Gait impairments in Parkinson's disease

M/EEG source localization for both subcortical and cortical sources using a convolutional neural network with a realistic head conductivity model

While electroencephalography (EEG) and magnetoencephalography (MEG) are well-established noninvasive methods in neuroscience and clinical medicine, they suffer from low spatial resolution. Electrophysiological source imaging (ESI) addresses this by noninvasively exploring the neuronal origins of M/EEG signals. Although subcortical structures are crucial to many brain functions and neuronal diseases, accurately localizing subcortical sources of M/EEG remains particularly challenging, and the feasibility is still a subject of debate. Traditional ESIs, which depend on explicitly defined regularization priors, have struggled to set optimal priors and accurately localize brain sources. To overcome this, we introduced a data-driven, deep learning-based ESI approach without the need for these priors. We proposed a four-layered convolutional neural network (4LCNN) designed to locate both subcortical and cortical sources underlying M/EEG signals. We also employed a sophisticated realistic head conductivity model using the state-of-the-art segmentation method of ten different head tissues from individual MRI data to generate realistic training data. This is the first attempt at deep learning-based ESI targeting subcortical regions. Our method showed excellent accuracy in source localization, particularly in subcortical areas compared to other methods. This was validated through M/EEG simulations, evoked responses, and invasive recordings. The potential for accurate source localization of the 4LCNNs demonstrated in this study suggests future contributions to various research endeavors such as the clinical diagnosis, understanding of the pathophysiology of various neuronal diseases, and basic brain functions.

Unraveling the stride: exploring the influence of neurogenic orthostatic hypotension on gait and balance in Parkinson's disease

PURPOSE

Neurogenic orthostatic hypotension (nOH) and gait impairment are frequent sources of disability in Parkinson's disease (PD). However, the impact of nOH on balance and gait features remains unclear. This cross-sectional study aimed to assess the influence of nOH on postural and gait parameters in a cohort of patients with PD by means of wearable inertial sensors.

METHODS

Gait and balance were assessed using Opal inertial sensors. nOH was defined as sustained systolic blood pressure (BP) drop ≥ 20 mmHg or diastolic BP drop ≥ 10 mmHg within 3 min of standing, with a ΔHR/ΔSBP ratio ≤ 0.5 bpm/mmHg. Analysis of covariance was performed to evaluate differences in gait/balance features between patients with and without nOH, adjusting for age, cognitive status, and motor disability. Moreover, we performed the same analysis considering the presence of hemodynamically relevant nOH (orthostatic mean BP ≤ 75 mmHg).

RESULTS

A total of 82 patients were enrolled, 26 with nOH (31.7%), of which 13 presented with hemodynamically relevant nOH. After correcting for confounders, nOH was independently associated with lower gait speed (p = 0.027), shorter stride length (p = 0.033), longer time for postural transitions (p = 0.004), and increased postural sway (p = 0.019). These differences were even more pronounced in patients with hemodynamically relevant nOH. Higher postural sway was associated with a 7.9-fold higher odds of falls (p = 0.040).

CONCLUSIONS

Our study presents an objective demonstration of the independent negative impact of nOH on gait and balance in PD, emphasizing the need for careful detection and management of nOH to mitigate gait and balance disturbances in PD.

Altered gait speed and brain network connectivity in Parkinson's disease

Slow gait speed and disrupted brain network connectivity are common in patients with Parkinson's disease (PD). This study aimed to clarify the relationship between gait speed and clinical characteristics in PD, and explore the underlying brain network mechanisms. Forty-two PD patients and 20 healthy controls (HC) were recruited. Statistical independent component analysis and correlation analysis were employed to investigate underlying neural mechanisms and relationships. PD patients exhibited significantly slower gait speed, which showed a significant negative correlation with postural instability and gait disturbance scores. Network connectivity analysis revealed decreased intranetwork functional connectivity (FC) within visual network (VN) and cerebellum network (CN), but increased internetwork FC between CN and both sensorimotor network (SMN) and frontoparietal network (FPN) in PD patients compared to HC. The slow gait speed PD subgroup demonstrated increased intranetwork FC within SMN and VN, along with decreased FC between VN and both FPN and default mode network. Correlation analyses revealed negative correlation between gait speed and FC of CN and positive correlation to FC of CN-SMN. Our study identified relationships between gait speed and clinical characteristics, and corresponding network connectivity alterations in PD patients, providing insights into the neural mechanisms underlying gait impairments in PD.

Exploring Responsiveness to Highly Challenging Balance and Gait Training in Parkinson's Disease

BACKGROUND

Exercise potentially improves gait, balance, and habitual physical activity in Parkinson's disease (PD). However, given the heterogeneous nature of the disease, it is likely that people respond differently to exercise interventions. Factors determining responsiveness to exercise interventions remain unclear.

OBJECTIVES

To address this uncertainty, we explored the responsiveness to our highly challenging balance and gait intervention (HiBalance) in people with PD.

METHODS

Thirty-nine participants with mild-moderate PD who underwent the HiBalance intervention from our randomized controlled trial were included. We defined response in three domains: (1) balance based on Mini-BESTest, (2) gait based on gait velocity, and (3) physical activity based on accelerometry-derived steps per day. In each domain, we explored three responsiveness levels: high, low, or non-responders according to the change from pre- to post-intervention. Separate Random Forests for each responder domain classified these responsiveness levels and identified variable importance.

RESULTS

Only the Random Forest for the balance domain classified all responsiveness levels above the chance level indicated by a Cohen's kappa of "slight" agreement. Variable importance differed among the responsiveness levels. Slow gait velocity indicated high responders in the balance domain but showed low probabilities for low and non-responders. For low and non-responders, fall history or no falls, respectively, were more important.

CONCLUSIONS

Among three responder domains and responsiveness levels, we could moderately classify responders in the balance domain, but not for the gait or physical activity domain. This can guide inclusion criteria for balance-targeted, personalized intervention studies in people with PD.

Better understanding fall risk: AI-based computer vision for contextual gait assessment

Contemporary research to better understand free-living fall risk assessment in Parkinson's disease (PD) often relies on the use of wearable inertial-based measurement units (IMUs) to quantify useful temporal and spatial gait characteristics (e.g., step time, step length). Although use of IMUs is useful to understand some intrinsic PD fall-risk factors, their use alone is limited as they do not provide information on extrinsic factors (e.g., obstacles). Here, we update on the use of ergonomic wearable video-based eye-tracking glasses coupled with AI-based computer vision methodologies to provide information efficiently and ethically in free-living home-based environments to better understand IMU-based data in a small group of people with PD. The use of video and AI within PD research can be seen as an evolutionary step to improve methods to understand fall risk more comprehensively.

Noradrenergic cardiac denervation is associated with gait velocity in Parkinson disease: a dual ligand PET study

PURPOSE

Preliminary data suggest that gait abnormalities in Parkinson disease (PD) may be associated with sympathetic cardiac denervation. No kinematic gait studies were performed to confirm this observation. We aimed to correlate spatiotemporal kinematic gait parameters with cardiac sympathetic denervation as determined by cardiac [11C]HED PET in PD.

METHODS

Retrospective database analysis of 27 PD patients with cardiac sympathetic denervation. All patients underwent spatiotemporal kinematic gait assessment (medication 'off' state), cardiac [11C]HED and dopaminergic brain [11C]DTBZ PET scans. We employed a hierarchical regression approach to examine associations between the extent of cardiac denervation, dopaminergic nigrostriatal neurodegeneration, and three gait parameters - velocity, step length and cadence.

RESULTS

More extensive cardiac denervation was associated with slower velocity (estimate: -1.034, 95% CI [-1.65, -0.42], p = 0.002), shorter step length (estimate: -0.818, 95% CI [-1.43, -0.21], p = 0.011) and lower cadence (estimate: -0.752, 95% CI [-1.28, -0.23], p = 0.007) explaining alone 30% (Adjusted-R²: 0.297), 20% (Adjusted-R²: 0.202) and 23% (Adjusted-R²: 0.227) of the variability, respecivetly. These associations remained independent of striatal dopaminergic impairment and confounding factors such as age, Hoehn and Yahr (HY) stages, peripheral neuropathy, cognition, and autonomic symptoms. In contrast, striatal dopaminergic denervation was significantly associated with step length (estimate: 0.883, 95% CI [0.29, 1.48], p = 0.005), explaining about 24% of the variability but was dependent of HY stage.

CONCLUSIONS

More severe cardiac noradrenergic denervation was associated with lower gait velocity, independent of striatal dopaminergic denervation and HY stage, impacting both step length and cadence. These results suggest independent contributions of the peripheral autonomic system degeneration on gait dynsfunction in PD.

