing on instrumental quantitative assessment of the walking of patients with dementia, during both single and dual tasks. The search was performed independently by two authors (C. R. and C. M.) from January 2018 to April 2020 using the PICOS criteria. Nine publications met the inclusion criteria and were included in the systematic review. Our meta-analysis showed that during a single task, most of the spatiotemporal parameters of gait discriminated best between patients with dementia and healthy controls, including speed, cadence, stride length, stride time, stride time variability, and stance time. In dual tasks, only speed, stride length, and stride time variability discriminated between the two groups. In addition, compared with spatial parameters (e.g. stride length), some temporal gait parameters were more correlated to the risk of falls during the comfortable walking in a single task, such as cadence, stride time, stride time variability, and stance time. During a dual task, only the variability of stride time was associated with the risk of falls.

A synthetic kinematic index of trunk displacement conveying the overall motor condition in Parkinson's disease

Parkinson's disease (PD) is characterized by motor impairment, affecting quality of life and increasing fall risk, due to ineffective postural control. To this day, the diagnosis remains based on clinical approach. Similarly, motor evaluation is based on heterogeneous, operator-dependent observational criteria. A synthetic, replicable index to quantify motor impairment is still lacking. Hence, we have designed a new measure of postural stability which assesses the trunk displacement in relation to the center of mass, that we named trunk displacement index (TDI). Twenty-three PD patients and twenty-three healthy controls underwent motor examination through a stereophotogrammetric system. A correlation analysis was performed to assess the relationship of TDI with gait parameters and clinical motor scale (UPDRS-III). The TDI sensitivity was estimated, comparing pre- and post- L-DOPA subclinical dose intake. The TDI showed significant correlations with many gait parameters and with the UPDRS-III. Furthermore, the TDI resulted capable in discriminating between off and on state in PD, whereas gait parameters failed two show any difference between those two conditions. Our results suggest that the TDI may be considered a highly sensitive biomechanical index, reflecting the overall motor condition in PD, and provided of clinical relevance due to the correlation with the clinical evaluation.

Treadmill-to-Overground Mapping of Marker Trajectory for Treadmill-Based Continuous Gait Analysis

A treadmill was used to perform continuous walking tests in a limited space that can be covered by marker-based optical motion capture systems. Most treadmill-based gait data are analyzed based on gait cycle percentage. However, achieving continuous walking motion trajectories over time without time normalization is often required, even if tests are performed under treadmill walking conditions. This study presents a treadmill-to-overground mapping method of optical marker trajectories for treadmill-based continuous gait analysis, by adopting a simple concept of virtual origin. The position vector from the backward moving virtual origin to a targeted marker within a limited walking volume is the same as the position vector from the fixed origin to the forward moving marker over the ground. With the proposed method, it is possible (i) to observe the change in physical quantity visually during the treadmill walking, and (ii) to obtain overground-mapped gait data for evaluating the accuracy of the inertial-measurement-unit-based trajectory estimation. The accuracy of the proposed method was verified from various treadmill walking tests, which showed that the total travel displacement error rate was 0.32% on average.

Increases in hypertension-induced cerebral microhemorrhages exacerbate gait dysfunction in a mouse model of Alzheimer's disease

Clinical studies show that cerebral amyloid angiopathy (CAA) associated with Alzheimer's disease (AD) and arterial hypertension are independent risk factors for cerebral microhemorrhages (CMHs). To test the hypothesis that amyloid pathology and hypertension interact to promote the development of CMHs, we induced hypertension in the Tg2576 mouse model of AD and respective controls by treatment with angiotensin II (Ang II) and the NO synthesis inhibitor L-NAME. The number, size, localization, and neurological consequences (gait alterations) of CMHs were compared. We found that compared to control mice, in TG2576 mice, the same level of hypertension led to significantly increased CMH burden and exacerbation of CMH-related gait alterations. In hypertensive TG2576 mice, CMHs were predominantly located in the cerebral cortex at the cortical-subcortical boundary, mimicking the clinical picture seen in patients with CAA. Collectively, amyloid pathologies exacerbate the effects of hypertension, promoting the genesis of CMHs, which likely contribute to their deleterious effects on cognitive function. Therapeutic strategies for prevention of CMHs that reduce blood pressure and preserve microvascular integrity are expected to exert neuroprotective effects in high-risk elderly AD patients.

