Falls and freezing of gait in Parkinson's disease: a review of two interconnected, episodic phenomena

Deep learning-based detection of affected body parts in Parkinson's disease and freezing of gait using time-series imaging

We proposed a deep learning method using a convolutional neural network on time-series (TS) images to detect and differentiate affected body parts in people with Parkinson's disease (PD) and freezing of gait (FOG) during 360° turning tasks. The 360° turning task was performed by 90 participants (60 people with PD [30 freezers and 30 nonfreezers] and 30 age-matched older adults (controls) at their preferred speed. The position and acceleration underwent preprocessing. The analysis was expanded from temporal to visual data using TS imaging methods. According to the PD vs. controls classification, the right lower third of the lateral shank (RTIB) on the least affected side (LAS) and the right calcaneus (RHEE) on the LAS were the most relevant body segments in the position and acceleration TS images. The RHEE marker exhibited the highest accuracy in the acceleration TS images. The identified markers for the classification of freezers vs. nonfreezers vs. controls were the left lateral humeral epicondyle (LELB) on the more affected side and the left posterior superior iliac spine (LPSI). The LPSI marker in the acceleration TS images displayed the highest accuracy. This approach could be a useful supplementary tool for determining PD severity and FOG.

The effect of deep brain stimulation on cortico-subcortical networks in Parkinson's disease patients with freezing of gait: Exhaustive exploration of a basic model

Current treatments of Parkinson's disease (PD) have limited efficacy in alleviating freezing of gait (FoG). In this context, concomitant deep brain stimulation (DBS) of the subthalamic nucleus (STN) and the substantia nigra pars reticulata (SNr) has been suggested as a potential therapeutic approach. However, the mechanisms underlying this approach are unknown. While the current rationale relies on network-based hypotheses of intensified disinhibition of brainstem locomotor areas to facilitate the release of gait motor programs, it is still unclear how simultaneous high-frequency DBS in two interconnected basal ganglia nuclei affects large-scale cortico-subcortical network activity. Here, we use a basic model of neural excitation, the susceptible-excited-refractory (SER) model, to compare effects of different stimulation modes of the network underlying FoG based on the mouse brain connectivity atlas. We develop a network-based computational framework to compare subcortical DBS targets through exhaustive analysis of the brain attractor dynamics in the healthy, PD, and DBS states. We show that combined STN+SNr DBS outperforms STN DBS in terms of the normalization of spike propagation flow in the FoG network. The framework aims to move toward a mechanistic understanding of the network effects of DBS and may be applicable to further perturbation-based therapies of brain disorders.

Development, Validation, and Limits of Freezing of Gait Detection Using a Single Waist-Worn Device

OBJECTIVE

Freezing of Gait (FOG) is prevalent in people with Parkinson's disease (PD) and severely disrupts mobility. Detecting the exact boundaries of FOG episodes may facilitate new technologies in "breaking" FOG in real-time. This study investigates the performance of automatic device-based FOG detection.

METHODS

Eight machine-learning classifiers (including Neural Networks, Ensemble methods, and Support Vector Machines) were developed using (i) accelerometer and (ii) combined accelerometer and gyroscope data from a waist-worn device. While wearing the device, 107 people with PD completed mobility tasks designed to elicit FOG. Two clinicians independently annotated exact FOG episodes using synchronized video and a flowchart algorithm based on international guidelines. Device-detected FOG episodes were compared to annotated episodes using 10-fold cross-validation and Interclass Correlation Coefficients (ICC) for agreement.

RESULTS

Development used 50,962 windows of data and annotated activities (>10 hours). Strong agreement between clinicians for precise FOG episodes was observed (90% sensitivity, 92% specificity, and ICC1,1 = 0.97 for total FOG duration). Device performance varied by method, complexity, and cost matrix. The Neural Network using 67 accelerometer features achieved high sensitivity to FOG (89% sensitivity, 81% specificity, and ICC1,1 = 0.83) and stability (validation loss 5%).

CONCLUSION

The waist-worn device consistently reported accurate detection of precise FOG episodes and compared well to more complex systems. The strong clinician agreement indicates room for improvement in future device-based FOG detection.

SIGNIFICANCE

This study may enhance PD care by reducing reliance on visual FOG inspection, demonstrating that high sensitivity in automatic FOG detection is achievable.

Iron and neuromelanin imaging in basal ganglia circuitry in Parkinson's disease with freezing of gait

OBJECTIVE

This study aimed to examine the structural alterations of the deep gray matter (DGM) in the basal ganglia circuitry of Parkinson's disease (PD) patients with freezing of gait (FOG) using quantitative susceptibility mapping (QSM) and neuromelanin-sensitive magnetic resonance imaging (NM-MRI).

METHODS

Twenty-five (25) PD patients with FOG (PD-FOG), 22 PD patients without FOG (PD-nFOG), and 30 age- and sex-matched healthy controls (HCs) underwent 3-dimensional multi-echo gradient recalled echo and NM-MRI scanning. The mean volume and susceptibility of the DGM on QSM data and the relative contrast (NMRC-SNpc) and volume (NMvolume-SNpc) of the substantia nigra pars compacta on NM-MRI were analyzed among groups. A multiple linear regression analysis was performed to explore the associations of FOG severity with MRI measurements and disease stage.

RESULTS

The PD-FOG group showed higher susceptibility in the bilateral caudal substantia nigra (SN) compared to the HC group. Both the PD-FOG and PD-nFOG groups showed lower volumes than the HC group in the bilateral caudate and putamen as determined from the QSM data. The NMvolume-SNpc on NM-MRI in the PD-FOG group was significantly lower than in the HC and PD-nFOG groups. Both the PD-FOG and PD-nFOG groups showed significantly decreased NMRC-SNpc.

CONCLUSIONS

The PD-FOG patients showed abnormal neostriatum atrophy, increases in iron deposition in the SN, and lower NMvolume-SNpc. The structural alterations of the DGM in the basal ganglia circuits could lead to the abnormal output of the basal ganglia circuit to trigger the FOG in PD patients.

Higher Order Polynomial Transformer for Fine-Grained Freezing of Gait Detection

Freezing of Gait (FoG) is a common symptom of Parkinson's disease (PD), manifesting as a brief, episodic absence, or marked reduction in walking, despite a patient's intention to move. Clinical assessment of FoG events from manual observations by experts is both time-consuming and highly subjective. Therefore, machine learning-based FoG identification methods would be desirable. In this article, we address this task as a fine-grained human action recognition problem based on vision inputs. A novel deep learning architecture, namely, higher order polynomial transformer (HP-Transformer), is proposed to incorporate pose and appearance feature sequences to formulate fine-grained FoG patterns. In particular, a higher order self-attention mechanism is proposed based on higher order polynomials. To this end, linear, bilinear, and trilinear transformers are formulated in pursuit of discriminative fine-grained representations. These representations are treated as multiple streams and further fused by a cross-order fusion strategy for FoG detection. Comprehensive experiments on a large in-house dataset collected during clinical assessments demonstrate the effectiveness of the proposed method, and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.92 is achieved for detecting FoG.

Knowledge mapping and research trends of accidental falls in patients with Parkinson's disease from 2003 to 2023: a bibliometric analysis

Background

Recent years have witnessed a rapid growth in research on accidental falls in patients with Parkinson's Disease (PD). However, a comprehensive and systematic bibliometric analysis is still lacking. This study aims to systematically analyze the current status and development trends of research related to accidental falls in patients with PD using bibliometric methods.

Methods

We retrieved literature related to accidental falls in patients with PD published between January 1, 2003, and December 31, 2023, from the Web of Science Core Collection (WoSCC) database. Statistical analysis and knowledge mapping of the literature were conducted using VOSviewer, CiteSpace, and Microsoft Excel software.

Results

A total of 3,195 publications related to accidental falls in patients with PD were retrieved. These articles were authored by 13,202 researchers from 3,834 institutions across 87 countries and published in 200 academic journals. Over the past 20 years, the number of published articles and citations has increased annually. The United States and the United Kingdom have the highest number of publications in this field, while Harvard University and Tel Aviv University are the most influential institutions. The Parkinsonism & Related Disorders journal published the highest number of articles, while the Movement Disorders journal had the highest number of citations. The most prolific author is Bloem, Bastiaan R, while the most cited author is Hausdorff, Jeffrey. The main research areas of these publications are Neurosciences, Biomedical, Electrical & Electronic, and Biochemistry & Molecular Biology. Currently, high-frequency keywords related to accidental falls in patients with PD include risk factors, clinical manifestations, and interventions. Prediction and prevention of accidental falls in such patients is a research topic with significant potential and is currently a major focus of research.

Conclusion

This study used bibliometric and knowledge mapping analysis to reveal the current research status and hotspots in the field of accidental falls in patients with PD. It also points out directions for future research. This study can provide theoretical support and practical guidance for scholars to further conduct related research.