Efficacy of high-frequency rTMS in the treatment of gait disorder and cognition in patients with Parkinson's disease based on wearable devices and eye-movement assessments

Background

Postural instability and gait disorder and cognitive dysfunction are common symptoms of Parkinson's disease (PD). Scale assessment is frequently used in the clinic to evaluate PD, but this technique is limited by its lack of sensitivity to changes in disease progression and its difficulty in capturing subtle movements and changes in cognitive function. It is currently believed that high-frequency repetitive transcranial magnetic stimulation (rTMS) can improve motor and cognitive dysfunction in patients with PD, though it remains controversial. Therefore, it is imperative to monitor and dynamically identify changes in postural instability and gait disorder, as well as those in cognitive dysfunction, in PD to develop targeted interventions. In this study, we observed the effect of high-frequency rTMS on gait disorders and cognitive functions in patients with PD by comparing data from wearable devices and eye-tracking devices before and after treatment.

Methods

A total of 159 patients with PD were included in this study. A GYENNO MATRIX wearable gait analyzer was used to monitor the objective gait data (including the timed up-and-go, narrow-track, and turning tests), the Eyeknow eye-tracking evaluation system was used to monitor the patient's eye movement cognition data (including the smooth pursuit, pro-saccade, and anti-saccade tests), and gait and cognitive function-related scales, including the Tinetti Balance Scale, Tinetti Gait Scale, Berg Balance Scale, Mini-Mental State Examination, and Montreal Cognitive Assessment (MoCA), were evaluated at the same time before and after high-frequency rTMS treatment.

Results

The mean step length, mean stride velocity, stride length, and mean step frequency of patients with PD in the timed up-and-go test all increased compared with those before rTMS treatment, whereas the mean stride time and double support decreased. In the narrow-track test, the mean stride velocity increased and the mean stride time decreased. In the turning test, the turning left duration, turning right duration, mean duration, mean number of steps, and average step duration decreased, while the mean angular velocity increased after rTMS treatment. Compared with those before rTMS treatment, the latency period of patients with PD in overlapping saccades decreased, the completion time of overlapping saccades decreased, and the average saccade speed increased. In the anti-saccade test, the completion time decreased and the average saccade speed increased after rTMS treatment. Compared with those before rTMS treatment, the Tinetti Balance Scale, Tinetti Gait Scale, Berg Balance Scale, Mini-Mental State Examination, and MoCA scores increased, and the MoCA sub-items improved in terms of visual-spatial and executive function, language, abstraction, delayed recall, and orientation after rTMS treatment.

Conclusion

High-frequency rTMS may be an effective therapy for improving gait disorders and cognitive functions in patients with PD.

Foot-Floor Contact Sequences: A Metric for Gait Assessment in Parkinson's Disease after Deep Brain Stimulation

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is to analyze the changes in the foot-floor contact sequences of Parkinson's Disease (PD) patients in the year following the implantation of Deep Brain Stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline (T0), at 3 months after subthalamic nucleus DBS neurosurgery (T1), and at 12 months (T2) after subthalamic nucleus DBS neurosurgery. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5 min walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in their UPDRS-III scores from 19.4 ± 1.8 to 10.2 ± 1.0 (T0 vs. T2) (p < 0.001). In straight-line walking, the percentages of atypical cycles of PD on the more affected side were 11.1 ± 1.5% (at T0), 3.1 ± 1.5% (at T1), and 5.1 ± 2.4% (at T2), while in controls it was 3.1 ± 1.3% (p < 0.0005). In turnings, this percentage was 13.7 ± 1.1% (at T0), 7.8 ± 1.1% (at T1), and 10.9 ± 1.8% (at T2), while in controls it was 8.1 ± 1.0% (p < 0.001). Therefore, in straight-line walking, the atypical cycles decreased by 72% at T1, and by 54% at T2 (with respect to baseline), while, in turnings, atypical cycles decreased by 43% at T1, and by 20% at T2. The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings.

Spatiotemporal, kinematic and kinetic gait characteristics in Parkinson's disease compared to healthy individuals: A systematic review with meta-analysis

BACKGROUND

Gait disorders are frequently reported in individuals with Parkinson's disease (PD). Despite extensive research, the specific gait features affected by PD remain inadequately defined. Therefore, this study aimed to investigate kinematic, kinetic, and spatiotemporal parameters of gait in individuals with PD compared to healthy controls.

METHODS

We conducted a systematic review in PubMed, CINAHL, and EMBASE up to March 2024 to retrieve studies assessing adults with PD, which examined gait compared to healthy controls. Two reviewers independently performed the screening process, extrapolation data and quality assessment. Studies were meta-analyzed using original units of measurement (mean difference, MD) to enhance the clinical understanding of the gait characteristics. The level of evidence was provided.

FINDINGS

Thirty-four studies were included (n = 1533 participants with PD and n = 1093 healthy controls). Moderate-to-strong evidence was found for reduced speed (MD:-0.21 m/s, 95 %CI: -0.27; -0.15), stride length (MD:-0.17 m, 95 %CI: -0.25; -0.09), swing time (MD:-1.16 % of gait cycle, 95 %CI: -2.30; -0.02), and sagittal range of motion of the lower limb joints in individuals with PD (hip: MD:-5.39°, 95 %CI: -10.42; -0.37; knee: MD:-11.05°, 95 %CI: -21.88; -0.22; ankle: MD:-4.03°, 95 %CI: -6.37; -1.69). An increase in double support time (MD:0.07 s, 95 %CI: 0.05; 0.10) and a decrease in cadence (MD: -4.93 steps/min, 95 %CI: -7.89; -1.98) were observed. Kinetic data showed diverse outcomes, making a meta-analysis not possible.

INTERPRETATION

PD is associated with changes in gait kinematics and spatiotemporal parameters, while kinetic aspects remain under investigated. Future research should focus on kinetics, joint angular velocity, and push-off parameters. PROSPERO registration: CRD42022347368.

Complexities and challenges of translating intervention success to real world gait in people with Parkinson's disease

Background

Unstable gait leading to falls negatively impacts the quality of life in many people with Parkinson's disease (PD). Systematic review evidence provides moderate to strong evidence of efficacy for a wide range of physiotherapy-based interventions to reduce gait impairment. However, outcomes have often focused on gait assessments conducted in controlled laboratory or clinical environments.

Objective

This perspective investigates the complexities and challenges of conducting real-world gait assessments in people with PD and the factors that may influence the translation from improved lab-assessed gait to improved real-world gait.

Methods

Through a thorough review of current literature, we present an in-depth analysis of current methodological approaches to real-world gait assessments and the challenges that may influence the translation of an intervention's success from lab-based outcomes to improved walking during daily life.

Results

We identified six key factors that may influence the translation of intervention success into real-world environments at different stages of the process. These factors comprise the gait intervention, parameters analyzed, sensor setup, assessment protocols, characteristics of walking bouts, and medication status. We provide recommendations for each factor based on our synthesis of current literature.

Conclusion

This perspective emphasizes the importance of measuring intervention success outside of the laboratory environment using real-world gait assessments. Our findings support the need for future studies to bridge the gap between proven efficacy for gait as assessed in controlled laboratory environments and real-world impact for people with PD.

Gait analysis in the early stage of Parkinson's disease with a machine learning approach

Background

Gait disorder is a prominent motor symptom in Parkinson's disease (PD), objective and quantitative assessment of gait is essential for diagnosing and treating PD, particularly in its early stage.

Methods

This study utilized a non-contact gait assessment system to investigate gait characteristics between individuals with PD and healthy controls, with a focus on early-stage PD. Additionally, we trained two machine learning models to differentiate early-stage PD patients from controls and to predict MDS-UPDRS III score.

Results

Early-stage PD patients demonstrated reduced stride length, decreased gait speed, slower stride and swing speeds, extended turning time, and reduced cadence compared to controls. Our model, after an integrated analysis of gait parameters, accurately identified early-stage PD patients. Moreover, the model indicated that gait parameters could predict the MDS-UPDRS III score using a machine learning regression approach.

Conclusion

The non-contact gait assessment system facilitates the objective and quantitative evaluation of gait disorder in PD patients, effectively distinguishing those in the early stage from healthy individuals. The system holds significant potential for the early detection of PD. It also harnesses gait parameters for a reasoned prediction of the MDS-UPDRS III score, thereby quantifying disease severity. Overall, gait assessment is a valuable method for the early identification and ongoing monitoring of PD.

Quantifying Asymmetric Gait Pattern Changes Using a Hidden Markov Model Similarity Measure (HMM-SM) on Inertial Sensor Signals

Wearable gait analysis systems using inertial sensors offer the potential for easy-to-use gait assessment in lab and free-living environments. This can enable objective long-term monitoring and decision making for individuals with gait disabilities. This study explores a novel approach that applies a hidden Markov model-based similarity measure (HMM-SM) to assess changes in gait patterns based on the gyroscope and accelerometer signals from just one or two inertial sensors. Eleven able-bodied individuals were equipped with a system which perturbed gait patterns by manipulating stance-time symmetry. Inertial sensor data were collected from various locations on the lower body to train hidden Markov models. The HMM-SM was evaluated to determine whether it corresponded to changes in gait as individuals deviated from their baseline, and whether it could provide a reliable measure of gait similarity. The HMM-SM showed consistent changes in accordance with stance-time symmetry in the following sensor configurations: pelvis, combined upper leg signals, and combined lower leg signals. Additionally, the HMM-SM demonstrated good reliability for the combined upper leg signals (ICC = 0.803) and lower leg signals (ICC = 0.795). These findings provide preliminary evidence that the HMM-SM could be useful in assessing changes in overall gait patterns. This could enable the development of compact, wearable systems for unsupervised gait assessment, without the requirement to pre-identify and measure a set of gait parameters.