Gait analysis in neurological populations: Progression in the use of wearables

Gait assessment is an essential tool for clinical applications not only to diagnose different neurological conditions but also to monitor disease progression as it contributes to the understanding of underlying deficits. There are established methods and models for data collection and interpretation of gait assessment within different pathologies. This narrative review aims to depict the evolution of gait assessment from observation and rating scales to wearable sensors and laboratory technologies and provide limitations and possible future directions in the field of gait assessment. In this context, we first present an extensive review of current clinical outcomes and gait models. Then, we demonstrate commercially available wearable technologies with their technical capabilities along with their use in gait assessment studies for various neurological conditions. In the next sections, a descriptive knowledge for existing inertial and EMG based algorithms and a sign based guide that shows the outcomes of previous neurological gait assessment studies are presented. Finally, we state a discussion for the use of wearables in gait assessment and speculate the possible research directions by revealing the limitations and knowledge gaps in the literature.

Weaker Braking Force, A New Marker of Worse Gait Stability in Alzheimer Disease

Background: Braking force is a gait marker associated with gait stability. This study aimed to determine the alteration of braking force and its correlation with gait stability in Alzheimer disease (AD).

Methods: A total of 32 AD patients and 32 healthy controls (HCs) were enrolled in this study. Gait parameters (braking force, gait variability, and fall risk) in the walking tests of Free walk, Barrier, and Count backward were measured by JiBuEn^® gait analysis system. Gait variability was calculated by the coefficient of variation (COV) of stride time, stance time, and swing time.

Results: The braking force of AD was significantly weaker than HCs in three walking tests (P < 0.001, P < 0.001, P = 0.007). Gait variability of AD showed significant elevation than HCs in the walking of Count backward (COV_stride: P = 0.013; COV_swing: P = 0.006). Fall risk of AD was significantly higher than HCs in three walking tests (P = 0.001, P = 0.001, P = 0.001). Braking force was negatively associated with fall risks in three walking tests (P < 0.001, P < 0.001, P < 0.001). There were significant negative correlations between braking force and gait variability in the walking of Free walk (COV_stride: P = 0.018; COV_swing: P = 0.013) and Barrier (COV_stride: P = 0.002; COV_swing: P = 0.001), but not Count backward (COV_stride: P = 0.888; COV_swing: P = 0.555).

Conclusion: Braking force was weaker in AD compared to HCs, reflecting the worse gait stability of AD. Our study suggests that weakening of braking force may be a new gait marker to indicate cognitive and motor impairment and predict fall risk in AD.

The continuum between neurodegeneration, brain plasticity, and movement: a critical appraisal

While the “physiological” aging process is associated with declines in motor and cognitive features, these changes do not significantly impair functions and activities of daily living. Differently, motor and cognitive impairment constitute the most common phenotypic expressions of neurodegeneration. Both manifestations frequently coexist in the same disease, thus making difficult to detect “pure” motor or cognitive conditions. Movement disorders are often characterized by cognitive disturbances, and neurodegenerative dementias often exhibit the occurrence of movement disorders. Such a phenotypic overlap suggests approaching these conditions by highlighting the commonalities of entities traditionally considered distinct. In the present review, we critically reappraised the common clinical and pathophysiological aspects of neurodegeneration in both animal models and patients, looking at motricity as a trait d’union over the spectrum of neurodegeneration and focusing on synaptopathy and oscillopathy as the common pathogenic background. Finally, we discussed the possible role of movement as neuroprotective intervention in neurodegenerative conditions, regardless of the etiology. The identification of commonalities is critical to drive future research and develop novel possible disease-modifying interventions.