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.

Freezing of gait in Parkinson's disease is related to imbalanced stopping-related cortical activity

Freezing of gait, characterized by involuntary interruptions of walking, is a debilitating motor symptom of Parkinson's disease that restricts people's autonomy. Previous brain imaging studies investigating the mechanisms underlying freezing were restricted to scan people in supine positions and yielded conflicting theories regarding the role of the supplementary motor area and other cortical regions. We used functional near-infrared spectroscopy to investigate cortical haemodynamics related to freezing in freely moving people. We measured functional near-infrared spectroscopy activity over multiple motor-related cortical areas in 23 persons with Parkinson's disease who experienced daily freezing ('freezers') and 22 age-matched controls during freezing-provoking tasks including turning and doorway passing, voluntary stops and actual freezing. Crucially, we corrected the measured signals for confounds of walking. We first compared cortical activity between freezers and controls during freezing-provoking tasks without freezing (i.e. turning and doorway passing) and during stops. Secondly, within the freezers, we compared cortical activity between freezing, stopping and freezing-provoking tasks without freezing. First, we show that turning and doorway passing (without freezing) resemble cortical activity during stopping in both groups involving activation of the supplementary motor area and prefrontal cortex, areas known for their role in inhibiting actions. During these freezing-provoking tasks, the freezers displayed higher activity in the premotor areas than controls. Secondly, we show that, during actual freezing events, activity in the prefrontal cortex was lower than during voluntary stopping. The cortical relation between the freezing-provoking tasks (turning and doorway passing) and stopping may explain their susceptibility to trigger freezing by activating a stopping mechanism. Besides, the stopping-related activity of the supplementary motor area and prefrontal cortex seems to be out of balance in freezers. In this paper, we postulate that freezing results from a paroxysmal imbalance between the supplementary motor area and prefrontal cortex, thereby extending upon the current role of the supplementary motor area in freezing pathophysiology.

Investigating the Effects of a Kinematic Gait Parameter-Based Haptic Cue on Toe Clearance in Parkinson's Patients

Recurrent falls pose a significant challenge for Parkinson's disease (PD) patients and are a leading cause of disability in this population. One contributing factor to these recurring falls is the reduced minimum toe clearance (mTC). Preventing such falls by enhancing mTC has become an important goal in gait training among PD patients. In this paper, we propose a wearable cueing-based novel gait training device in anticipation of improved mTC. The cueing device records the foot strike angle (FSA) and cues the participants if the FSA is observed above a threshold. The patients with PD (n = 8) were recruited and asked to walk under two conditions: (a) with cue and (b) without cue at a self-selected speed during the ON medication state. Kinetic and kinematic gait parameters such as vertical ground reaction force, center of pressure, toe clearance, and FSA were recorded. A Mann-Whitney U test showed a significant increase (p < 0.001) in the toe clearance (within 34% to 64% of the swing phase from the toe-off instance) and FSA, from 87.60 mm and - 5.43degrees respectively during without cue to 94.29 mm and 2.93degrees respectively during with cue walking condition except in one subject. These findings support the potential incorporation of an FSA-based cueing device for toe clearance improvement among PD patients. In addition, the wearable setup supports the cueing device applicability outside laboratory and home settings.

Dynamic gait stability in people with mild to moderate Parkinson's disease

BACKGROUND

Falls are a serious health threat for people with Parkinson's disease. Dynamic gait stability has been associated with fall risk. Developing effective fall prevention interventions requires a sound understanding of how Parkinson's disease affects dynamic gait stability. This study compared dynamic gait stability within the Feasible Stability Region framework between people with and without Parkinson's disease during level walking at a self-selected speed.

METHODS

Twenty adults with Parkinson's disease and twenty age- and gender-matched healthy individuals were recruited. Dynamic gait stability at two gait instants: touchdown and liftoff, was assessed as the primary outcome measurement. Spatiotemporal gait parameters, including stance phase duration, step length, gait speed, and cadence were determined as explanatory variables.

FINDINGS

People with Parkinson's disease walked more slowly (p < 0.001) with a shorter step (p = 0.05), and prolonged stance phase (p = 0.04) than their healthy peers with moderate to large effect sizes. Dynamic gait stability did not show any group-associated differences (p > 0.36).

INTERPRETATION

Despite the different gait parameters between groups, people with Parkinson's disease exhibited similar dynamic gait stability to their healthy counterparts. To compensate for the potential dynamic gait stability deficit resulting from slow gait speed, individuals with Parkinson's disease adopted a short step length to shift the center of mass motion state closer to the Feasible Stability Region. Our findings could provide insight into the impact of Parkinson's disease on the control of dynamic gait stability.

A Pragmatic Review on Spinal Cord Stimulation Therapy for Parkinson's Disease Gait Related Disorders: Gaps and Controversies

BACKGROUND

Parkinson's Disease (PD) is a progressive neurological disorder that results in potentially debilitating mobility deficits. Recently, spinal cord stimulation (SCS) has been proposed as a novel therapy for PD gait disorders. The highest levels of evidence remain limited for SCS.

OBJECTIVES

In this systematic review and narrative synthesis, the literature was searched using combinations of key phrases indicating spinal cord stimulation and PD.

METHODS

We included pre-clinical studies and all published clinical trials, case reports, conference abstracts as well as protocols for ongoing clinical trials. Additionally, we included trials of SCS applied to atypical parkinsonism.

RESULTS

A total of 45 human studies and trials met the inclusion criteria. Based on the narrative synthesis, a number of knowledge gaps and future avenues of potential research were identified. This review demonstrated that evidence for SCS is currently not sufficient to recommend it as an evidence-based therapy for PD related gait disorders. There remain challenges and significant barriers to widespread implementation, including issues regarding patient selection, effective outcome selection, stimulation location and mode, and in programming parameter optimization. Results of early randomized controlled trials are currently pending. SCS is prone to placebo, lessebo and nocebo as well as blinding effects which may impact interpretation of outcomes, particularly when studies are underpowered.

CONCLUSION

Therapies such as SCS may build on current evidence and be shown to improve specific gait features in PD. Early negative trials should be interpreted with caution, as more evidence will be required to develop effective methodologies in order to drive clinical outcomes.

Impacts of gait freeze on quality of life in Parkinson's disease, from the perspectives of patients and their carers

BACKGROUND

The World Health Organisation (WHO) reports that morbidity and mortality due to Parkinson's disease (PD) are increasing faster than for other neurodegenerative conditions. People with Parkinson's (PwP) present with a variety of motor symptoms, such as tremor, bradykinesia, and rigidity. Freezing of gait (FoG) is a significant motor symptom that manifests as temporary episodes of inability to move one's feet, despite the intention to walk.

AIMS

This study examined the impact of FoG on quality of life (QoL) within an Irish cohort of PwP, from the perspectives of both PwP and their carers, using validated questionnaires that had been adapted for online use.

METHODS

PwP and their carers were recruited by outreach to the Irish Parkinson's Community. Anonymous online questionnaires were distributed, which combined a demographic survey with several clinically validated surveys, including Freezing of Gait Questionnaire (FoG-Q), Parkinson's Disease Questionnaire 8 (PDQ-8), and Parkinson's Disease Carer Questionnaire (PDQ-C).

RESULTS

There was a strong correlation (p < 0.001) between severity of FoG and lower QoL among PwP. Significant correlation was also found between FoG severity and several motor symptoms, such as postural instability and difficulty with balance, and non-motor symptoms, such as cognitive changes and pain/discomfort. FoG severity correlated with disease progression. Significant correlation was also found between FoG and symptoms, as assessed from the perspective of the patients' carers.

CONCLUSIONS

This study shows that FoG is a significant detriment to the QoL of PwP, from the perspectives of patients and carers. This method of assessing FoG and QoL using online questionnaires has potential to enhance the reach and flexibility of this type of research. These findings will inform future studies on larger cohorts and highlight unmet clinical needs in PwP.

Smartphone usage during walking decreases the positive persistency in gait cycle variability

Gait cycle variability during steady walking, described by the stride interval time series, has been used as a gait-stability-related measure. In particular, the positive persistency in the stride intervals with 1/f-like fluctuation and reduction of the persistency are the well-documented metrics that can characterize gait patterns of healthy young adults and elderly including patients with neurological diseases, respectively. Here, we examined effects of a dual task on gait cycle variability in healthy young adults, based on the mean and standard deviation statistics as well as the positive persistency of the stride intervals during steady walking on a treadmill. Specifically, three gait conditions were examined: control condition, non-cognitive task with holding a smartphone in front of the chest using their dominant hand and looking fixedly at a blank screen of the smartphone, and cognitive motor task with holding a smartphone as in the non-cognitive task and playing a puzzle game displayed on the smartphone by one-thumb operation. We showed that only the positive persistency, not the mean and standard deviation statistics, was affected by the cognitive and motor load of smartphone usage in the cognitive condition. More specifically, the positive persistency exhibited in the control and the non-cognitive conditions was significantly reduced in the cognitive condition. Our results suggest that the decrease in the positive persistency during the cognitive task, which might represent the deterioration of healthy gait pattern, is caused endogenously by the cognitive and motor load, not necessarily by the reduction of visual field as often hypothesized.

