Gait impairments in Parkinson's disease

Effects of Repetitive Transcranial Magnetic Stimulation on Motor Symptoms in Parkinson's Disease: A Meta-Analysis

BACKGROUND

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique that has been closely examined as a possible treatment for Parkinson's disease (PD). Owing to various rTMS protocols and results, the optimal mode and suitable PD symptoms have yet to be established.

OBJECTIVES

This study intends to systematically evaluate the efficacy of rTMS intervention and identify optimal stimulation protocol of rTMS for specific motor symptoms.

METHODS

PubMed and web of Science databases were searched before January 2022. Eligible studies included sham-controlled and randomized clinical trials of rTMS intervention for motor dysfunction in patients with PD. Standard mean difference (SMD) was calculated with random-effects models. The effects of rTMS on motor symptoms were mainly estimated by the UPDRS-III.

RESULTS

A total of 1172 articles were identified, of which 32 articles met the inclusion criteria for meta-analysis. The pooled evidence suggested that rTMS relieves motor symptoms of patients with PD (SMD 0.64, 95%CI [0.47, 0.80]). High frequency stimulation on M1 is the most effective mode of intervention (SMD 0.79, 95%CI [0.52, 1.07]). HF rTMS has significant therapeutic effects on limbs motor function (SMD 1.93, 95%CI [0.73, 3.12] for upper limb function and SMD 0.88, 95%CI [0.43, 1.33] for lower limb function), akinesia (SMD 1.17, 95%CI [0.43, 1.92), rigidity (SMD 1.02, 95%CI [0.12, 1.92]) and tremor(SMD 0.91, 95%CI [0.15, 1.67]).

CONCLUSION

rTMS therapy is an effective treatment for motor symptoms of PD and the individualized stimulation protocols for different symptoms would further improve its clinical efficacy.

Fall risk in older adults mediates the association between depression, executive dysfunction and daily life

Introduction

The present study aimed to identify signs of frequent fall-related body dysfunction (depression/cognition) as exhibited in daily activities among older adults. The role of fall risk in mediating body dysfunction and daily activities was also explored.

Method

Participants included 123 non-institutionalised older adults. Depression and cognitive status were measured by the Geriatric Depression Scale (GDS-15) and the Montreal Cognitive Assessment (MoCA). Fall risk was determined by a questionnaire, supported by the Time Up and Go test (TUG). Executive functions (EF) were assessed by the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) and the Alternate Executive Function Performance Test medication management performance-based assessment. Daily life measures included the Barthel and Instrumental scale of activities of daily living, and World Health Organization Quality of Life questionnaire.

Results

Based on a falls risk score, 39 out of 123 participants (32%) were high-risk fallers. High-risk fallers showed greater body dysfunction, as recognised in daily activities. Structural equation modelling (SEM) revealed that fall risk mediated the associations among depression, executive dysfunction and daily activities.

Conclusion

Emotional and cognitive dysfunctions that affect people with high fall risk may manifest while older people perform daily activities. Community fall prevention programmes should screen for such fall-related dysfunction and provide strategies to minimise falls and enhance daily function.

The Efficacy of a Newly Developed Cueing Device for Gait Mobility in Parkinson’s Disease

Background. External cues are effective in improving gait in people with Parkinson’s disease (PD). However, the most effective cueing method has yet to be determined. Objective. The aim of this study was to compare the immediate effects of using visual, auditory, or somatosensory cues on their own or in combination during walking compared to no cues in people with PD. Methods. This was a single blinded, randomly selected, controlled study. Twenty people with PD with an age range of 46–79 years and Hoehn and Yahr scores of 1–3 were recruited. Participants were studied under 4 cueing conditions; no cue, visual, auditory, or somatosensory cues, which were randomly selected individually or in a combination. Results. A repeated measures ANOVA with pairwise comparisons using Bonferroni correction showed that any single or combination of the cues resulted in an improvement in gait velocity and stride length compared to no cue. Some significant differences were also seen when comparing different combinations of cues, specifically stride length showed significant improvements when additional cues were added to the light cue. The statistically significant difference was set at $p<0.05$ . Conclusions. Walking using visual, auditory, or somatosensory cues can immediately improve gait mobility in people with PD. Any or a combination of the cues tested could be chosen depending on the ability of the individual to use that cue.

Machine Learning Approach to Support the Detection of Parkinson's Disease in IMU-Based Gait Analysis

The aim of this study was to determine which supervised machine learning (ML) algorithm can most accurately classify people with Parkinson’s disease (pwPD) from speed-matched healthy subjects (HS) based on a selected minimum set of IMU-derived gait features. Twenty-two gait features were extrapolated from the trunk acceleration patterns of 81 pwPD and 80 HS, including spatiotemporal, pelvic kinematics, and acceleration-derived gait stability indexes. After a three-level feature selection procedure, seven gait features were considered for implementing five ML algorithms: support vector machine (SVM), artificial neural network, decision trees (DT), random forest (RF), and K-nearest neighbors. Accuracy, precision, recall, and F1 score were calculated. SVM, DT, and RF showed the best classification performances, with prediction accuracy higher than 80% on the test set. The conceptual model of approaching ML that we proposed could reduce the risk of overrepresenting multicollinear gait features in the model, reducing the risk of overfitting in the test performances while fostering the explainability of the results.

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

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

Foot Trajectory Features in Gait of Parkinson’s Disease Patients

Parkinson’s disease (PD) is a progressive neurological disorder characterized by movement disorders, such as gait instability. This study investigated whether certain spatial features of foot trajectory are characteristic of patients with PD. The foot trajectory of patients with mild and advanced PD in on-state and healthy older and young individuals was estimated from acceleration and angular velocity measured by inertial measurement units placed on the subject’s shanks, just above the ankles. We selected six spatial variables in the foot trajectory: forward and vertical displacements from heel strike to toe-off, maximum clearance, and change in supporting leg (F1 to F3 and V1 to V3, respectively). Healthy young individuals had the greatest F2 and F3 values, followed by healthy older individuals, and then mild PD patients. Conversely, the vertical displacements of mild PD patients were larger than the healthy older individuals. Still, those of healthy older individuals were smaller than the healthy young individuals except for V3. All six displacements of the advanced PD patients were smaller than the mild PD patients. To investigate features in foot trajectories in detail, a principal components analysis and soft-margin kernel support vector machine was used in machine learning. The accuracy in distinguishing between mild PD patients and healthy older individuals and between mild and advanced PD patients was 96.3 and 84.2%, respectively. The vertical and forward displacements in the foot trajectory was the main contributor. These results reveal that large vertical displacements and small forward ones characterize mild and advanced PD patients, respectively.

Sensor-based gait analysis in the premotor stage of LRRK2 G2019S-associated Parkinson's disease

INTRODUCTION

There is a need for biomarkers to monitor the earliest phases of Parkinson's disease (PD), especially in premotor stages. Here, we studied whether there are early gait alterations in carriers of the G2019S mutation of LRRK2 that can be detected by means of an inertial sensor system.

METHODS

Twenty-one idiopathic PD patients, 20 LRRK2-G2019S PD, 27 asymptomatic carriers of LRRK2-G2019S mutation (AsG2019S) and 36 controls walked equipped with 16 lightweight inertial sensors in three different experiments: i/normal gait, ii/fast gait and iii/dual-task gait. In the AsG2019S group, DaT-SPECT (¹²³I-ioflupane) with semi-quantitative analysis was carried out. Motor and cognitive performance were evaluated using MDS-UPDRS-III and MoCA scales. We employed neural network techniques to classify individuals based on their walking patterns.

RESULTS

PD patients and controls showed differences in speed, stride length and arm swing amplitude, variability and asymmetry in all three tasks (p < 0.01). In the AsG2019S group, the only differences were detected during fast walking, with greater step time on the non-dominant side (p < 0.05), lower step/stride time variability (p < 0.01) and lower step time asymmetry (p < 0.01). DaT uptake showed a significant correlation with step time during fast walking on the non-dominant side (r = -0.52; p < 0.01). The neural network was able to differentiate between AsG2019S and healthy controls with an accuracy rate of 82.5%.

CONCLUSION

Our sensor-based analysis did not detect substantial and robust changes in the gait of LRRK2-G2019S asymptomatic mutation carriers. Nonetheless, step or stride time during fast walking, supported by the observed correlation with striatal DaT binding deserves consideration as a potential biomarker in future studies.

Progressive Worsening of Gait and Motor Abnormalities in Older Adults With Dravet Syndrome

BACKGROUND AND OBJECTIVES

Relative to the pediatric population, there is very limited information about Dravet Syndrome (DS) in adults. In addition to some of the gait abnormalities reported in children with DS (such as crouch gait and ataxia), adults with this condition have other gait and motor disturbances. Our primary objective was to examine gait and motor manifestations in older adults with DS.

