Arm swing as a potential new prodromal marker of Parkinson's disease

Feasibility of differentiating gait in Parkinson's disease and spinocerebellar degeneration using a pose estimation algorithm in two-dimensional video

BACKGROUND

Although pose estimation algorithms have been used to analyze videos of patients with Parkinson's disease (PD) to assess symptoms, their feasibility for differentiating PD from other neurological disorders that cause gait disturbances has not been evaluated yet. We aimed to determine whether it was possible to differentiate between PD and spinocerebellar degeneration (SCD) by analyzing video recordings of patient gait using a pose estimation algorithm.

METHODS

We videotaped 82 patients with PD and 61 patients with SCD performing the timed up-and-go test. A pose estimation algorithm was used to extract the coordinates of 25 key points of the participants from these videos. A transformer-based deep neural network (DNN) model was trained to predict PD or SCD using the extracted coordinate data. We employed a leave-one-participant-out cross-validation method to evaluate the predictive performance of the trained model using accuracy, sensitivity, and specificity. As there were significant differences in age, weight, and body mass index between the PD and SCD groups, propensity score matching was used to perform the same experiment in a population that did not differ in these clinical characteristics.

RESULTS

The accuracy, sensitivity, and specificity of the trained model were 0.86, 0.94, and 0.75 for all participants and 0.83, 0.88, and 0.78 for the participants extracted by propensity score matching.

CONCLUSION

The differentiation of PD and SCD using key point coordinates extracted from gait videos and the DNN model was feasible and could be used as a collaborative tool in clinical practice and telemedicine.

Validity of the Short Weekly Calendar Planning Activity in patients with Parkinson disease and nonmanifesting LRRK2 and GBA carriers

BACKGROUND AND PURPOSE

Subtle executive dysfunction is common in people newly diagnosed with Parkinson disease (PD), even when general cognitive abilities are intact. This study examined the Short Weekly Calendar Planning Activity (WCPA-10)'s known-group construct validity, comparing persons with PD to healthy controls (HCs) and nonmanifesting carriers of LRRK2 and GBA gene mutations to HCs. Additionally, convergent and ecological validity was examined.

METHODS

The study included 73 participants: 22 with idiopathic PD (iPD) who do not carry any of the founder GBA mutations or LRRK2-G2019S, 29 nonmanifesting carriers of the G2019S-LRRK2 (n = 14) and GBA (n = 15) mutations, and 22 HCs. Known-group validity was determined using the WCPA-10, convergent validity by also using the Montreal Cognitive Assessment (MoCA) and Color Trails Test (CTT), and ecological validity by using the WCPA-10, Schwab and England Activities of Daily Living Scale (SE ADL), and Physical Activity Scale for the Elderly (PASE).

RESULTS

Known-group validity of the WCPA-10 was established for the iPD group only; they followed fewer rules (p = 0.020), were slower (p = 0.003) and less efficient (p = 0.001), used more strategies (p = 0.017) on the WCPA-10, and achieved significantly lower CTT scores (p < 0.001) than the HCs. The nonmanifesting carriers and HCs were similar on all cognitive tests. Convergent and ecological validity of the WCPA-10 were partially established, with few correlations between WCPA-10 outcome measures and the MoCA (r = 0.50, r = 0.41), CTT-2 (r = 0.43), SE ADL (r = 0.41), and PASE (r = 0.54, r = 0.46, r = 0.31).

CONCLUSIONS

This study affirms the known-group validity for most (four) WCPA-10 scores and partially confirms its convergent and ecological validity for PD.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art

Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Nordic walking and arm swing asymmetry in people with Parkinson's disease: protocol for a randomised clinical trial

People with Parkinson's disease (PD) face disruptions in arm swing (AS) motion during walking, including a reduction in amplitude and an increase in asymmetry. Both conditions are detrimental to gait performance. Nordic walking (NW) is a walking modality that uses poles and can positively affect the parameters of AS. This study aims to compare an NW with a free walking (FW) protocol and investigate its effects on AS asymmetry, AS amplitude and gait parameters in people with PD. Twenty-eight people with PD, stages 1-3 on the Hoehn and Yahr Scale, will be randomly assigned to the NW training group (n=14) or the FW training group (n=14). The primary outcomes are amplitude asymmetry of AS (%) and AS amplitude (deg). We will also analyse temporospatial measurements during walking, functional mobility and quality of life. Blinded researchers will conduct evaluations at baseline (T0), postintervention (T1) and at 1 month follow-up (T2). Participants will complete 24 supervised NW or FW training sessions for 12 weeks. This is the first study to address the effects of NW on the asymmetry of AS, AS amplitude and its influence on gait parameters. We hypothesise that an NW programme in PD will reduce the asymmetry and increase the AS amplitude during gait to a greater extent than FW. The results of this study may provide new evidence to understand the effects of NW on gait in people with PD. The study was registered in ClinicalTrial.gov (NCT06342271).

Movement disorders following mechanical thrombectomy resulting in ischemic lesions of the basal ganglia: An emerging clinical entity

BACKGROUND AND PURPOSE

Post-stroke movement disorders (PMDs) following ischemic lesions of the basal ganglia (BG) are a known entity, but data regarding their incidence are lacking. Ischemic strokes secondary to proximal middle cerebral artery (MCA) occlusion treated with thrombectomy represent a model of selective damage to the BG. The aim of this study was to assess the prevalence and features of movement disorders after selective BG ischemia in patients with successfully reperfused acute ischemic stroke (AIS).

METHODS

We enrolled 64 consecutive subjects with AIS due to proximal MCA occlusion treated with thrombectomy. Patients were clinically evaluated by a movement disorders specialist for PMDs onset at baseline, and after 6 and 12 months.

RESULTS

None of the patients showed an identifiable movement disorder in the subacute phase of the stroke. At 6 and 12 months, respectively, 7/25 (28%) and 7/13 (53.8%) evaluated patients developed PMDs. The clinical spectrum of PMDs encompassed parkinsonism, dystonia and chorea, either isolated or combined. In most patients, symptoms were contralateral to the lesion, although a subset of patients presented with bilateral involvement and prominent axial signs.

CONCLUSION

Post-stroke movement disorders are not uncommon in long-term follow-up of successfully reperfused AIS. Follow-up conducted by a multidisciplinary team is strongly advisable in patients with selective lesions of the BG after AIS, even if asymptomatic at discharge.