Causality-Enhanced Multiple Instance Learning With Graph Convolutional Networks for Parkinsonian Freezing-of-Gait Assessment

Freezing of gait (FoG) is a common disabling symptom of Parkinson's disease (PD). It is clinically characterized by sudden and transient walking interruptions for specific human body parts, and it presents the localization in time and space. Due to the difficulty in extracting global fine-grained features from lengthy videos, developing an automated five-point FoG scoring system is quite challenging. Therefore, we propose a novel video-based automated five-classification FoG assessment method with a causality-enhanced multiple-instance-learning graph convolutional network (GCN). This method involves developing a temporal segmentation GCN to segment each video into three motion stages for stage-level feature modeling, followed by a multiple-instance-learning framework to divide each stage into short clips for instance-level feature extraction. Subsequently, an uncertainty-driven multiple-instance-learning GCN is developed to capture spatial and temporal fine-grained features through GCN scheme and uncertainty learning, respectively, for acquiring global representations. Finally, a causality-enhanced graph generation strategy is proposed to exploit causal inference for mining and enhancing human structures causally related to clinical assessment, thereby extracting spatial causal features. Extensive experimental results demonstrate the excellent performance of the proposed method on five-classification FoG assessment with an accuracy of 62.72% and an acceptable accuracy of 91.32%, which is confirmed by independent testing. Additionally, it enables temporal and spatial localization of FoG events to a certain extent, facilitating reasonable clinical interpretations. In conclusion, our method provides a valuable tool for automated FoG assessment in PD, and the proposed causality-related component exhibits promising potential for extension to other general and medical fine-grained action recognition tasks.

Beta Burst-Driven Adaptive Deep Brain Stimulation Improves Gait Impairment and Freezing of Gait in Parkinson's Disease

Background

Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD) that is often refractory to medication. Pathological prolonged beta bursts within the subthalamic nucleus (STN) are associated with both worse impairment and freezing behavior in PD, which are improved with deep brain stimulation (DBS). The goal of the current study was to investigate the feasibility, safety, and tolerability of beta burst-driven adaptive DBS (aDBS) for FOG in PD.

Methods

Seven individuals with PD were implanted with the investigational Summit™ RC+S DBS system (Medtronic, PLC) with leads placed bilaterally in the STN. A PC-in-the-loop architecture was used to adjust stimulation amplitude in real-time based on the observed beta burst durations in the STN. Participants performed either a harnessed stepping-in-place task or a free walking turning and barrier course, as well as clinical motor assessments and instrumented measures of bradykinesia, OFF stimulation, on aDBS, continuous DBS (cDBS), or random intermittent DBS (iDBS).

Results

Beta burst driven aDBS was successfully implemented and deemed safe and tolerable in all seven participants. Gait metrics such as overall percent time freezing and mean peak shank angular velocity improved from OFF to aDBS and showed similar efficacy as cDBS. Similar improvements were also seen for overall clinical motor impairment, including tremor, as well as quantitative metrics of bradykinesia.

Conclusion

Beta burst driven adaptive DBS was feasible, safe, and tolerable in individuals with PD with gait impairment and FOG.

Video-Based Detection of Freezing of Gait in Daily Clinical Practice in Patients With Parkinsonism

Freezing of gait (FoG) is a prevalent symptom among individuals with Parkinson's disease and related disorders. FoG detection from videos has been developed recently; however, the process requires using videos filmed within a controlled environment. We attempted to establish an automatic FoG detection method from videos taken in uncontrolled environments such as in daily clinical practices. Motion features of 16 patients were extracted from timed-up-and-go test in 109 video data points, through object tracking and three-dimension pose estimation. These motion features were utilized to form the FoG detection model, which combined rule-based and machine learning-based models. The rule-based model distinguished the frames in which the patient was walking from those when the patient has stopped, using the pelvic position coordinates; the machine learning-based model distinguished between FoG and stop using a combined one-dimensional convolutional neural network and long short-term memory (1dCNN-LSTM). The model achieved a high intraclass correlation coefficient of 0.75-0.94 with a manually-annotated duration of FoG and %FoG. This method is novel as it combines object tracking, 3D pose estimation, and expert-guided feature selection in the preprocessing and modeling phases, enabling FoG detection even from videos captured in uncontrolled environments.

Correlation between motor function and health-related quality of life in early to mid-stage patients with Parkinson disease: a cross-sectional observational study

Aim

To investigate the correlation between motor function and health-related quality of life (HrQOL) in early to mid-stage patients with Parkinson disease (PwP).

Methods

This cross-sectional study recruited PwP from April 2020 to December 2023 at the outpatient clinic of Peking Union Medical College Hospital in Beijing, China. The motor symptoms were assessed using Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part 3. Balance function was evaluated using the Berg Balance Scale (BBS), and the risk of fall using Timed Up-and-Go test (TUG), and Five Times Sit-to-Stand test (FTSST). Freezing of gait questionnaire (FOGQ) was used to evaluate the severity of gait. The Intelligent Device for Energy Expenditure and Physical Activity (IDEEA) recorded gait cycle parameters, and the isokinetic dynamometer measured muscle strength. The Parkinson's Disease Questionnaire-39 (PDQ-39) was used to measure HrQOL. All assessments were tested during the on state. Spearman correlation was conducted to evaluate the correlation between motor function and HrQOL.

Results

243 patients with mean age of 69.33 years were enrolled. The PDQ-39 score was strongly correlated with FOG in H&Y stage III (r = 0.653, p < 0.001) and moderately correlated in H&Y stage I (r = 0.471, p < 0.001) and H&Y stage II (r = 0.386, p < 0.001). Furthermore, the FOG was strongly correlated with mobility domain at H&Y stage III (r = 0.694, p < 0.001) and moderately correlated at H&Y stage I (r = 0.431, p < 0.001) and H&Y stage II (r = 0.434, p < 0.001). All motor function scores were correlated with PDQ-39 scores at H&Y stage III (p < 0.05).

Conclusion

Motor function correlated with HrQOL in early to mid-stage PwP, and FOG was the main factor, especially affecting mobility, activities of daily life and communication. HrQOL in patients at different disease stages were variously affected by motor function, and HrQOL and multiple dimensions was significantly associated with motor function in patients at H&Y stage III.

Intelligent diagnosis system based on artificial intelligence models for predicting freezing of gait in Parkinson's disease

Introduction

Freezing of gait (FoG) is a significant issue for those with Parkinson's disease (PD) since it is a primary contributor to falls and is linked to a poor superiority of life. The underlying apparatus is still not understood; however, it is postulated that it is associated with cognitive disorders, namely impairments in executive and visuospatial functions. During episodes of FoG, patients may experience the risk of falling, which significantly effects their quality of life.

Methods

This research aims to systematically evaluate the effectiveness of machine learning approaches in accurately predicting a FoG event before it occurs. The system was tested using a dataset collected from the Kaggle repository and comprises 3D accelerometer data collected from the lower backs of people who suffer from episodes of FoG, a severe indication frequently realized in persons with Parkinson's disease. Data were acquired by measuring acceleration from 65 patients and 20 healthy senior adults while they engaged in simulated daily life tasks. Of the total participants, 45 exhibited indications of FoG. This research utilizes seven machine learning methods, namely the decision tree, random forest, Knearest neighbors algorithm, LightGBM, and CatBoost models. The Gated Recurrent Unit (GRU)-Transformers and Longterm Recurrent Convolutional Networks (LRCN) models were applied to predict FoG. The construction and model parameters were planned to enhance performance by mitigating computational difficulty and evaluation duration.

Results

The decision tree exhibited exceptional performance, achieving sensitivity rates of 91% in terms of accuracy, precision, recall, and F1- score metrics for the FoG, transition, and normal activity classes, respectively. It has been noted that the system has the capacity to anticipate FoG objectively and precisely. This system will be instrumental in advancing consideration in furthering the comprehension and handling of FoG.

