Cognitive associations with comprehensive gait and static balance measures in Parkinson's disease

Visuospatial Skills Explain Differences in the Ability to Use Propulsion Biofeedback Post-stroke

BACKGROUND AND PURPOSE

Visual biofeedback can be used to help people post-stroke reduce biomechanical gait impairments. Using visual biofeedback engages an explicit, cognitively demanding motor learning process. Participants with better overall cognitive function are better able to use visual biofeedback to promote locomotor learning; however, which specific cognitive domains are responsible for this effect are unknown. We aimed to understand which cognitive domains were associated with performance during acquisition and immediate retention when using visual biofeedback to increase paretic propulsion in individuals post-stroke.

METHODS

Participants post-stroke completed cognitive testing, which provided scores for different cognitive domains, including executive function, immediate memory, visuospatial/constructional skills, language, attention, and delayed memory. Next, participants completed a single session of paretic propulsion biofeedback training, where we collected treadmill-walking data for 20 min with biofeedback and 2 min without biofeedback. We fit separate regression models to determine if cognitive domain scores, motor impairment (measured with the lower-extremity Fugl-Meyer), and gait speed could explain propulsion error and variability during biofeedback use and recall error during immediate retention.

RESULTS

Visuospatial/constructional skills and motor impairment best-explained propulsion error during biofeedback use (adjusted R 2  = 0.56, P = 0.0008), and attention best-explained performance variability (adjusted R 2  = 0.17, P = 0.048). Language skills best-explained recall error during immediate retention (adjusted R 2  = 0.37, P = 0.02).

DISCUSSION AND CONCLUSIONS

These results demonstrate that specific cognitive domain impairments explain variability in locomotor learning outcomes in individuals with chronic stroke. This suggests that with further investigation, specific cognitive impairment information may be useful to predict responsiveness to interventions and personalize training parameters to facilitate locomotor learning.

Frontal cortex neurometabolites and mobility in older adults: a preliminary study

BACKGROUND

The frontal cortex, relevant to global cognition and motor function, is recruited to compensate for mobility dysfunction in older adults. However, the in vivo neurophysiological (e.g., neurometabolites) underpinnings of the frontal cortex compensation for mobility dysfunction remain poorly understood. The purpose of this study was to investigate the relationships among frontal cortex neurophysiology, mobility, and cognition in healthy older adults.

METHODS

Magnetic Resonance Spectroscopy (MRS) quantified N-acetylasparate (tNAA) and total choline (tCho) concentrations and ratios in the frontal cortex in 21 older adults. Four inertial sensors recorded the Timed Up & Go (TUG) test. Cognition was assessed using the Flanker Inhibitory Control and Attention Test which requires conflict resolution because of response interference from flanking distractors during incongruent trials. Congruent trials require no conflict resolution.

RESULTS

tNAA concentration significantly related to the standing (p = 0.04) and sitting (p = 0.03) lean angles. tCho concentration (p = 0.04) and tCho ratio (p = 0.02) significantly related to TUG duration. tCho concentration significantly related to incongruent response time (p = 0.01). tCho ratio significantly related to both congruent (p = 0.009) and incongruent (p < 0.001) response times. Congruent (p = 0.02) and incongruent (p = 0.02) Flanker response times significantly related to TUG duration.

CONCLUSIONS

Altered levels of frontal cortex neurometabolites are associated with both mobility and cognitive abilities in healthy older adults. Identifying neurometabolites associated with frontal cortex compensation of mobility dysfunction could improve targeted therapies aimed at improving mobility in older adults.

Cholinergic nucleus degeneration and its association with gait impairment in Parkinson's disease

BACKGROUND

The contribution of cholinergic degeneration to gait disturbance in Parkinson's disease (PD) is increasingly recognized, yet its relationship with dopaminergic-resistant gait parameters has been poorly investigated. We investigated the association between comprehensive gait parameters and cholinergic nucleus degeneration in PD.

METHODS

This cross-sectional study enrolled 84 PD patients and 69 controls. All subjects underwent brain structural magnetic resonance imaging to assess the gray matter density (GMD) and volume (GMV) of the cholinergic nuclei (Ch123/Ch4). Gait parameters under single-task (ST) and dual-task (DT) walking tests were acquired using sensor wearables in PD group. We compared cholinergic nucleus morphology and gait performance between groups and examined their association.

RESULTS

PD patients exhibited significantly decreased GMD and GMV of the left Ch4 compared to controls after reaching HY stage > 2. Significant correlations were observed between multiple gait parameters and bilateral Ch123/Ch4. After multiple testing correction, the Ch123/Ch4 degeneration was significantly associated with shorter stride length, lower gait velocity, longer stance phase, smaller ankle toe-off and heel-strike angles under both ST and DT condition. For PD patients with HY stage 1-2, there were no significant degeneration of Ch123/4, and only right side Ch123/Ch4 were corrected with the gait parameters. However, as the disease progressed to HY stage > 2, bilateral Ch123/Ch4 nuclei showed correlations with gait performance, with more extensive significant correlations were observed in the right side.

CONCLUSIONS

Our study demonstrated the progressive association between cholinergic nuclei degeneration and gait impairment across different stages of PD, and highlighting the potential lateralization of the cholinergic nuclei's impact on gait impairment. These findings offer insights for the design and implementation of future clinical trials investigating cholinergic treatments as a promising approach to address gait impairments in PD.

Dual-Task vs. Single-Task Gait Training to Improve Spatiotemporal Gait Parameters in People with Parkinson's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

People with Parkinson's disease (pwPD) present alterations of spatiotemporal gait parameters that impact walking ability. While preliminary studies suggested that dual-task gait training improves spatiotemporal gait parameters, it remains unclear whether dual-task gait training specifically improves dual-task gait performance compared to single-task gait training. The aim of this review is to assess the effect of dual-task training relative to single-task gait training on specific gait parameters during dual-task tests in pwPD.

METHODS

We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs), searching three electronic databases. Two reviewers independently selected RCTs, extracted data, and applied the Cochrane risk-of-bias tool for randomized trials (Version 2) and the GRADE framework for assessing the certainty of evidence. The primary outcomes were dual-task gait speed, stride length, and cadence. Secondary outcomes included dual-task costs on gait speed, balance confidence, and quality of life.

RESULTS

We included 14 RCTs (548 patients). Meta-analyses showed effects favoring dual-task training over single-task training in improving dual-task gait speed (standardized mean difference [SMD] = 0.48, 95% confidence interval [CI] = 0.20-0.77; 11 studies; low certainty evidence), stride length (mean difference [MD] = 0.09 m, 95% CI = 0.04-0.14; 4 studies; very low certainty evidence), and cadence (MD = 5.45 steps/min, 95% CI = 3.59-7.31; 5 studies; very low certainty evidence). We also found a significant effect of dual-task training over single-task training on dual-task cost and quality of life, but not on balance confidence.

CONCLUSIONS

Our findings support the use of dual-task training relative to single-task training to improve dual-task spatiotemporal gait parameters in pwPD. Further studies are encouraged to better define the features of dual-task training and the clinical characteristics of pwPD to identify better responders.

Neurocognitive Impairment and Social Cognition in Parkinson's Disease Patients

In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson's disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.