Cycling reduces the entropy of neuronal activity in the human adult cortex

Brain Complexity (BC) have successfully been applied to study the brain electroencephalographic signal (EEG) in health and disease. In this study, we employed recurrence entropy to quantify BC associated with the neurophysiology of movement by comparing BC in both resting state and cycling movement. We measured EEG in 24 healthy adults and placed the electrodes on occipital, parietal, temporal and frontal sites on both the right and left sides of the brain. We computed the recurrence entropy from EEG measurements during cycling and resting states. Entropy is higher in the resting state than in the cycling state for all brain regions analysed. This reduction in complexity is a result of the repetitive movements that occur during cycling. These movements lead to continuous sensorial feedback, resulting in reduced entropy and sensorimotor processing.

Functional Near-Infrared Spectroscopy in neurodegenerative disease: a review

In recent years, with the aggravation of aging, the incidence of neurodegenerative diseases is increasing year by year, and the prognosis of patients is poor. Functional Near-Infrared Spectroscopy (fNIRS) is a new and non-invasive neuroimaging technology, which has been gradually deepened in the application research of neurodegenerative diseases by virtue of its unique neurooxygen signal brain functional imaging characteristics in monitoring the disease condition, making treatment plans and evaluating the treatment effect. In this paper, the mechanism of action and technical characteristics of fNIRS are briefly introduced, and the application research of fNIRS in different neurodegenerative diseases is summarized in order to provide new ideas for future related research and clinical application.

Model-based cueing-as-needed for walking in Parkinson's disease: A randomized cross-over study

BACKGROUND

Correcting of the lack of regularity in steps is a key component of gait rehabilitation in Parkinson's disease. We proposed to introduce adaptive spatial auditory cueing (ASAC) based on verbal instruction "lengthen the step" automatically delivered when the stride length decreased below a predetermined threshold.

OBJECTIVES

The present study compared the effect of usual rhythmic auditory cueing versus ASAC used during a walking training in Parkinson's disease.

METHODS

Fifteen patients with Parkinson's disease performed both interventions in randomized order, one week apart: a 20-minute walking training with rhythmic auditory cueing, in form of a metronome adjusted on 110% of the patient's own cadence, or ASAC delivered when the stride length is less than 110% of the patient's own stride length. Assessment criteria were walking distance covered during the intervention, speed, step length, cadence, coefficients of variation of step length and step duration, and indexes of spatial and temporal asymmetry during a walking test before and just after the intervention.

RESULTS

The walking distance is higher with ASAC compared with rhythmic auditory cueing (rhythmic auditory cueing, 905 (203) m, mean (standard deviation); ASAC, 1043 (212) m; P=0.002). Between-intervention comparison showed some similar effects on walking after the intervention including free speed and step length increases (P<0.05).

CONCLUSION

The distance covered during 20-minute walking with ASAC increases by 15% compared to the use of classical rhythmic auditory cueing, while the immediate therapeutic effects show similar spatial-temporal benefits on short-distance walking. Auditory biofeedback cueing promoting the increase in step length might improve gait relearning in Parkinson's disease.

Hypoxia Pathways in Parkinson's Disease: From Pathogenesis to Therapeutic Targets

The human brain is highly dependent on oxygen, utilizing approximately 20% of the body's oxygen at rest. Oxygen deprivation to the brain can lead to loss of consciousness within seconds and death within minutes. Recent studies have identified regions of the brain with spontaneous episodic hypoxia, referred to as "hypoxic pockets". Hypoxia can also result from impaired blood flow due to conditions such as heart disease, blood clots, stroke, or hemorrhage, as well as from reduced oxygen intake or excessive oxygen consumption caused by factors like low ambient oxygen, pulmonary diseases, infections, inflammation, and cancer. Severe hypoxia in the brain can manifest symptoms similar to Parkinson's disease (PD), including cerebral edema, mood disturbances, and cognitive impairments. Additionally, the development of PD appears to be closely associated with hypoxia and hypoxic pathways. This review seeks to investigate the molecular interactions between hypoxia and PD, emphasizing the pathological role of hypoxic pathways in PD and exploring their potential as therapeutic targets.

The effectiveness of action observation and motor imagery in freezing of gait, speed, physical function and balance in Parkinson's disease: a systematic review and meta-analysis

BACKGROUND

Parkinson's Disease (PD) is a neurodegenerative disease that produces balance and gait disorders. Action observation (AO) and motor imagery (MI) therapies appear to facilitate motor planning influencing balance and gait relearning.

OBJECTIVE

To investigate the effectiveness of AO and MI in isolation or combined (AO-MI), compared to sham interventions for the improvement of freezing of gait (FOG), speed, physical function and balance among individuals with PD.

METHODS

PubMed, Web of science, PEDro, Scopus and Cochrane Library were searched from inception to January 2024. Studies included were randomized controlled trials (RCTs). The study quality and risk of bias were assessed with PEDro scale and the Cochrane tool, respectively. The certainty of evidence was evaluated with GRADEpro GDT.

RESULTS

Eight RCTs were included, with a methodological quality ranged from fair to high. There were statistically significant results in FOG at follow-up when comparing AO to sham intervention (SMD= -0.50, 95% CI -0.88, -0.11; I2: 0%) 3 studies, 107 participants). Interventions based on MI compared to sham intervention were statistically significant in speed at post-treatment (MD = -0.06, 95% CI -0.04, -0.08; I2: 0%) and balance at post-treatment (SMD = -0.97; 95% CI -1.79, -0.15).

CONCLUSIONS

Very low certainty of evidence was found proposing that: AO produce improvements in FOG at follow-up; and MI produce improvements in speed and balance at post-treatment.

The Role of Deep Learning and Gait Analysis in Parkinson's Disease: A Systematic Review

Parkinson's disease (PD) is the second most common movement disorder in the world. It is characterized by motor and non-motor symptoms that have a profound impact on the independence and quality of life of people affected by the disease, which increases caregivers' burdens. The use of the quantitative gait data of people with PD and deep learning (DL) approaches based on gait are emerging as increasingly promising methods to support and aid clinical decision making, with the aim of providing a quantitative and objective diagnosis, as well as an additional tool for disease monitoring. This will allow for the early detection of the disease, assessment of progression, and implementation of therapeutic interventions. In this paper, the authors provide a systematic review of emerging DL techniques recently proposed for the analysis of PD by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Scopus, PubMed, and Web of Science databases were searched across an interval of six years (between 2018, when the first article was published, and 2023). A total of 25 articles were included in this review, which reports studies on the movement analysis of PD patients using both wearable and non-wearable sensors. Additionally, these studies employed DL networks for classification, diagnosis, and monitoring purposes. The authors demonstrate that there is a wide employment in the field of PD of convolutional neural networks for analyzing signals from wearable sensors and pose estimation networks for motion analysis from videos. In addition, the authors discuss current difficulties and highlight future solutions for PD monitoring and disease progression.

Current interventional model for movement in Parkinson's disease: network meta-analysis based on the improvement of motor ability

Aim

To identify optimally therapeutic exercise interventions for improving motor ability among patients with Parkinson's disease (PD), we conducted a network meta-analysis (NMA) of randomized controlled trials comparing different exercise regimens.

Methods

Relevant RCTs were retrieved by searching PubMed, Embase, Cochrane, Web of Science, CINAHL, CBM, China National Knowledge Infrastructure (CNKI), Wan fang, VIP, and other databases from inception to July 9, 2023 is available in English as the primary language. Exercise outcomes as measured by Movement Disorder Society- Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS-III) score change were evaluated and ranked using STATA software version 18.0. All included studies were assessed for methodological quality using the Cochrane Risk of Bias tool.

Results

The final NMA included 71 studies involving 3,732 participants, 87 intervention experiments, and 27distinct interventions. Although most exercise interventions showed some efficacy (reducing MDS-UPDRS-III score), cumulative ranking probability surface (SUCRA) values indicated that the best exercise interventions for motor function improvement were archery (95.6%), riding a bicycle (80.9%), and binary rhythm dance (80.8%).

Conclusion

An exercise intervention comprising archery, cycling, and(or) binary rhythm dance may yield superior improvements in motor function among patients with Parkinson's disease.