Visual feedback improves propulsive force generation during treadmill walking in people with Parkinson disease

Persons with Parkinson's disease experience gait alterations, such as reduced step length. Gait dysfunction is a significant research priority as the current treatments targeting gait impairment are limited. This study aimed to investigate the effects of visual biofeedback on propulsive force during treadmill walking in persons with Parkinson's. Sixteen ambulatory persons with Parkinson's participated in the study. They received real-time biofeedback of anterior ground reaction force during treadmill walking at a constant speed. Peak propulsive force values were measured and normalized to body weight. Spatiotemporal parameters were also assessed, including stride length and double support percent. Persons with Parkinson's significantly increased peak propulsive force during biofeedback compared to baseline (p <.0001, Cohen's dz = 1.69). Variability in peak anterior ground reaction force decreased across repeated trials (p <.0001, dz = 1.51). While spatiotemporal parameters did not show significant changes individually, stride length and double support percent improved marginally during biofeedback trials. Persons with Parkinson's can increase propulsive force with visual biofeedback, suggesting the presence of a propulsive reserve. Though stride length did not significantly change, clinically meaningful improvements were observed. Targeting push-off force through visual biofeedback may offer a potential rehabilitation technique to enhance gait performance in Persons with Parkinson's. Future studies could explore the long-term efficacy of this intervention and investigate additional strategies to improve gait in Parkinson's disease.

Identifying Subtle Motor Deficits Before Parkinson's Disease is Diagnosed: What to Look for?

Motor deficits typical of Parkinson's disease (PD), such as gait and balance disturbances, tremor, reduced arm swing and finger movement, and voice and breathing changes, are believed to manifest several years prior to clinical diagnosis. Here we describe the evidence for the presence and progression of motor deficits in this pre-diagnostic phase in order to provide suggestions for the design of future observational studies for an effective, quantitatively oriented investigation. On the one hand, these future studies must detect these motor deficits in as large (potentially, population-based) cohorts as possible with high sensitivity and specificity. On the other hand, they must describe the progression of these motor deficits in the pre-diagnostic phase as accurately as possible, to support the testing of the effect of pharmacological and non-pharmacological interventions. Digital technologies and artificial intelligence can substantially accelerate this process.

Gait Analysis with Wearable Sensors in Isolated REM Sleep Behavior Disorder Associated with Phenoconversion: An Explorative Study

Background

Gait disturbance is a vital characteristic of motor manifestation in α- synucleinopathies, especially Parkinson's disease. Subtle gait alterations are present in isolated rapid eye movement sleep behavior disorder (iRBD) patients before phenoconversion; it is yet unclear, if gait analysis may predict phenoconversion.

Objective

To investigate subtle gait alterations and explore whether gait analysis using wearable sensors is associated with phenoconversion of iRBD to α-synucleinopathies.

Methods

Thirty-one polysomnography-confirmed iRBD patients and 33 healthy controls (HCs) were enrolled at baseline. All participants walked for a minute while wearing 6 inertial sensors on bilateral wrists, ankles, and the trunk (sternal and lumbar region). Three conditions were tested: (i) normal walking, (ii) fast walking, and (iii) dual-task walking.

Results

Decreased arm range of motion and increased gait variation (stride length, stride time and stride velocity) discriminate converters from HCs at baseline. After an average of 5.40 years of follow-up, 10 patients converted to neurodegenerative diseases (converters). Cox regression analysis showed higher value of stride length asymmetry under normal walking condition to be associated with an early conversion of iRBD to α- synucleinopathies (adjusted HR 4.468, 95% CI 1.088- 18.349, p = 0.038).

Conclusions

Stride length asymmetry is associated with progression to α- synucleinopathies in patients with iRBD. Gait analysis with wearable sensors may be useful for screening, monitoring, and risk stratification for disease-modifying therapy trials in patients with iRBD.

Mastering Our Own Magic in the Evolution Toward Precision Practice

Edelle (Edee) Field-Fote, PT, PhD, FASIA, FAPTA, the 54th Mary McMillan lecturer, is director of the Shepherd Center Spinal Cord Injury Research Program & Hulse Laboratory; professor in the division of physical therapy at Emory University School of Medicine; and professor of the practice in the school of biological sciences at the Georgia Institute of Technology. In her role as the director of spinal cord injury (SCI) research at Shepherd Center, Field-Fote leads a team dedicated to improving motor function in people with SCI through the development of neuromodulation and neurorehabilitation approaches informed by the latest neuroscience research and guided by outcomes that have meaning for people with SCI. With a clinical background as a physical therapist, PhD training in a preclinical model of SCI, and postdoctoral training in motor control physiology, her 25-plus years of SCI research have spanned the breadth of basic and clinical/translational research related to SCI. Dr Field-Fote has conducted randomized clinical trials with funding from the National Institutes of Health since 1997; other clinical trials in her lab have been funded by the Department of Defense, the National Institute on Disability Independent Living and Rehabilitation Research, and numerous foundations. Field-Fote is the recipient of multiple honors from the American Physical Therapy Association (APTA) and its components. She is a Fellow of APTA and a Fellow of the American Spinal Injury Association. She has also served in numerous APTA and APTA component appointed or elected positions and as a member and president of the Foundation for Physical Therapy Research Board of Trustees.

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.

A Comparative Analysis of Symmetry Indices for Spatiotemporal Gait Features in Early Parkinson's Disease

This study compared the five most commonly used equations for calculating gait symmetry in discrete variables among Parkinson's disease patients. Twelve patients (five women and seven men) performed ten consecutive gait trials on a 10 m walkway. Gait data were collected using eight optoelectronic cameras (100 fr/s). The analysis focused on various spatiotemporal parameters, including cadence, step time, stride time, single support, double support, walking speed, step length, stride length, step width, and foot angle. Five symmetry indices were calculated for each trial rather than averaging the ten recorded trials. The variability in and reliability of each symmetry equation were assessed using the coefficient of variation (CV) and intraclass correlation coefficient (ICC), respectively. Additionally, Bland-Altman plots were produced to visualize the agreement between each pair of methods for each spatiotemporal parameter. The results revealed that the symmetry ratio method exhibited lower variability and higher reliability compared with the other four indices across all spatiotemporal gait parameters. However, it was found that the reliability of a single trial was generally poor, regardless of the symmetry calculation formula used. Therefore, we recommend basing measurements of gait asymmetry in Parkinson's disease on multiple trials.

Detection and Characterization of Walking Bouts Using a Single Wrist-Worn Accelerometer in Free-living Conditions

Detection and characterization of abnormalities of movement are important to develop a method for detecting early signs of Parkinson's disease (PD). Most of the current research in detection of characteristic reduction of movements due to PD, known as parkinsonism, requires using a set of invasive sensors in a clinical or controlled environment. Actigraphy has been widely used in medical research as a non-invasive data acquisition method in free-living conditions for long periods of time. The proposed algorithm uses triaxial accelerometer data obtained through actigraphy to detect walking bouts at least 10 seconds long and characterize them using cadence and arm swing. Accurate detection of walking periods is the first step toward the characterization of movement based on gait abnormalities. The algorithm was based on a Walking Score (WS) derived using the value of the auto-correlation function (ACF) for the Resultant acceleration vector. The algorithm achieved a precision of 0.90, recall of 0.77, and F1 score of 0.83 compared to the expert scoring for walking bout detection. We additionally described a method to measure arm swing amplitude.