Insights into Parkinson's Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis

Parkinson's Disease (PD) is a complex neurodegenerative disorder characterized by a spectrum of motor and non-motor symptoms, prominently featuring the freezing of gait (FOG), which significantly impairs patients' quality of life. Despite extensive research, the precise mechanisms underlying FOG remain elusive, posing challenges for effective management and treatment. This paper presents a comprehensive meta-analysis of FOG prediction and detection methodologies, with a focus on the integration of wearable sensor technology and machine learning (ML) approaches. Through an exhaustive review of the literature, this study identifies key trends, datasets, preprocessing techniques, feature extraction methods, evaluation metrics, and comparative analyses between ML and non-ML approaches. The analysis also explores the utilization of cueing devices. The limited adoption of explainable AI (XAI) approaches in FOG prediction research represents a significant gap. Improving user acceptance and comprehension requires an understanding of the logic underlying algorithm predictions. Current FOG detection and prediction research has a number of limitations, which are identified in the discussion. These include issues with cueing devices, dataset constraints, ethical and privacy concerns, financial and accessibility restrictions, and the requirement for multidisciplinary collaboration. Future research avenues center on refining explainability, expanding and diversifying datasets, adhering to user requirements, and increasing detection and prediction accuracy. The findings contribute to advancing the understanding of FOG and offer valuable guidance for the development of more effective detection and prediction methodologies, ultimately benefiting individuals affected by PD.

Research progress on the application of anti-gravity treadmill in the rehabilitation of Parkinson's disease patients: a mini review

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. It is the second most common chronic progressive neurodegenerative disease. PD still lacks a known cure or prophylactic medication. Current treatments primarily address symptoms without halting the progression of PD, and the side effects of dopaminergic therapy become more apparent over time. In contrast, physical therapy, with its lower risk of side effects and potential cardiovascular benefits, may provide greater benefits to patients. The Anti-Gravity Treadmill is an emerging rehabilitation therapy device with high safety, which minimizes patients' fear and allows them to focus more on a normal, correct gait, and has a promising clinical application. Based on this premise, this study aims to summarize and analyze the relevant studies on the application of the anti-gravity treadmill in PD patients, providing a reference for PD rehabilitation practice and establishing a theoretical basis for future research in this area.

On-Demand Cueing for Freezing of Gait in Parkinson's Disease: A Randomized Controlled Trial

BACKGROUND

Cueing can alleviate freezing of gait (FOG) in people with Parkinson's disease (PD), but using the same cues continuously in daily life may compromise effectiveness. Therefore, we developed the DeFOG-system to deliver personalized auditory cues on detection of a FOG episode.

OBJECTIVES

We aimed to evaluate the effects of DeFOG during a FOG-provoking protocol: (1) after 4 weeks of DeFOG-use in daily life against an active control group; (2) after immediate DeFOG-use (within-group) in different medication states.

METHOD

In this randomized controlled trial, 63 people with PD and daily FOG were allocated to the DeFOG or active control group. Both groups received feedback on their daily living step counts using the device, but the DeFOG group also received on-demand cueing. Video-rated FOG severity was compared pre- and post-intervention through a FOG-provoking protocol administered at home off and on-medication, but without using DeFOG. Within-group effects were tested by comparing FOG during the protocol with and without DeFOG.

RESULTS

DeFOG-use during the 4 weeks was similar between groups, but we found no between-group differences in FOG-severity. However, the within-group analysis showed that FOG was alleviated by DeFOG (effect size d = 0.57), regardless of medication state. Combining DeFOG and medication yielded an effect size of d = 0.67.

CONCLUSIONS

DeFOG reduced FOG considerably in a population of severe freezers both off and on medication. Nonetheless, 4 weeks of DeFOG-use in daily life did not ameliorate FOG during the protocol unless DeFOG was worn. These findings suggest that on-demand cueing is only effective when used, similar to other walking aids. © 2024 International Parkinson and Movement Disorder Society.

New quantitative evaluation of anticipatory postural adjustments using a smartphone in patients with Parkinson's disease

OBJECTIVE

To investigate a smartphone-enabled quantitative evaluation of anticipatory postural adjustments (APA) during one-leg stance (OLS) movements among individuals with Parkinson's disease (PD).

METHODS

This cross-sectional study included 10 young controls, 10 older individuals, and 13 individuals with PD. A smartphone and accelerometer were attached to the participants' lower back (L5), and the movements of the lower back toward the stance side during OLS were measured. For acceleration, the time to the peak value in the stance direction (peak latency [PL]) and the amount of displacement to the peak value in the stance direction (peak magnitude [PM]) were analyzed as APA characteristics. Additionally, the measured PL was divided by the PM for each group to obtain the APA ratio (APAr) as a new index.

RESULTS

Individuals with PD showed a delayed PL and decreased PM (vs. young controls: p = .002 for PL, p < .001 for PM) (vs. older individuals: p = .022 for PL, p = .001 for PM). The APAr clustered the young controls, older individuals, and individuals with PD. According to the receiver operating characteristic curve the APAr value was 0.95, and individuals in the PD group were identified (i.e. area under the curve: 0.98; sensitivity: 85.0%; specificity: 100%). Moreover the APAr was correlated with severity and balance ability in individuals with PD (p = .015 for NFOG-Q, p = .028 for UPDRS, p = .036 for TUG, p = .015 for Mini-BESTest, p = .018 for OLS time).

CONCLUSIONS

This smartphone-based evaluation using the APAr index was reflective of disease severity and decreased balance ability among individuals with PD. The facilitation of this measurement can help clinicians and physiotherapists quantitatively evaluate the APA of individuals with PD at laboratories and hospitals as well as in home environments.

On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study

Goal: Parkinson's disease (PD) can lead to gait impairment and Freezing of Gait (FoG). Recent advances in cueing technologies have enhanced mobility in PD patients. While sensor technology and machine learning offer real-time detection for on-demand cueing, existing systems are limited by the usage of smartphones between the sensor(s) and cueing device(s) for data processing. By avoiding this we aim at improving usability, robustness, and detection delay. Methods: We present a new technical solution, that runs detection and cueing algorithms directly on the sensing and cueing devices, bypassing the smartphone. This solution relies on edge computing on the devices' hardware. The wearable system consists of a single inertial sensor to control a stimulator and enables machine-learning-based FoG detection by classifying foot motion phases as either normal or FoG-affected. We demonstrate the system's functionality and safety during on-demand gait-synchronous electrical cueing in two patients, performing freezing of gait assessments. As references, motion phases and FoG episodes have been video-annotated. Results: The analysis confirms adequate gait phase and FoG detection performance. The mobility assistant detected foot motions with a rate above 94 % and classified them with an accuracy of 84 % into normal or FoG-affected. The FoG detection delay is mainly defined by the foot-motion duration, which is below the delay in existing sliding-window approaches. Conclusions: Direct computing on the sensor and cueing devices ensures robust detection of FoG-affected motions for on demand cueing synchronized with the gait. The proposed solution can be easily adopted to other sensor and cueing modalities.

Extraction of the pull force from inertial sensors during the pull test for Parkinson's disease: A reliability study

OBJECTIVE

To examine the inter- and intra-rater reliability of the pull test in patients with Parkinson's disease (PD) using the extracted pull force.

METHODS

In this inter- and intra-rater reliability study, two raters performed a pull test on 30 patients with PD. The pull force was quantified using inertial sensors attached to the rater's right hand and the patient's lower trunk. In this study, the pull force was calculated as an extracted three-dimensional vector quantity, the resultant acceleration, and was expressed in m/s2. Inter- and intra-rater reliabilities were analyzed using the interclass correlation coefficient (ICC) for the pull force and Cohen's weighted kappa (κw) for the pull test score. Furthermore, Bland-Altman analysis was used to investigate systematic errors.

RESULTS

The inter- and intra-rater reliability of the pull force was very poor (ICC = 0.033-0.214). Bland-Altman analysis revealed no systematic errors in the pull forces between the two test points. Conversely, κw for the pull test scores ranged from 0.763 to 0.920, indicating substantial to almost perfect agreement.

CONCLUSION

The pull test score was reliable despite variations in the quantified pull force for inter- and intra-rater reliability. Our findings suggest that the pull test is a robust tool for evaluating postural instability in patients with PD and that the pull force probably does not affect scoring performance.

Imbalance and gait impairment in Parkinson's disease: discussing postural instability and ataxia

Gait and balance difficulties pose significant clinical challenges in Parkinson's disease (PD). The impairment of physiological mechanisms responsible for maintaining natural orthostatism plays a central role in the pathophysiology of postural instability observed in PD. In addition to the well-known rigidity and abnormalities in muscles and joints, various brain regions involved in the regulation of posture, balance, and gait, such as the basal ganglia, cerebellum, and brainstem regions like the pontine peduncle nucleus, are affected in individuals with PD. The recognition of the cerebellum's role in PD has been increasingly acknowledged. Cortical areas and their connections are associated with freezing of gait, a type of frontal lobe ataxia commonly observed in PD. Furthermore, impairments in the peripheral nervous system, including those caused by levodopatherapy, can contribute to gait impairment and imbalance in PD patients. Consequently, individuals with PD may exhibit frontal ataxia, sensory ataxia, and even cerebellar ataxia as underlying causes of gait disturbances and imbalance, starting from the early stages of the disease. The complex interplay between dysfunctional brain regions, impaired cortical connections, and peripheral nervous system abnormalities contributes to the multifaceted nature of gait and balance difficulties in PD. Understanding the intricate mechanisms is crucial for the development of effective therapeutic approaches targeting these specific deficits in PD.