Associations between baseline cognitive status and motor outcomes after treadmill training in people with Parkinson's disease: a pilot study

PURPOSE

To determine the effect of baseline cognition on gait outcomes after a treadmill training program for people with Parkinson's disease (PD).

METHODS

This pilot clinical trial involved people with PD who were classified as having no cognitive impairment (PD-NCI) or mild cognitive impairment (PD-MCI). Baseline executive function and memory were assessed. The intervention was a 10-week gait training program (twice-weekly treadmill sessions), with structured speed and distance progression and verbal cues for gait quality. Response to intervention was assessed by gait speed measured after week 2 (short-term) and week 10 (long-term).

RESULTS

Participants (n = 19; 12 PD-NCI, 7 PD-MCI) had a mean (standard deviation) age of 66.5 (6.3) years, disease duration of 8.8 (6.3) years, and MDS-UPDRS III score of 21.3 (10.7). Gait speed increased at short-term and long-term assessments. The response did not differ between PD-NCI and PD-MCI groups; however, better baseline memory performance and milder PD motor severity were independently associated with greater improvements in gait speed in unadjusted and adjusted models.

CONCLUSIONS

These findings suggest that memory impairments and more severe motor involvement can influence the response to gait rehabilitation in PD and highlight the need for treatments optimized for people with greater cognitive and motor impairment.IMPLICATIONS FOR REHABILITATIONCognitive deficits in Parkinson's disease (PD) could impact motor learning and gait rehabilitation, yet little is known about the effects of cognitive impairments on the response to rehabilitation in people with PD.This study demonstrates that the response to gait rehabilitation did not differ between people with PD who had no cognitive impairment and those with mild cognitive impairment.Across all participants, better baseline memory was associated with greater improvements in gait speed.Rehabilitation professionals should be mindful of PD severity, as those with more substantial memory and motor impairments may require additional dosing or support to maximize gait training benefits.

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

Background

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

Methods

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

Results

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

Conclusion

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

Cognitive status and sleep quality can explain the fear of falling and fall history in people with Parkinson's disease

Fear of falling (FOF) is highly prevalent in people with Parkinson's disease (PwPD) and contributes to high fall risk. Studies reporting on the relationship between falls, FOF, and non-motor factors such as cognitive function and sleep quality in Parkinson's disease are limited. This study aimed to investigate (1) the relationship of cognitive function and sleep quality with FOF, and history of falls in PwPD; (2) differences in cognitive function and sleep quality between Parkinson's disease fallers and non-fallers; and (3) a cut-off score for cognitive function and sleep quality to discriminate Parkinson's disease fallers from non-fallers. Fifty PwPD were assessed for FOF [Falls Efficacy Scale-International (FES-I)], cognition [Montréal Cognitive Assessment (MOCA)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and falls history. The MOCA is significantly associated with FES-I scores ( R2  = 0.429, P  < 0.0001). Both MOCA ( P  = 0.012) and PSQI ( P  = 0.027) were associated with falls history even after adjusting for confounding factors (age, sex, L-dopa use, Parkinson's disease severity). Both MOCA and PSQI scores were able to distinguish fallers from non-fallers with cut-off scores of 15.5 and 7.5, respectively. Although our findings revealed that both cognitive function and sleep quality are important factors influencing falls and FOF in PwPD, it remains to be determined if addressing cognitive impairments and poor sleep quality may favorably impact balance before integrating such screenings into fall prevention programs.

Exploring mobility dysfunction in people with and without impaired cognition in Parkinson disease

INTRODUCTION

The relationship between mobility and cognition has been studied in the aging population and associations have been also reported in people with Parkinson's disease (PD).

OBJECTIVE

To compare different aspects of gait and balance between individuals with PD who have normal cognition and those with impaired cognition, using both clinical and instrumented measures.

METHODS

One-hundred forty-three participants with PD were divided into two groups: 1) normal cognition (n = 71) and 2) impaired cognition (n = 72) based on the Montreal Cognitive Assessment (MoCA) cut-off. Groups were compared using instrumented and clinical measures of gait and balance in the following domains: Sensory Orientation, Anticipatory Postural Adjustments, Automatic Postural Responses and Dynamic Balance for Gait. Instrumented measures were obtained via wearable sensors while performing eight different motor tasks and clinical measures were obtained with the Mini-BESTest.

RESULTS

The total Mini-BESTest score was not different between groups. However, the Dynamic Gait domain was worse in individuals with impaired cognition. Among the instrumented measures across domains, all significant group differences were in the Dynamic Gait domain, specifically, dual-task gait speed, dual-task stride length, stance time, and turn velocity.

CONCLUSIONS

Dynamic balance during gait was more impaired in people with PD who had abnormal cognition than those with normal cognition, for both clinical and instrumented measures. All other balance domains did not differ between groups, for both instrumented and clinical measures.

Using the Instrumented Sway System (ISway) to Identify and Compare Balance Domain Deficits in People With Multiple Sclerosis

OBJECTIVE

To develop a multiple sclerosis (MS)-specific model of balance and examine differences between (1) MS and neurotypical controls and (2) people with MS (PwMS) with (MS-F) and without a fall history (MS-NF).

DESIGN AND SETTING

A cross-sectional study was conducted at the Gait and Balance Laboratory at the University of Kansas Medical Center. Balance was measured from the instrumented sway system (ISway) assessment.

PARTICIPANTS

In total, 118 people with relapsing-remitting MS (MS-F=39; MS-NF=79) and 46 age-matched neurotypical controls.

INTERVENTION

Not applicable.

OUTCOME MEASURES

A total of 22 sway measures obtained from the ISway were entered into an exploratory factor analysis to identify underlying balance domains. The model-derived balance domains were compared between (1) PwMS and age-matched, neurotypical controls and (2) MS-F and MS-NF.

RESULTS

Three distinct balance domains were identified: (1) sway amplitude and velocity, (2) sway frequency and jerk mediolateral, and (3) sway frequency and jerk anteroposterior, explaining 81.66% of balance variance. PwMS exhibited worse performance (ie, greater amplitude and velocity of sway) in the sway velocity and amplitude domain compared to age-matched neurotypical controls (P=.003). MS-F also exhibited worse performance in the sway velocity and amplitude domain compared to MS-NF (P=.046). The anteroposterior and mediolateral sway frequency and jerk domains were not different between PwMS and neurotypical controls nor between MS-F and MS-NF.

CONCLUSIONS

This study identified a 3-factor, MS-specific balance model, demonstrating that PwMS, particularly those with a fall history, exhibit disproportionate impairments in sway amplitude and velocity. Identifying postural stability outcomes and domains that are altered in PwMS and clinically relevant (eg, related to falls) would help isolate potential treatment targets.

Gait and balance in apolipoprotein Ɛ4 allele carriers in older adults and Parkinson's disease

Background

Gait and balance impairments are among the most troublesome and heterogeneous in Parkinson's disease (PD). This heterogeneity may, in part, reflect genetic variation. The apolipoprotein E (APOE) gene has three major allelic variants (ε2, ε3 and ε4). Previous work has demonstrated that older adult (OA) APOE ε4 carriers demonstrate gait deficits. This study compared gait and balance measures between APOE ε4 carriers and non-carriers in both OA and PD.