Wearable movement-tracking data identify Parkinson's disease years before clinical diagnosis

Parkinson's disease is a progressive neurodegenerative movement disorder with a long latent phase and currently no disease-modifying treatments. Reliable predictive biomarkers that could transform efforts to develop neuroprotective treatments remain to be identified. Using UK Biobank, we investigated the predictive value of accelerometry in identifying prodromal Parkinson's disease in the general population and compared this digital biomarker with models based on genetics, lifestyle, blood biochemistry or prodromal symptoms data. Machine learning models trained using accelerometry data achieved better test performance in distinguishing both clinically diagnosed Parkinson's disease (n = 153) (area under precision recall curve (AUPRC) 0.14 ± 0.04) and prodromal Parkinson's disease (n = 113) up to 7 years pre-diagnosis (AUPRC 0.07 ± 0.03) from the general population (n = 33,009) compared with all other modalities tested (genetics: AUPRC = 0.01 ± 0.00, P = 2.2 × 10-3; lifestyle: AUPRC = 0.03 ± 0.04, P = 2.5 × 10-3; blood biochemistry: AUPRC = 0.01 ± 0.00, P = 4.1 × 10-3; prodromal signs: AUPRC = 0.01 ± 0.00, P = 3.6 × 10-3). Accelerometry is a potentially important, low-cost screening tool for determining people at risk of developing Parkinson's disease and identifying participants for clinical trials of neuroprotective treatments.

Neurophysiology of cerebellar ataxias and gait disorders

There are numerous forms of cerebellar disorders from sporadic to genetic diseases. The aim of this chapter is to provide an overview of the advances and emerging techniques during these last 2 decades in the neurophysiological tests useful in cerebellar patients for clinical and research purposes. Clinically, patients exhibit various combinations of a vestibulocerebellar syndrome, a cerebellar cognitive affective syndrome and a cerebellar motor syndrome which will be discussed throughout this chapter. Cerebellar patients show abnormal Bereitschaftpotentials (BPs) and mismatch negativity. Cerebellar EEG is now being applied in cerebellar disorders to unravel impaired electrophysiological patterns associated within disorders of the cerebellar cortex. Eyeblink conditioning is significantly impaired in cerebellar disorders: the ability to acquire conditioned eyeblink responses is reduced in hereditary ataxias, in cerebellar stroke and after tumor surgery of the cerebellum. Furthermore, impaired eyeblink conditioning is an early marker of cerebellar degenerative disease. General rules of motor control suggest that optimal strategies are needed to execute voluntary movements in the complex environment of daily life. A high degree of adaptability is required for learning procedures underlying motor control as sensorimotor adaptation is essential to perform accurate goal-directed movements. Cerebellar patients show impairments during online visuomotor adaptation tasks. Cerebellum-motor cortex inhibition (CBI) is a neurophysiological biomarker showing an inverse association between cerebellothalamocortical tract integrity and ataxia severity. Ataxic gait is characterized by increased step width, reduced ankle joint range of motion, increased gait variability, lack of intra-limb inter-joint and inter-segmental coordination, impaired foot ground placement and loss of trunk control. Taken together, these techniques provide a neurophysiological framework for a better appraisal of cerebellar disorders.

Dysfunctional neuro-muscular mechanisms explain gradual gait changes in prodromal spastic paraplegia

BACKGROUND

In Hereditary Spastic Paraplegia (HSP) type 4 (SPG4) a length-dependent axonal degeneration in the cortico-spinal tract leads to progressing symptoms of hyperreflexia, muscle weakness, and spasticity of lower extremities. Even before the manifestation of spastic gait, in the prodromal phase, axonal degeneration leads to subtle gait changes. These gait changes - depicted by digital gait recording - are related to disease severity in prodromal and early-to-moderate manifest SPG4 participants.

METHODS

We hypothesize that dysfunctional neuro-muscular mechanisms such as hyperreflexia and muscle weakness explain these disease severity-related gait changes of prodromal and early-to-moderate manifest SPG4 participants. We test our hypothesis in computer simulation with a neuro-muscular model of human walking. We introduce neuro-muscular dysfunction by gradually increasing sensory-motor reflex sensitivity based on increased velocity feedback and gradually increasing muscle weakness by reducing maximum isometric force.

RESULTS

By increasing hyperreflexia of plantarflexor and dorsiflexor muscles, we found gradual muscular and kinematic changes in neuro-musculoskeletal simulations that are comparable to subtle gait changes found in prodromal SPG4 participants.

CONCLUSIONS

Predicting kinematic changes of prodromal and early-to-moderate manifest SPG4 participants by gradual alterations of sensory-motor reflex sensitivity allows us to link gait as a directly accessible performance marker to emerging neuro-muscular changes for early therapeutic interventions.

Added forearm weights for gait pattern normalization in patients with Parkinson's disease

Patients with Parkinson's Disease presented gait impairment. Applying additional weights to enhancing sensory input may improve gait impairment. We assumed that gait impairment could be improved when patients walked with additional forearm weights, and the gait improvement was associated with clinical characteristic of Parkinson's Disease. Thirty patients with Parkinson's Disease and 30 age-sex matched controls were recruited. Spatiotemporal and joint kinematics parameters were evaluated by a three-dimensional motion capture system in normal walking and walking with sandbags, respectively. The comparisons of spatiotemporal parameters were analyzed using t-test or nonparametric tests. The comparison of joint kinematic data was analyzed using statistical parametric mapping. The correlation between motor symptom and gait parameters changes was analyzed using Pearson's correlation analysis. During normal walking, patients showed deteriorated gait compared with controls. After applying weights to forearms patients increased cadence (p = 0.004), speed (p < 0.001) and step length (p = 0.048), and decreased stride time (p = 0.003). The hip angles significantly increased during 5%-23% and 87%-100% of gait cycle, while knee angles during 9%-25% and 88%-98% of the gait cycle, and ankle angles in 92%-100% of gait cycle. The gait parameters of patients with forearm-loading showed no significant difference compared with healthy subjects walking normally. The change of gait parameters correlated positively with the axial and tremor severity while correlated negatively with the rigidity sub-score. Patients with tremor dominant subtype also showed greater improvement of speed and step time compared with patients with postural instability/gait difficulty subtype. Applying added weights bilaterally to the forearms of patients can normalize gait patterns. Notably, patients with higher scores on axial and tremor and lower rigidity scores gained more benefits.