METHODS

This study has a prospective arm where 6 patients (mean age 32-years-old) were examined through a modified version of the Unified Parkinson's Disease Rating Scale (mUPDRS) in 2014 and again in 2019. mUPDRS scores were assigned to gait, resting tremors, facial expression, arising from a chair, posture, and body bradykinesia. The cross-sectional arm includes mUPDRS testing in patients that were not evaluated in 2014, and an instrumental gait analysis (IGA). These cross-sectional tests were done in the 2019-2020 period. The IGA was performed using the ProtoKinetics software with a gait mat built with sensors and two cameras capturing the sagittal and coronal planes. The IGA was performed in a group of 17 patients with DS (mean age: 31-years-old), the control group consisted of 81 healthy individuals, whose mean age was 62-years-old. Regression analyses were performed for the IGA and mUPDRS data.

RESULTS

Five out of six participants evaluated prospectively over 5 years experienced worsening of their parkinsonian manifestations, including gait. Two patients (47 and 51 years old) who were initially ambulatory, could no longer walk 5 years later. The cross-sectional analysis of mUPDRS in a larger group of adults showed that worse scores for arising from a chair (p= 0.04), body bradykinesia (p= 0.01), and gait (p= 0.0003) were positively associated with age. The IGA cross-sectional arm revealed that all 17 adults with DS had abnormal gait parameters in all domains tested. This group of patients performed worse than the healthy and older control group.

DISCUSSION

Although seizures may decrease in older adults with DS, this prospective and cross-sectional study showed that their motor symptoms and gait become progressively worse as they age.

Similarities, differences and overlaps between frailty and Parkinson's disease

Parkinson's disease is a neurodegenerative disorder clinically characterized by bradykinesia, rest tremor, rigidity, and postural and gait disturbances, which are frequently observed in older people. It also shows non-motor symptoms, such as depression, anxiety, cognitive impairment and dementia. The number of patients is gradually increasing worldwide. Aging is a risk factor for the onset of Parkinson's disease, and various physiological effects of aging influence its progression. Frailty is a geriatric syndrome in which the reversible and vulnerable status between robustness and disability is affected by various physiological stressors with aging. Frailty consists of physical, psychological and social aspects. Furthermore, sarcopenia, a syndrome characterized by the loss of muscle mass, strength and function, is also significantly associated with frailty. To maintain the quality of life of older people, frailty, including sarcopenia, should be quickly and appropriately managed. Polypharmacy is an important factor causing the progression of frailty in geriatric syndrome. Although Parkinson's disease and frailty have similar symptoms, and are considered to affect each other, the clinical features and mechanisms of both largely remain unclear. Nevertheless, little literature on the relationship between frailty and Parkinson's disease is currently available. This narrative review aims to clarify the relationships between Parkinson's disease and frailty, not only on the physical, but also on the mental, cognitive, and social aspects and issues regarding polypharmacy in Parkinson's disease explored by previous studies. Geriatr Gerontol Int 2022; 22: 259-270.

Association between irritable bowel syndrome and Parkinson's disease: A systematic review and meta-analysis

BACKGROUND

Growing evidence suggests that irritable bowel syndrome (IBS) and Parkinson's disease (PD) share similar pathological mechanisms and risk factors.

METHODS

We performed a systematic review and meta-analysis of the evidence for a relationship between IBS and PD. Risk estimates from individual studies were pooled using random-effects models.

RESULTS

Six articles involving 58,645 patients with PD were included in our meta-analysis. The overall risk for PD in IBS patients was significantly higher than that in the general population (odds ratio [OR], 1.5; 95% confidence interval [CI], 1.29-1.75; p < .001). Subgroup analysis revealed no significant differences in risk between men (OR = 1.47, 95% CI: 1.3-1.67; p < .001) and women (OR = 1.51, 95% CI: 1.29-1.75; p < .001); however, older (≥65 years) IBS patients (OR = 1.44, 95% CI: 1.3-1.59; p < .001) may be at higher risk for PD than younger (40-64 years) patients (OR = 1.32, 95% CI: 1.05-1.64; p = .017).

CONCLUSION

Overall, the PD risk was higher in IBS patients than others, indicating that the intestinal disorder may serve as a warning sign for PD.

Events Detection of Anticipatory Postural Adjustments through a Wearable Accelerometer Sensor Is Comparable to That Measured by the Force Platform in Subjects with Parkinson's Disease

Out-of-the-lab instrumented gait testing focuses on steady-state gait and usually does not include gait initiation (GI) measures. GI involves Anticipatory Postural Adjustments (APAs), which propel the center of mass (COM) forward and laterally before the first step. These movements are impaired in persons with Parkinson’s disease (PD), contributing to their pathological gait. The use of a simple GI testing system, outside the lab, would allow improving gait rehabilitation of PD patients. Here, we evaluated the metrological quality of using a single inertial measurement unit for APA detection as compared with the use of a gold-standard system, i.e., the force platforms. Twenty-five PD and eight elderly subjects (ELD) were asked to initiate gait in response to auditory stimuli while wearing an IMU on the trunk. Temporal parameters (APA-Onset, Time-to-Toe-Off, Time-to-Heel-Strike, APA-Duration, Swing-Duration) extracted from the accelerometric data and force platforms were significantly correlated (mean(SD), r: 0.99(0.01), slope: 0.97(0.02)) showing a good level of agreement (LOA [s]: 0.04(0.01), CV [%]: 2.9(1.7)). PD showed longer APA-Duration compared to ELD ([s] 0.81(0.17) vs. 0.59(0.09) p < 0.01). APA parameters showed moderate correlation with the MDS-UPDRS Rigidity, Characterizing-FOG questionnaire and FAB-2 planning. The single IMU-based reconstruction algorithm was effective in measuring APAs timings in PD. The current work sets the stage for future developments of tele-rehabilitation and home-based exercises.

Analysis of efficacy and safety of linezolid-based chemotherapeutic regimens for postoperative multidrug-resistant spinal tuberculosis patients

OBJECTIVES

The study aimed to explore the efficacy and safety of linezolid-based chemotherapeutic regimens for postoperative multidrug-resistant spinal tuberculosis patients.

METHODS

The randomized controlled study included 50 Mycobacterium tuberculosis culture or pathological confirmed multidrug resistant tuberculosis patients who received spinal surgery from January 2018 to February 2020. Twenty-five patients were assigned to the control group and the study group, respectively. Random number method was used for patients allocation and they were treated with levofloxacin, pyrazinamide, thiisonicotinamide enteric-coated tablet, amikacin sulfate injection, and sodium p-amino salicylate injection, accompanied linezolid or not.

RESULTS

The overall effective rate of the study group was higher than that of the control group (88.00% vs. 64.00%, P<0.05). The severity of pain at 3 and 6 months postoperatively was lower in the study group than that the control group (P<0.05). Postoperatively, the study group had higher bone graft fusion rate, shorter mean bone graft fusion time and higher paraspinal cyst absorption rate than the control group (P<0.05). Postoperatively, the study group had lower levels of PCT, ESR and CRP than the control group (P<0.05). All patients had normal hepatic and renal function, and no statistical difference of adverse effects between 2 groups were found.

CONCLUSIONS

Linezolid-based chemotherapeutic regimens can effectively treat postoperative multidrug-resistant spinal tuberculosis patients, but have higher rates of adverse reactions.

Proof of Concept in Artificial-Intelligence-Based Wearable Gait Monitoring for Parkinson's Disease Management Optimization

Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder, affecting 6.2 million patients and causing disability and decreased quality of life. The research is oriented nowadays toward artificial intelligence (AI)-based wearables for early diagnosis and long-term PD monitoring. Our primary objective is the monitoring and assessment of gait in PD patients. We propose a wearable physiograph for qualitative and quantitative gait assessment, which performs bilateral tracking of the foot biomechanics and unilateral tracking of arm balance. Gait patterns are assessed by means of correlation. The surface plot of a correlation coefficient matrix, generated from the recorded signals, is classified using convolutional neural networks into physiological or PD-specific gait. The novelty is given by the proposed AI-based decisional support procedure for gait assessment. A proof of concept of the proposed physiograph is validated in a clinical environment on five patients and five healthy controls, proving to be a feasible solution for ubiquitous gait monitoring and assessment in PD. PD management demonstrates the complexity of the human body. A platform empowering multidisciplinary, AI-evidence-based decision support assessments for optimal dosing between drug and non-drug therapy could lay the foundation for affordable precision medicine.