Comparison of gait speeds from wearable camera and accelerometer in structured and semi-structured environments

A feasibility study was conducted to investigate the use of a wearable gait analysis system for classifying gait speed using a low-cost wearable camera in a semi-structured indoor setting. Data were collected from 19 participants who wore the system during indoor walk sequences at varying self-determined speeds (slow, medium, and fast). Gait parameters using this system were compared with parameters obtained from a vest comprising of a single triaxial accelerometer and from a marker-based optical motion-capture system. Computer-vision techniques and signal processing methods were used to generate frequency-domain gait parameters from each gait-recording device, and those parameters were analysed to determine the effectiveness of the different measurement systems in discriminating gait speed. Results indicate that the authors’ low-cost, portable, vision-based system can be effectively used for in-home gait analysis.

Spatiotemporal quantification of gait in common marmosets

BACKGROUND

Objective gait evaluation in humans is used as a predictive disability outcome measure as well as an indicator for intervention effectiveness. Parallel methods of gait analysis in nonhuman primate models are essential for clinical translation. The goal of this study was to first assess whether marmosets' gait data could be reliably collected in a Noldus CatWalk XT10.6 and second, establish a testing protocol to assess gait and the intraindividual variability during repeated testing.

NEW METHOD

The CatWalk, originally developed for rodents, was modified and used to assess gait in eight adult common marmoset monkeys across multiple days and trials. Data was first analyzed to identify valid runs. Repeated measures ANOVA was completed for the following gait measures: mean base of support, average stride length, average swing time, and average stance time.

RESULTS

Raters had a high level of concurrence of usable data across all trials with successful trials including four consecutive hindfoot footfalls, during a continuous, uninterrupted segment of walking. A significant main effect of time (p < 0.000) but not rater (p = 0.98) was present with significant interactions for time by subject (p < 0.000), but not rater per subject (p = 0.538), time (p = 0.186), or three-way interaction (p = 0.297).

COMPARISON WITH EXISTING METHOD(S)

Gait has been assessed using force-plate and video data. The CatWalk allowed reproducible, automated and translational locomotor data to be collected at multiple time points with detailed analyses that identified a diagonal gait pattern.

CONCLUSIONS

The CatWalk system, similar to those used in humans, can be effectively used to quantify spatiotemporal characteristics of gait in the common marmoset.

A Parametric Identification Method of Human Gait Differences and its Application in Rehabilitation

In order to understand the regularity of human motion, characteristic description is widely used in gait analysis. For completely expressing gait information and providing more concise indicators, parametric description is also particularly significant as a means of analysis. Therefore, in this paper, the mathematical models of gait curves based on the generalized extension-Bézier curve were investigated, of which the shape parameters were used as individual gait characteristics to distinguish whether the gait is normal or not and to assist in judging rehabilitation. To evaluate the models, angle data from three joints (hip, knee, and ankle) were recorded with motion capture system when participants (10 healthy males and 6 male patients with ankle fracture) were walking at comfortable velocity along a walkway. Then, the shape parameters of each subject were obtained by applying the mathematical models, and the parameter range of the normal group was further summarized. Through comparison, it could be found that most shape parameters of patients exceed the normal ranges in varying degrees, and are concentrated on specific parameters. The results can not only help to judge the recovery stages of patients but also figure out the corresponding abnormal postures, so as to provide guidance for rehabilitation training.

Permutation Entropy and Irreversibility in Gait Kinematic Time Series from Patients with Mild Cognitive Decline and Early Alzheimer’s Dementia

Gait is a basic cognitive purposeful action that has been shown to be altered in late stages of neurodegenerative dementias. Nevertheless, alterations are less clear in mild forms of dementia, and the potential use of gait analysis as a biomarker of initial cognitive decline has hitherto mostly been neglected. Herein, we report the results of a study of gait kinematic time series for two groups of patients (mild cognitive impairment and mild Alzheimer’s disease) and a group of matched control subjects. Two metrics based on permutation patterns are considered, respectively measuring the complexity and irreversibility of the time series. Results indicate that kinematic disorganisation is present in early phases of cognitive impairment; in addition, they depict a rich scenario, in which some joint movements display an increased complexity and irreversibility, while others a marked decrease. Beyond their potential use as biomarkers, complexity and irreversibility metrics can open a new door to the understanding of the role of the nervous system in gait, as well as its adaptation and compensatory mechanisms.