Antiparkinsonian medication masks motor signal progression in de novo patients

Patients not yet receiving medication provide insight to drug-naïve early physiology of Parkinson's Disease (PD). Wearable sensors can measure changes in motor features before and after introduction of antiparkinsonian medication. We aimed to identify features of upper limb bradykinesia, postural stability, and gait that measurably progress in de novo PD patients prior to the start of medication, and determine whether these features remain sensitive to progression in the period after commencement of antiparkinsonian medication. Upper limb motion was measured using an inertial sensor worn on a finger, while postural stability and gait were recorded using an array of six wearable sensors. Patients were tested over nine visits at three monthly intervals. The timepoint of start of medication was noted. Three upper limb bradykinetic features (finger tapping speed, pronation supination speed, and pronation supination amplitude) and three gait features (gait speed, arm range of motion, duration of stance phase) were found to progress in unmedicated early-stage PD patients. In all features, progression was masked after the start of medication. Commencing antiparkinsonian medication is known to lead to masking of progression signals in clinical measures in de novo PD patients. In this study, we show that this effect is also observed with digital measures of bradykinetic and gait motor features.

Arm swing deviations in patients with Parkinson's disease at different gait velocities

Asymmetry of arm swing (AS) has been described as a characteristic of normal physiological gait. In patients with Parkinson's disease (PWPD), a one-sided reduction of AS can occur already as a prodromal symptom. There is limited evidence regarding AS in PWPD, but a growing interest in AS as a focus of exercise therapy. The differences of AS between 32 healthy subjects (HS) and 36 mildly-to-moderately impaired PWPD were assessed in overground walking at various gait speeds. Assessments were carried out with a sensor-based gait measurement system over a 40 m walk in very slow, slow, preferred, fast, and very fast gait speed. Longitudinal and AS kinematics were compared with ANOVA function and regression analysis. PWPD exhibited a one-sided reduction of AS compared to HS at normal, fast, and very fast walking. AS coordination, representing the timing of reciprocity of right and left AS, was reduced in PWPD in very slow and normal walking. With respect to leg movements, PWPD exhibited an increase in stride time variability in very slow gait. There were no group differences for cadence, stride length, and gait velocity. This study informs about the kinematics of AS at various gait velocities ranging from very slow to very fast in mildly-to-moderately impaired PWPD. Reduced one-sided AS can be considered as a very early sign of parkinsonian gait disturbance that precedes alterations of locomotive leg movements and improves at faster gait speeds.

Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study

Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinson's disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic. At home, participants wore the smartwatch for seven days after each clinic visit and completed motor, speech and cognitive tasks on the smartphone every other week. Features derived from the devices, particularly arm swing, the proportion of time with tremor, and finger tapping, differed significantly between individuals with early PD and age-matched controls and had variable correlation with traditional assessments. Longitudinal assessments will inform the value of these digital measures for use in future clinical trials.

A novel clinical sign to assess the risk of Parkinson's disease in patients with isolated asymmetric arm swing

INTRODUCTION

An isolated asymmetric arm swing can represent the beginning of Parkinson's disease (PD) but also be related to physiological or non-specific musculoskeletal pathology.

PATIENTS AND METHODS

In this brief clinical observation including 15 patients with asymmetric arm swing, we provide a new clinical clue to evaluate the risk of subjacent parkinsonism.

RESULTS

Among non-parkinsonian subjects, the immobilization of the contralateral arm, by asking the patient to put his hand on the contralateral shoulder, induced a clear increase in the amplitude of the arm swing, whereas in PD patients, the arm swing amplitude did not significantly vary when the contralateral upper limb was immobilized.

CONCLUSIONS

This novel clinical sign may be helpful when approaching patients with gait abnormalities and specifically reduced arm swing.

Effects of Gyroscope on Arm Swing and Gait in Healthy Volunteers

Background. Arm swing has a crucial role in gait. It is essential in terms of regulating gait parameters and balance during walking. In the case of bradykinesia, the arms act as a generator to maintain lower extremity movement while walking. The way gyroscopes work makes them useful in arm swings. In this study, the arm swing is facilitated by a new type of gyroscope. As a main purpose, a gyroscope was used to increase arm swing during pendulum exercise and walking. Methods. Thirty healthy volunteers were included in the study. The study covered three situations. The first evaluation was performed without the gyroscope. The second evaluation was performed while the gyroscope was installed but not activated. The final evaluation was made while the gyroscope was installed and powered up. The effect of the gyroscope on the arm swing was evaluated by the Dartfish®, and the gait was evaluated with the Zebris® force distribution measurement analysis system. Results. According to the results, the gyroscope increases the arm swing in the pendulum exercise ( $p<0.05$ ). Furthermore, using the gyroscope, the step width decreased, and the gait cycle time increased ( $p<0.05$ ). Conclusions. The gyroscope is suitable for facilitating arm swings in healthy volunteers. This study is essential to demonstrate the effect of a gyroscope on extremity movements for the first time. In the future, a medical device that has the features of a gyroscope can be designed for its use in the treatment of Parkinson’s disease and Senile Bradykinesia.

Who is at Risk of Parkinson Disease? Refining the Preclinical Phase of GBA1 and LRRK2 Variant Carriers: a Clinical, Biochemical, and Imaging Approach

PURPOSE OF REVIEW

Genetic variants in GBA1 and LRRK2 genes are the commonest genetic risk factor for Parkinson disease (PD); however, the preclinical profile of GBA1 and LRRK2 variant carriers who will develop PD is unclear. This review aims to highlight the more sensitive markers that can stratify PD risk in non-manifesting GBA1 and LRRK2 variant carriers.

RECENT FINDINGS

Several case-control and a few longitudinal studies evaluated clinical, biochemical, and neuroimaging markers within cohorts of non-manifesting carriers of GBA1 and LRRK2 variants. Despite similar levels of penetrance of PD in GBA1 and LRRK2 variant carriers (10-30%), these individuals have distinct preclinical profiles. GBA1 variant carriers at higher risk of PD can present with prodromal symptoms suggestive of PD (hyposmia), display increased α-synuclein levels in peripheral blood mononuclear cells, and show dopamine transporter abnormalities. LRRK2 variant carriers at higher risk of PD might show subtle motor abnormalities, but no prodromal symptoms, higher exposure to some environmental factors (non-steroid anti-inflammatory drugs), and peripheral inflammatory profile. This information will help clinicians tailor appropriate screening tests and counseling and facilitate researchers in the development of predictive markers, disease-modifying treatments, and selection of healthy individuals who might benefit from preventive interventions.

Role of novel endpoints and evaluations of response in Parkinson disease

With progress in our understanding of Parkinson disease (PD) and other neurodegenerative disorders, from clinical features to imaging, genetic, and molecular characterization comes the opportunity to refine and revise how we measure these diseases and what outcome measures are used as endpoints in clinical trials. While several rater-, patient-, and milestone-based outcomes for PD exist that may serve as clinical trial endpoints, there remains an unmet need for endpoints that are clinically meaningful, patient centric while also being more objective and quantitative, less susceptible to effects of symptomatic therapy (for disease-modification trials), and that can be measured over a short period and yet accurately represent longer-term outcomes. Several novel outcomes that may be used as endpoints in PD clinical trials are in development, including digital measures of signs and symptoms, as well a growing array of imaging and biospecimen biomarkers. This chapter provides an overview of the state of PD outcome measures as of 2022, including considerations for selection of clinical trial endpoints in PD, advantages and limitations of existing measures, and emerging potential novel endpoints.