Fear of Falling Does Not Influence Dual-Task Gait Costs in People with Parkinson's Disease: A Cross-Sectional Study

Cognitive deficits and fear of falling (FOF) can both influence gait patterns in Parkinson’s disease (PD). While cognitive deficits contribute to gait changes under dual-task (DT) conditions, it is unclear if FOF also influences changes to gait while performing a cognitive task. Here, we aimed to explore the association between FOF and DT costs in PD, we additionally describe associations between FOF, cognition, and gait parameters under single-task and DT. In 40 PD patients, motor symptoms (MDS-revised version of the Unified Parkinson’s Disease Rating Scale, Hoehn and Yahr), FOF (Falls Efficacy Scale International), and Montreal Cognitive Assessment (MoCA) were assessed. Spatiotemporal gait parameters were recorded with a validated mobile gait analysis system with inertial measurement units at each foot while patients walked in a 50 m hallway at their preferred speed under single-task and DT conditions. Under single-task conditions, stride length (β = 0.798) and spatial variability (β = 0.202) were associated with FOF (adjusted R2 = 0.19, p < 0.001) while the MoCA was only weakly associated with temporal variability (adjusted R2 = 0.05, p < 0.001). Under DT conditions, speed, stride length, and cadence decreased, while spatial variability, temporal variability, and stride duration increased with the largest effect size for speed. DT costs of stride length (β = 0.42) and age (β = 0.58) explained 18% of the MoCA variance. However, FOF was not associated with the DT costs of gait parameters. Gait difficulties in PD may exacerbate when cognitive tasks are added during walking. However, FOF does not appear to have a relevant effect on dual-task costs of gait.

Disparities in depression among Chinese older adults with neurodegenerative diseases

OBJECTIVES

Neurodegenerative diseases (NDs), such as Parkinson's disease and Alzheimer's disease and related dementias, are a leading cause of death and disability in China. Although studies have demonstrated that depression is associated with NDs, little is known about the factors impacting this relationship. This study aimed to explore and identify the risk and protective factors of depression among Chinese older adults with NDs.

METHODS

Data selection was based on the behavioral model of late-life depression. Data from the latest wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS, 1998-2014) in 2014 were analyzed. Among the sample, 334 older adults aged 65 and older with NDs were included in the analysis. A logistic regression analysis was conducted by SPSS 24.0.

RESULTS

Participants who lived in urban areas (O.R.= 2.494, p< .05) or needed more support for Activity of Daily Living (O.R.= 1.136, p< .05) were more likely to have depression. Participants who lived with household members (O.R.= .380, p< .05), self-reported their health status as fair (O.R.= .250, p< .01), or believed their health status remained the same (O.R.= .331, p< .01) were less likely to have depression.

CONCLUSION

Our findings suggest that policymakers and healthcare professionals should pay specific attention to the regional disparities of healthcare services and the cultural background to understand the relationship between NDs and depression and improve the well-being of ND patients.

A multimodal Parkinson quantification by fusing eye and gait motion patterns, using covariance descriptors, from non-invasive computer vision

BACKGROUND AND OBJECTIVE

Parkinson's disease (PD) is a motor neurodegenerative disease principally manifested by motor disabilities, such as postural instability, bradykinesia, tremor, and stiffness. In clinical practice, there exist several diagnostic rating scales that coarsely allow the measurement, characterization and classification of disease progression. These scales, however, are only based on strong changes in kinematic patterns, and the classification remains subjective, depending on the expertise of physicians. In addition, even for experts, disease analysis based on independent classical motor patterns lacks sufficient sensitivity to establish disease progression. Consequently, the disease diagnosis, stage, and progression could be affected by misinterpretations that lead to incorrect or inefficient treatment plans. This work introduces a multimodal non-invasive strategy based on video descriptors that integrate patterns from gait and eye fixation modalities to assist PD quantification and to support the diagnosis and follow-up of the patient. The multimodal representation is achieved from a compact covariance descriptor that characterizes postural and time changes of both information sources to improve disease classification.

METHODS

A multimodal approach is introduced as a computational method to capture movement abnormalities associated with PD. Two modalities (gait and eye fixation) are recorded in markerless video sequences. Then, each modality sequence is represented, at each frame, by primitive features composed of (1) kinematic measures extracted from a dense optical flow, and (2) deep features extracted from a convolutional network. The spatial distributions of these characteristics are compactly coded in covariance matrices, making it possible to map each particular dynamic in a Riemannian manifold. The temporal mean covariance is then computed and submitted to a supervised Random Forest algorithm to obtain a disease prediction for a particular patient. The fusion of the covariance descriptors and eye movements integrating deep and kinematic features is evaluated to assess their contribution to disease quantification and prediction. In particular, in this study, the gait quantification is associated with typical patterns observed by the specialist, while ocular fixation, associated with early disease characterization, complements the analysis.

RESULTS

In a study conducted with 13 control subjects and 13 PD patients, the fusion of gait and ocular fixation, integrating deep and kinematic features, achieved an average accuracy of 100% for early and late fusion. The classification probabilities show high confidence in the prediction diagnosis, the control subjects probabilities being lower than 0.27 with early fusion and 0.3 with late fusion, and those of the PD patients, being higher than 0.62 with early fusion and 0.51 with late fusion. Furthermore, it is observed that higher probability outputs are correlated with more advanced stages of the disease, according to the H&Y scale.

CONCLUSIONS

A novel approach for fusing motion modalities captured in markerless video sequences was introduced. This multimodal integration had a remarkable discrimination performance in a study conducted with PD and control patients. The representation of compact covariance descriptors from kinematic and deep features suggests that the proposed strategy is a potential tool to support diagnosis and subsequent monitoring of the disease. During fusion it was observed that devoting major attention to eye fixational patterns may contribute to a better quantification of the disease, especially at stage 2.

The Diverse Gait Dataset: Gait Segmentation Using Inertial Sensors for Pedestrian Localization with Different Genders, Heights and Walking Speeds

Stride length estimation is one of the most crucial aspects of Pedestrian Dead Reckoning (PDR). Due to the measurement noise of inertial sensors, individual variances of pedestrians, and the uncertainty in pedestrians walking, there is a substantial error in the assessment of stride length, which causes the accumulated deviation of Pedestrian Dead Reckoning (PDR). With the help of multi-gait analysis, which decomposes strides in time and space with greater detail and accuracy, a novel and revolutionary stride estimating model or scheme could improve the performance of PDR on different users. This paper presents a diverse stride gait dataset by using inertial sensors that collect foot movement data from people of different genders, heights, and walking speeds. The dataset contains 4690 walking strides data and 19,083 gait labels. Based on the dataset, we propose a threshold-independent stride segmentation algorithm called SDATW and achieve an F-measure of 0.835. We also provide the detailed results of recognizing four gaits under different walking speeds, demonstrating the utility of our dataset for helping train stride segmentation algorithms and gait detection algorithms.

Rodent models for gait network disorders in Parkinson's disease - a translational perspective

Gait impairments in Parkinson's disease remain a scientific and therapeutic challenge. The advent of new deep brain stimulation (DBS) devices capable of recording brain activity from chronically implanted electrodes has fostered new studies of gait in freely moving patients. The hope is to identify gait-related neural biomarkers and improve therapy using closed-loop DBS. In this context, animal models offer the opportunity to investigate gait network activity at multiple biological scales and address unresolved questions from clinical research. Yet, the contribution of rodent models to the development of future neuromodulation therapies will rely on translational validity. In this review, we summarize the most effective strategies to model parkinsonian gait in rodents. We discuss how clinical observations have inspired targeted brain lesions in animal models, and whether resulting motor deficits and network oscillations match recent findings in humans. Gait impairments with hypo-, bradykinesia and altered limb rhythmicity were successfully modelled in rodents. However, clear evidence for the presence of freezing of gait was missing. The identification of reliable neural biomarkers for gait impairments has remained challenging in both animals and humans. Moving forward, we expect that the ongoing investigation of circuit specific neuromodulation strategies in animal models will lead to future optimizations of gait therapy in Parkinson's disease.

A Systematic Review of Non-Pharmacological Interventions to Improve Gait Asymmetries in Neurological Populations

Gait asymmetries are commonly observed in neurological populations and linked to decreased gait velocity, balance decrements, increased fall risk, and heightened metabolic cost. Interventions designed to improve gait asymmetries have varying methods and results. The purpose of this systematic review was to investigate non-pharmacological interventions to improve gait asymmetries in neurological populations. Keyword searches were conducted using PubMed, CINAHL, and Academic Search Complete. The search yielded 14 studies for inclusion. Gait was assessed using 3D motion capture systems (n = 7), pressure-sensitive mats (e.g., GAITRite; n = 5), and positional sensors (n = 2). The gait variables most commonly analyzed for asymmetry were step length (n = 11), stance time (n = 9), and swing time (n = 5). Interventions to improve gait asymmetries predominantly used gait training techniques via a split-belt treadmill (n = 6), followed by insoles/orthoses (n = 3). The literature suggests that a wide range of methods can be used to improve spatiotemporal asymmetries. However, future research should further examine kinematic and kinetic gait asymmetries. Additionally, researchers should explore the necessary frequency and duration of various intervention strategies to achieve the greatest improvement in gait asymmetries, and to determine the best symmetry equation for quantifying gait asymmetries.