Parkinson's disease diagnosis using deep learning: A bibliometric analysis and literature review

Parkinson's Disease (PD) is a progressive neurodegenerative illness triggered by decreased dopamine secretion. Deep Learning (DL) has gained substantial attention in PD diagnosis research, with an increase in the number of published papers in this discipline. PD detection using DL has presented more promising outcomes as compared with common machine learning approaches. This article aims to conduct a bibliometric analysis and a literature review focusing on the prominent developments taking place in this area. To achieve the target of the study, we retrieved and analyzed the available research papers in the Scopus database. Following that, we conducted a bibliometric analysis to inspect the structure of keywords, authors, and countries in the surveyed studies by providing visual representations of the bibliometric data using VOSviewer software. The study also provides an in-depth review of the literature focusing on different indicators of PD, deployed approaches, and performance metrics. The outcomes indicate the firm development of PD diagnosis using DL approaches over time and a large diversity of studies worldwide. Additionally, the literature review presented a research gap in DL approaches related to incremental learning, particularly in relation to big data analysis.

Exploring Potential Predictors of Treadmill Training Effects in People With Parkinson Disease

OBJECTIVE

To explore the potential predictors of people with Parkinson disease (PD) who would benefit the most from treadmill training.

DESIGN

A cohort study.

SETTING

Medical university rehabilitation settings.

PARTICIPANTS

Seventy participants diagnosed of idiopathic PD.

INTERVENTIONS

Twelve sessions of treadmill training.

MAIN OUTCOME MEASURES

Hierarchical logistic regression models were used to explore significant predictors of the treadmill training effect with respect to 3 health domains: Unified Parkinson's Disease Rating Scales part III (UPDRS III); gait speed; Parkinson's Disease Questionnaire-39 (PDQ-39). A receiver operating characteristic (ROC) curve analysis was conducted to identify proper cut-off points for clinical use.

RESULTS

Male sex (adjusted odds ratio [OR]: 3.73, P=.036) significantly predicted the improvement of UPDRS III. Individuals with a slower baseline gait speed (cut-off: 0.92 m/s, adjusted OR: 14.06, P<.001) and higher baseline balance confidence measured by the Activity-specific Balance Confidence scale (cut-off: 84.5 points, adjusted OR: 4.66, P=.022) have greater potential to achieve clinically relevant improvements in gait speed. A poorer baseline PDQ-39 score (cut-off: 23.1, adjusted OR: 7.47, P<.001) predicted a greater quality of life improvement after treadmill training.

CONCLUSIONS

These findings provide a guideline for clinicians to easily identify suitable candidates for treadmill training. Generalization to more advanced patients with PD warrants further investigation.

Mesencephalic Locomotor Region and Presynaptic Inhibition during Anticipatory Postural Adjustments in People with Parkinson's Disease

Individuals with Parkinson's disease (PD) and freezing of gait (FOG) have a loss of presynaptic inhibition (PSI) during anticipatory postural adjustments (APAs) for step initiation. The mesencephalic locomotor region (MLR) has connections to the reticulospinal tract that mediates inhibitory interneurons responsible for modulating PSI and APAs. Here, we hypothesized that MLR activity during step initiation would explain the loss of PSI during APAs for step initiation in FOG (freezers). Freezers (n = 34) were assessed in the ON-medication state. We assessed the beta of blood oxygenation level-dependent signal change of areas known to initiate and pace gait (e.g., MLR) during a functional magnetic resonance imaging protocol of an APA task. In addition, we assessed the PSI of the soleus muscle during APA for step initiation, and clinical (e.g., disease duration) and behavioral (e.g., FOG severity and APA amplitude for step initiation) variables. A linear multiple regression model showed that MLR activity (R2 = 0.32, p = 0.0006) and APA amplitude (R2 = 0.13, p = 0.0097) explained together 45% of the loss of PSI during step initiation in freezers. Decreased MLR activity during a simulated APA task is related to a higher loss of PSI during APA for step initiation. Deficits in central and spinal inhibitions during APA may be related to FOG pathophysiology.

Freezing of Gait Is Associated with Daily Activity Limitations among Individuals with Parkinson's Disease and Mild Cognitive Impairment

This study investigated the relationship between freezing of gait and daily activities among individuals with mild cognitive impairment due to Parkinson's disease by determining differences in caregiver-reported daily activity performance between individuals with and without freezing of gait. Cross-sectional baseline data from a longitudinal cohort study were used with 24 participants. Caregivers completed the Activities of Daily Living Questionnaire (ADLQ). Using a Mann-Whitney U test, findings indicated that participants with freezing of gait reported overall higher functional impairment levels on the ADLQ (p=.001), including the household, travel, self-care, employment and recreation, and communication subscores, indicating more perceived impairment. Findings show freezing of gait is associated with daily activity limitations in the home and the community among individuals with mild cognitive impairment due to Parkinson's disease. Clinicians should consider assessing freezing of gait, as early detection can inform the selection of interventions and strategies to minimize its impact on the performance of daily activities.

A Transferable Lidar-Based Method to Conduct Contactless Assessments of Gait Parameters in Diverse Home-like Environments

Gait abnormalities in older adults are linked to increased risks of falls, institutionalization, and mortality, necessitating accurate and frequent gait assessments beyond traditional clinical settings. Current methods, such as pressure-sensitive walkways, often lack the continuous natural environment monitoring needed to understand an individual's gait fully during their daily activities. To address this gap, we present a Lidar-based method capable of unobtrusively and continuously tracking human leg movements in diverse home-like environments, aiming to match the accuracy of a clinical reference measurement system. We developed a calibration-free step extraction algorithm based on mathematical morphology to realize Lidar-based gait analysis. Clinical gait parameters of 45 healthy individuals were measured using Lidar and reference systems (a pressure-sensitive walkway and a video recording system). Each participant participated in three predefined ambulation experiments by walking over the walkway. We observed linear relationships with strong positive correlations (R2>0.9) between the values of the gait parameters (step and stride length, step and stride time, cadence, and velocity) measured with the Lidar sensors and the pressure-sensitive walkway reference system. Moreover, the lower and upper 95% confidence intervals of all gait parameters were tight. The proposed algorithm can accurately derive gait parameters from Lidar data captured in home-like environments, with a performance not significantly less accurate than clinical reference systems.

Dynamic evaluation of spine kinematics in individuals with Parkinson's disease and freezing of gait

BACKGROUND

Freezing of gait (FoG) is an episodic failure of gait exposing people with Parkinson's disease (PD) to a high risk of falling. Despite growing evidence of the interconnection between impaired trunk control and FoG, a detailed description of spinal kinematics during walking is still lacking in this population.

RESEARCH QUESTION

Do spinal alterations impact gait performance in individuals with PD and FoG?

METHODS

We analyzed kinematic data of 47 PD participants suffering (PD-FOG, N = 24) or not suffering from FoG (PD-NFOG, N = 23) and 15 healthy controls (HCO) during quiet standing and unperturbed walking. We estimated the main spinal variables (i.e., spinal length, lordosis and kyphosis angles, trunk inclination), the pelvis angles, and the shoulder-pelvis angles during gait and standing. We studied differences across conditions and groups and the relationships between postural and gait parameters using linear regression methods.

RESULTS

During standing and walking, both PD groups showed increased trunk inclination and decreased lordosis angle with respect to HCO, as well as a decreased range in variation of kyphosis angle, pelvic obliquity, and shoulder-pelvis angles. Only PD-FOG participants showed reduced range of lordosis angle and spinal length compared to HCO. PD-FOG individuals were also not able to straighten their spine during walking compared to standing. Stride length and velocity were decreased in both patient groups compared to HCO, while swing duration was reduced only in the PD-FOG group. In individuals with FoG, trunk inclination and lordosis angle showed moderate but significant positive correlations with all gait alterations.

SIGNIFICANCE

Spine alterations impacted gait performance in individuals with PD suffering from FoG. Excessive trunk inclination and poor mastering of the lordosis spinal region may create an unfavourable postural precondition for forward walking. Physical therapy should target combined spinal and stepping alterations in these individuals.