Deep Brain Stimulation and Levodopa Affect Gait Variability in Parkinson Disease Differently

BACKGROUND

Both dopaminergic medication and subthalamic nucleus (STN) deep brain stimulation (DBS) can improve the amplitude and speed of gait in Parkinson disease (PD), but relatively little is known about their comparative effects on gait variability. Gait irregularity has been linked to the degeneration of cholinergic neurons in the pedunculopontine nucleus (PPN).

OBJECTIVES

The STN and PPN have reciprocal connections, and we hypothesized that STN DBS might improve gait variability by modulating PPN function. Dopaminergic medication should not do this, and we therefore sought to compare the effects of medication and STN DBS on gait variability.

MATERIALS AND METHODS

We studied 11 patients with STN DBS systems on and off with no alteration to their medication, and 15 patients with PD without DBS systems on and off medication. Participants walked for two minutes in each state, wearing six inertial measurement units. Variability has previously often been expressed in terms of SD or coefficient of variation over a testing session, but these measures conflate long-term variability (eg, gradual slowing, which is not necessarily pathological) with short-term variability (true irregularity). We used Poincaré analysis to separate the short- and long-term variability.

RESULTS

DBS decreased short-term variability in lower limb gait parameters, whereas medication did not have this effect. In contrast, STN DBS had no effect on arm swing and trunk motion variability, whereas medication increased them, without obvious dyskinesia.

CONCLUSIONS

Our results suggest that STN DBS acts through a nondopaminergic mechanism to reduce gait variability. We believe that the most likely explanation is the retrograde activation of cholinergic PPN projection neurons.

Feasibility of a Novel Therapist-Assisted Feedback System for Gait Training in Parkinson's Disease

We tested the feasibility of one session of treadmill training using a novel physical therapist assisted system (Mobility Rehab) using wearable sensors on the upper and lower limbs of 10 people with Parkinson's disease (PD). Participants performed a 2-min walk overground before and after 15 min of treadmill training with Mobility Rehab, which included an electronic tablet (to visualize gait metrics) and five Opal sensors placed on both the wrists and feet and on the sternum area to measure gait and provide feedback on six gait metrics (foot-strike angle, trunk coronal range-of-motion (ROM), arm swing ROM, double-support duration, gait-cycle duration, and step asymmetry). The physical therapist used Mobility Rehab to select one or two gait metrics (from the six) to focus on during the treadmill training. Foot-strike angle (effect size (ES) = 0.56, 95% Confidence Interval (CI) = 0.14 to 0.97), trunk coronal RoM (ES = 1.39, 95% CI = 0.73 to 2.06), and arm swing RoM (ES = 1.64, 95% CI = 0.71 to 2.58) during overground walking showed significant and moderate-to-large ES following treadmill training with Mobility Rehab. Participants perceived moderate (60%) and excellent (30%) effects of Mobility Rehab on their gait. No adverse events were reported. One session of treadmill training with Mobility Rehab is feasible for people with mild-to-moderate PD.

Automatic ML-based vestibular gait classification: examining the effects of IMU placement and gait task selection

BACKGROUND

Vestibular deficits can impair an individual's ability to maintain postural and/or gaze stability. Characterizing gait abnormalities among individuals affected by vestibular deficits could help identify patients at high risk of falling and inform rehabilitation programs. Commonly used gait assessment tools rely on simple measures such as timing and visual observations of path deviations by clinicians. These simple measures may not capture subtle changes in gait kinematics. Therefore, we investigated the use of wearable inertial measurement units (IMUs) and machine learning (ML) approaches to automatically discriminate between gait patterns of individuals with vestibular deficits and age-matched controls. The goal of this study was to examine the effects of IMU placement and gait task selection on the performance of automatic vestibular gait classifiers.

METHODS

Thirty study participants (15 with vestibular deficits and 15 age-matched controls) participated in a single-session gait study during which they performed seven gait tasks while donning a full-body set of IMUs. Classification performance was reported in terms of area under the receiver operating characteristic curve (AUROC) scores for Random Forest models trained on data from each IMU placement for each gait task.

RESULTS

Several models were able to classify vestibular gait better than random (AUROC > 0.5), but their performance varied according to IMU placement and gait task selection. Results indicated that a single IMU placed on the left arm when walking with eyes closed resulted in the highest AUROC score for a single IMU (AUROC = 0.88 [0.84, 0.89]). Feature permutation results indicated that participants with vestibular deficits reduced their arm swing compared to age-matched controls while they walked with eyes closed.

CONCLUSIONS

These findings highlighted differences in upper extremity kinematics during walking with eyes closed that were characteristic of vestibular deficits and showed evidence of the discriminative ability of IMU-based automated screening for vestibular deficits. Further research should explore the mechanisms driving arm swing differences in the vestibular population.

Upper-extremity kinematics and interlimb movement correlation in persons with Parkinson Disease on irregular terrain, cross-slope, and under dual-task condition

Background

A defining clinical characteristics of Parkinson disease is reduced upper-extremity movements. Irregular terrain, the presence of a cross slope, and dual-task conditions have been found to alter the lower-limb gait characteristics of persons with Parkinson disease but there is little information how different environmental and cognitive conditions impact upper-limb kinematics as well as interlimb movement correlation.

Research question

Do environmental conditions, such as irregular terrain and the presence of cross slope, as well as dual-task condition impact the upper-extremity kinematics and interlimb movement correlation of persons with Parkinson disease compared to healthy, age-matched controls?

Methods

Three-dimensional whole-body gait data were collected for nine participants with mild-to-moderate Parkinson disease and nine healthy age-matched control participants. All participants ambulated on a regular terrain, irregular terrain, with and without cross slope, and under dual and single-task conditions. The primary outcomes were arm swing magnitude, arm swing asymmetry, and normalized cross-correlation between the ipsilateral arms and contralateral legs, which characterized movement correlation.

Results

For all conditions, persons with Parkinson disease exhibited reduced arm swing magnitude and greater arm swing asymmetry compared to the healthy controls. All participants increased their arm swing magnitude on the irregular surface and under the dual-task condition. In the healthy group, the arm swing asymmetry was invariant to terrain but declined under the dual-task condition while the persons with Parkinson disease exhibited increased asymmetry on the cross slope, on the irregular terrain, and under the dual-task condition. Interlimb movement correlation decreased on the irregular terrain for the persons with Parkinson disease while the healthy group exhibited decreased interlimb movement correlation on the cross slope as well as under the dual-task condition.