Factors Influencing Habitual Physical Activity in Parkinson’s Disease: Considering the Psychosocial State and Wellbeing of People with Parkinson’s and Their Carers

Participating in habitual physical activity (HPA) may slow onset of dependency and disability for people with Parkinson’s disease (PwP). While cognitive and physical determinants of HPA are well understood, psychosocial influences are not. This pilot study aimed to identify psychosocial factors associated with HPA to guide future intervention development. Sixty-four PwP participated in this study; forty had carer informants. PwP participants wore a tri-axial accelerometer on the lower back continuously for seven days at two timepoints (18 months apart), measuring volume, pattern and variability of HPA. Linear mixed effects analysis identified relationships between demographic, clinical and psychosocial data and HPA from baseline to 18 months. Key results in PwP with carers indicated that carer anxiety and depression were associated with increased HPA volume (p < 0.01), while poorer carer self-care was associated with reduced volume of HPA over 18 months (p < 0.01). Greater carer strain was associated with taking longer walking bouts after 18 months (p < 0.01). Greater carer depression was associated with lower variability of HPA cross-sectionally (p = 0.009). This pilot study provides preliminary novel evidence that psychosocial outcomes from PwP’s carers may impact HPA in Parkinson’s disease. Interventions to improve HPA could target both PwP and carers and consider approaches that also support psychosocial wellbeing.

Cortical correlates of gait compensation strategies in Parkinson's disease

Objective

Gait impairment in persons with Parkinson disease is common and debilitating. Compensation strategies (eg, external cues) are an essential part of rehabilitation, but their underlying mechanisms remain unclear. Using electroencephalography (EEG), we explored the cortical correlates of 3 categories of strategies: external cueing, internal cueing, and action observation.

Methods

Eighteen participants with Parkinson disease and gait impairment were included. We recorded 126‐channel EEG during both stance and gait on a treadmill under 4 conditions: (1) uncued, (2) external cueing (listening to a metronome), (3) internal cueing (silent rhythmic counting), and (4) action observation (observing another person walking). To control for the effects of sensory processing of the cues, we computed relative power changes as the difference in power spectral density between walking and standing for each condition.

Results

Relative to uncued gait, the use of all 3 compensation strategies induced a decrease of beta band activity in sensorimotor areas, indicative of increased cortical activation. Parieto‐occipital alpha band activity decreased with external and internal cueing, and increased with action observation. Only internal cueing induced a change in frontal cortical activation, showing a decrease of beta band activity compared to uncued gait.

Interpretation

The application of compensation strategies resulted in changed cortical activity compared to uncued gait, which could not be solely attributed to sensory processing of the cueing modality. Our findings suggest there are multiple routes to control gait, and different compensation strategies seem to rely on different cortical mechanisms to achieve enhanced central motor activation in persons with Parkinson disease. ANN NEUROL 2022;91:329–341

Force Platform-Based Intervention Program for Individuals Suffering with Neurodegenerative Diseases like Parkinson

The term "neurodegenerative disease" refers to a set of illnesses that primarily affect brain's neurons. Substantia nigra (a midbrain dopaminergic nucleus) with lack of hormone called dopamine causes Parkinson's disease (PD), a neurological disorder. PD leads to tremor, stiffness, impaired posture and balance, and loss of automatic movements. Patient with Parkinson's often develops a parkinsonian gait that includes a tendency to lean forward, small quick steps as if hurrying forward, and reduced swinging of the arms. They also may have trouble initiating or continuing movement. Gait analysis is often used to diagnose neurodegenerative illnesses and determine their stage. In this study, we attempt to investigate postural balance, and of gait signals for Parkinson's patients, also, we incorporate interim rehabilitation technique. We included 25 PD patients who had 2.5 to 3 IV score of Hoehn and Yahr scale. A ten-minute walk test has been performed to observe primary and secondary results of dual task interference on gait velocities, and gait time motion vector for right and left legs was observed. Two experimental ground conditions include three conditions of trunk alignment, that is, erect on a regular basis (RE), trunk dorsiflexion 30° (TF1), and trunk dorsiflexion 50° (TF2) were analysed. We identified the walking speed of PD patients was decreased, and trunk dorsiflexion variables influence the gait pattern of Parkinson's disease patients, where higher 95% CI for TF1 condition was reported. The regular erect trunk showed swing time reduction (0.7%) in PD, so the higher unified PD rating scale (UPDRS) values have significant difference in swing phase time in Parkinson's patients. The average Hoehn and Yahr scale (H&Y scale) was 4.3 ± 2.5 reported in the study participants. In a 10-week follow-up evaluation, the stance duration was shown to be substantial, as was the slower speed gait in the baseline condition. Excessive flexion was discovered in our investigation at the lower limb joints, particularly the knee and ankle. Patients with Parkinson's disease had similar maximum dorsiflexion and minimum plantarflexion values in stance. The trunk fraction conditions were found significant in patients after rehabilitation training. The best response to rehabilitation treatment was seen when the trunk was rotated. When steps and posture distribution analysis performed, we found that the trunk flexure 1 (p < 0.05), and trunk flexure 2 (p < 0.01) were shown significant values. When GRF threshold characteristics are employed, mean accuracy improves by 52%. Regardless of gait posture, the step regular trunk flexure had significantly higher posture than the corresponding level steps, with a considerable rise in the 50 in trunk dorsiflexion 2 gait relative to the step "L." This study shows that there was some significant improvement observed in the gait parameters among patients with PD's which shows positive impact of the intervention. Furthermore, rehabilitation programmes can aid and improve poor gait features in patients with Parkinson's disease, especially those who are in the early stages of the condition. This gait and balance research provides a rationale for intervention treatments, and their use in clinical practise enhances evidence of therapeutic efficacy. However, prolonged follow-up is needed to determine whether the advantages will remain all across disease's course, and future studies may recommend a specific rehabilitation technique based on gait analysis results.

Kinematic Analysis of 360° Turning in Stroke Survivors Using Wearable Motion Sensors

Background: A stroke often bequeaths surviving patients with impaired neuromusculoskeletal systems subjecting them to increased risk of injury (e.g., due to falls) even during activities of daily living. The risk of injuries to such individuals can be related to alterations in their movement. Using inertial sensors to record the digital biomarkers during turning could reveal the relevant turning alterations. Objectives: In this study, movement alterations in stroke survivors (SS) were studied and compared to healthy individuals (HI) in the entire turning task due to its requirement of synergistic application of multiple bodily systems. Methods: The motion of 28 participants (14 SS, 14 HI) during turning was captured using a set of four Inertial Measurement Units, placed on their sternum, sacrum, and both shanks. The motion signals were segmented using the temporal and spatial segmentation of the data from the leading and trailing shanks. Several kinematic parameters, including the range of motion and angular velocity of the four body segments, turning time, the number of cycles involved in the turning task, and portion of the stance phase while turning, were extracted for each participant. Results: The results of temporal processing of the data and comparison between the SS and HI showed that SS had more cycles involved in turning, turn duration, stance phase, range of motion in flexion–extension, and lateral bending for sternum and sacrum (p-value < 0.035). However, HI exhibited larger angular velocity in flexion–extension for all four segments. The results of the spatial processing, in agreement with the prior method, showed no difference between the range of motion in flexion–extension of both shanks (p-value > 0.08). However, it revealed that the angular velocity of the shanks of leading and trailing legs in the direction of turn was more extensive in the HI (p-value < 0.01). Conclusions: The changes in upper/lower body segments of SS could be adequately identified and quantified by IMU sensors. The identified kinematic changes in SS, such as the lower flexion–extension angular velocity of the four body segments and larger lateral bending range of motion in sternum and sacrum compared to HI in turning, could be due to the lack of proper core stability and effect of turning on vestibular system of the participants. This research could facilitate the development of a targeted and efficient rehabilitation program focusing on the affected aspects of turning movement for the stroke community.

A Practical Guide to the Evaluation of Compensation Strategies for Gait Impairment in Parkinson's Disease

The application of compensation strategies is an important element of gait rehabilitation in persons with Parkinson's disease. While the efficacy of these strategies is generally very high, a tailored, personalized approach is necessary to determine the optimal strategies for every patient. We propose a straightforward, practical guide to the evaluation of compensation strategies in clinical practice: considering the primary gait target(s) to optimize functional mobility, the context in which the strategies will be employed in daily life, and patient-specific personal preferences. Furthermore, we introduce www.walkingwithparkinson.com as a resource on the available compensation strategies, developed specifically for persons with Parkinson's disease, their carers, and (allied) healthcare professionals.