Detection and prediction of freezing of gait with wearable sensors in Parkinson's disease

Freezing of gait (FoG) is one of the most distressing symptoms of Parkinson's Disease (PD), commonly occurring in patients at middle and late stages of the disease. Automatic and accurate FoG detection and prediction have emerged as a promising tool for long-term monitoring of PD and implementation of gait assistance systems. This paper reviews the recent development of FoG detection and prediction using wearable sensors, with attention on identifying knowledge gaps that need to be filled in future research. This review searched the PubMed and Web of Science databases to collect studies that detect or predict FoG with wearable sensors. After screening, 89 of 270 articles were included. The data description, extracted features, detection/prediction methods, and classification performance were extracted from the articles. As the number of papers of this area is increasing, the performance has been steadily improved. However, small datasets and inconsistent evaluation processes still hinder the application of FoG detection and prediction with wearable sensors in clinical practice.

Residual effects of combined vibratory and plantar stimulation while seated influences plantar pressure and spatiotemporal gait measures in individuals with Parkinson's disease exhibiting freezing of gait

Introduction

Combined plantar pressure and vibratory stimulation has been shown to decrease freezing of gait (FOG) episodes and improve spatiotemporal gait parameters compared to single stimulation in Parkinson's disease (PD) patients with FOG. However, the effect of combined plantar stimulations on plantar pressure analysis has never been explored.

Methods

Forty PD patients with frequent FOG were allocated to either FOG shoes embedded with a 100 Hz vibratory stimulation at the Achilles tendons and a soft thickened silicone pad at the hallux and sole, or sham shoes with a non-working vibratory motor and a flat non-pressure silicone pad (20 patients per arm) while seated for 96 s. The objective gait and plantar pressure analysis were measured immediately after the stimulation. Outcomes included the normalized percentage of changes in percent FOG (%FOG) and plantar pressure in the heel-strike and push-off phase that were compared between pre- and post-stimulations.

Results

The FOG shoes group showed significantly decreased %FOG (81.5 ± 28.9% vs. 6.8 ± 22.1%, p < 0.001), plantar pressure in the heel-strike (47.8 ± 43.7% vs. 4.3 ± 9.8%, p < 0.001), plantar pressure in the push-off (57.7 ± 59.6% vs. 6.2 ± 11.6%, p < 0.001), force time integral (FTI) (40.9 ± 32.5% vs. 6.6 ± 17.3%, p < 0.001), and decreased heel contact time (19.3 ± 12.3% vs. 22.7 ± 32.5%, p < 0.001) when compared to the sham group. There was a strong negative correlation between %FOG and peak plantar pressure (r = -0.440, p = 0.005), plantar pressure in the heel-strike (r = -0.847, p < 0.001).

Conclusion

Our study demonstrated that the FOG shoe could decrease FOG episodes by improving the heel-strike pressure, toe push-off and normalized heel-to-toe plantar pressure, suggesting that modification inputs from the peripheral sensory systems might significant improvement in FOG in PD.

Effects of ankle isokinetic training on muscle strength and balance amongst older women with mild Parkinson's disease: A randomised trial

BACKGROUND

Patients with Parkinson's disease frequently experience problems with balance and gait.

OBJECTIVE

This study examined the influences of regular ankle isokinetic muscle strength training on muscle strength and balance ability amongst elderly women with mild Parkinson's disease.

METHODS

A total of 55 elderly women with mild Parkinson's disease were randomly divided into the experimental group (n= 28) and the control group (n= 27) for 16 weeks. The experimental group was trained for 16 weeks by using isokinetic muscle strength training.

RESULTS

After 16 weeks of training in the experimental group, the peak torque (PT) of ankle (average of the left and right sides) dorsiflexion, plantarflexion, eversion and inversion, and the standing balance index revealed that the left and right stability and overall stability indexes significantly increased by 25.9%, 43.5%, 62.7%, 82.8%, 37.1% and 32.2%, respectively (p< 0.05). The experimental group exhibited significantly increased PT of ankle dorsiflexion, plantarflexion, eversion and inversion. Moreover, the left and right stability and overall stability indexes were significantly improved compared with those of the control group (p< 0.05). This study found a linear regression relationship between the PT of ankle inversion and overall stability index.

CONCLUSION

This study determined that ankle isokinetic muscle strength training improved ankle dorsiflexion, plantarflexion, eversion and inversion muscle strength, and balance ability amongst elderly women with mild Parkinson's disease. However, it did not improve stability in the anterior and posterior directions. Ankle inversion muscle strength is more likely to affect overall balance.

Subthalamic and pallidal neurons are modulated during externally cued movements in Parkinson's disease

External sensory cues can reduce freezing of gait in people with Parkinson's disease (PD), yet the role of the basal ganglia in these movements is unclear. We used microelectrode recordings to examine modulations in single unit (SU) and oscillatory local field potentials (LFP) during auditory-cued rhythmic pedaling movements of the feet. We tested five blocks of increasing cue frequencies (1 Hz, 1.5 Hz, 2 Hz, 2.5 Hz, and 3 Hz) in 24 people with PD undergoing deep brain stimulation surgery of the subthalamic nucleus (STN) or globus pallidus internus (GPi). Single unit firing and beta band LFPs (13-30 Hz) in response to movement onsets or cue onsets were examined. We found that the timing accuracy of foot pedaling decreased with faster cue frequencies. Increasing cue frequencies also attenuated firing rates in both STN and GPi neurons. Peak beta power in the GPi and STN showed different responses to the task. GPi beta power showed persistent suppression with fast cues and phasic modulation with slow cues. STN beta power showed enhanced beta synchronization following movement. STN beta power also correlated with rate of pedaling. Overall, we showed task-related responses in the GPi and STN during auditory-cued movements with differential roles in sensory and motor control. The results suggest a role for both input and output basal ganglia nuclei in auditory rhythmic pacing of gait-like movements in PD.

Comparison of state-of-the-art deep learning architectures for detection of freezing of gait in Parkinson's disease

Introduction

Freezing of gait (FOG) is one of the most debilitating motor symptoms experienced by patients with Parkinson's disease (PD). FOG detection is possible using acceleration data from wearable sensors, and a convolutional neural network (CNN) is often used to determine the presence of FOG epochs. We compared the performance of a standard CNN for the detection of FOG with two more complex networks, which are well suited for time series data, the MiniRocket and the InceptionTime.

Methods

We combined acceleration data of people with PD across four studies. The final data set was split into a training (80%) and hold-out test (20%) set. A fifth study was included as an unseen test set. The data were windowed (2 s) and five-fold cross-validation was applied. The CNN, MiniRocket, and InceptionTime models were evaluated using a receiver operating characteristic (ROC) curve and its area under the curve (AUC). Multiple sensor configurations were evaluated for the best model. The geometric mean was subsequently calculated to select the optimal threshold. The selected model and threshold were evaluated on the hold-out and unseen test set.

Results

A total of 70 participants (23.7 h, 9% FOG) were included in this study for training and testing, and in addition, 10 participants provided an unseen test set (2.4 h, 11% FOG). The CNN performed best (AUC = 0.86) in comparison to the InceptionTime (AUC = 0.82) and MiniRocket (AUC = 0.76) models. For the CNN, we found a similar performance for a seven-sensor configuration (lumbar, upper and lower legs and feet; AUC = 0.86), six-sensor configuration (upper and lower legs and feet; AUC = 0.87), and two-sensor configuration (lower legs; AUC = 0.86). The optimal threshold of 0.45 resulted in a sensitivity of 77% and a specificity of 58% for the hold-out set (AUC = 0.72), and a sensitivity of 85% and a specificity of 68% for the unseen test set (AUC = 0.90).

Conclusion

We confirmed that deep learning can be used to detect FOG in a large, heterogeneous dataset. The CNN model outperformed more complex networks. This model could be employed in future personalized interventions, with the ultimate goal of using automated FOG detection to trigger real-time cues to alleviate FOG in daily life.

Triggers for freezing of gait in individuals with Parkinson's disease: a systematic review

Background

Freezing of Gait (FOG) is a motor symptom frequently observed in advanced Parkinson's disease. However, due to its paroxysmal nature and diverse presentation, assessing FOG in a clinical setting can be challenging. Before FOG can be fully investigated, it is critical that a reliable experimental setting is established in which FOG can be evoked in a standardized manner, but the efficacy of various gait tasks and triggers for eliciting FOG remains unclear.

Objectives

This study aimed to conduct a systematic review of the existing literature and evaluate the available evidence for the relationship between specific motor tasks, triggers, and FOG episodes in individuals with Parkinson's disease (PwPD).

Methods

We conducted a literature search on four online databases (PubMed, Web of Science, EMBASE, and Cochrane Library) using the keywords "Parkinson's disease," "Freezing of Gait", "triggers" and "tasks". A total of 128 articles met the inclusion criteria and were included in our analysis.

Results

The review found that a wide range of gait tasks were employed in studies assessing FOG among PD patients. However, three tasks (turning, dual tasking, and straight walking) emerged as the most frequently used. Turning (28%) appears to be the most effective trigger for eliciting FOG in PwPD, followed by walking through a doorway (14%) and dual tasking (10%).