Significance

Persons with Parkinson disease were able to increase their arm swing magnitude when their balance was challenged and the most significant threat to their safety as defined by the greatest reduction in the interlimb movement correlation was the irregular terrain.

•

Persons with PD had reduced arm swing magnitude compared to healthy participants.

•

Persons with PD increased arm swing magnitude when their balance was challenged.

•

The irregular terrain was the condition that impacted both health groups the most.

•

Dual-task increased arm swing magnitude and reduced interlimb movement correlation.

Longitudinal clinical and biomarker characteristics of non-manifesting LRRK2 G2019S carriers in the PPMI cohort

We examined 2-year longitudinal change in clinical features and biomarkers in LRRK2 non-manifesting carriers (NMCs) versus healthy controls (HCs) enrolled in the Parkinson's Progression Markers Initiative (PPMI). We analyzed 2-year longitudinal data from 176 LRRK2 G2019S NMCs and 185 HCs. All participants were assessed annually with comprehensive motor and non-motor scales, dopamine transporter (DAT) imaging, and biofluid biomarkers. The latter included cerebrospinal fluid (CSF) Abeta, total tau and phospho-tau; serum urate and neurofilament light chain (NfL); and urine bis(monoacylglycerol) phosphate (BMP). At baseline, LRRK2 G2019S NMCs had a mean (SD) age of 62 (7.7) years and were 56% female. 13% had DAT deficit (defined as <65% of age/sex-expected lowest putamen SBR) and 11% had hyposmia (defined as ≤15th percentile for age and sex). Only 5 of 176 LRRK2 NMCs developed PD during follow-up. Although NMCs scored significantly worse on numerous clinical scales at baseline than HCs, there was no longitudinal change in any clinical measures over 2 years or in DAT binding. There were no longitudinal differences in CSF and serum biomarkers between NMCs and HCs. Urinary BMP was significantly elevated in NMCs at all time points but did not change longitudinally. Neither baseline biofluid biomarkers nor the presence of DAT deficit correlated with 2-year change in clinical outcomes. We observed no significant 2-year longitudinal change in clinical or biomarker measures in LRRK2 G2019S NMCs in this large, well-characterized cohort even in the participants with baseline DAT deficit. These findings highlight the essential need for further enrichment biomarker discovery in addition to DAT deficit and longer follow-up to enable the selection of NMCs at the highest risk for conversion to enable future prevention clinical trials.

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

Background

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

Methods

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

Results

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

Conclusion

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

Arm-swing kinematics in Parkinson's disease: A systematic review and meta-analysis

BACKGROUND

Parkinson's disease (PD) causes postural instability and gait abnormalities that may be associated with an arm swing reduction.

OBJECTIVE

To conduct systematic review and meta-analysis to determine the kinematic patterns of arm-swing during gait in people with PD METHODS: A computer literature search of the PubMed, EMBASE, WOS, PEDro, SCOPUS and SciELO databases was conducted. Terms related to PD and arm-swing were combined to find studies that performed a free walking evaluation of the arm-swing of PD patients on or off medication compared to healthy controls. After a standardized evaluation by three examiners, fifteen articles met inclusion criteria. Random effects meta-analysis models were utilized to quantify (1) the arm-swing range of motion (RoM); (2) the arm-swing amplitude; (3) the arm-swing velocity; and (4) the arm-swing asymmetry.

RESULTS

On average, arm-swing RoM (7.07°), amplitude (0.8 cm), and velocity (0.31 m/s) were significantly decreased in PD compared to healthy controls. Healthy subjects had significantly more symmetrical arm-swing (8.16%) than people with PD. Effect sizes were moderate-large.

CONCLUSIONS

People with PD have significant differences in RoM, amplitude, velocity, and asymmetry of arm-swing during gait compared to the healthy control group. Medication phase does not significantly influence arm-swing characteristics. Further studies will be needed to determine whether different disease characteristics influence the biomechanics of arm-swing during gait.

Petri net transition times as training features for multiclass models to support the detection of neurodegenerative diseases

This paper proposes the transition times of Petri net models of human gait as training features for multiclass random forests (RFs) and classification trees (CTs). These models are designed to support screening for neurodegenerative diseases. The proposed Petri net describes gait in terms of nine cyclic phases and the timing of the nine events that mark the transition between phases. Since the transition times between strides vary, each is represented as a random variable characterized by its mean and standard deviation. These transition times are calculated using the PhysioNet database of vertical ground reaction forces (VGRFs) generated by feet-ground contact. This database comprises the VGRFs of four groups: amyotrophic lateral sclerosis, the control group, Huntington's disease, and Parkinson disease. The RF produced an overall classification accuracy of 91%, and the specificities and sensitivities for each class were between 80% and 100%. However, despite this high performance, the RF-generated models demonstrated lack of interpretability prompted the training of a CT using identical features. The obtained tree comprised only four features and required a maximum of three comparisons. However, this simplification dramatically reduced the overall accuracy from 90.6% to 62.3%. The proposed set features were compared with those included in PhysioNet database of VGRFs. In terms of both the RF and CT, more accurate models were established using our features than those of the PhysioNet.

Evaluation of Arm Swing Features and Asymmetry during Gait in Parkinson's Disease Using the Azure Kinect Sensor

Arm swinging is a typical feature of human walking: Continuous and rhythmic movement of the upper limbs is important to ensure postural stability and walking efficiency. However, several factors can interfere with arm swings, making walking more risky and unstable: These include aging, neurological diseases, hemiplegia, and other comorbidities that affect motor control and coordination. Objective assessment of arm swings during walking could play a role in preventing adverse consequences, allowing appropriate treatments and rehabilitation protocols to be activated for recovery and improvement. This paper presents a system for gait analysis based on Microsoft Azure Kinect DK sensor and its body-tracking algorithm: It allows noninvasive full-body tracking, thus enabling simultaneous analysis of different aspects of walking, including arm swing characteristics. Sixteen subjects with Parkinson's disease and 13 healthy controls were recruited with the aim of evaluating differences in arm swing features and correlating them with traditional gait parameters. Preliminary results show significant differences between the two groups and a strong correlation between the parameters. The study thus highlights the ability of the proposed system to quantify arm swing features, thus offering a simple tool to provide a more comprehensive gait assessment.