Perceived exercise habits of individuals with Parkinson’s disease living in the community

Context

Exercise has been shown to improve gait in individuals with Parkinson’s disease (PD). Stepping practice at higher intensity levels has been suggested as a beneficial treatment option to improve gait in the neurological population. Unfortunately, this mode is poorly understood and underutilized within the PD population. Information on what individuals with PD are doing for exercise would be beneficial to help tailor exercise programs to improve gait and provide exercise options in the community for intensity-based exercise.

Objective

To investigate the current exercise habits of individuals living with PD in the community aimed at improving walking and to understand the impact of perceived intensity on daily exercise practices.

Design, setting, participants

One hundred thirty-eight individuals with PD living in the community were surveyed online regarding their current exercise habits.

Main outcome measure

A total of 22 questions aimed to understand exercise selection, focus, and perceived intensity. Questions asked basic demographic, symptom presentation and management of disease related symptoms that were present while living with PD. Exercise questions focused understanding participants current function level, practice exercise habits and perceived levels of exercise intensity during daily routines.

Results

Of the 138 individuals surveyed for this preliminary study, eighty-seven percent of individuals with PD participated in exercise with seventy-five percent choosing walking as a mode for exercise. Sixty-five percent of the respondents noted that despite exercise, their walking speed and endurance has worsened since diagnosis. Eighty-one percent perceived exercising at moderate intensity levels, however little provocation of intensity symptoms was noted.

Conclusion

Our preliminary study survey results suggest that individuals with PD are exercising but not at high enough intensity levels to promote improvements in gait performance. Individuals with PD may need to be pushed at higher intensity levels, beyond their voluntary limits, to induce gait performance changes. These findings can provide a foundation for future fitness interventions within this population to target improving gait.

Imaging the neural underpinnings of freezing of gait in Parkinson’s disease

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Review of recent (after 2012) imaging studies on Parkinsonian freezing of gait.

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Virtual reality studies report functional decoupling of cortico-striatal circuits.

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Motor imagery studies reveal increased recruitment of parieto-occipital regions.

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fNIRS studies converge on reporting higher activity within prefrontal regions.

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Imaging findings support pathophysiological models of freezing of gait.

Freezing of gait (FoG) is a paroxysmal and sporadic gait impairment that severely affects PD patients’ quality of life. This review summarizes current neuroimaging investigations that characterize the neural underpinnings of FoG in PD. The review presents and discusses the latest advances across multiple methodological domains that shed light on structural correlates, connectivity changes, and activation patterns associated with the different pathophysiological models of FoG in PD. Resting-state fMRI studies mainly report cortico-striatal decoupling and disruptions in connectivity along the dorsal stream of visuomotor processing, thus supporting the ‘interference’ and the ‘perceptual dysfunction’ models of FoG. Task-based MRI studies employing virtual reality and motor imagery paradigms reveal a disruption in functional connectivity between cortical and subcortical regions and an increased recruitment of parieto-occipital regions, thus corroborating the ‘interference’ and ‘perceptual dysfunction’ models of FoG. The main findings of fNIRS studies of actual gait primarily reveal increased recruitment of frontal areas during gait, supporting the ‘executive dysfunction’ model of FoG. Finally, we discuss how identifying the neural substrates of FoG may open new avenues to develop efficient treatment strategies.

Relationship Between Brain Volumes and Objective Balance and Gait Measures in Parkinson's Disease

BACKGROUND

Instrumented measures of balance and gait measure more specific balance and gait impairments than clinical rating scales. No prior studies have used objective balance/gait measures to examine associations with ventricular and brain volumes in people with Parkinson's disease (PD).

OBJECTIVE

To test the hypothesis that larger ventricular and smaller cortical and subcortical volumes are associated with impaired balance and gait in people with PD.

METHODS

Regional volumes from structural brain images were included from 96 PD and 50 control subjects. Wearable inertial sensors quantified gait, anticipatory postural adjustments prior to step initiation (APAs), postural responses to a manual push, and standing postural sway on a foam surface. Multiple linear regression models assessed the relationship between brain volumes and balance/gait and their interactions in PD and controls, controlling for sex, age and corrected for multiple comparisons.

RESULTS

Smaller brainstem and subcortical gray matter volumes were associated with larger sway area in people with PD, but not healthy controls. In contrast, larger ventricle volume was associated with smaller APAs in healthy controls, but not in people with PD. A sub-analysis in PD showed significant interactions between freezers and non-freezers, in several subcortical areas with stride time variability, gait speed and step initiation.

CONCLUSION

Our models indicate that smaller subcortical and brainstem volumes may be indicators of standing balance dysfunction in people with PD whereas enlarged ventricles may be related to step initiation difficulties in healthy aging. Also, multiple subcortical region atrophy may be associated with freezing of gait in PD.

An intensive exercise-based training program reduces prefrontal activity during usual walking in patients with Parkinson’s disease

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Patients with Parkinson’s disease have increased prefrontal activity during usual walking.

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After SIROCCO training, prefrontal activity decreased and gait performance improved in patients.

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An intensive exercise-based training program increased automaticity of gait in patients with PD.

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Findings highlight the potential of neuroplasticity in PD after exercise.

Introduction

Parkinson’s disease (PD) leads to a progressive loss of locomotor automaticity. Consequently, PD patients rely more on executive resources for the control of gait, resulting in increased prefrontal activity while walking. Exercise-based training programs may improve automaticity of walking and reduce prefrontal activity in this population. This study aimed to assess the effect of an intensive multidisciplinary exercise-based training program on prefrontal activity and gait performance during usual walking in PD patients.

Method

Fourteen patients (mean age: 67 ± 9; disease duration: 6 ± 5 years; Hoehn and Yahr score: 1.9 ± 0.6) were included in this study. They were assessed in ON stage at three different times at 5-week intervals: two times before the training program (T0 and T1) and once after the training program (T2). Gait performance (stride time, speed, stride length, cadence, and their respective coefficient of variation) and cortical activity in the dorsolateral prefrontal cortex (DLPFC) using functional near infrared spectroscopy (fNIRS) were measured during usual walking.

Results

Patients had reduced cortical activity of the DLPFC at T2 compared to T1 (p = 0.003). Patients had shorter stride time at T2 compared to T1 (p = 0.025) and tended to have longer stride length at T2 than at T1 (p = 0.056).

Conclusion

The training program led to positive effects on prefrontal activity and gait performance. Reduced prefrontal activity during usual walking after training program suggests that patients may have a greater reserve capacity to face more challenging walking conditions. Further studies will investigate the effect of this training on cortical activity during dual-task walking..

Surrogates for rigidity and PIGD MDS-UPDRS subscores using wearable sensors

BACKGROUND

Telemedicine has the advantage of expanding access to care for patients with Parkinson's Disease (PD). However, rigidity and postural instability in PD are difficult to measure remotely, and are important measures of functional impairment and fall risk.

RESEARCH QUESTION

Can measures from wearable sensors be used as future surrogates for the MDS-UPDRS rigidity and Postural Instability and Gait Difficulty (PIGD) subscores?

METHODS

Thirty-one individuals with mild to moderate PD wore 3 inertial sensors at home for one week to measure quantity and quality of gait and turning in daily life. Separately, we performed a clinical assessment and balance characterization of postural sway with the same wearable sensors in the laboratory (On medication). We then first performed a traditional correlation analysis between clinical scores and objective measures of gait and balance followed by multivariable linear regression employing a best subset selection strategy.

RESULTS

The number of walking bouts and turns correlated significantly with the rigidity subscore, while the number of turns, foot pitch angle, and sway area while standing correlated significantly with the PIGD subscore (p < 0.05). The multivariable linear regression showed that rigidity subscore was best predicted by the number of walking bouts while the PIGD subscore was best predicted by a combination of number of walking bouts, gait speed, and postural sway.

SIGNIFICANCE

The correlation between objective sensor data and MDS-UPDRS rigidity and PIGD scores paves the way for future larger studies that evaluate use of objective sensor data to supplement remote MDS-UPDRS assessment.

Gait Abnormalities in Parkinson's Disease Are Associated with Extracellular Free-Water Characteristics in the Substantia Nigra

BACKGROUND

Gait impairments are common in Parkinson's disease (PD). The pathological mechanisms are complex and not thoroughly elucidated, thus quantitative and objective parameters that closely relate to gait characteristics are critically needed to improve the diagnostic assessments and monitor disease progression. The substantia nigra is a relay structure within basal ganglia brainstem loops that is centrally involved in gait modulation.