Methods

334 people with PD (81 APOE ε4 carriers and 253 non-carriers) and 144 OA (41 carriers and 103 non-carriers) were recruited. Gait and balance were assessed using body-worn inertial sensors. Two-way analyses of covariance (ANCOVA) compared gait and balance characteristics between APOE ε4 carriers and non-carriers in people with PD and OA, controlling for age, gender, and testing site.

Results

Gait and balance were worse in people with PD compared to OA. However, there were no differences between APOE ε4 carriers and non-carriers in either the OA or PD group. In addition, there were no significant group (OA/PD) by APOE ε4 status (carrier/non-carrier) interaction effects for any measures of gait or balance.

Conclusions

Although we found expected impairments in gait and balance in PD compared to OA, gait and balance characteristics did not differ between APOE ε4 carriers and non-carriers in either group. While APOE status did not impact gait and balance in this cross-sectional study, future work is needed to determine whether progression of gait and balance deficits is faster in PD APOE Ɛ4 carriers.

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

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

Identification of a Gait Pattern for Detecting Mild Cognitive Impairment in Parkinson's Disease

The aim of this study was to determine a gait pattern, i.e., a subset of spatial and temporal parameters, through a supervised machine learning (ML) approach, which could be used to reliably distinguish Parkinson's Disease (PD) patients with and without mild cognitive impairment (MCI). Thus, 80 PD patients underwent gait analysis and spatial-temporal parameters were acquired in three different conditions (normal gait, motor dual task and cognitive dual task). Statistical analysis was performed to investigate the data and, then, five ML algorithms and the wrapper method were implemented: Decision Tree (DT), Random Forest (RF), Naïve Bayes (NB), Support Vector Machine (SVM) and K-Nearest Neighbour (KNN). First, the algorithms for classifying PD patients with MCI were trained and validated on an internal dataset (sixty patients) and, then, the performance was tested by using an external dataset (twenty patients). Specificity, sensitivity, precision, accuracy and area under the receiver operating characteristic curve were calculated. SVM and RF showed the best performance and detected MCI with an accuracy of over 80.0%. The key features emerging from this study are stance phase, mean velocity, step length and cycle length; moreover, the major number of features selected by the wrapper belonged to the cognitive dual task, thus, supporting the close relationship between gait dysfunction and MCI in PD.

Step-Counting Accuracy of a Commercial Smartwatch in Mild-to-Moderate PD Patients and Effect of Spatiotemporal Gait Parameters, Laterality of Symptoms, Pharmacological State, and Clinical Variables

Commercial smartwatches could be useful for step counting and monitoring ambulatory activity. However, in Parkinson's disease (PD) patients, an altered gait, pharmacological condition, and symptoms lateralization may affect their accuracy and potential usefulness in research and clinical routine. Steps were counted during a 6 min walk in 47 patients with PD and 47 healthy subjects (HS) wearing a Garmin Vivosmart 4 (GV4) on each wrist. Manual step counting was used as a reference. An inertial sensor (BTS G-Walk), placed on the lower back, was used to compute spatial-temporal gait parameters. Intraclass correlation coefficient (ICC) and mean absolute percentage error (MAPE) were used for accuracy evaluation and the Spearman test was used to assess the correlations between variables. The GV4 overestimated steps in PD patients with only a poor-to-moderate agreement. The OFF pharmacological state and wearing the device on the most-affected body side led to an unacceptable accuracy. The GV4 showed an excellent agreement and MAPE in HS at a self-selected speed, but an unacceptable performance at a slow speed. In PD patients, MAPE was not associated with gait parameters and clinical variables. The accuracy of commercial smartwatches for monitoring step counting might be reduced in PD patients and further influenced by the pharmacological condition and placement of the device.

Machine learning can predict mild cognitive impairment in Parkinson's disease

BACKGROUND

Clinical markers of cognitive decline in Parkinson's disease (PD) encompass several mental non-motor symptoms such as hallucinations, apathy, anxiety, and depression. Furthermore, freezing of gait (FOG) and specific gait alterations have been associated with cognitive dysfunction in PD. Finally, although low cerebrospinal fluid levels of amyloid-β42 have been found to predict cognitive decline in PD, hitherto PET imaging of amyloid-β (Aβ) failed to consistently demonstrate the association between Aβ plaques deposition and mild cognitive impairment in PD (PD-MCI).

AIM

Finding significant features associated with PD-MCI through a machine learning approach.

PATIENTS AND METHODS

Patients were assessed with an extensive clinical and neuropsychological examination. Clinical evaluation included the assessment of mental non-motor symptoms and FOG using the specific items of the MDS-UPDRS I and II. Based on the neuropsychological examination, patients were classified as subjects without and with MCI (noPD-MCI, PD-MCI). All patients were evaluated using a motion analysis system. A subgroup of PD patients also underwent amyloid PET imaging. PD-MCI and noPD-MCI subjects were compared with a univariate statistical analysis on demographic data, clinical features, gait analysis variables, and amyloid PET data. Then, machine learning analysis was performed two times: Model 1 was implemented with age, clinical variables (hallucinations/psychosis, depression, anxiety, apathy, sleep problems, FOG), and gait features, while Model 2, including only the subgroup performing PET, was implemented with PET variables combined with the top five features of the former model.

RESULTS

Seventy-five PD patients were enrolled (33 PD-MCI and 42 noPD-MCI). PD-MCI vs. noPD-MCI resulted in older and showed worse gait patterns, mainly characterized by increased dynamic instability and reduced step length; when comparing amyloid PET data, the two groups did not differ. Regarding the machine learning analyses, evaluation metrics were satisfactory for Model 1 overcoming 80% for accuracy and specificity, whereas they were disappointing for Model 2.

CONCLUSIONS

This study demonstrates that machine learning implemented with specific clinical features and gait variables exhibits high accuracy in predicting PD-MCI, whereas amyloid PET imaging is not able to increase prediction. Additionally, our results prompt that a data mining approach on certain gait parameters might represent a reliable surrogate biomarker of PD-MCI.

Single- and dual-task gait performance and their diagnostic value in early-stage Parkinson's disease

Background

Gait parameters are considered potential diagnostic markers of Parkinson's disease (PD). We aimed to 1) assess the gait impairment in early-stage PD and its related factors in the single-task (ST) and dual-task (DT) walking tests and 2) evaluate and compare the diagnostic value of gait parameters for early-stage PD under ST and DT conditions.

Methods

A total of 97 early-stage PD patients and 41 healthy controls (HC) were enrolled at Hwa Mei hospital. Gait parameters were gathered and compared between the two groups in the ST and DT walking test, controlling for covariates. Utilizing the receiver operating characteristic curve, diagnostic parameters were investigated.

Results

In the ST walking test, significantly altered gait patterns could be observed in early-stage PD patients in all domains of gait, except for asymmetry (P < 0.05). Compared to the ST walking test, the early-stage PD group performed poorly in the DT walking test in the pace, rhythm, variability and postural control domain (P < 0.05). Older, heavier subjects, as well as those with lower height, lower level of education and lower gait velocity, were found to have a poorer gait performance (P < 0.05). Stride length (AUC = 0.823, sensitivity, 68.0%; specificity, 85.4%; P < 0.001) and heel strike angle (AUC = 0.796, sensitivity, 71.1%; specificity, 80.5%; P < 0.001) could distinguish early-stage PD patients from HCs with moderate accuracy, independent of covariates. The diagnostic accuracy of gait parameters under ST conditions were statistically noninferior to those under DT conditions(P>0.05). Combining all gait parameters with diagnostic values under ST and DT walking test, the predictive power significantly increased with an AUC of 0.924 (sensitivity, 85.4%; specificity, 92.7%; P < 0.001).