Evaluation of Smartphone Technology on Spatiotemporal Gait in Older and Diseased Adult Populations

Objective: Advancements in smartphone technology provide availability to evaluate movement in a more practical and feasible manner, improving clinicians' ability to diagnose and treat adults at risk for mobility loss. The purpose of this study was to evaluate the validity and reliability of a smartphone application to measure spatiotemporal outcomes during level (primary) and uphill/downhill (secondary) walking with and without an assistive device for older adults (OAs), Parkinson's Disease (PD) and cerebrovascular accident (CVA) populations. Methods: A total of 50 adults (OA = 20; PD = 15; CVA = 15) underwent gait analysis at self-selected gait speeds under 0-degree, 5-degree uphill and 5-degree downhill environments. The validity and reliability of the smartphone outcomes were compared to a motion-capture laboratory. Bland-Altman analysis was used to evaluate limits of agreement between the two systems. Intraclass correlation coefficients (ICCs) were used to determine absolute agreement, and Pearson correlation coefficients (r) were used to assess the strength of the association between the two systems. Results: For level walking, Bland-Altman analysis revealed relatively equal estimations of spatiotemporal outcomes between systems for OAs without an assistive device and slight to mild under- and overestimations of outcomes between systems for PD and CVA with and without an assistive device. Moderate to very high correlations between systems (without an assistive device: OA r-range, 0.72-0.99; PD r-range, 0.87-0.97; CVA r-range, 0.56-0.99; with an assistive device: PD r-range, 0.35-0.98; CVA r-range, 0.50-0.99) were also observed. Poor to excellent ICCs for reliability between systems (without an assistive device: OA ICC range, 0.71-0.99; PD ICC range, 0.73-0.97; CVA ICC range, 0.56-0.99; with an assistive device: PD ICC range, 0.22-0.98; CVA ICC range, 0.44-0.99) were observed across all outcomes. Conclusions: This smartphone application can be clinically useful in detecting most spatiotemporal outcomes in various walking environments for older and diseased adults at risk for mobility loss.

Parkinson's disease motor intervention patterns: a network meta-analysis based on patient motor function

Background

Parkinson's disease is characterized by symptoms such as bradykinesia and rigidity, which worsen as the disease progresses, significantly impacting patients' independence and quality of life. This study utilizes a network meta-analysis approach to quantify information gathered from randomized controlled trials (RCTs) regarding motor interventions that effectively improve the motor function of Parkinson's disease patients, aiming to provide evidence for selecting appropriate exercise intervention strategies for patients.

Methods

A systematic search strategy for randomized controlled trials (RCTs) restricted to English was constructed based on multiple biomedical databases. Databases searched included PubMed, Embase, Cochrane, Web of Science, CINAHL, CBM, China National Knowledge Infrastructure (CNKI), Wan fang, VIP, etc., with searches conducted from inception to July 9, 2023. Two authors screened all studies, extracted data, and used frequency domain analysis methods. Network meta-analysis was performed using STATA software version 18.0 to compare and rank exercises that could effectively improve the motor function of Parkinson's disease patients (measured by indicators such as MDS-UPDRS-III, TUG, BBS, Mini-BES Test, 6MWT scores). Additionally, a series of analyses and evaluations were conducted, such as assessing the methodological quality of included studies using the Cochrane risk of bias tool.

Results

The network meta-analysis included a total of 111 studies involving 5,358 participants, 133 intervention experiments, and 31 intervention measures. Although most exercise interventions showed effectiveness, cumulative ranking curves under the surface (SUCRA) values showed that archery exercise significantly improved patients' MDS-UPDRS-III scores (SUCRA = 95.6%), significantly superior to routine care [standardized mean difference (SMD = 16.92, 95%CI = -28.97, -4.87)]. High-intensity and agility exercise (High strength and agility) referred to as high-intensity exercise or agility training or a combination of both, collectively termed as high-intensity agility training, significantly improved patients' completion time for the time-up-and-go test (SUCRA = 99.7%), (SMD = -7.88, 95%CI = -9.47, -6.28). Dance and Tai Chi exercises significantly improved patients' balance abilities: Mini-Balance Evaluation Systems Test (SUCRA = 77.9%), (SMD = 5.25, 95%CI = -0.42, 10.92) for dance intervention and Berg Balance Scale (SUCRA = 94.7%), (SMD = 11.22, 95%CI = 3.26, 19.18) for Tai Chi intervention. Dance also significantly improved patients' walking ability in the 6-min walk test (SUCRA = 80.5%), (SMD = 71.31, 95%CI = 13.77, 128.84).

Conclusion

Compared to other exercises, archery, dance, Tai Chi, and high-intensity agility exercises demonstrate superior efficacy in improving the motor function of Parkinson's disease patients.

Case report: Levodopa challenge test is important in identifying dopamine-induced freezing of gait in patient with Parkinson's disease

Introduction

Freezing of gait (FOG) is a disabling and heterogeneous symptom in patients with Parkinson's disease (PD). Among them, dopamine-induced FOG is rare and difficult to identify. The treatment of dopamine-induced FOG is complex.

Case presentation

We herein presented a case of PD patient who complicated with refractory FOG. It was identified as dopamine-induced FOG during levodopa challenge test. Her symptoms were alleviated after we reduced the total equivalent dosage of levodopa.

Conclusion

Our report emphasizes the importance of levodopa challenge test in identifying different types of FOG, which is very important for further adjusting treatment.

Gait Analysis and Magnetic Resonance Imaging Characteristics in Patients with Isolated Rapid Eye Movement Sleep Behavior Disorder

BACKGROUND

Isolated rapid eye movement sleep behavioral disorder (iRBD) can precede neurodegenerative diseases. There is an urgent need for biomarkers to aid early intervention and neuroprotection.

OBJECTIVE

The aim is to assess quantitative motor, cognitive, and brain magnetic resonance imaging (MRI) characteristics in iRBD patients.

METHODS

Thirty-eight polysomnography-confirmed iRBD patients and 28 age- and sex-matched healthy controls underwent clinical, cognitive, and motor functional evaluations, along with brain MRI. Motor tasks included nine-hole peg test, five-times-sit-to-stand test, timed-up-and-go test, and 4-meter walking test with and without cognitive dual task. Quantitative spatiotemporal gait parameters were obtained using an optoelectronic system. Brain MRI analysis included functional connectivity (FC) of the main resting-state networks, gray matter (GM) volume using voxel-based morphometry, cortical thickness, and deep GM and brainstem volumes using FMRIB's Integrated Registration and Segmentation Tool and FreeSurfer.

RESULTS

iRBD patients relative to healthy subjects exhibited a poorer performance during the nine-hole peg test and five-times-sit-to-stand test, and greater asymmetry of arm-swing amplitude and stride length variability during dual-task gait. Dual task significantly worsened the walking performance of iRBD patients more than healthy controls. iRBD patients exhibited nonmotor symptoms, and memory, abstract reasoning, and visuospatial deficits. iRBD patients exhibited decreased FC of pallidum and putamen within the basal ganglia network and occipital and temporal areas within the visuo-associative network, and a reduced volume of the supramarginal gyrus. Brain functional alterations correlated with gait changes.

CONCLUSIONS

Subtle motor and nonmotor alterations were identified in iRBD patients, alongside brain structural and functional MRI changes. These findings may represent early signs of neurodegeneration and contribute to the development of predictive models for progression to parkinsonism. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Position paper on how technology for human motion analysis and relevant clinical applications have evolved over the past decades: Striking a balance between accuracy and convenience

BACKGROUND

Over the past decades, tremendous technological advances have emerged in human motion analysis (HMA).

RESEARCH QUESTION

How has technology for analysing human motion evolved over the past decades, and what clinical applications has it enabled?

METHODS

The literature on HMA has been extensively reviewed, focusing on three main approaches: Fully-Instrumented Gait Analysis (FGA), Wearable Sensor Analysis (WSA), and Deep-Learning Video Analysis (DVA), considering both technical and clinical aspects.

RESULTS

FGA techniques relying on data collected using stereophotogrammetric systems, force plates, and electromyographic sensors have been dramatically improved providing highly accurate estimates of the biomechanics of motion. WSA techniques have been developed with the advances in data collection at home and in community settings. DVA techniques have emerged through artificial intelligence, which has marked the last decade. Some authors have considered WSA and DVA techniques as alternatives to "traditional" HMA techniques. They have suggested that WSA and DVA techniques are destined to replace FGA.

SIGNIFICANCE

We argue that FGA, WSA, and DVA complement each other and hence should be accounted as "synergistic" in the context of modern HMA and its clinical applications. We point out that DVA techniques are especially attractive as screening techniques, WSA methods enable data collection in the home and community for extensive periods of time, and FGA does maintain superior accuracy and should be the preferred technique when a complete and highly accurate biomechanical data is required. Accordingly, we envision that future clinical applications of HMA would favour screening patients using DVA in the outpatient setting. If deemed clinically appropriate, then WSA would be used to collect data in the home and community to derive relevant information. If accurate kinetic data is needed, then patients should be referred to specialized centres where an FGA system is available, together with medical imaging and thorough clinical assessments.