OBJECTIVE

We tested the hypothesis that quantitative gait biomechanics are related to the microstructural integrity of the substantia nigra and PD-relevant gait abnormalities are independent from bradykinesia-linked speed reductions.

METHODS

Thirty-eight PD patients and 33 age-matched control participants walked on a treadmill at fixed speeds. Gait parameters were fed into a principal component analysis to delineate relevant features. We applied the neurite orientation dispersion and density imaging (NODDI) model on diffusion-weighted MR-images to calculate the free-water content as an advanced marker of microstructural integrity of the substantia nigra and tested its associations with gait parameters.

RESULTS

Patients showed increased duration of stance phase, load response, pre-swing, and double support time, as well as reduced duration of single support and swing time. Gait rhythmic alterations associated positively with the free-water content in the right substantia nigra in PD, indicating that patients with more severe neurodegeneration extend the duration of stance phase, load response, and pre-swing.

CONCLUSION

The results provide evidence that gait alterations are not merely a byproduct of bradykinesia-related reduced walking speed. The data-supported association between free-water and the rhythmic component highlights the potential of substantia nigra microstructure imaging as a measure of gait-dysfunction and disease-progression.

Neural Variability in the Prefrontal Cortex as a Reflection of Neural Flexibility and Stability in Patients With Parkinson Disease

BACKGROUND AND OBJECTIVES

Functional Near-Infrared Spectroscopy (fNIRS) studies provide direct evidence to the important role of the prefrontal cortex (PFC) during walking in aging and Parkinson's disease (PD). Most studies mainly explored mean HbO2 levels, while moment-to-moment variability measures have been rarely investigated. Variability measures can inform on flexibility that is imperative for adaptive function. We hypothesized that patients with PD will show less variability in HbO2 signals during walking compared to healthy controls.

METHODS

206 participants, 57 healthy controls (age: 68.9±1.0 years; 27 women) and 149 idiopathic PD patients (age: 69.8±0.6 years, 50 women, disease duration: 8.27±5.51 years) performed usual walking and dual-task walking (serial 3 subtractions) with an fNIRS system placed on the forehead. HbO2 variability was calculated using the standard deviation (SD), range, and mean detrended time series of fNIRS-derived HbO2 signal evaluated during each walking task. HbO2 variability was compared between groups and between walking tasks using mixed model analyses.

RESULTS

Higher variability (SD, range, mean detrended time series) was observed during dual-task walking, compared to usual walking (p<0.025), but this was derived from the differences within the healthy control group (group X task interaction: p<0.007). On the other hand, task repetition demonstrated reduced variability in healthy controls but increased variability in patients with PD (interaction group*walk-repetition: p<0.048). The MDS-UPDRS motor score correlated with HbO2 range (r=0.142, p=0.050) and HbO2 SD (r=0.173, p=0.018) during usual walking in all participants.

DISCUSSION

In this study, we suggest a new way to interpret changes in HbO2 variability. We relate increased HbO2 variability to flexible adaptation to environmental challenges and decreased HbO2 variability to the stability of performance. Our results show that both are limited in PD however, further investigation of these concepts is required. Moreover, HbO2 variability measures are an important aspect of brain function that adds new insights into the role of PFC during walking with aging and PD.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that patients with PD have more variability within Hb02 signals during usual-walking, compared to healthy controls, but not during dual-task walking.

Using a Portable Gait Rhythmogram to Examine the Effect of Music Therapy on Parkinson's Disease-Related Gait Disturbance

External cues improve walking by evoking internal rhythm formation related to gait in the brain in patients with Parkinson’s disease (PD). This study examined the usefulness of using a portable gait rhythmogram (PGR) in music therapy on PD-related gait disturbance. A total of 19 subjects with PD who exhibited gait disturbance were evaluated for gait speed and step length during a 10 m straight walking task. Moreover, acceleration, cadence, and trajectory of the center of the body were estimated using a PGR. Walking tasks were created while incorporating music intervention that gradually increased in tempo from 90 to 120 beats per minute (BPM). We then evaluated whether immediate improvement in gait could be recognized even without music after walking tasks by comparing pre- (pre-MT) and post-music therapy (post-MT) values. Post-MT gait showed significant improvement in acceleration, gait speed, cadence, and step length. During transitions throughout the walking tasks, acceleration, gait speed, cadence, and step length gradually increased in tasks with music. With regard to the trajectory of the center of the body, we recognized a reduction in post-MT medio-lateral amplitude. Music therapy immediately improved gait disturbance in patients with PD, and the effectiveness was objectively shown using PGR.

Movement-related EEG signatures associated with freezing of gait in Parkinson's disease: an integrative analysis

Freezing of gait is the most severe gait deficit associated with Parkinson's disease and significantly affects patients' independence and consequently their quality of life. The lack of a clear understanding of its underlying neurophysiological mechanism has resulted in limited effectiveness of the current treatment options. In this study, we investigated EEG features over (pre-)supplementary motor area and primary motor cortex during a simple cue-based ankle dorsiflexion movement. These features include movement-related cortical potentials (0.05-5 Hz) and brain oscillations (1-50 Hz). Electromyogram signal from the tibialis anterior muscle of the dominant foot was used to determine the movement onset. The EEG features before, during and following the onset of the movement were compared among three groups of participants: patients with freezing (N = 14, 11 males), patients without freezing (N = 14, 13 males) and healthy age-matched controls (N = 13, 10 males) with 15 recorded trials for each individual. Additionally, Parkinson's disease patients with freezing of gait were separated into mild (N = 7) and severe cases (N = 5), so that EEG features associated with freezing severity could be investigated. The results indicated significant differences between patients with severe freezing of gait compared to healthy controls and patients without freezing of gait. In addition, patients with mild and severe freezing represented cortical activity differences. For patients with freezing, the initial component of movement-related cortical potential is significantly lower than that of the healthy controls (P = 0.002) and is affected by the severity of freezing. Furthermore, a striking absence of beta frequency band (12-35 Hz) desynchronization was observed in patients with freezing, especially low-beta frequency band over Cz, before the movement, which was also associated with the severity of the freezing of gait. Low-beta (13-20 Hz) and high-beta (21-35 Hz) frequency band activities represented unique features for each group. Beta event-related desynchronization over Cz present in healthy controls prior to movement onset, was partially replaced by the theta band (4-8 Hz) synchrony in patients with freezing. Patients with severe freezing also represented some level of theta band synchronization over contralateral supplementary motor area. This suggests the involvement of cognitive processing over the motor cortex in controlling cue-based voluntary movement as a compensatory mechanism associated with freezing of gait. The EEG features identified in this study are indicative of important freezing of gait clinical characteristics such as severity and contribute to a better understanding of the underlying neurophysiology of the mysterious phenomenon of freezing of gait.

The effects of levodopa in the spatiotemporal gait parameters are mediated by self-selected gait speed in Parkinson's disease

In individuals with Parkinson's disease (PD), the medication induces different and inconsistent results in the spatiotemporal parameters of gait, making it difficult to understand its effects on gait. As spatiotemporal gait parameters have been reported to be affected by gait speed, it is essential to consider the gait speed when studying walking biomechanics to interpret the results better when comparing the gait pattern of different conditions. Since the medication alters the self-selected gait speed of individuals with PD, this study analysed whether the change in gait speed can explain the selective effects of l-DOPA on the spatiotemporal parameters of gait in individuals with PD. We analysed the spatiotemporal gait parameters at the self-selected speed of 22 individuals with PD under ON and OFF states of l-DOPA medication. Bayesian mediation analysis evaluated which gait variables were affected by the medication state and checked if those effects were mediated by speed changes induced by medication. The gait speed was significantly higher among ON compared with OFF medication. All the spatiotemporal parameters of the gait were mediated by speed, with proportions of mediation close to 1 (effect entirely explained by speed changes). Our results show that a change in gait speed better explains the changes in the spatiotemporal gait parameters than the ON-OFF phenomenon. As an implication for rehabilitation, our results suggest that it is possible to assess the effect of l-DOPA on improving motor symptoms related to gait disorders by measuring gait speed.

A versatile computational algorithm for time-series data analysis and machine-learning models

Here we introduce Local Topological Recurrence Analysis (LoTRA), a simple computational approach for analyzing time-series data. Its versatility is elucidated using simulated data, Parkinsonian gait, and in vivo brain dynamics. We also show that this algorithm can be used to build a remarkably simple machine-learning model capable of outperforming deep-learning models in detecting Parkinson’s disease from a single digital handwriting test.