Conclusion

Gait patterns altered in patients with early-stage PD but the gait symmetry remained preserved. Stride length and heel strike angle were the two most prominent gait parameters of altered gait in early-stage of PD that could serve as diagnostic markers of early-stage PD. Our findings are helpful to understand the gait pattern of early-stage PD and its related factors and can be conducive to the development of new diagnostic tools for early-stage PD.

The relationships of postural stability with muscle strength and proprioception are different among older adults over and under 75 years of age

Purpose

The relationships of postural stability with its three potential contributing factors, namely, muscle strength, tactile sensation, and proprioception, have not been clarified at different ages among older adults. Differences in the relationships may explain the increased incidence of falls among older adults 75 and older. This study compared the postural stability and its three factors between the older adults younger or older than 75 and investigated their age-specific relationships.

Methods

A total of 152 participants were recruited and divided into younger-old (65–74 years, n = 83) or older-old adults (≥75 years, n = 69) groups. Their Berg Balance Scale (BBS) and the Timed Up and Go (TUG) performance, muscle strength, tactile sensation, and proprioception were tested. The group differences and age-specific relationships of the performance with the three factors were examined.

Results

Compared to the younger-older adults, the older-old adults had lower BBS and higher TUG scores, weaker muscle strength, and worse proprioception. Muscle strength and proprioception were correlated with BBS and TUG among the younger-older adults. Only muscle strength but not proprioception among the older-old adults was correlated with BBS and TUG.

Conclusion

The older-old adults over 75 years have poorer postural stability, muscle strength, and proprioception compared to the younger-old adults aged 65–74 years. Proprioception provides information on postural stability among younger-old adults but not among older-old adults. Keeping proprioception from deteriorating with age could be a key to reducing falls in older-old adults.

Cognitive, psychological and social factors associated with older adults' mobility: a scoping review of self-report and performance-based measures

Although many factors have been associated with mobility among older adults, there is paucity of research that explores the complexity of factors that influence mobility. This review aims to synthesise the available evidence for factors comprising the cognitive, psychological, and social mobility determinants and their associations with mobility self-reported and performance-based outcomes in older adults (60 years). We followed Arksey and O'Malley's five stages of a scoping review and searched PubMed, EMBASE, PsychINFO, Web of Science, AgeLine, Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature and Sociological Abstract databases. Reviewers in pairs independently conducted title, abstract, full-text screening and data extraction. We reported associations by analyses rather than articles because articles reported multiple associations for factors and several mobility outcomes. Associations were categorised as significantly positive, negative, or not significant. We included 183 peer-reviewed articles published in 27 countries, most of which were cross-sectional studies and conducted among community-dwelling older adults. The 183 articles reported 630 analyses, of which 381 (60.5%) were significantly associated with mobility outcomes in the expected direction. For example, older adults with higher cognitive functioning such as better executive functioning had better mobility outcomes (e.g., faster gait speed), and those with poor psychological outcomes, such as depressive symptoms, or social outcomes such as reduced social network, had poorer mobility outcomes (e.g., slower gait speed) compared to their counterparts. Studies exploring the association between cognitive factors, personality (a psychological factor) and self-reported mobility outcomes (e.g., walking for transportation or driving), and social factors and performance-based mobility outcomes in older adults are limited. Understanding the additive relationships between cognitive, psychological, and social factors highlights the complexity of older adults' mobility across different forms of mobility, including independence, use of assistive devices, transportation, and driving.

Cognition as a mediator for gait and balance impairments in GBA-related Parkinson's disease

The extent to which the heterogeneity of gait and balance problems in PD may be explained by genetic variation is unknown. Variants in the glucocerebrosidase (GBA) gene are the strongest known genetic risk factor for PD and are associated with greater motor and cognitive severity. However, the impact of GBA variants on comprehensive measures of gait and balance and their relationship to cognition remains unknown. We aimed to determine differences in gait and balance impairments in those with and without GBA variants (mutation carriers and E326K polymorphism) and explore direct and indirect effects of GBA status on gait, balance, and cognition. 332 participants, 43 of whom had GBA variants, were recruited. Participants completed a comprehensive, objective assessment of gait and standing balance using body-worn inertial sensors. Group differences in gait and balance between PD with and without GBA variants were assessed with linear regression, adjusting for age, gender, clinical testing site, disease duration, and apolipoprotein E (APOE) ɛ4 status. Structural equation modeling (SEM) explored direct relationships between GBA status and gait and balance and indirect relationships between GBA status and gait and balance via cognition. The GBA variant group had more impaired gait (pace and variability) and balance (sway area/jerk and sway velocity), than the non-GBA variant group. SEM demonstrated cognition as a mediator of GBA status on gait and balance. The close relationships among GBA, gait/balance, and cognition suggest potential for novel therapeutics to target the GBA pathway and/or cognition to improve mobility in PD GBA variants.

Smartphone-Based Neuropsychological Assessment in Parkinson's Disease: Feasibility, Validity, and Contextually Driven Variability in Cognition

OBJECTIVES

The prevalence of neurodegenerative disorders demands methods of accessible assessment that reliably captures cognition in daily life contexts. We investigated the feasibility of smartphone cognitive assessment in people with Parkinson's disease (PD), who may have cognitive impairment in addition to motor-related problems that limit attending in-person clinics. We examined how daily-life factors predicted smartphone cognitive performance and examined the convergent validity of smartphone assessment with traditional neuropsychological tests.

METHODS

Twenty-seven nondemented individuals with mild-moderate PD attended one in-lab session and responded to smartphone notifications over 10 days. The smartphone app queried participants 5x/day about their location, mood, alertness, exercise, and medication state and administered mobile games of working memory and executive function.

RESULTS

Response rate to prompts was high, demonstrating feasibility of the approach. Between-subject reliability was high on both cognitive games. Within-subject variability was higher for working memory than executive function. Strong convergent validity was seen between traditional tests and smartphone working memory but not executive function, reflecting the latter's ceiling effects. Participants performed better on mobile working memory tasks when at home and after recent exercise. Less self-reported daytime sleepiness and lower PD symptom burden predicted a stronger association between later time of day and higher smartphone test performance.

CONCLUSIONS

These findings support feasibility and validity of repeat smartphone assessments of cognition and provide preliminary evidence of the effects of context on cognitive variability in PD. Further development of this accessible assessment method could increase sensitivity and specificity regarding daily cognitive dysfunction for PD and other clinical populations.

Mild Cognitive Impairment Subtypes Are Associated With Peculiar Gait Patterns in Parkinson's Disease

Background

Mild cognitive impairment (MCI) is frequent in Parkinson's disease (PD) and represents a risk factor for the development of dementia associated with PD (PDD). Since PDD has been associated with disability, caregiver burden, and an increase in health-related costs, early detection of MCI associated with PD (PD-MCI) and its biomarkers is crucial.