Who to Enroll in Parkinson Disease Prevention Trials? The Case for Composite Prodromal Cohorts

Significant progress has been made in expanding our understanding of prodromal Parkinson disease (PD), particularly for recognition of early motor and nonmotor signs and symptoms. Although identification of these prodromal features may improve our understanding of the earliest stages of PD, they are individually insufficient for early disease detection and enrollment of participants in prevention trials in most cases because of low sensitivity, specificity, and positive predictive value. Composite cohorts, composed of individuals with multiple co-occurring prodromal features, are an important resource for conducting prodromal PD research and eventual prevention trials because they are more representative of the population at risk for PD, allow investigators to evaluate the efficacy of an intervention across individuals with varying prodromal feature patterns, are able to produce larger sample sizes, and capture individuals at different stages of prodromal PD. A key challenge in identifying individuals with prodromal disease for composite cohorts and prevention trial participation is that we know little about the natural history of prodromal PD. To move toward prevention trials, it is critical that we better understand common prodromal feature patterns and be able to predict the probability of progression and phenoconversion. Ongoing research in cohort studies and administrative databases is beginning to address these questions, but further longitudinal analyses in a large population-based sample are necessary to provide a convincing and definitive strategy for identifying individuals to be enrolled in a prevention trial.

Outcome Assessment in Parkinson Disease Prevention Trials: Utility of Clinical and Digital Measures

BACKGROUND AND OBJECTIVES

The prodromal phase of Parkinson disease (PD) is accompanied by subtle clinical signs that are not sufficient for diagnosis but could potentially be measured in the context of clinical trials of therapies intended to delay or prevent more definitive clinical features. The objective of this study was to review the available literature on the presence and time course of subtle motor features in prodromal PD in the context of planning for possible clinical trials.

METHODS

We reviewed the available literature based on expert opinion. We considered a range of outcomes including measurement of clinical features, patient-reported outcomes, digital markers, and clinical diagnosis.

RESULTS

We considered these features and measures in the context of patient stratification, intermediate outcomes, and clinically relevant end points, including phenoconversion.

DISCUSSION

Substantial progress has been made in understanding how motor features evolve in the period immediately before a PD diagnosis. Digital measures hold substantial progress for measurement precision and may be additionally relevant because they can be used in naturalistic environments outside the clinic. Future studies should focus on advancing digital sensor technology and analysis and developing methods to implement available methods, particularly determination of a clinical diagnosis of PD, in a clinical trial context.

Path to Parkinson Disease Prevention: Conclusion and Outlook

Tremendous progress in our understanding of the pathophysiology and clinical manifestations of the prodromal phase of Parkinson disease (PD) offers a unique opportunity to start therapeutic interventions as early as possible to slow or even stop the progression to clinically manifest motor PD. A Parkinson's Prevention Conference, "Planning for Prevention of Parkinson's: A trial design symposium and workshop" was convened to discuss all issues that need to be addressed before the launch of the first PD prevention study. In this review, we summarize the major opportunities and challenges in designing prevention trials in PD, organized by the following critical trial design questions: Who (should be enrolled)? What (to test)? How (to measure prevention)? and the pivotal question, When during the prodromal disease (should we start these trials)? We outline the implications of these questions and their meaning for a responsible, sustainable, and fruitful further planning for prevention trials. Despite the great progress that has been made, it needs to be acknowledged that several queries remain to be carefully considered and addressed because prevention trials are being planned and become a reality.

Detection and assessment of Parkinson's disease based on gait analysis: A survey

Neurological disorders represent one of the leading causes of disability and mortality in the world. Parkinson's Disease (PD), for example, affecting millions of people worldwide is often manifested as impaired posture and gait. These impairments have been used as a clinical sign for the early detection of PD, as well as an objective index for pervasive monitoring of the PD patients in daily life. This review presents the evidence that demonstrates the relationship between human gait and PD, and illustrates the role of different gait analysis systems based on vision or wearable sensors. It also provides a comprehensive overview of the available automatic recognition systems for the detection and management of PD. The intervening measures for improving gait performance are summarized, in which the smart devices for gait intervention are emphasized. Finally, this review highlights some of the new opportunities in detecting, monitoring, and treating of PD based on gait, which could facilitate the development of objective gait-based biomarkers for personalized support and treatment of PD.

Gait alterations in Parkinson’s disease at the stage of hemiparkinsonism—A longitudinal study

Background

Progressive gait impairment in Parkinson’s disease (PD) leads to significant disability. Quantitative gait parameters analysis provides valuable information about fine gait alterations.

Objectives

To analyse change of gait parameters in patients with early PD at the stage of hemiparkinsonism and after 1 year of follow up, taking into account clinical asymmetry.

Methods

Consecutive early PD outpatients with strictly unilateral motor features underwent clinical and neuropsychological assessment at the study entry and after 1 year of follow up. Gait was assessed with GAITRite walkway using dual-task methodology. Spatiotemporal gait parameters (step time and length, swing time and double support time) and their coefficients of variation (CV), gait velocity and heel-to-heel base support were evaluated.

Results

We included 42 PD patients with disease duration of 1.3 years (±1.13). Progression of motor and non-motor symptoms, without significant cognitive worsening, was observed after 1 year of follow up. Significant shortening of the swing time, prolongation of the double support and increase of their CVs were observed during all task conditions similarly for most parameters on symptomatic and asymptomatic bodysides, except for CV for the swing time under the combined task.

Conclusion

Alterations of the swing time and double support time are already present even at the asymptomatic body side, and progress similarly, or even at faster pace, at this side, despite dopaminergic treatment These parameters deserve further investigation in larger, prospective studies to address their potential to serve as markers of progression in interventional disease modifying trials with early PD patients.

Virtual exam for Parkinson's disease enables frequent and reliable remote measurements of motor function

Sensor-based remote monitoring could help better track Parkinson's disease (PD) progression, and measure patients' response to putative disease-modifying therapeutic interventions. To be useful, the remotely-collected measurements should be valid, reliable, and sensitive to change, and people with PD must engage with the technology. We developed a smartwatch-based active assessment that enables unsupervised measurement of motor signs of PD. Participants with early-stage PD (N = 388, 64% men, average age 63) wore a smartwatch for a median of 390 days. Participants performed unsupervised motor tasks both in-clinic (once) and remotely (twice weekly for one year). Dropout rate was 5.4%. Median wear-time was 21.1 h/day, and 59% of per-protocol remote assessments were completed. Analytical validation was established for in-clinic measurements, which showed moderate-to-strong correlations with consensus MDS-UPDRS Part III ratings for rest tremor (⍴ = 0.70), bradykinesia (⍴ = -0.62), and gait (⍴ = -0.46). Test-retest reliability of remote measurements, aggregated monthly, was good-to-excellent (ICC = 0.75-0.96). Remote measurements were sensitive to the known effects of dopaminergic medication (on vs off Cohen's d = 0.19-0.54). Of note, in-clinic assessments often did not reflect the patients' typical status at home. This demonstrates the feasibility of smartwatch-based unsupervised active tests, and establishes the analytical validity of associated digital measurements. Weekly measurements provide a real-life distribution of disease severity, as it fluctuates longitudinally. Sensitivity to medication-induced change and improved reliability imply that these methods could help reduce sample sizes needed to demonstrate a response to therapeutic interventions or disease progression.