Reduced inhibitory synaptic transmission onto striatopallidal neurons may underlie aging-related motor skill deficits

Human beings are living longer than ever before and aging is accompanied by an increased incidence of motor deficits, including those associated with the neurodegenerative conditions, Parkinson's disease (PD) and Huntington's disease (HD). However, the biological correlates underlying this epidemiological finding, especially the functional basis at the synapse level, have been elusive. This study reveals that motor skill performance examined via rotarod, beam walking and pole tests is impaired in aged mice. This study, via electrophysiology recordings, further identifies an aging-related reduction in the efficacy of inhibitory synaptic transmission onto dorsolateral striatum (DLS) indirect-pathway medium spiny neurons (iMSNs), i.e., a disinhibition effect on DLS iMSNs. In addition, pharmacologically enhancing the activity of DLS iMSNs by infusing an adenosine A2A receptor (A2AR) agonist, which presumably mimics the disinhibition effect, impairs motor skill performance in young mice, simulating the behavior in aged naïve mice. Conversely, pharmacologically suppressing the activity of DLS iMSNs by infusing an A2AR antagonist, in order to offset the disinhibition effect, restores motor skill performance in aged mice, mimicking the behavior in young naïve mice. In conclusion, this study identifies a functional inhibitory synaptic plasticity in DLS iMSNs that likely contributes to the aging-related motor skill deficits, which would potentially serve as a striatal synaptic basis underlying age being a prominent risk factor for neurodegenerative motor deficits.

The role of robot-assisted training on rehabilitation outcomes in Parkinson's disease: a systematic review and meta-analysis

PURPOSE

The study aims to assess the efficacy of robot-assisted rehabilitation training on upper and lower limb motor function and fatigue in Parkinson's disease (PD), and to explore the best-acting robotic rehabilitation program.

METHODS

We searched studies in seven databases and the search period was from the build to 30 June 2023. Two researchers independently screened studies and assessed the quality of the studies for data extraction.

RESULTS

A total of 21 studies were included, 18 studies related to lower limbs rehabilitation and 3 studies related to upper limbs rehabilitation, involving a total of 787 participants. The results showed that robot-assisted rehabilitation significantly improved indicators of lower limb motor function UPDRS Part III (WMD = -3.58, 95% CI = -5.91 to -1.25, p = 0.003) and BBS (WMD = 4.24, 95% CI = 2.88 to 5.54, p < 0.001), as well as non-motor symptoms of fatigue (WMD = -13.39, 95% CI = -17.92 to -8.86, p < 0.001) in PD patients. At the level of upper limb function, there was no statistically significant difference in the outcome measures of PFS (WMD = -0.25, 95% CI = -4.44 to 3.93, p = 0.9) and BBT (WMD = 1.73, 95% CI = -2.85 to 6.33, p = 0.458).

CONCLUSION

Robot-assisted rehabilitation significantly improved motor function, fatigue, and balance confidence in PD patients, but current evidence doesn't show that intelligent rehabilitation systems improve upper limb function. In particular, robotics combined with virtual reality worked best.

Sensor-Based Gait and Balance Assessment in Healthy Adults: Analysis of Short-Term Training and Sensor Placement Effects

While the analysis of gait and balance can be an important indicator of age- or disease-related changes, it remains unclear if repeated performance of gait and balance tests in healthy adults leads to habituation effects, if short-term gait and balance training can improve gait and balance performance, and whether the placement of wearable sensors influences the measurement accuracy. Healthy adults were assessed before and after performing weekly gait and balance tests over three weeks by using a force plate, motion capturing system and smartphone. The intervention group (n = 25) additionally received a home-based gait and balance training plan. Another sample of healthy adults (n = 32) was assessed once to analyze the impact of sensor placement (lower back vs. lower abdomen) on gait and balance analysis. Both the control and intervention group exhibited improvements in gait/stance. However, the trends over time were similar for both groups, suggesting that targeted training and repeated task performance equally contributed to the improvement of the measured variables. Since no significant differences were found in sensor placement, we suggest that a smartphone used as a wearable sensor could be worn both on the lower abdomen and the lower back in gait and balance analyses.

Efficacy of personalized repetitive transcranial magnetic stimulation based on functional reserve to enhance ambulatory function in patients with Parkinson's disease: study protocol for a randomized controlled trial

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is one of the non-invasive brain stimulations that modulate cortical excitability through magnetic pulses. However, the effects of rTMS on Parkinson's disease (PD) have yielded mixed results, influenced by factors including various rTMS stimulation parameters as well as the clinical characteristics of patients with PD. There is no clear evidence regarding which patients should be applied with which parameters of rTMS. The study aims to investigate the efficacy and safety of personalized rTMS in patients with PD, focusing on individual functional reserves to improve ambulatory function.

METHODS

This is a prospective, exploratory, multi-center, single-blind, parallel-group, randomized controlled trial. Sixty patients with PD will be recruited for this study. This study comprises two sub-studies, each structured as a two-arm trial. Participants are classified into sub-studies based on their functional reserves for ambulatory function, into either the motor or cognitive priority group. The Timed-Up and Go (TUG) test is employed under both single and cognitive dual-task conditions (serial 3 subtraction). The motor dual-task effect, using stride length, and the cognitive dual-task effect, using the correct response rate of subtraction, are calculated. In the motor priority group, high-frequency rTMS targets the primary motor cortex of the lower limb, whereas the cognitive priority group receives rTMS over the left dorsolateral prefrontal cortex. The active comparator for each sub-study is bilateral rTMS of the primary motor cortex of the upper limb. Over 4 weeks, the participants will undergo 10 rTMS sessions, with evaluations conducted pre-intervention, mid-intervention, immediately post-intervention, and at 2-month follow-up. The primary outcome is a change in TUG time between the pre- and immediate post-intervention evaluations. The secondary outcome variables are the TUG under cognitive dual-task conditions, Movement Disorder Society-Unified Parkinson's Disease Rating Scale Part III, New Freezing of Gait Questionnaire, Digit Span, trail-making test, transcranial magnetic stimulation-induced motor-evoked potentials, diffusion tensor imaging, and resting state functional magnetic resonance imaging.

DISCUSSION

The study will reveal the effect of personalized rTMS based on functional reserve compared to the conventional rTMS approach in PD. Furthermore, the findings of this study may provide empirical evidence for an rTMS protocol tailored to individual functional reserves to enhance ambulatory function in patients with PD.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06350617. Registered on 5 April 2024.

Lower-Limb Exoskeletons for Gait Training in Parkinson's Disease: The State of the Art and Future Perspectives

Gait dysfunction (GD) is a common impairment of Parkinson's disease (PD), which negatively impacts patients' quality of life. Among the most recent rehabilitation technologies, a lower-limb powered exoskeleton (LLEXO) arises as a useful instrument for gait training in several neurological conditions, including PD. However, some questions relating to methods of use, achievable results, and usefulness compared to traditional rehabilitation methodologies still require clear answers. Therefore, in this review, we aim to summarise and analyse all the studies that have applied an LLEXO to train gait in PD patients. Literature research on PubMed and Scopus retrieved five articles, comprising 46 PD participants stable on medications (age: 71.7 ± 3.7 years, 24 males, Hoehn and Yahr: 2.1 ± 0.6). Compared to traditional rehabilitation, low-profile lower-limb exoskeleton (lp-LLEXO) training brought major improvements towards walking capacity and gait speed, while there are no clear major benefits regarding the dual-task gait cost index and freezing of gait symptoms. Importantly, the results suggest that lp-LLEXO training is more beneficial for patients with an intermediate-to-severe level of disease severity (Hoehn and Yahr > 2.5). This review could provide a novel framework for implementing LLEXO in clinical practise, highlighting its benefits and limitations towards gait training.

Brain modulation after exergaming training in advanced forms of Parkinson's disease: a randomized controlled study

BACKGROUND

Physical activity combined with virtual reality and exergaming has emerged as a new technique to improve engagement and provide clinical benefit for gait and balance disorders in people with Parkinson's disease (PD).

OBJECTIVE

To investigate the effects of a training protocol using a home-based exergaming system on brain volume and resting-state functional connectivity (rs-FC) in persons with PD.

METHODS

A single blind randomized controlled trial was conducted in people with PD with gait and/or balance disorders. The experimental (active) group performed 18 training sessions at home by playing a custom-designed exergame with full body movements, standing in front of a RGB-D Kinect® motion sensor, while the control group played using the computer keyboard. Both groups received the same training program. Clinical scales, gait recordings, and brain MRI were performed before and after training. We assessed the effects of both training on both the grey matter volumes (GVM) and rs-FC, within and between groups.