Objective

Given that gait is considered a surrogate marker for cognitive decline in PD, the aim of this study was to compare gait patterns in PD-MCI subtypes in order to verify the existence of an association between specific gait features and particular MCI subtypes.

Methods

A total of 67 patients with PD were consecutively enrolled and assessed by an extensive clinical and cognitive examination. Based on the neuropsychological examination, patients were diagnosed as patients with MCI (PD-MCI) and without MCI (no-PD-MCI) and categorized in MCI subtypes. All patients were evaluated using a motion capture system of a BTS Bioengineering equipped with six IR digital cameras. Gait of the patients was assessed in the ON-state under three different tasks (a single task and two dual tasks). Statistical analysis included the t-test, the Kruskal-Wallis test with post hoc analysis, and the exploratory correlation analysis.

Results

Gait pattern was poorer in PD-MCI vs. no-PD-MCI in all tasks. Among PD-MCI subtypes, multiple-domain PD-MCI and amnestic PD-MCI were coupled with worse gait patterns, notably in the dual task.

Conclusion

Both the magnitude of cognitive impairment and the presence of memory dysfunction are associated with increased measures of dynamic unbalance, especially in dual-task conditions, likely mirroring the progressive involvement of posterior cortical networks.

Assessment of postural sway with a pendant-mounted wearable sensor

BACKGROUND

Body-worn inertial measurement unit (IMU) sensors have been widely used in postural stability and balance studies because of their low cost and convenience. In most of these studies, a single IMU sensor is attached to a waist belt near the body's center of mass. Some populations such as pregnant women, however, may find a waist belt challenging in terms of fit and comfort. For this reason it may be useful to identify an alternative location for placement of an IMU and a more comfortable means for attaching the sensor to the body. Research question Does placing an IMU sensor in a pendant worn around the neck permit discrimination between conditions with varying postural stability?

METHODS

Twenty-six healthy participants performed three standing tasks (double-leg, tandem, and single-leg standing) under eyes-open and eyes-closed vision conditions to preliminarily assess the ability of the pendant sensor to discriminate between balance conditions. Discrimination based upon data from a belt-mounted IMU was assessed in the same trials. Differences in standard deviation of acceleration components, sway area, and jerkiness due to trial condition and sensor were evaluated using analysis of variance followed by post hoc comparisons. These data were also incorporated into receiver-operator characteristic (ROC) curve analysis to assess the effectiveness of each sensor at discriminating between conditions.

RESULTS

Stability was found to vary across conditions, but there was no interaction between stability and sensor location (all p ≥ 0.323). ROC curve analysis showed that sensors in both locations were good discriminators between conditions. Significance Placing an IMU in a pendant may be feasible for studying and monitoring postural instability. This approach may be especially valuable when considering populations for which wearing a belt is uncomfortable.

Modulating Cognitive–Motor Multitasking with Commercial-off-the-Shelf Non-Invasive Brain Stimulation

One growing area of multitasking research involves a focus on performing cognitive and motor tasks in tandem. In these situations, increasing either cognitive or motor demands has implications for performance in both tasks, an effect which is thought to be due to competing neural resources. Separate research suggests that non-invasive brain stimulation may offer a means to mitigate performance decrements experienced during multitasking. In the present study, we investigated the degree to which a commercially available non-invasive brain stimulation device (Halo Sport) alters balance performance in the presence of different types of cognitive demands. Specifically, we tested if performing a secondary cognitive task impacts postural sway in healthy young adults and if we could mitigate this impact using transcranial direct current stimulation (tDCS) applied over the primary motor cortex. Furthermore, we included conditions of unstable and stable surfaces and found that lower surface stability increased postural sway. In addition, we found that cognitive load impacted postural sway but in the opposite pattern we had anticipated, with higher sway found in the single-task control condition compared to executive function conditions. Finally, we found a small but significant effect of tDCS on balance with decreased sway for active (compared to sham) tDCS.

The Specificity of Cognitive-Motor Dual-Task Interference on Balance in Young and Older Adults

Standing upright on stable and unstable surfaces requires postural control. Postural control declines as humans age, presenting greater risk of fall-related injury and other negative health outcomes. Secondary cognitive tasks can further impact balance, which highlights the importance of coordination between cognitive and motor processes. Past research indicates that this coordination relies on executive function (EF; the ability to control, maintain, and flexibly direct attention to achieve goals), which coincidentally declines as humans age. This suggests that secondary cognitive tasks requiring EF may exert a greater influence on balance compared to non-EF secondary tasks, and this interaction could be exaggerated among older adults. In the current study, we had younger and older adults complete two Surface Stability conditions (standing upright on stable vs. unstable surfaces) under varying Cognitive Load; participants completed EF (Shifting, Inhibiting, Updating) and non-EF (Processing Speed) secondary cognitive tasks on tablets, as well as a single task control scenario with no secondary cognitive task. Our primary balance measure of interest was sway area, which was measured with an array of wearable inertial measurement unit sensors. Replicating prior work, we found a main effect of Surface Stability with less sway on stable surfaces compared to unstable surfaces, and we found an interaction between Age and Surface Stability with older adults exhibiting significantly greater sway selectively on unstable surfaces compared to younger adults. New findings revealed a main effect of Cognitive Load on sway, with the single task condition having significantly less sway than two of the EF conditions (Updating and Shifting) and the non-EF condition (Processing Speed). We also found an interaction of Cognitive Load and Surface Stability on postural control, where Surface Stability impacted sway the most for the single task and two of the executive function conditions (Inhibition and Shifting). Interestingly, Age did not interact with Cognitive Load, suggesting that both age groups were equally impacted by secondary cognitive tasks, regardless the presence or type of secondary cognitive task. Taken together, these patterns suggest that cognitive demands vary in their impact on posture control across stable vs. unstable surfaces, and that EF involvement may not be the driving mechanism explaining cognitive-motor dual-task interference on balance.

Executive function and relation to static balance metrics in chronic mild TBI: A LIMBIC-CENC secondary analysis

Introduction

Among patients with traumatic brain injury (TBI), postural instability often persists chronically with negative consequences such as higher fall risk. One explanation may be reduced executive function (EF) required to effectively process, interpret and combine, sensory information. In other populations, a decline in higher cognitive functions are associated with a decline in walking and balance skills. Considering the link between EF decline and reduction in functional capacity, we investigated whether specific tests of executive function could predict balance function in a cohort of individuals with a history of chronic mild TBI (mTBI) and compared to individuals with a negative history of mTBI.

Methods

Secondary analysis was performed on the local LIMBIC-CENC cohort (N = 338, 259 mTBI, mean 45 ± STD 10 age). Static balance was assessed with the sensory organization test (SOT). Hierarchical regression was used for each EF test outcome using the following blocks: (1) the number of TBIs sustained, age, and sex; (2) the separate Trail making test (TMT); (3) anti-saccade eye tracking items (error, latency, and accuracy); (4) Oddball distractor stimulus P300 and N200 at PZ and FZ response; and (5) Oddball target stimulus P300 and N200 at PZ and FZ response.

Results

The full model with all predictors accounted for between 15.2% and 21.5% of the variability in the balance measures. The number of TBI's) showed a negative association with the SOT2 score (p = 0.002). Additionally, longer times to complete TMT part B were shown to be related to a worse SOT1 score (p = 0.038). EEG distractors had the most influence on the SOT3 score (p = 0.019). Lastly, the SOT-composite and SOT5 scores were shown to be associated with longer inhibition latencies and errors (anti-saccade latency and error, p = 0.026 and p = 0.043 respectively).