Conclusion

This review thereby supports the utilisation of turning, especially a 360-degree turn, as a reliable trigger for FOG in PwPD. This finding could be beneficial to clinicians conducting clinical evaluations and researchers aiming to assess FOG in a laboratory environment.

A meta-analysis identifies factors predicting the future development of freezing of gait in Parkinson's disease

Freezing of gait (FOG) is a debilitating problem that is common among many, but not all, people with Parkinson's disease (PD). Numerous attempts have been made at treating FOG to reduce its negative impact on fall risk, functional independence, and health-related quality of life. However, optimal treatment remains elusive. Observational studies have recently investigated factors that differ among patients with PD who later develop FOG, compared to those who do not. With prediction and prevention in mind, we conducted a systematic review and meta-analysis of publications through 31.12.2022 to identify risk factors. Studies were included if they used a cohort design, included patients with PD without FOG at baseline, data on possible FOG predictors were measured at baseline, and incident FOG was assessed at follow-up. 1068 original papers were identified, 38 met a-priori criteria, and 35 studies were included in the meta-analysis (n = 8973; mean follow-up: 4.1 ± 2.7 years). Factors significantly associated with a risk of incident FOG included: higher age at onset of PD, greater severity of motor symptoms, depression, anxiety, poorer cognitive status, and use of levodopa and COMT inhibitors. Most results were robust in four subgroup analyses. These findings indicate that changes associated with FOG incidence can be detected in a subset of patients with PD, sometimes as long as 12 years before FOG manifests, supporting the possibility of predicting FOG incidence. Intriguingly, some of these factors may be modifiable, suggesting that steps can be taken to lower the risk and possibly even prevent the future development of FOG.

The effect of doorway characteristics on freezing of gait in Parkinson's disease

Background

Freezing of gait is a debilitating symptom in Parkinson's disease, during which a sudden motor block prevents someone from moving forward. Remarkably, doorways can provoke freezing. Most research has focused on the influence of doorway width, and little is known about other doorway characteristics influencing doorway freezing.

Objective

Firstly, to provide guidelines on how to design doorways for people with freezing. Secondly, to compare people with doorway freezing to people without doorway freezing, and to explore the underlying mechanisms of doorway freezing.

Methods

We designed a web-based, structured survey consisting of two parts. Part I (n = 171 responders), open to people with Parkinson's disease with freezing in general, aimed to compare people with doorway freezing to people without doorway freezing. We explored underlying processes related to doorway freezing with the Gait-Specific Attention Profile (G-SAP), inquiring about conscious movement processes occurring during doorway passing. Part II (n = 60), open for people experiencing weekly doorway freezing episodes, inquired about the influence of specific doorway characteristics on freezing.

Results

People with doorway freezing (69% of Part I) had higher freezing severity, longer disease duration, and scored higher on all sub scores of the G-SAP (indicating heightened motor, attentional, and emotional thoughts when passing through doorways) than people without doorway freezing. The main categories provoking doorway freezing were: dimensions of the door and surroundings, clutter around the door, lighting conditions, and automatic doors.

Conclusion

We provide recommendations on how to maximally avoid freezing in a practical setting. Furthermore, we suggest that doorways trigger freezing based on visuomotor, attentional, and emotional processes.

The reliability and validity of the 3-m backward walk test in people with Parkinson's disease

BACKGROUND

People with Parkinson's disease (PwPD) lose the ability in backward walking which is an important part of mobility in daily life. The 3-m backward walk test (3MBWT) evaluates backward walking; however, its reliability and validity have not been examined in PwPD yet.

AIMS

To examine (1) the test-retest reliability of the 3MBWT in PwPD; (2) the minimum detectable change in the 3MBWT times; (3) the concurrent and known-groups validity of the 3MBWT; and (4) the optimum cutoff time which best discriminates fallers from non-fallers with Parkinson's disease (PD).

METHODS

This cross-sectional study included 36 PwPD and 33 healthy people. The 3MBWT was conducted with the 10-m walk test, timed up and go test, Berg Balance Scale, four square step test, activity-specific balance confidence scale, Movement Disorders Society Sponsored Unified Parkinson's Disease Rating Scale, and Hoehn and Yahr Scale.

RESULTS

The 3MBWT demonstrated excellent test-retest reliability (ICC = 0.965). The MDC of 2.13 s was determined. The 3MBWT had moderate to high correlations with the other outcome measures (correlation coefficient ranged from -0.592 to 0.858). On the 3MBWT times, there were significant differences between PwPD and healthy people, and between fallers and non-fallers with PD (p < 0.001 and p < 0.001, respectively). A 3MBWT time of 10.31 s was found to best discriminate fallers from non-fallers with PD.

CONCLUSIONS

The 3MBWT is a reliable, valid, and easy to administer outcome measure to assess backward walking performance in PwPD, indicating it to be used in practice and research.

Investigating gait-responsive somatosensory cueing from a wearable device to improve walking in Parkinson's disease

Freezing-of-gait (FOG) and impaired walking are common features of Parkinson's disease (PD). Provision of external stimuli (cueing) can improve gait, however, many cueing methods are simplistic, increase task loading or have limited utility in a real-world setting. Closed-loop (automated) somatosensory cueing systems have the potential to deliver personalised, discrete cues at the appropriate time, without requiring user input. Further development of cue delivery methods and FOG-detection are required to achieve this. In this feasibility study, we aimed to test if FOG-initiated vibration cues applied to the lower-leg via wearable devices can improve gait in PD, and to develop real-time FOG-detection algorithms. 17 participants with Parkinson's disease and daily FOG were recruited. During 1 h study sessions, participants undertook 4 complex walking circuits, each with a different intervention: continuous rhythmic vibration cueing (CC), responsive cueing (RC; cues initiated by the research team in response to FOG), device worn with no cueing (NC), or no device (ND). Study sessions were grouped into 3 stages/blocks (A-C), separated by a gap of several weeks, enabling improvements to circuit design and the cueing device to be implemented. Video and onboard inertial measurement unit (IMU) data were analyzed for FOG events and gait metrics. RC significantly improved circuit completion times demonstrating improved overall performance across a range of walking activities. Step frequency was significantly enhanced by RC during stages B and C. During stage C, > 10 FOG events were recorded in 45% of participants without cueing (NC), which was significantly reduced by RC. A machine learning framework achieved 83% sensitivity and 80% specificity for FOG detection using IMU data. Together, these data support the feasibility of closed-loop cueing approaches coupling real-time FOG detection with responsive somatosensory lower-leg cueing to improve gait in PD.

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and people with early Parkinson's disease: Study protocol for a cross-sectional Mobile Brain/Body Imaging (MoBI) study

Background

Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks.

Methods

The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson's Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics.

Discussion

This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems.

Clinical Trial Registration

ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).

Role of the functional head impulse test in evaluating vestibulo-ocular reflex abnormalities in individuals with Parkinson's disease

PURPOSE

To assess vestibular-ocular reflex (VOR) function in patients with Parkinson's disease (PD) using a new method called functional head impulse test (fHIT).

STUDY DESIGN

Case-control study.

SETTING

Tertiary medical center.

PARTICIPANTS

Twenty individuals with PD were recruited for PD group, and twenty healthy individuals for the control group. Ages of both groups ranged from 47 to 76 years.

MAIN OUTCOME MEASURES

According to the modified Hoehn-Yahr score, PD group was classified as an early stage with a range of 1-2.5 and a mid-late stage with a range of 3-5. Percentage of correct answers (%CA) was calculated using fHIT for lateral, anterior and posterior semicircular canal (SCC) planes.

RESULTS

PD group had statistically lower fHIT %CA in the right lateral, left lateral, and left posterior SCC planes compared to control group (p < .05). There was no statistical difference between two PD severity groups and functional VOR abnormality.

CONCLUSION

It was concluded that the functional VOR in the right lateral and left lateral and left posterior SCC plane was affected in individuals with PD. Our results show that impaired VOR and reduced dynamic visual acuity should be considered in individuals with PD for vestibular rehabilitation exercises.

Arm swing asymmetry in people with Parkinson's disease and its relationship with gait: A systematic review and meta-analysis

BACKGROUND

Individuals with Parkinson's disease present arm swing alterations that can adversely affect their locomotion.

OBJECTIVE

To identify differences in arm swing asymmetry (ASA) between individuals with Parkinson's disease (PD) and healthy individuals and to investigate the relationship between ASA, temporal-spatial gait parameters, and disease progression.

METHODS

A literature search was conducted in PubMed, Scopus, ProQuest, Web of Science, and EBSCOhost up to February 2023. Cross-sectional studies evaluating parameters of arm swing (AS) and ASA were included. Methodological quality was assessed using the Critical Appraisal Checklist, and the quality of the evidence was measured with a modified Grading of Recommendations Assessment, Development, and Evaluation.