RESULTS

Twenty-three patients were enrolled and randomly assigned to either the active (n = 11) or control (n = 12) training groups. Comparing pre- to post-training, the active group showed significant improvements in gait and balance disorders, with decreased rs-FC between the sensorimotor, attentional and basal ganglia networks, but with an increase between the cerebellar and basal ganglia networks. In contrast, the control group showed no significant changes, and rs-FC significantly decreased in the mesolimbic and visuospatial cerebellar and basal ganglia networks. Post-training, the rs-FC was greater in the active relative to the control group between the basal ganglia, motor cortical and cerebellar areas, and bilaterally between the insula and the inferior temporal lobe. Conversely, rs FC was lower in the active relative to the control group between the pedunculopontine nucleus and cerebellar areas, between the temporal inferior lobes and the right thalamus, between the left putamen and dorsolateral prefrontal cortex, and within the default mode network.

CONCLUSIONS

Full-body movement training using a customized exergame induced brain rs-FC changes within the sensorimotor, attentional and cerebellar networks in people with PD. Further research is needed to comprehensively understand the neurophysiological effects of such training approaches. Trial registration ClinicalTrials.gov NCT03560089.

No evidence for effects of low-intensity vestibular noise stimulation on mild-to-moderate gait impairments in patients with Parkinson's disease

BACKGROUND

Gait impairment is a key feature in later stages of Parkinson's disease (PD), which often responds poorly to pharmacological therapies. Neuromodulatory treatment by low-intensity noisy galvanic vestibular stimulation (nGVS) has indicated positive effects on postural instability in PD, which may possibly be conveyed to improvement of dynamic gait dysfunction.

OBJECTIVE

To investigate the effects of individually tuned nGVS on normal and cognitively challenged walking in PD patients with mild-to-moderate gait dysfunction.

METHODS

Effects of nGVS of varying intensities (0-0.7 mA) on body sway were examined in 32 patients with PD (ON medication state, Hoehn and Yahr: 2.3 ± 0.5), who were standing with eyes closed on a posturographic force plate. Treatment response and optimal nGVS stimulation intensity were determined on an individual patient level. In a second step, the effects of optimal nGVS vs. sham treatment on walking with preferred speed and with a cognitive dual task were investigated by assessment of spatiotemporal gait parameters on a pressure-sensitive gait carpet.

RESULTS

Evaluation of individual balance responses yielded that 59% of patients displayed a beneficial balance response to nGVS treatment with an average optimal improvement of 23%. However, optimal nGVS had no effects on gait parameters neither for the normal nor the cognitively challenged walking condition compared to sham stimulation irrespective of the nGVS responder status.

CONCLUSIONS

Low-intensity nGVS seems to have differential treatment effects on static postural imbalance and continuous gait dysfunction in PD, which could be explained by a selective modulation of midbrain-thalamic circuits of balance control.

Dual-task gait has prognostic value for cognitive decline in Parkinson's disease

INTRODUCTION

Cognitive decline frequently occurs in individuals with Parkinson's disease (PD), but the clinical methods to predict the onset of cognitive changes are limited. Given preliminary evidence of the link between gait and cognition, the purpose of this study was to determine if dual task (DT) gait was related to declines in cognition over two years in PD.

METHODS

A retrospective two-year longitudinal study of 48 individuals with PD using data from the Parkinson's Progression Markers Initiative of the Michael J. Fox Foundation. The following data were extracted at baseline: spatiotemporal gait (during single and DT), demographics (age, sex), PD disease duration (time since diagnosis), motor function (Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS)), and cognition (Montreal Cognitive Assessment (MoCA)), with MoCA scores also extracted after two years.

RESULTS

A binomial logistic regression was conducted, with all covariates (above) in block 1 and DT effect (DTE) of gait characteristics in block 2 entered in a stepwise fashion. The final model was statistically significant (χ2(6) = 23.20, p < 0.001) and correctly classified 78.7 % of participants by cognitive status after two years. Only DTE of arm swing asymmetry (ASA) (p = 0.030) was included in block 2 such that a 1 % decline in DTE resulted in 1.6 % increased odds of cognitive decline.

CONCLUSIONS

Individuals with greater change in arm swing asymmetry from single to DT gait may be more likely to experience a decline in cognition within two years. These results suggested that reduced automaticity or poor utilization of attentional resources may be indicative of subtle changes in cognition and indicate that DT paradigms may hold promise as a marker of future cognitive decline.

Proposal and validation of an equation to identify sarcopenia using bioelectrical impedance analysis-derived parameters

OBJECTIVE

This study aimed to develop a simpler approach for diagnosing sarcopenia by using only bioelectrical impedance vector analysis parameters.

METHODS

The study design was a cross-sectional study. The research was conducted based on the Itabashi Longitudinal Study on Aging, a community-based cohort study, with data collected from the 2022 and 2023 surveys in Itabashi Ward, Tokyo, Japan. The development cohort consisted of 1146 participants from the 2022 survey, and the validation cohort included 656 participants from the 2023 survey. Both cohorts were comprised of community-dwelling older adults with similar inclusion criteria. Sarcopenia was defined according to the Asian Working Group for Sarcopenia 2019 criteria. The logistic model utilized height divided by impedance at 50 kHz and phase angle to establish a new regression equation to identify sarcopenia. Regression equations were generated for the development cohort and validated for the validation cohort. Discriminatory ability was assessed using the area under the receiver operating characteristic curve (AUC) for men and women.

RESULTS

The prevalence of sarcopenia was 20.7% and 14.8% in the development and validation cohort, respectively. The AUC (95% confidence interval) of the logistic model in discriminating sarcopenia was 0.92 (0.88, 0.95) for men and 0.82 (0.78, 0.86) for women in the development cohort and 0.85 (0.78, 0.91) for men and 0.90 (0.86, 0.95) for women in the validation cohort.

CONCLUSION

The study demonstrated that a simple formula using bioelectrical parameters at 50 kHz proved useful in identifying sarcopenia in the older adult population.

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.

Protopanaxadiols Eliminate Behavioral Impairments and Mitochondrial Dysfunction in Parkinson's Disease Mice Model

Currently, there are no effective therapies to cure Parkinson's disease (PD), which is the second most common neurodegenerative disease primarily characterized by motor dysfunction and degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc). Protopanaxadiols (PPDs), including 20 (R)- protopanaxadiol (R-PPD) and 20 (S)- protopanaxadiol (S-PPD), are main metabolites of ginsenosides. The role of ginsenosides in neurodegenerative diseases has been thoroughly studied, however, it is unknown whether PPDs can attenuate behavioral deficits and dopaminergic neuron injury in PD model mice to date. Here, we administered PPDs to MPTP-induced PD model mice and monitored the effects on behavior and dopaminergic neurons to investigate the effects of R-PPD and S-PPD against PD. Our results showed that R-PPD and S-PPD (at a dose of 20 mg/kg, i.g.) treatment alleviated MPTP (30 mg/kg, i.p.) induced behavioral deficits. Besides, R-PPD and S-PPD protected MPP+-induced neuron injury and mitochondrial dysfunction, and reduced the abnormal expression of Cyt C, Bax, caspase-3 and Bcl-2. These findings demonstrate that R-PPD and S-PPD were potentially useful to ameliorate PD.

Short Step Length Estimation for Parkinson's Disease Patients by Using Fusion Data From Camera-IMU in Smart Glasses

Shortened step length is a prominent motor abnormality in Parkinson's disease (PD) patients. Current methods for estimating short step length have the limitation of relying on laboratory scenarios, wearing multiple sensors, and inaccurate estimation results from a single sensor. In this paper, we proposed a novel method for estimating short step length for PD patients by fusing data from camera and inertial measurement units in smart glasses. A simultaneous localization and mapping technique and acceleration thresholding-based step detection technique were combined to realize the step length estimation. Two sets of experiments were conducted to demonstrate the performance of our method. In the first set of experiments with 12 healthy subjects, the proposed method demonstrated an average error of 8.44% across all experiments including six fixed step lengths below 30 cm. The second set of straightly walking experiments were implemented with 12 PD patients, the proposed method exhibited an average error of 4.27% compared to a standard gait evaluation technique in total walking distance. Notably, among the results of step lengths below 40 cm, our method agreed with the standard technique (R 2=0.8659). This study offers a promising approach for estimating short step length for PD patients during smart glasses-based gait training.

Age- and Parkinson-related differences in trunk and lower-limb muscle activation during four balance tasks: A case-control pilot study

BACKGROUND

Poor postural control has been reported in people with Parkinson's disease, which could be explained by the changes in muscular activation patterns related to antigravitational muscles. This study aims to measure the muscle activation of antigravitational muscles during balance tasks in individuals, with and without Parkinson's.

METHODS

Sixteen (16) participants (9 with Parkinson's), aged ≥65 yrs., performed 2 × 30-s trials of 4 balance tasks (bipodal and semi-tandem opened eyes and closed eyes) on a force platform (center of pressure measurement); while surface electromyography measurements were obtained bilaterally on the multifidus at L5, biceps femoris and medialis gastrocnemius. Electromyography amplitude analysis was processed by the Root Mean Square (250 ms window epochs) and normalized by the peak of activation during the balance task, to determine each muscle's activity level.