Conclusions

These findings show that integration and re-weighting of sensory input when vision is occluded or corrupted is most related to EF. This indicates that combat-exposed Veterans and Service Members have greater problems when they need to differentiate between cues when vision is not a reliable input. In sum, these findings suggest that EF could be important for interpreting sensory information to identify balance challenges in chronic mTBI.

Which model best assesses gait in healthy elderly? A confirmatory factor analysis of existing conceptual gait models

BACKGROUND

Various conceptual gait models have been created with exploratory factor analysis to assess gait performance in healthy individuals or patients with orthopaedic or neurological diseases. However, a direct comparison between these models, to determine which is best for assessing gait in healthy elderly subjects, has never been performed. Confirmatory factor analysis is a statistical technique which allows to compare the structure of these models and to evaluate their validity and reliability.

RESEARCH QUESTION

Which of the current models for evaluating gait shows the best construct, convergent and discriminant validity and reliability when replicated in a sample of healthy elderly subjects?

METHODS

92 healthy elderly subjects (aged 73.3 ± 6.8 years) were enrolled. Participants were instructed to walk on a baropodometric walkway; gait variables were then extracted and analyzed according to 8 different gait models (published between 2007 and 2019). Correlation between variables of each model were investigated. The number of factors to include for each model was assessed with different criteria of principal component analysis. The construct validity of the gait models was assessed in terms of goodness of fit indexes through confirmatory factor analysis. Convergent and discriminant validity and reliability of the models were also assessed.

RESULTS

Of the models considered, only our model previously created for patients with Parkinson's Disease reached convergence, with an excellent fit in all indexes (χ² = 18.34, df = 13, p = 0.15, RMSEA = 0.06 (95%CI = 0.00-0.13), CFI = 0.98, TLI = 0.96, SRMR = 0.05). The model showed an acceptable convergent validity. The three factors resulted to be mutually independent (correlations among factors <0.85) and reliable. Most of the other seven considered models presented a high number (12.5-65%) of highly inter-related variables and more factors than necessary.

SIGNIFICANCE

Future studies can use our gait model as a framework for clinical practice or research.

Enriched Rehabilitation Improves Gait Disorder and Cognitive Function in Parkinson's Disease: A Randomized Clinical Trial

Background: Studies on non-pharmacological strategies for improving gait performance and cognition in Parkinson's disease (PD) are of great significance. We aimed to investigate the effect of and mechanism underlying enriched rehabilitation as a potentially effective strategy for improving gait performance and cognition in early-stage PD. Methods: Forty participants with early-stage PD were randomly assigned to receive 12 weeks (2 h/day, 6 days/week) of enriched rehabilitation (ER; n = 20; mean age, 66.14 ± 4.15 years; 45% men) or conventional rehabilitation (CR; n = 20; mean age 65.32 ± 4.23 years; 50% men). In addition, 20 age-matched healthy volunteers were enrolled as a control (HC) group. We assessed the general motor function using the Unified PD Rating Scale-Part III (UPDRS-III) and gait performance during single-task (ST) and dual-task (DT) conditions pre- and post-intervention. Cognitive function assessments included the Montreal Cognitive Assessment (MoCA), the Symbol Digit Modalities Test (SDMT), and the Trail Making Test (TMT), which were conducted pre- and post-intervention. We also investigated alteration in positive resting-state functional connectivity (RSFC) of the left dorsolateral prefrontal cortex (DLPFC) in participants with PD, mediated by ER, using functional magnetic resonance imaging (fMRI). Results: Compared with the HC group, PD participants in both ER and CR groups performed consistently poorer on cognitive and motor assessments. Significant improvements were observed in general motor function as assessed by the UPDRS-III in both ER and CR groups post-intervention. However, only the ER group showed improvements in gait parameters under ST and DT conditions post-intervention. Moreover, ER had a significant effect on cognition, which was reflected in increased MoCA, SDMT, and TMT scores post-intervention. MoCA, SDMT, and TMT scores were significantly different between ER and CR groups post-intervention. The RSFC analysis showed strengthened positive functional connectivity between the left DLPFC and other brain areas including the left insula and left inferior frontal gyrus (LIFG) post-ER. Conclusion: Our findings indicated that ER could serve as a potentially effective therapy for early-stage PD for improving gait performance and cognitive function. The underlying mechanism based on fMRI involved strengthened RSFC between the left DLPFC and other brain areas (e.g., the left insula and LIFG).

Classification of Parkinson's disease with freezing of gait based on 360° turning analysis using 36 kinematic features

BACKGROUND

Freezing of gait (FOG) is a sensitive problem, which is caused by motor control deficits and requires greater attention during postural transitions such as turning in people with Parkinson's disease (PD). However, the turning characteristics have not yet been extensively investigated to distinguish between people with PD with and without FOG (freezers and non-freezers) based on full-body kinematic analysis during the turning task. The objectives of this study were to identify the machine learning model that best classifies people with PD and freezers and reveal the associations between clinical characteristics and turning features based on feature selection through stepwise regression.

METHODS

The study recruited 77 people with PD (31 freezers and 46 non-freezers) and 34 age-matched older adults. The 360° turning task was performed at the preferred speed for the inner step of the more affected limb. All experiments on the people with PD were performed in the "Off" state of medication. The full-body kinematic features during the turning task were extracted using the three-dimensional motion capture system. These features were selected via stepwise regression.

RESULTS

In feature selection through stepwise regression, five and six features were identified to distinguish between people with PD and controls and between freezers and non-freezers (PD and FOG classification problem), respectively. The machine learning model accuracies revealed that the random forest (RF) model had 98.1% accuracy when using all turning features and 98.0% accuracy when using the five features selected for PD classification. In addition, RF and logistic regression showed accuracies of 79.4% when using all turning features and 72.9% when using the six selected features for FOG classification.

CONCLUSION

We suggest that our study leads to understanding of the turning characteristics of people with PD and freezers during the 360° turning task for the inner step of the more affected limb and may help improve the objective classification and clinical assessment by disease progression using turning features.

Cortical and Cerebellar Oscillatory Responses to Postural Instability in Parkinson's Disease

Introduction: Posture and balance dysfunctions critically impair activities of daily living of patients with progressing Parkinson's disease (PD). However, the neural mechanisms underlying postural instability in PD are poorly understood, and specific therapies are lacking. Previous electrophysiological studies have shown distinct cortical oscillations with a significant contribution of the cerebellum during postural control tasks in healthy individuals.

Methods: We investigated cortical and mid-cerebellar oscillatory activity via electroencephalography (EEG) during a postural control task in 10 PD patients with postural instability (PDPI+), 11 PD patients without postural instability (PDPI–), and 15 age-matched healthy control participants. Relative spectral power was analyzed in the theta (4–7 Hz) and beta (13–30 Hz) frequency bands.

Results: Time-dependent postural measurements computed by accelerometer signals showed poor performance in PDPI+ participants. EEG results revealed that theta power was profoundly lower in mid-frontal and mid-cerebellar regions during the postural control task in PDPI+, compared to PDPI– and control participants. In addition, theta power was correlated with postural control performance in PD subjects. No significant changes in beta power were observed. Additionally, oscillatory changes during the postural control task differed from the resting state.