Mobility assessment in people with Alzheimer disease using smartphone sensors

Background

Understanding the functional status of people with Alzheimer Disease (AD), both in a single (ST) and cognitive dual task (DT) activities is essential for identifying signs of early-stage neurodegeneration. This study aims to compare the performance quality of several tasks using sensors embedded in an Android device, among people at different stages of Alzheimer and people without dementia. The secondary aim is to analyze the effect of cognitive task performance on mobility tasks.

Methods

This is a cross-sectional study including 22 participants in the control group (CG), 18 in the group with mild AD and 22 in the group with moderate AD. They performed two mobility tests, under ST and DT conditions, which were registered using an Android device. Postural control was measured by medial-lateral and anterior-posterior displacements of the COM (MLDisp and APDisp, respectively) and gait, with the vertical and medial-lateral range of the COM (Vrange and MLrange). Further, the sit-to-stand (PStand) and turning and sit power (PTurnSit), the total time required to complete the test and the reaction time were measured.

Results

There were no differences between the two AD stages either for ST or DT in any of the variables (p > 0.05). Nevertheless, people at both stages showed significantly lower values of PStand and PTurnSit and larger Total time and Reaction time compared to CG (p < 0.05). Further, Vrange is also lower in CDR1G than in CG (p < 0.05). The DT had a significant deleterious effect on MLDisp in all groups (p < 0.05) and on APDisp only in moderate AD for DT.

Conclusions

Our findings indicate that AD patients present impairments in some key functional abilities, such as gait, turning and sitting, sit to stand, and reaction time, both in mild and moderate AD. Nevertheless, an exclusively cognitive task only influences the postural control in people with AD.

Inertial wearables as pragmatic tools in dementia

Dementia is a critically important issue due to its wide impact on health services as well as its personal and societal costs. Limitations exist for current dementia protocols, and there are calls to introduce modern technology that facilitates the addition of digital biomarkers to routine clinical practice. Wearable technology (wearables) are nearly ubiquitous in everyday life, gathering discrete and continuous digital data on habitual activities, but their utility in modern medicine remains low. Due to advances in data analytics, wearables are now commonly discussed as pragmatic tools to aid the diagnosis and treatment of a range of neurological disorders. Inertial sensor-based wearables are one such technology; they offer a low-cost approach to quantify routine movements that are fundamental to normal activities of daily living, most notably postural control and gait. Here, we provide a narrative review of how wearables are providing useful postural control and gait data to facilitate the capture of digital markers to aid dementia research. We outline the history of wearables, from their humble beginnings to their current use beyond the clinic, and explore their integration into modern systems, as well as the ongoing standardisation and regulatory efforts to integrate their use in clinical trials.

Development of a Strategy to Predict and Detect Falls Using Wearable Sensors

Falls are a prevalent problem in actual society. Some falls result in injuries and the cost associated with their treatment is high. This is a complex problem that requires several steps in order to be tackled. Firstly, it is crucial to develop strategies that recognize the locomotion mode, indicating the state of the subject in various situations. This article aims to develop a strategy capable of identifying normal gait, the pre-fall condition, and the fall situation, based on a wearable system (IMUs-based). This system was used to collect data from healthy subjects that mimicked falls. The strategy consists, essentially, in the construction and use of classifiers as tools for recognizing the locomotion modes. Two approaches were explored. Associative Skill Memories (ASMs) based classifier and a Convolutional Neural Network (CNN) classifier based on deep learning. Finally, these classifiers were compared, providing for a tool with a good accuracy in recognizing the locomotion modes. Results have shown that the accuracy of the classifiers was quite acceptable. The CNN presented the best results with 92.71% of accuracy considering the pre-fall step different from normal steps, and 100% when not considering.