FINDINGS

The Parkinson's group reported lower muscle activation than control across tasks (in mean for multifidus = 8%, biceps femoris = 16%, gastrocnemius = 7%), although not statistically significant. Parkinson's reported significantly poorer postural control than control, mainly for the center of pressure sway ellipse area (p = 0.016) from challenge balance tasks such as semi-tandem.

INTERPRETATION

Poor postural control was confirmed in the Parkinson's group, but not significantly associated by the changes from muscle activation of trunk and lower limbs, during balance performance.

3D Kinematics Quantifies Gait Response to Levodopa earlier and to a more Comprehensive Extent than the MDS-Unified Parkinson's Disease Rating Scale in Patients with Motor Complications

BACKGROUND

Quantitative 3D movement analysis using inertial measurement units (IMUs) allows for a more detailed characterization of motor patterns than clinical assessment alone. It is essential to discriminate between gait features that are responsive or unresponsive to current therapies to better understand the underlying pathophysiological basis and identify potential therapeutic strategies.

OBJECTIVES

This study aims to characterize the responsiveness and temporal evolution of different gait subcomponents in Parkinson's disease (PD) patients in their OFF and various ON states following levodopa administration, utilizing both wearable sensors and the gold-standard MDS-UPDRS motor part III.

METHODS

Seventeen PD patients were assessed while wearing a full-body set of 15 IMUs in their OFF state and at 20-minute intervals following the administration of a supra-threshold levodopa dose. Gait was reconstructed using a biomechanical model of the human body to quantify how each feature was modulated. Comparisons with non-PD control subjects were conducted in parallel.

RESULTS

Significant motor changes were observed in both the upper and lower limbs according to the MDS-UPDRS III, 40 minutes after levodopa intake. IMU-assisted 3D kinematics detected significant motor alterations as early as 20 minutes after levodopa administration, particularly in upper limbs metrics. Although all "pace-domain" gait features showed significant improvement in the Best-ON state, most rhythmicity, asymmetry, and variability features did not.

CONCLUSION

IMUs are capable of detecting motor alterations earlier and in a more comprehensive manner than the MDS-UPDRS III. The upper limbs respond more rapidly to levodopa, possibly reflecting distinct thresholds to levodopa across striatal regions.

Imaging body-mind crosstalk in young adults

Objective

There is evidence that complex relationships exist between motor functions, brain structure, and cognitive functions, particularly in the aging population. However, whether such relationships observed in older adults could extend to other age groups (e.g., younger adults) remains to be elucidated. Thus, the current study addressed this gap in the literature by investigating potential associations between motor functions, brain structure, and cognitive functions in a large cohort of young adults.

Methods

In the current study, data from 910 participants (22-35 yr) were retrieved from the Human Connectome Project. Interactions between motor functions (i.e., cardiorespiratory fitness, gait speed, hand dexterity, and handgrip strength), brain structure (i.e., cortical thickness, surface area, and subcortical volumes), and cognitive functions were examined using linear mixed-effects models and mediation analyses. The performance of different machine-learning classifiers to discriminate young adults at three different levels (related to each motor function) was compared.

Results

Cardiorespiratory fitness and hand dexterity were positively associated with fluid and crystallized intelligence in young adults, whereas gait speed and handgrip strength were correlated with specific measures of fluid intelligence (e.g., inhibitory control, flexibility, sustained attention, and spatial orientation; false discovery rate [FDR] corrected, p < 0.05). The relationships between cardiorespiratory fitness and domains of cognitive function were mediated by surface area and cortical volume in regions involved in the default mode, sensorimotor, and limbic networks (FDR corrected, p < 0.05). Associations between handgrip strength and fluid intelligence were mediated by surface area and volume in regions involved in the salience and limbic networks (FDR corrected, p < 0.05). Four machine-learning classifiers with feature importance ranking were built to discriminate young adults with different levels of cardiorespiratory fitness (random forest), gait speed, hand dexterity (support vector machine with the radial kernel), and handgrip strength (artificial neural network).

Conclusions

In summary, similar to observations in older adults, the current study provides empirical evidence (i) that motor functions in young adults are positively related to specific measures of cognitive functions, and (ii) that such relationships are at least partially mediated by distinct brain structures. Furthermore, our analyses suggest that machine-learning classifier has a promising potential to be used as a classification tool and decision support for identifying populations with below-average motor and cognitive functions.

Association between the sarcopenia-related traits and Parkinson's disease: A bidirectional two-sample Mendelian randomization study

OBJECTIVE

To explore the causal association between sarcopenia-related traits and Parkinson's disease by Mendelian randomization (MR) approach.

METHODS

A genome-wide association study (GWAS) of sarcopenia-related traits was done at the UK Biobank (UKB). The traits were appendicular lean mass, low hand grip strength (including the European Working Group on Sarcopenia in Older People (EWGSOP) and the Foundation for the National Institutes of Health (FNIH) criteria and usual walking pace. The International Parkinson's Disease Genomics Consortium (IPDGC) gave us GWAS data for Parkinson's disease (PD). We used three different types of MR analyses: including Inverse-variance weighted (IVW), Mendelian randomized Egger regression (MR-Egger), and weighted median methods (both weighted and simple modes).

RESULTS

The MR analysis showed that low hand grip strength was negatively associated with the risk of developing Parkinson's disease, including EWGSOP criterion (odds ratio (OR) = 0.734; 95% confidence interval (CI) = 0.575-0.937, P = 0.013) and FNIH criterion (OR = 0.619; 95% CI = 0.419-0.914, P = 0.016), and usual walking pace was also a risk factor for Parkinson's disease (OR = 3.307, 95% CI = 1.277-8.565, P = 0.014).

CONCLUSIONS

In European population, low hand grip strength is negatively associated with the risk of developing Parkinson's disease, and usual walking pace is also a risk factor for Parkinson's disease. Further exploration of the potential genetic mechanisms underlying hand grip strength and Parkinson's disease and the potential relationship between walking pace, balance, and falls in Parkinson's patients may help to reduce the burden of sarcopenia and Parkinson's disease.

Wearable sensor-based quantitative gait analysis in Parkinson's disease patients with different motor subtypes

Gait impairments are among the most common and disabling symptoms of Parkinson's disease and worsen as the disease progresses. Early detection and diagnosis of subtype-specific gait deficits, as well as progression monitoring, can help to implement effective and preventive personalized treatment for PD patients. Yet, the gait features have not been fully studied in PD and its motor subtypes. To characterize comprehensive and objective gait alterations and to identify the potential gait biomarkers for early diagnosis, subtype differentiation, and disease severity monitoring. We analyzed gait parameters related to upper/lower limbs, trunk and lumbar, and postural transitions from 24 tremor-dominant (TD) and 20 postural instability gait difficulty (PIGD) dominant PD patients who were in early stage and 39 matched healthy controls (HC) during the Timed Up and Go test using wearable sensors. Results show: (1) Both TD and PIGD groups showed restricted backswing range in bilateral lower extremities and more affected side (MAS) arm, reduced trunk and lumbar rotation range in the coronal plane, and low turning efficiency. The receiver operating characteristic (ROC) analysis revealed these objective gait features had high discriminative value in distinguishing both PD subtypes from the HC with the area under the curve (AUC) values of 0.7~0.9 (p < 0.01). (2) Subtle but measurable gait differences existed between TD and PIGD patients before the onset of clinically apparent gait impairment. (3) Specific gait parameters were significantly associated with disease severity in TD and PIGD subtypes. Objective gait biomarkers based on wearable sensors may facilitate timely and personalized gait treatments in PD subtypes through early diagnosis, subtype differentiation, and disease severity monitoring.

Exploring the role of anticipatory postural adjustment duration within APA2 subphase as a potential mediator between clinical disease severity and fall risk in Parkinson's disease

Introduction

People with Parkinson's Disease (PD) often show reduced anticipatory postural adjustments (APAs) before voluntary steps, impacting their stability. The specific subphase within the APA stage contributing significantly to fall risk remains unclear.

Methods

We analyzed center of pressure (CoP) trajectory parameters, including duration, length, and velocity, throughout gait initiation. This examination encompassed both the postural phase, referred to as anticipatory postural adjustment (APA) (APA1, APA2a, APA2b), and the subsequent locomotor phases (LOC). Participants were instructed to initiate a step and then stop (initiating a single step). Furthermore, we conducted assessments of clinical disease severity using the Unified Parkinson's Disease Rating Scale (UPDRS) and evaluated fall risk using Tinetti gait and balance scores during off-medication periods.

Results

Freezing of gait (FOG) was observed in 18 out of 110 participants during the measurement of CoP trajectories. The Ramer-Douglas-Peucker algorithm successfully identified CoP displacement trajectories in 105 participants (95.5%), while the remaining 5 cases could not be identified due to FOG. Tinetti balance and gait score showed significant associations with levodopa equivalent daily dose, UPDRS total score, disease duration, duration (s) in APA2a (s) and LOC (s), length in APA1 (cm) and APA2b (cm), mediolateral velocity in APA1 (X) (cm/s), APA2a (X) (cm/s), APA2b (X) (cm/s) and LOC (X) (cm/s), and anterior-posterior velocity in APA2a (Z) (cm/s) and APA2b (Z) (cm/s). Multiple linear regression revealed that only duration (s) in APA2a and UPDRS total score was independently associated with Tinetti gait and balance score. Further mediation analysis showed that the duration (s) in APA2a served as a mediator between UPDRS total score and Tinetti balance and gait score (Sobel test, p = 0.047).