Conclusion: This study underlines the involvement of mid-frontal and mid-cerebellar regions in postural stability during a balance task and emphasizes the important role of theta oscillations therein for postural control in PD.

Relationships Between Sensorimotor Inhibition and Mobility in Older Adults With and Without Parkinson's Disease

BACKGROUND

Reduced cortical sensorimotor inhibition is associated with mobility and cognitive impairments in people with Parkinson's disease (PD) and older adults (OAs). However, there is a lack of clarity regarding the relationships among sensorimotor, cognitive, and mobility impairments. The purpose of this study was to determine how cortical sensorimotor inhibition relates to impairments in mobility and cognition in people with PD and OAs.

METHOD

Cortical sensorimotor inhibition was characterized with short-latency afferent inhibition (SAI) in 81 people with PD and 69 OAs. Six inertial sensors recorded single- and dual-task gait and postural sway characteristics during a 2-minute walk and a 1-minute quiet stance. Cognition was assessed across the memory, visuospatial, executive function, attention, and language domains.

RESULTS

SAI was significantly impaired in the PD compared to the OA group. The PD group preformed significantly worse across all gait and postural sway tasks. In PD, SAI significantly correlated with single-task foot strike angle and stride length variability, sway area, and jerkiness of sway in the coronal and sagittal planes. In OAs, SAI significantly related to single-task gait speed and stride length, dual-task stride length, and immediate recall (memory domain). No relationship among mobility, cognition, and SAI was observed.

CONCLUSIONS

Impaired SAI related to slower gait in OA and to increased gait variability and postural sway in people with PD, all of which have been shown to be related to increased fall risk.

Quantitative Evaluation of Gait Changes Using APDM Inertial Sensors After the External Lumbar Drain in Patients With Idiopathic Normal Pressure Hydrocephalus

Objectives: Gait and balance disturbances are common symptoms of idiopathic normal pressure hydrocephalus (iNPH). This study aimed to quantitatively evaluate gait and balance parameters after external lumbar drainage (ELD) using APDM inertial sensors.

Methods: Two-minute walkway tests were performed in 36 patients with suspected iNPH and 20 healthy controls. A total of 36 patients underwent ELD. According to clinical outcomes, 20 patients were defined as responders, and the other 16 as non-responders. The gait parameters were documented, and the corresponding differences between responders and non-responders were calculated.

Results: When compared with healthy controls, patients with suspected iNPH exhibited decreased cadence, reduced gait speed, a higher percentage of double support, decreased elevation at mid-swing, reduced foot strike angle, shorter stride length, difficulty in turning, and impaired balance functions. After the ELD, all these manifestations, except elevation at mid-swing and balance functions, were significantly improved in responders. The change of Z-score absolute value in the six parameters, except for foot strike angle, was >1. No significant improvement was observed in non-responders.

Conclusion: APDM inertial sensors are useful for the quantitative assessment of gait impairment in patients with iNPH, which may be a valuable tool for identifying candidates that are suitable for shunting operations.

Cross-sectional associations between cognition and mobility in Parkinson's disease

Cross-sectional studies show an association of decline in mental flexibility and inhibitory control with reduced gait speed and falls, as well as divided attention deficit and difficulty in initiating gait.

The correlation of non-motor symptoms and sleep on balance in Parkinson's disease patients with normal cognition and mild cognitive impairment

BACKGROUND

Parkinson's disease (PD) is characterized by non-motor symptoms (NMS) as well as by motor symptoms. Together with the impairment of cognitive functions, NMS and sleep also affect motor symptoms negatively. The aim of our study is to examine the correlation of NMS and sleep on balance in PD patients with normal cognition (PD-NC) and with mild cognitive impairment (PD-MCI).

METHODS

A total of 69 patients were included in our study. Using the Standardized Mini-Mental State Examination, participants were divided into 2 groups, PD-NC and PD-MCI. Patients were assessed with the Unified Parkinson's Disease Rating Scale (UPDRS), the Berg Balance Scale (BBS), the Tinetti Balance Assessment Tool (TBAT), the Non-Motor Symptoms Questionnaire (NMSQ), and the Parkinson's Disease Questionnaire (PDQ-39).

RESULTS

PD-MCI patients had statistically significant worse motor symptoms and more balance disorder compared to PD-NC (UPDRS: p = 0.009; BBS: p = 0.010; TBAT: p = 0.004). PD-MCI patients had greater severity of non-motor symptoms and worse sleep quality than the PD-NC group (NMSQ-total: p = 0.02; NMSQ-sleep total: p = 0.01). The evaluation has shown that with a diagnosis of MCI, NMS, and sleeping problems were correlated, and the correlation was associated with impairment of the balance function. While being more pronounced in the PD-MCI group, quality of life was affected in both groups (p < 0.05).

CONCLUSION

Our data demonstrate a negative effect on the balance function in patients with cognitive impairment suffering increased NMS and sleeping disorders. Treatment of these patients needs to concentrate on NMS and cognitive functions as much as on motor symptoms.

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.

Effects of the agility boot camp with cognitive challenge (ABC-C) exercise program for Parkinson’s disease

Few exercise interventions practice both gait and balance tasks with cognitive tasks to improve functional mobility in people with PD. We aimed to investigate whether the Agility Boot Camp with Cognitive Challenge (ABC-C), that simultaneously targets both mobility and cognitive function, improves dynamic balance and dual-task gait in individuals with Parkinson’s disease (PD). We used a cross-over, single-blind, randomized controlled trial to determine efficacy of the exercise intervention. Eighty-six people with idiopathic PD were randomized into either an exercise (ABC-C)-first or an active, placebo, education-first intervention and then crossed over to the other intervention. Both interventions were carried out in small groups led by a certified exercise trainer (90-min sessions, 3 times a week, for 6 weeks). Outcome measures were assessed Off levodopa at baseline and after the first and second interventions. A linear mixed-effects model tested the treatment effects on the Mini-BESTest for balance, dual-task cost on gait speed, SCOPA-COG, the UPDRS Parts II and III and the PDQ-39. Although no significant treatment effects were observed for the Mini-BESTest, SCOPA-COG or MDS-UPDRS Part III, the ABC-C intervention significantly improved the following outcomes: anticipatory postural adjustment sub-score of the Mini-BESTest (p = 0.004), dual-task cost on gait speed (p = 0.001), MDS-UPDRS Part II score (p = 0.01), PIGD sub-score of MDS-UPDRS Part III (p = 0.02), and the activities of daily living domain of the PDQ-39 (p = 0.003). Participants with more severe motor impairment or more severe cognitive dysfunction improved their total Mini-BESTest scores after exercise. The ABC-C exercise intervention can improve specific balance deficits, cognitive-gait interference, and perceived functional independence and quality of life, especially in participants with more severe PD, but a longer period of intervention may be required to improve global cognitive and motor function.

Short-Term Effects of Single-Session Split-Belt Treadmill Training on Dual-Task Performance in Parkinson's Disease and Healthy Elderly

Background: Dual-tasking is challenging for people with Parkinson's disease and freezing of gait (PD+FOG) and can exacerbate freezing episodes and falls. Split-belt treadmill training (SBT) is a novel tool to train complex gait and may improve dual-task (DT) walking and turning.