RESULTS

Fourteen studies were included in the systematic review (1130 participants). Irrespective of the medication phase (ON or OFF) and the type of walk test employed, the meta-analysis showed moderate-quality evidence that individuals with PD have increased ASA amplitude (SMD = 0.84; 95% CI: 0.69, 0.99; I²= 0%).Very low-quality evidence suggests higher ASA velocity (SMD=0.64; 95% CI: 0.24, 1.05; I²=59%) and lower AS amplitude on both the most affected (ES = -1.99, 95% CI: -3.04, -0.94, I2: 91%) and the least affected sides (ES = -0.75, 95% CI: -1.05, -0.44; I²=66%). Meta-regression indicated that ASA is inversely related to disease duration (Z: -2.4892, P< 0.05) and motor symptoms progression (Z: -2.1336, P< 0.05).

CONCLUSIONS

Regardless of the medication phase and the type of walk test employed, individuals with PD exhibited greater ASA and decreased AS amplitude than healthy individuals. ASA decreases as the disease progresses and symptoms worsen.

Nordic walking training in persons with Parkinson's disease: Individualized prescription-A case series

INTRODUCTION

Physical therapy interventions for patients with Parkinson's disease prioritize task-specific exercise to address gait and motor dysfunction. Nordic walking (NW) is a moderate intensity exercise promoting walking speed and rhythm. This case series describes the application of customized NW training in individuals with varied severity of Parkinson's gait dysfunction and the outcomes specific to gait, motor and non-motor symptoms; and NW engagement and retention in the follow-up phase.

CASE DESCRIPTION

Three individuals with idiopathic PD (two males and one female; ages 59-69; Hoehn & Yahr stages II-III) participated. Supervised NW training phase included 15 one-hour sessions over 6-weeks, individually progressed for each participant. During the 3-month follow-up phase independent NW exercise was prescribed 3 times a week. Primary outcome measures examined gait function and impairment-based measures assessed Parkinson's motor and nonmotor symptoms.

OUTCOMES

Participants improved in: 10-Meter walk-fast speed (0.13, 0.18, 0.15 m/s; respectively); 6-Minute Walk distance (137.5, 56.4, 129.4 m, respectively); Unified Parkinson's Disease Rating Scale-Motor Score (-6, -7, -14, respectively); and all Timed-Up-Go subtests. Participant 2 had 44.4% decline in freezing episodes and reduced fall rate. Participants' gains were retained at the 3-month follow-up.

DISCUSSION

This case series suggests that NW has therapeutic benefits for three individuals with varied Parkinson's gait dysfunction. Independent NW exercise was sustained post-training and motor and gait function gains were retained.

Spinal Cord Stimulation for Gait Disorders in Parkinson's Disease and Atypical Parkinsonism: A Systematic Review of Preclinical and Clinical Data

BACKGROUND

Falls in extrapyramidal disorders, particularly Parkinson's disease (PD), multisystem atrophy (MSA), and progressive supranuclear palsy (PSP), are key milestones affecting patients' quality of life, incurring increased morbidity/mortality and high healthcare costs. Unfortunately, gait and balance in parkinsonisms respond poorly to currently available treatments. A serendipitous observation of improved gait and balance in patients with PD receiving spinal cord stimulation (SCS) for back pain kindled an interest in using SCS to treat gait disorders in parkinsonisms.

OBJECTIVES

We reviewed preclinical and clinical studies of SCS to treat gait dysfunction in parkinsonisms, covering its putative mechanisms and efficacies.

MATERIALS AND METHODS

Preclinical studies in animal models of PD and clinical studies in patients with PD, PSP, and MSA who received SCS for gait disorders were included. The main outcome assessed was clinical improvement in gait, together with outcome measures used and possible mechanism of actions.

RESULTS

We identified 500 references, and 45 met the selection criteria and have been included in this study for analysis. Despite positive results in animal models, the outcomes in human studies are inconsistent.

CONCLUSIONS

The lack of blind and statistically powered studies, the heterogeneity in patient selection and study outcomes, and the poor understanding of the underlying mechanisms of action of SCS are some of the limiting factors in the field. Addressing these limitations will allow us to draw more reliable conclusions on the effects of SCS on gait and balance in extrapyramidal disorders.

Upregulation of the parietal cortex improves freezing of gait in Parkinson's disease

BACKGROUND The posterior parietal cortex (PPC) is a key brain area for visuospatial processing and locomotion. It has been repetitively shown to be involved in the neural correlates of freezing of gait (FOG), a common symptom of Parkinson's disease (PD). However, current neuroimaging modalities do not allow to precisely determine the role of the PPC during real FOG episodes. OBJECTIVES The purpose of this study was to modulate the PPC cortical excitability using repetitive transcranial magnetic stimulation (rTMS) to determine whether the PPC contributes to FOG or compensates for dysfunctional neural networks to reduce FOG. METHODS Fourteen participants with PD who experience freezing took part in a proof of principle study consisting of three experimental sessions targeting the PPC with inhibitory, excitatory, and sham rTMS. Objective FOG outcomes and cortical excitability measurements were acquired before and after each stimulation protocol. RESULTS Increasing PPC excitability resulted in significantly fewer freezing episodes and percent time frozen during a FOG-provoking task. This reduction in FOG most likely emerged from the trend in PPC inhibiting the lower leg motor cortex excitability. CONCLUSION Our results suggest that the recruitment of the PPC is linked to less FOG, providing support for the beneficial role of the PPC upregulation in preventing FOG. This could potentially be linked to a reduction of the cortical input burden on the basal ganglia prior to FOG. Excitatory rTMS interventions targeting the PPC may have the potential to reduce FOG.

Multivariate CNN Model for Human Locomotion Activity Recognition with a Wearable Exoskeleton Robot

This study introduces a novel convolutional neural network (CNN) architecture, encompassing both single and multi-head designs, developed to identify a user's locomotion activity while using a wearable lower limb robot. Our research involved 500 healthy adult participants in an activities of daily living (ADL) space, conducted from 1 September to 30 November 2022. We collected prospective data to identify five locomotion activities (level ground walking, stair ascent/descent, and ramp ascent/descent) across three terrains: flat ground, staircase, and ramp. To evaluate the predictive capabilities of the proposed CNN architectures, we compared its performance with three other models: one CNN and two hybrid models (CNN-LSTM and LSTM-CNN). Experiments were conducted using multivariate signals of various types obtained from electromyograms (EMGs) and the wearable robot. Our results reveal that the deeper CNN architecture significantly surpasses the performance of the three competing models. The proposed model, leveraging encoder data such as hip angles and velocities, along with postural signals such as roll, pitch, and yaw from the wearable lower limb robot, achieved superior performance with an inference speed of 1.14 s. Specifically, the F-measure performance of the proposed model reached 96.17%, compared to 90.68% for DDLMI, 94.41% for DeepConvLSTM, and 95.57% for LSTM-CNN, respectively.

A Physical Rehabilitation Approach for Parkinson's Disease: A Systematic Literature Review

Parkinson's disease (PD) is one of the most common neurological ailments. With diverse motor affectations (postural instability, resting tremor, bradykinesia, and rigidity), people with Parkinson's disease (PwP) have a broad spectrum of non-motor symptoms. These include autonomic function changes, cognitive deterioration, neuropsychiatric difficulties, and sleep interruptions. Psychological disturbances, such as anxiety and sadness, are common among PwP. This discomfort is often accompanied by a decrease in general functioning, both at work and in social contacts. Furthermore, people who are experiencing psychological distress have a quick decrease in both physical and cognitive capacities. Furthermore, Pwp who also suffer from anxiety and depression are more likely to acquire dementia. It is worth noting that studies have shown good outcomes in the treatment of physical disabilities in PWP and the various therapeutics available for each affected body part, such as in the legs when they have walking problems, resting tremor in their hands, or micrography, which is a common symptom in these patients. The medical research databases PubMed/Medline, Google Scholar, and the Cochrane Library were used to look for relevant materials. Upon meticulous scrutiny, a thorough investigation was conducted on the papers at hand. A total of 10 publications were meticulously selected based on stringent qualifying criteria. The present investigation examines various perspectives regarding the physical rehabilitation of individuals diagnosed with PD. The majority of therapeutic interventions employed revolve around cutting-edge technologies, such as virtual reality (VR), combined with exercise regimens. These interventions have demonstrated notable statistical significance in terms of enhancing various physical aspects, including endurance, performance, gait capacity, perception, and overall independence in daily life activities. One of the gathered studies makes use of the therapeutic benefits of yoga to help PwP deal with their anxiety and improve their mental health. Based on the aforementioned information, further investigation is required to ascertain the optimal approach for physical rehabilitation management and develop diverse strategies aimed at assisting individuals with PD in attaining physical autonomy.