Convolutional neural network ensemble for Parkinson's disease detection from voice recordings

The computerized detection of Parkinson's disease (PD) will facilitate population screening and frequent monitoring and provide a more objective measure of symptoms, benefiting both patients and healthcare providers. Dysarthria is an early symptom of the disease and examining it for computerized diagnosis and monitoring has been proposed. Deep learning-based approaches have advantages for such applications because they do not require manual feature extraction, and while this approach has achieved excellent results in speech recognition, its utilization in the detection of pathological voices is limited. In this work, we present an ensemble of convolutional neural networks (CNNs) for the detection of PD from the voice recordings of 50 healthy people and 50 people with PD obtained from PC-GITA, a publicly available database. We propose a multiple-fine-tuning method to train the base CNN. This approach reduces the semantical gap between the source task that has been used for network pretraining and the target task by expanding the training process by including training on another dataset. Training and testing were performed for each vowel separately, and a 10-fold validation was performed to test the models. The performance was measured by using accuracy, sensitivity, specificity and area under the ROC curve (AUC). The results show that this approach was able to distinguish between the voices of people with PD and those of healthy people for all vowels. While there were small differences between the different vowels, the best performance was when/a/was considered; we achieved 99% accuracy, 86.2% sensitivity, 93.3% specificity and 89.6% AUC. This shows that the method has potential for use in clinical practice for the screening, diagnosis and monitoring of PD, with the advantage that vowel-based voice recordings can be performed online without requiring additional hardware.

Effect of Foot Orthoses and Shoes in Parkinson's Disease Patients: A PRISMA Systematic Review

Reduced plantar foot sensation, postural instability, and gait difficulties are characteristic of Parkinson´s disease patients. A systematic review was carried out to determine the effect of the different types of insoles and shoes in these patients. Several databases were used to search for relevant articles reporting Parkinson´s disease patients undergoing treatment with any type of insole and footwear. All titles and abstracts were reviewed independently by two reviewers and the available data were extracted. The study eligibility criteria were any type of experimental study that included Parkinson’s disease patients treated with any type of insole or footwear. Eight studies were selected. Interventions used were textured insoles, footwear modifications, and habitual footwear. Three different outcomes were evaluated in each study: gait parameters, balance, and plantar sensation. According to the data available from this systematic review, the most important conclusion is that more controlled studies are needed in this research field. There are indications to suggest that textured insoles have positive effects on gait parameters, balance, and plantar sensation in Parkinson’s disease patients.

Kinematic Assessment of Turning and Walking Tasks Among Stroke Survivors by Employing Wearable Sensors and Pressure Platform

Stroke survivors often experience reduced movement capabilities due to alterations in their neuromusculoskeletal systems. Modern sensor technologies and motion analyses can facilitate the determination of these changes. Our work aims to assess the potential of using wearable motion sensors to analyze the movement of stroke survivors and identifying the affected functions. We recruited 10 participants (5 stroke survivors, 5 healthy individuals) and conducted a controlled laboratory evaluation for two of the most common daily activities: turning and walking. Among the extracted kinematic parameters, range of trunk and sacrum lateral bending in turning were significantly larger in stroke survivors (p-value<0.02). However, no statistical difference in mean angular velocity and range of motion for trunk/sacrum/shank flexion-extension were obtained in the turning task. Our results also indicated that during walking, while there was no difference in swing time, double support portion of gait among the stroke group was significantly larger (p-value = 0.001). Outcomes of this investigation may help in designing new rehabilitation programs for stroke and other neurological disorders and/or in improving the efficacy of such programs.Clinical Relevance- This study may provide a better insight on the detailed functional differences between stroke survivors and healthy individuals which in turn could be used to develop a more efficient rehabilitation program for stroke community.

An inertial sensor-based algorithm for turning detection during gait

Patients with Parkinson's disease (PD) can be divided into two subtypes based on clinical features, namely tremor-dominant (TD) and postural instability and gait difficulty (PIGD). Detection of PIGD symptoms is crucial for early diagnosis of PD and timely clinical intervention. However, patients at the early stage may not exhibit obvious motor dysfunctions during normal straight walking leading to difficulties in PD identification. Researchers have found that patients would show significant motor deteriorations in turning due to their cognition limitation. Therefore, turning detection is essential for quantitative motion analysis in the gait assessment of PD patients. In this study, we proposed a novel inertial-sensor-based algorithm for turning detection. Ten healthy young participants were enrolled in the experiment where they were required to walk along a 7-meter pathway with two 180 degree turns at their comfortable walking speed. Five inertial sensors were attached to the upper trunk, the shank and the foot of both legs. The algorithm performance was validated using an optical motion capture system for reference and two sensor combination options (upper trunk and shank sensors, upper trunk and foot sensors) were compared. The results showed that the proposed algorithm achieved accuracy over 98% for identifying the turning state of both legs. The integration of the upper trunk and foot sensors had no significant effect on the detection accuracy compared to that with the use of the upper trunk and shank sensors. Our algorithm has the potential to be implemented in the motion analysis model for complicated gait tasks, which has great potential in the early diagnosis of PIGD.

Indoor Human Localization and Gait Analysis using Machine Learning for In-home Health Monitoring

Homes equipped with ambient sensors can measure physiological signals correlated with the resident's health without requiring a wearable device. Gait characteristics may reveal physical imbalances or recognize changes in cognitive health. In this paper, we use the physical interactions with floor to both localize the resident and monitor their gait. Accelerometers are placed at the corners of the room for sensing. Gradient boosting regression was used to perform localization with an accuracy of 82%, reasonably accounting for inhomogeneity in the floor with just 3 sensors. A method using step time variance is proposed to detect gait imbalances; results on induced limps are presented.

Prediction of Parkinsonian Gait in Older Adults with Dementia using Joint Trajectories and Gait Features from 2D Video. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:5700-5703. [PMID: 34892415 DOI: 10.1109/embc46164.2021.9630563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Older adults with dementia have a high risk of developing drug-induced parkinsonism; however, formal clinical gait assessments are too infrequent to capture fluctuations in their gait. Camera-based human pose estimation and tracking provides a means to frequently monitor gait in nonclinical settings. In this study, 2160 walking bouts from 49 participants were recorded using a ceiling-mounted camera. Recorded color videos were processed using AlphaPose to obtain 2D joint trajectories of the participant as they were walking down a hallway of the unit. A subset of 324 walking bouts from 14 participants were annotated with clinical scores of parkinsonism on the Unified Parkinson's Disease Rating Scale (UPDRS)-gait scale. Linear, random forest, and ordinal logistic regression models were evaluated for regression to UPDRS-gait scores using engineered 2D gait features calculated from the AlphaPose joint trajectories. Additionally, spatial temporal graph convolutional networks (ST-GCNs) were trained to predict UPDRS-gait scores from joint trajectories and gait features using a two-stage training scheme (self-supervised pretraining stage on all walks followed by a finetuning stage on labelled walks). All models were trained using leave-one-subject-out cross-validation to simulate testing on previously unseen participants. The macro-averaged F1-score was 0.333 for the best model operating on only gait features and 0.372 for the top ST-GCN model that used both joint trajectories and gait features as input. When accepting predicted scores that were only off by at most 1 point on the UPDRS-gait scale, the accuracy of the model that only used gait features was 82.8%, while the model that also used joint trajectories had an accuracy of 94.2%.Clinical Relevance- The combination of gait features and joint trajectories capture parkinsonian qualities in gait better than either group of data individually.

Virtual reality balance training to improve balance and mobility in Parkinson's disease: a systematic review and meta-analysis

BACKGROUND

In the last few years, virtual reality (VR) has been increasingly used to strengthen the effect of balance training (BT) in Parkinson's disease (PD).

OBJECTIVE

We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) to compare the effects of VR-BT relative to BT alone for improving balance and mobility PD subjects with balance/mobility difficulties.

METHODS

Four electronic databases were searched: 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. Primary outcomes were balanced (Berg Balance Scale-BBS), mobility (Timed Up and Go-TUG) and walking speed. Secondary outcomes were falls, walking distance and stability, spatial gait parameters, balance confidence, sensory integration ability, motor signs and quality of life.

RESULTS

We included 22 studies (901 patients). Meta-analysis on fourteen trials (430 patients) showed a mean difference (MD) of 2.09 points (95% confidence interval [CI] 0.86-3.33) on BBS favoring VR-BT compared to BT (low certainty evidence). Subgroup analyses showed higher balance improvement in most affected subjects (moderate certainty evidence) and using VR rehabilitation-specific systems vs. VR non-specific systems. Eight trials (236 patients) assessing mobility showed a MD of 1.55 s (95% CI 0.04-3.06) on TUG favoring VR-BT (very low certainty evidence). No differences were observed in walking speed. Estimated effects were not maintained for any outcome at follow-up.