Objective: To investigate the single-session effects of SBT on DT walking and DT turning performance in PD+FOG and older adults (OA), compared to regular treadmill training.

Methods: Forty-five PD+FOG and 36 OA participated in a single training session (30 min). They were randomized into one of four training groups: (A) SB75—steady belt speed ratio 0.75:1; (B) SB50—steady belt speed ratio 0.5:1; (C) SBCR—changing belt speed ratios between 0.75:1 and 0.5:1; and (D) Tied-Belt (TBT). Over-ground straight-line gait and an alternating turning in place task combined with a cognitive dual-task (DT) (auditory Stroop) were assessed pre- and post-training, and the following day (retention). Constrained longitudinal data analysis was used to investigate the training effects for all participants and for PD+FOG alone.

Results: DT gait speed improved at post-training for all groups (p < 0.001). However, SBT (SB50 and SBCR) led to larger post-training improvements compared to TBT, which were still visible at retention (SB50). For mean DT turning speed and Stroop response time while walking, only SBT groups showed significant improvements at post-training or retention. DT stride length, peak DT turning speed, and Stroop performance index while walking also showed larger gains in SBT compared to TBT. Results for PD+FOG alone showed similar effects although with smaller effect sizes.

Conclusions: A single session of SBT in PD+FOG and OA showed larger short-term effects on DT walking and turning compared to TBT. Cognitive DT performance was also improved in SBT, likely due to reduced cortical control of gait. These results illustrate the potential for SBT to improve DT during complex gait and possibly reduce fall risk in clinical and healthy populations.

Digital Measures That Matter to Patients: A Framework to Guide the Selection and Development of Digital Measures of Health

Background

With the rise of connected sensor technologies, there are seemingly endless possibilities for new ways to measure health. These technologies offer researchers and clinicians opportunities to go beyond brief snapshots of data captured by traditional in-clinic assessments, to redefine health and disease. Given the myriad opportunities for measurement, how do research or clinical teams know what they should be measuring? Patient engagement, early and often, is paramount to thoughtfully selecting what is most important. Regulators encourage stakeholders to have a patient focus but actionable steps for continuous engagement are not well defined. Without patient-focused measurement, stakeholders risk entrenching digital versions of poor traditional assessments and proliferating low-value tools that are ineffective, burdensome, and reduce both quality and efficiency in clinical care and research.

Summary

This article synthesizes and defines a sequential framework of core principles for selecting and developing measurements in research and clinical care that are meaningful for patients. We propose next steps to drive forward the science of high-quality patient engagement in support of measures of health that matter in the era of digital medicine.

Key Messages

All measures of health should be meaningful, regardless of the product's regulatory classification, type of measure, or context of use. To evaluate meaningfulness of signals derived from digital sensors, the following four-level framework is useful: Meaningful Aspect of Health, Concept of Interest, Outcome to be measured, and Endpoint (exclusive to research). Incorporating patient input is a dynamic process that requires more than a single, transactional touch point but rather should be conducted continuously throughout the measurement selection process. We recommend that developers, clinicians, and researchers reevaluate processes for more continuous patient engagement in the development, deployment, and interpretation of digital measures of health.

Sensorimotor Inhibition and Mobility in Genetic Subgroups of Parkinson's Disease

Background: Mobility and sensorimotor inhibition impairments are heterogeneous in Parkinson's disease (PD). Genetics may contribute to this heterogeneity since the apolipoprotein (APOE) ε4 allele and glucocerebrosidase (GBA) gene variants have been related to mobility impairments in otherwise healthy older adult (OA) and PD cohorts. The purpose of this study is to determine if APOE or GBA genetic status affects sensorimotor inhibition and whether the relationship between sensorimotor inhibition and mobility differs in genetic sub-groups of PD. Methods: Ninety-three participants with idiopathic PD (53 non-carriers; 23 ε4 carriers; 17 GBA variants) and 72 OA (45 non-carriers; 27 ε4 carriers) had sensorimotor inhibition characterized by short-latency afferent inhibition. Mobility was assessed in four gait domains (pace/turning, rhythm, trunk, variability) and two postural sway domains (area/jerkiness and velocity) using inertial sensors. Results: Sensorimotor inhibition was worse in the PD than OA group, with no effect of genetic status. Gait pace/turning was slower and variability was higher (p < 0.01) in PD compared to OA. Postural sway area/jerkiness (p < 0.01) and velocity (p < 0.01) were also worse in the PD than OA group. Genetic status was not significantly related to any gait or postural sway domain. Sensorimotor inhibition was significantly correlated with gait variability (r = 0.27; p = 0.02) and trunk movement (r = 0.23; p = 0.045) in the PD group. In PD non-carriers, sensorimotor inhibition related to variability (r = 0.35; p = 0.010) and trunk movement (r = 0.31; p = 0.025). In the PD ε4 group, sensorimotor inhibition only related to rhythm (r = 0.47; p = 0.024), while sensorimotor inhibition related to pace/turning (r = -0.49; p = 0.046) and rhythm (r = 0.59; p = 0.013) in the PD GBA group. Sensorimotor inhibition was significantly correlated with gait pace/turning (r = -0.27; p = 0.04) in the OA group. There was no relationship between sensorimotor inhibition and postural sway. Conclusion: ε4 and GBA genetic status did not affect sensorimotor inhibition or mobility impairments in this PD cohort. However, worse sensorimotor inhibition was associated with gait variability in PD non-carriers, but with gait rhythm in PD ε4 carriers and with gait rhythm and pace in PD with GBA variants. Impaired sensorimotor inhibition had a larger effect on mobility in people with PD than OA and affected different domains of mobility depending on genetic status.

Gait Performance in People with Symptomatic, Chronic Mild Traumatic Brain Injury

There is a dearth of knowledge about how symptom severity affects gait in the chronic (>3 months) mild traumatic brain injury (mTBI) population despite up to 53% of people reporting persisting symptoms after mTBI. The aim of this investigation was to determine whether gait is affected in a symptomatic, chronic mTBI group and to assess the relationship between gait performance and symptom severity on the Neurobehavioral Symptom Inventory (NSI). Gait was assessed under single- and dual-task conditions using five inertial sensors in 57 control subjects and 65 persons with chronic mTBI (1.0 year from mTBI). The single- and dual-task gait domains of Pace, Rhythm, Variability, and Turning were calculated from individual gait characteristics. Dual-task cost (DTC) was calculated for each domain. The mTBI group walked (domain z-score mean difference, single-task = 0.70; dual-task = 0.71) and turned (z-score mean difference, single-task = 0.69; dual-task = 0.70) slower (p < 0.001) under both gait conditions, with less rhythm under dual-task gait (z-score difference = 0.21; p = 0.001). DTC was not different between groups. Higher NSI somatic subscore was related to higher single- and dual-task gait variability as well as slower dual-task pace and turning (p < 0.01). Persons with chronic mTBI and persistent symptoms exhibited altered gait, particularly under dual-task, and worse gait performance related to greater symptom severity. Future gait research in chronic mTBI should assess the possible underlying physiological mechanisms for persistent symptoms and gait deficits.