Conclusion

APA2 subphase duration mediates the link between disease severity and fall risk in PD, suggesting that longer APA2a duration may indicate reduced control during gait initiation, thereby increasing fall risk.

Exploring the Potentials of Wearable Technologies in Managing Vestibular Hypofunction

The vestibular system is dedicated to gaze stabilization, postural balance, and spatial orientation; this makes vestibular function crucial for our ability to interact effectively with our environment. Vestibular hypofunction (VH) progresses over time, and it presents differently in its early and advanced stages. In the initial stages of VH, the effects of VH are mitigated using vestibular rehabilitation therapy (VRT), which can be facilitated with the aid of technology. At more advanced stages of VH, novel techniques that use wearable technologies for sensory augmentation and sensory substitution have been applied to manage VH. Despite this, the potential of assistive technologies for VH management remains underexplored over the past decades. Hence, in this review article, we present the state-of-the-art technologies for facilitating early-stage VRT and for managing advanced-stage VH. Also, challenges and strategies on how these technologies can be improved to enable long-term ambulatory and home use are presented.

Unobtrusive measurement of gait parameters using seismographs: An observational study

Analyzing irregularities in walking patterns helps detect human locomotion abnormalities that can signal health changes. Traditional observation-based assessments have limitations due to subjective biases and capture only a single time point. Ambient and wearable sensor technologies allow continuous and objective locomotion monitoring but face challenges due to the need for specialized expertise and user compliance. This work proposes a seismograph-based algorithm for quantifying human gait, incorporating a step extraction algorithm derived from mathematical morphologies, with the goal of achieving the accuracy of clinical reference systems. To evaluate our method, we compared the gait parameters of 50 healthy participants, as recorded by seismographs, and those obtained from reference systems (a pressure-sensitive walkway and a camera system). Participants performed four walking tests, including traversing a walkway and completing the timed up-and-go (TUG) test. In our findings, we observed linear relationships with strong positive correlations (R2 > 0.9) and tight 95% confidence intervals for all gait parameters (step time, cycle time, ambulation time, and cadence). We demonstrated that clinical gait parameters and TUG mobility test timings can be accurately derived from seismographic signals, with our method exhibiting no significant differences from established clinical reference systems.

Imbalance and Falls in Patients with Parkinson's Disease: Causes and Recent Developments in Training and Sensor-Based Assessment

Imbalance and falls in patients with Parkinson's disease (PD) do not only reduce their quality of life but also their life expectancy. Aging-related symptoms as well as disease-specific motor and non-motor symptoms contribute to these conditions and should be treated when appropriate. In addition to an active lifestyle, advanced exercise training is useful and effective, especially for less medically responsive symptoms such as freezing of gait and postural instability at advanced stages. As treadmill training in non-immersive virtual reality, including dual tasks, significantly reduced the number of falls in PD patients, the mechanism(s) explaining this effect should be further investigated. Such research could help to select the most suitable patients and develop the most effective training protocols based on this novel technology. Real-life digital surrogate markers of mobility, such as those describing aspects of endurance, performance, and the complexity of specific movements, can further improve the quality of mobility assessment using wearables.

Combined diagnosis for Parkinson's disease via gait and eye movement disorders

BACKGROUND AND OBJECTIVES

With the discovery of the potential role of gait and eye movement disorders in Parkinson's disease (PD) recognition, we intend to investigate the combined diagnostic value of gait and eye movement disorders for PD.

METHODS

We enrolled some Chinese PD patients and healthy controls and separated them into the training and validation sets based on enrollment time. Performance in five oculomotor paradigms and in one gait paradigm was examined using an infrared eye tracking device and a wearable gait analysis device. We developed and validated a combined model for PD diagnosis via multivariate stepwise logistic regression analysis. Furthermore, subgroup comparisons and multi-model comparison were performed to assess its applicability and advantages.

RESULTS

A total of 145 PD patients and 80 healthy controls in China were recruited. The pro-saccade velocity, the trunk-sway max, and the turn mean angular velocity were finally screened out for the model development. Incorporating age factor, the ternary model demonstrated more satisfactory performance on ROC (AUC of 0.953 in the training set and AUC of 0.972 in the validation set), calibration curve, and decision curve. A nomogram was drawn to visualize the model. The combined model outperforms individual models with a broad application and the unique diagnostic value for early detection of PD patients, especially TD-PD patients.

CONCLUSION

We demonstrated the presence of gait and eye movement disorders, as well as the feasibility, applicability, and superiority of employing them together to diagnose PD.

Psychometric properties of the Brazilian-Portuguese version of the Falls Behavioral Scale in people with Parkinson's disease

PURPOSE

To verify the psychometric properties of the Brazilian-Portuguese version of the Falls Behavioral (FaB-Brazil) Scale in Parkinson's disease (PD).

MATERIAL AND METHODS

Participants (n = 96) were assessed by disease-specific, self-report and functional mobility measures. Internal consistency of the FaB-Brazil scale was evaluated using Cronbach's alpha and inter-rater and test-retest reliability using intraclass correlation coefficients (ICC). The standard error of measurement (SEM), minimal detectable change (MDC), ceiling and floor effects, and convergent and discriminative validity were evaluated.

RESULTS

Internal consistency was moderate (α = 0.77). Excellent inter-rater (ICC = 0.90; p < 0.001) and test-retest (ICC = 0.91; p < 0.001) reliability were found. The SEM was 0.20 and MDC was 0.38. Ceiling and floor effects were not found. Convergent validity was established by the positive correlations between the FaB-Brazil scale and age, modified Hoehn and Yahr, PD duration, Movement Disorders Society-Unified Parkinson's Disease Rating Scale, Motor Aspects of Experiences of Daily Living, Timed Up & Go and 8-item Parkinson's Disease Questionnaire, and negative correlations between the FaB-Brazil scale and community mobility, Schwab & England, and Activities-specific Balance Confidence scale. Females showed greater protective behaviors than males; recurrent fallers showed greater protective behaviors than non-recurrent fallers (p < 0.05).

CONCLUSIONS

The FaB-Brazil scale is reliable and valid for assessing people with PD.

Validity, reliability, and measurement error of the Japanese version of the Freezing of Gait Questionnaire for patients with Parkinson's disease

BACKGROUND

The Freezing of Gait Questionnaire has been translated into several languages. However, it has not been translated into Japanese and its measurement error remains unclear.Objectives: This study aimed to translate the Freezing of Gait Questionnaire into Japanese, investigate its validity and reliability, and calculate its measurement errors.

METHODS

Thirty-five patients with Parkinson's disease participated in the study. The Freezing of Gait Questionnaire was translated into Japanese using a forward - backward translation method. Convergent validity was assessed using the Freezing of Gait Questionnaire and Unified Parkinson's Disease Rating Scale Part II(item 14-freezing). The content validity index was calculated using the Freezing of Gait Questionnaire score using correlation coefficients. Internal consistency was measured using Cronbach's alpha. The test - retest reliability was evaluated using the intraclass correlation coefficient(1,1). The Bland - Altman analysis was performed to detect the limits of agreement.

RESULTS

The mean Freezing of Gait Questionnaire score was 9.1 (5.0) points. Convergent validity was 0.655 and content validity index was 0.958. Cronbach's alpha was 0.958, intraclass correlation coefficient(1,1) was 0.951, and the limits of agreement ranged from - 4.9 to3.2 points.

CONCLUSIONS

The Japanese version of the Freezing of Gait Questionnaire is a valid and useful tool to evaluate patients with Parkinson's disease.

A wearable sensor and machine learning estimate step length in older adults and patients with neurological disorders

Step length is an important diagnostic and prognostic measure of health and disease. Wearable devices can estimate step length continuously (e.g., in clinic or real-world settings), however, the accuracy of current estimation methods is not yet optimal. We developed machine-learning models to estimate step length based on data derived from a single lower-back inertial measurement unit worn by 472 young and older adults with different neurological conditions, including Parkinson's disease and healthy controls. Studying more than 80,000 steps, the best model showed high accuracy for a single step (root mean square error, RMSE = 6.08 cm, ICC(2,1) = 0.89) and higher accuracy when averaged over ten consecutive steps (RMSE = 4.79 cm, ICC(2,1) = 0.93), successfully reaching the predefined goal of an RMSE below 5 cm (often considered the minimal-clinically-important-difference). Combining machine-learning with a single, wearable sensor generates accurate step length measures, even in patients with neurologic disease. Additional research may be needed to further reduce the errors in certain conditions.