CONCLUSIONS

This review suggests that VR-BT is more effective than BT to improve balance in PD subjects immediately after training, particularly in individuals with higher postural instability at baseline.

A pathophysiological model of gait captures the details of the impairment of pace/rhythm, variability and asymmetry in Parkinsonian patients at distinct stages of the disease

Locomotion in people with Parkinson' disease (pwPD) worsens with the progression of disease, affecting independence and quality of life. At present, clinical practice guidelines recommend a basic evaluation of gait, even though the variables (gait speed, cadence, step length) may not be satisfactory for assessing the evolution of locomotion over the course of the disease. Collecting variables into factors of a conceptual model enhances the clinical assessment of disease severity. Our aim is to evaluate if factors highlight gait differences between pwPD and healthy subjects (HS) and do it at earlier stages of disease compared to single variables. Gait characteristics of 298 pwPD and 84 HS able to walk without assistance were assessed using a baropodometric walkway (GAITRite®). According to the structure of a model previously validated in pwPD, eight spatiotemporal variables were grouped in three factors: pace/rhythm, variability and asymmetry. The model, created from the combination of three factor scores, proved to outperform the single variables or the factors in discriminating pwPD from HS. When considering the pwPD split into the different Hoehn and Yahr (H&Y) stages, the spatiotemporal variables, factor scores and the model showed that multiple impairments of gait appear at H&Y stage 2.5, with the greatest difference from HS at stage 4. A contrasting behavior was found for the asymmetry variables and factor, which showed differences from the HS already in the early stages of PD. Our findings support the use of factor scores and of the model with respect to the single variables in gait staging in PD.

Gait Analyses of Parkinson’s Disease Patients Using Multiscale Entropy

Parkinson’s disease (PD) is a type of neurodegenerative diseases. PD influences gait in many aspects: reduced gait speed and step length, increased axial rigidity, and impaired rhythmicity. Gait-related data used in this study are from PhysioNet. Twenty-one PD patients and five healthy controls (CO) were sorted into four groups: PD without task (PDw), PD with dual task (PDd), control without task (COw), and control with dual task (COd). Since dual task actions are attention demanding, either gait or cognitive function may be affected. To quantify the used walking data, eight pressure sensors installed in each insole are used to measure the vertical ground reaction force. Thus, quantitative measurement analysis is performed utilizing multiscale entropy (MSE) and complexity index (CI) to analyze and differentiate between the ground reaction force of the four different groups. Results show that the CI of patients with PD is higher than that of CO and 11 of the sensor signals are statistically significant (p < 0.05). The COd group has larger CI values at the beginning (p = 0.021) but they get lower at the end of the test (p = 0.000) compared to that in the COw group. The end-of-test CI for the PDw group is lower in one of the feet sensor signals, and in the right total ground reaction force compared to the PDd group counterparts. In conclusion, when people start to adjust their gait due to pathology or stress, CI may increase first and reach a peak, but it decreases afterward when stress or pathology is further increased.

Perception and Use of Compensation Strategies for Gait Impairment by Persons With Parkinson Disease

BACKGROUND AND OBJECTIVES

Gait impairments are common and disabling in Parkinson disease (PD). Applying compensation strategies helps to overcome these gait deficits. Clinical observations suggest that the efficacy of different compensation strategies varies depending on both individual patient characteristics and the context in which the strategies are applied. This has never been investigated systematically, hampering the ability of clinicians to provide a more personalized approach to gait rehabilitation. We had 3 aims: (1) to evaluate patients' awareness and actual use of compensation categories for gait impairments in PD, (2) to investigate the patient-rated efficacy of the various compensation strategies and whether this efficacy depends on the context in which the strategies are applied, and (3) to explore differences in the efficacy between subgroups based on sex, age, disease duration, freezing status, and ability to perform a dual task.

METHODS

A survey was conducted among 4,324 adults with PD and self-reported disabling gait impairments.

RESULTS

The main findings are as follows: (1) compensation strategies for gait impairments are commonly used by persons with PD, but their awareness of the full spectrum of available strategies is limited; (2) the patient-rated efficacy of compensation strategies is high but varies depending on the context in which they are applied; and (3) compensation strategies are useful for all types of patients with PD, but the efficacy of the different strategies varies per person.

DISCUSSION

The choice of compensation strategies for gait impairment in PD should be tailored to the individual patient and to the context in which the strategy needs to be applied.

CLASSIFICATION OF EVIDENCE

This data provides Class IV evidence that compensation strategies are an effective treatment for gait impairment in patients with PD.

Does Subthalamic Deep Brain Stimulation Impact Asymmetry and Dyscoordination of Gait in Parkinson's Disease?

Background. Subthalamic deep brain stimulation (STN-DBS) is an effective treatment for selected Parkinson's disease (PD) patients. Gait characteristics are often altered after surgery, but quantitative therapeutic effects are poorly described. Objective. The goal of this study was to systematically investigate modifications in asymmetry and dyscoordination of gait 6 months postoperatively in patients with PD and compare the outcomes with preoperative baseline and to asymptomatic controls without PD. Methods. A convenience sample of thirty-two patients with PD (19 with postural instability and gait disorder (PIGD) type and 13 with tremor dominant disease) and 51 asymptomatic controls participated. Parkinson patients were tested prior to the surgery in both OFF and ON medication states, and 6-months postoperatively in the ON stimulation condition. Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) I to IV and medication were compared to preoperative conditions. Asymmetry ratios, phase coordination index, and walking speed were assessed. Results. MDS-UPDRS I to IV at 6 months improved significantly, and levodopa equivalent daily dosages significantly decreased. STN-DBS increased step time asymmetry (hedges' g effect sizes [95% confidence interval] between pre- and post-surgery: .27 [-.13, .73]) and phase coordination index (.29 [-.08, .67]). These effects were higher in the PIGD subgroup than the tremor dominant (step time asymmetry: .38 [-.06, .90] vs .09 [-.83, 1.0] and phase coordination index: .39 [-.04, .84] vs .13 [-.76, .96]). Conclusions. This study provides objective evidence of how STN-DBS increases asymmetry and dyscoordination of gait in patients with PD and suggests motor subtypes-associated differences in the treatment response.

Perceptions of Compensation Strategies for Gait Impairments in Parkinson's Disease: A Survey Among 320 Healthcare Professionals

Compensation strategies are an essential part of managing gait impairments in people with Parkinson’s disease (PD). We conducted an online survey among 320 healthcare professionals with specific expertise in PD management, to evaluate their knowledge of compensation strategies for gait impairments in people with PD, and whether they applied these in daily practice. Only 35% of professionals was aware of all categories of compensation strategies. Importantly, just 23% actually applied all seven available categories of strategies when treating people with PD in clinical practice. We discuss the clinical implications, and provide recommendations to overcome this knowledge gap.

The Effects of Intensive Neurorehabilitation on Sequence Effect in Parkinson's Disease Patients With and Without Freezing of Gait

Background: The sequence effect (SE), defined as a reduction in amplitude of repetitive movements, is a common clinical feature of Parkinson's disease (PD) and is supposed to be a major contributor to freezing of gait (FOG). During walking, SE manifests as a step-by-step reduction in step length when approaching a turning point or gait destination, resulting in the so-called destination sequence effect (dSE). Previous studies explored the therapeutic effects of several strategies on SE, but none of them evaluated the role of an intensive rehabilitative program. Objectives: Here we aim to study the effects of a 4-week rehabilitative program on dSE in patients with PD with and without FOG. Methods: Forty-three patients (30 males, 70.6 ± 7.5 years old) with idiopathic PD were enrolled. The subjects were divided into two groups: patients with (PD + FOG, n = 23) and without FOG (PD - FOG, n = 20). All patients underwent a standardized 4-week intensive rehabilitation in-hospital program. At hospital admission (T0) and discharge (T1), all subjects were evaluated with an inertial gait analysis for dSE recording. Results: At T0, the dSE was more negative in the PD + FOG group (-0.80 ± 0.6) when compared to the PD - FOG group (-0.39 ± 0.3) (p = 0.007), even when controlling for several clinical and demographic features. At T1, the dSE was reduced in the overall study population (p = 0.001), with a more pronounced improvement in the PD + FOG group (T0: -0.80 ± 0.6; T1: -0.23 ± 0.4) when compared to the PD - FOG group (T0: -0.39 ± 0.3; T1: -0.22 ± 0.5) (p = 0.012). At T1, we described in the overall study population an improvement in speed, cadence, stride duration, and stride length (p = 0.001 for all variables). Conclusions: dSE is a core feature of PD gait dysfunction, specifically in patients with FOG. A 4-week intensive rehabilitative program improved dSE in PD patients, exerting a more notable beneficial effect in the PD + FOG group.