Type and Location of Wearable Sensors for Monitoring Falls during Static and Dynamic Tasks in Healthy Elderly: A Review

In recent years, the meaning of successful living has moved from extending lifetime to improving the quality of aging, mainly in terms of high cognitive and physical functioning together with avoiding diseases. In healthy elderly, falls represent an alarming accident both in terms of number of events and the consequent decrease in the quality of life. Stability control is a key approach for studying the genesis of falls, for detecting the event and trying to develop methodologies to prevent it. Wearable sensors have proved to be very useful in monitoring and analyzing the stability of subjects. Within this manuscript, a review of the approaches proposed in the literature for fall risk assessment, fall prevention and fall detection in healthy elderly is provided. The review has been carried out by using the most adopted publication databases and by defining a search strategy based on keywords and boolean algebra constructs. The analysis aims at evaluating the state of the art of such kind of monitoring, both in terms of most adopted sensor technologies and of their location on the human body. The review has been extended to both dynamic and static analyses. In order to provide a useful tool for researchers involved in this field, the manuscript also focuses on the tests conducted in the analyzed studies, mainly in terms of characteristics of the population involved and of the tasks used. Finally, the main trends related to sensor typology, sensor location and tasks have been identified.

Motor Phenotype in Neurodegenerative Disorders: Gait and Balance Platform Study Design Protocol for the Ontario Neurodegenerative Research Initiative (ONDRI)

Background:

The association of cognitive and motor impairments in Alzheimer’s disease and other neurodegenerative diseases is thought to be related to damage in the common brain networks shared by cognitive and cortical motor control processes. These common brain networks play a pivotal role in selecting movements and postural synergies that meet an individual’s needs. Pathology in this “highest level” of motor control produces abnormalities of gait and posture referred to as highest-level gait disorders. Impairments in cognition and mobility, including falls, are present in almost all neurodegenerative diseases, suggesting common mechanisms that still need to be unraveled.

Objective:

To identify motor-cognitive profiles across neurodegenerative diseases in a large cohort of patients.

Methods:

Cohort study that includes up to 500 participants, followed every year for three years, across five neurodegenerative disease groups: Alzheimer’s disease/mild cognitive impairment, frontotemporal degeneration, vascular cognitive impairment, amyotrophic lateral sclerosis, and Parkinson’s disease. Gait and balance will be assessed using accelerometers and electronic walkways, evaluated at different levels of cognitive and sensory complexity, using the dual-task paradigm.

Results:

Comparison of cognitive and motor performances across neurodegenerative groups will allow the identification of motor-cognitive phenotypes through the standardized evaluation of gait and balance characteristics.

Conclusions:

As part of the Ontario Neurodegenerative Research Initiative (ONDRI), the gait and balance platform aims to identify motor-cognitive profiles across neurodegenerative diseases. Gait assessment, particularly while dual-tasking, will help dissect the cognitive and motor contribution in mobility and cognitive decline, progression to dementia syndromes, and future adverse outcomes including falls and mortality.

Loss of gait control assessed by cognitive-motor dual-tasks: pros and cons in detecting people at risk of developing Alzheimer's and Parkinson's diseases

Alzheimer's and Parkinson's diseases are age-related progressive neurodegenerative diseases of increasing prevalence worldwide. In the absence of curative therapy, current research is interested in prevention, by identifying subtle signs of early-stage neurodegeneration. Today, the field of behavioral neuroscience has emerged as one of the most promising areas of research on this topic. Recently, it has been shown that the exacerbation of gait disorders under dual-task conditions (i.e., simultaneous performance of cognitive and motor tasks) could be a characteristic feature of Alzheimer's and Parkinson's diseases. The cognitive-motor dual-task paradigm during walking allows to assess whether (i) executive attention is abnormally impaired in prodromal Alzheimer's disease or (ii) compensation strategies are used in order to preserve gait function when the basal ganglia system is altered in prodromal Parkinson's disease. This review aims at (i) identifying patterns of dual-task-related gait changes that are specific to Alzheimer's and Parkinson's diseases, respectively, (ii) demonstrating that these changes could potentially be used as prediagnostic markers for disease onset, (iii) reviewing pros and cons of existing dual-task studies, and (iv) proposing future directions for clinical research.