Machine Learning Classifiers to Evaluate Data From Gait Analysis With Depth Cameras in Patients With Parkinson's Disease

Introduction

The assessments of the motor symptoms in Parkinson's disease (PD) are usually limited to clinical rating scales (MDS UPDRS III), and it depends on the clinician's experience. This study aims to propose a machine learning technique algorithm using the variables from upper and lower limbs, to classify people with PD from healthy people, using data from a portable low-cost device (RGB-D camera). And can be used to support the diagnosis and follow-up of patients in developing countries and remote areas.

Methods

We used Kinect®eMotion system to capture the spatiotemporal gait data from 30 patients with PD and 30 healthy age-matched controls in three walking trials. First, a correlation matrix was made using the variables of upper and lower limbs. After this, we applied a backward feature selection model using R and Python to determine the most relevant variables. Three further analyses were done using variables selected from backward feature selection model (Dataset A), movement disorders specialist (Dataset B), and all the variables from the dataset (Dataset C). We ran seven machine learning models for each model. Dataset was divided 80% for algorithm training and 20% for evaluation. Finally, a causal inference model (CIM) using the DoWhy library was performed on Dataset B due to its accuracy and simplicity.

Results

The Random Forest model is the most accurate for all three variable Datasets (Dataset A: 81.8%; Dataset B: 83.6%; Dataset C: 84.5%) followed by the support vector machine. The CIM shows a relation between leg variables and the arms swing asymmetry (ASA) and a proportional relationship between ASA and the diagnosis of PD with a robust estimator (1,537).

Conclusions

Machine learning techniques based on objective measures using portable low-cost devices (Kinect®eMotion) are useful and accurate to classify patients with Parkinson's disease. This method can be used to evaluate patients remotely and help clinicians make decisions regarding follow-up and treatment.

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.

Parkinson's disease motor symptoms rescue by CRISPRa-reprogramming astrocytes into GABAergic neurons

Direct reprogramming based on genetic factors resembles a promising strategy to replace lost cells in degenerative diseases such as Parkinson's disease. For this, we developed a knock‐in mouse line carrying a dual dCas9 transactivator system (dCAM) allowing the conditional in vivo activation of endogenous genes. To enable a translational application, we additionally established an AAV‐based strategy carrying intein‐split‐dCas9 in combination with activators (AAV‐dCAS). Both approaches were successful in reprogramming striatal astrocytes into induced GABAergic neurons confirmed by single‐cell transcriptome analysis of reprogrammed neurons in vivo. These GABAergic neurons functionally integrate into striatal circuits, alleviating voluntary motor behavior aspects in a 6‐OHDA Parkinson's disease model. Our results suggest a novel intervention strategy beyond the restoration of dopamine levels. Thus, the AAV‐dCAS approach might enable an alternative route for clinical therapies of Parkinson's disease.

Smoothness of movement in idiopathic cervical dystonia

Smoothness (i.e. non-intermittency) of movement is a clinically important property of the voluntary movement with accuracy and proper speed. Resting head position and head voluntary movements are impaired in cervical dystonia. The current work aims to evaluate if the smoothness of voluntary head rotations is reduced in this disease. Twenty-six cervical dystonia patients and 26 controls completed rightward and leftward head rotations. Patients’ movements were differentiated into “towards-dystonia” (rotation accentuated the torticollis) and “away-dystonia”. Smoothness was quantified by the angular jerk and arc length of the spectrum of angular speed (i.e. SPARC, arbitrary units). Movement amplitude (mean, 95% CI) on the horizontal plane was larger in controls (63.8°, 58.3°–69.2°) than patients when moving towards-dystonia (52.8°, 46.3°–59.4°; P = 0.006). Controls’ movements (49.4°/s, 41.9–56.9°/s) were faster than movements towards-dystonia (31.6°/s, 25.2–37.9°/s; P < 0.001) and away-dystonia (29.2°/s, 22.9–35.5°/s; P < 0.001). After taking into account the different amplitude and speed, SPARC-derived (but not jerk-derived) indices showed reduced smoothness in patients rotating away-dystonia (1.48, 1.35–1.61) compared to controls (1.88, 1.72–2.03; P < 0.001). Poor smoothness is a motor disturbance independent of movement amplitude and speed in cervical dystonia. Therefore, it should be assessed when evaluating this disease, its progression, and treatments.

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.

Dual tasking reduces gait asymmetry of trajectory deviation during obstacle circumvention in people with Parkinson's disease

BACKGROUND

Certain aspects of gait may depend on cognition, and the effects of dual-tasking (DT) on gait asymmetry (GA) during obstacle circumvention in people with Parkinson's disease (pwPD) may be walking phase-dependent. While the approaching phase requires allocating significant cognitive resources to perform the task, outweighing the available resources may increase GA. During the avoiding phase, the obstacle could be used as an external cue, enhancing the attention to the obstacle and, consequently, improving gait control and regulating GA.

OBJECTIVE

The study investigated the effects of obstacle circumvention during gait with DT on GA in pwPD, considering the circumvention phase.

METHODS

Thirty participants, 15 pwPD and 15 neurologically healthy individuals, circumvented an obstacle 20 times (in total) according to side (right and left side) and DT (presence and absence). Spatial-temporal stride parameters, medial-lateral and horizontal trajectory deviations from the original path, strategy to obstacle circumvention (lead limb away from or close to the obstacle during the crossing step), and gaze parameters were calculated during the approaching and avoiding phases. The parameters were grouped considering the side that the obstacle was circumvented during each task, and the symmetry index was calculated.

RESULTS

The results showed greater asymmetry of time of fixations, width, duration, and velocity during the approaching phase (p < 0.02), whereas the avoiding phase decreased asymmetry of medial-lateral and horizontal trajectory deviations parameters (p < 0.001) during obstacle circumvention with DT, in both pwPD and control group.

CONCLUSIONS

The findings offer a basis for considering that goal-directed movement control may regulate GA in pwPD.

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 coupling between upper and lower limb muscles in Parkinsonian gait

OBJECTIVE

To explore to what extent neuronal coupling between upper and lower limb muscles during gait is preserved or affected in patients with Parkinson's Disease (PD).

METHODS

Electromyography recordings were obtained from the bilateral deltoideus anterior and bilateral rectus femoris and biceps femoris muscles during overground gait in 20 healthy participants (median age 69 years) and 20 PD patients (median age 68.5 years). PD patients were able to walk independently (Hoehn and Yahr scale: Stage 2-3), had an equally distributed symptom laterality (6 left side, 7 both sides and 7 right side) and no cognitive problems or tremor dominant PD. Time-dependent directional intermuscular coherence analysis was employed to compare the neural coupling between upper and lower limb muscles between healthy participants and PD patients in three different directions: zero-lag (i.e. common driver), forward (i.e. shoulders driving the legs) and reverse component (i.e. legs driving the shoulders).

RESULTS

Compared to healthy participants, PD patients exhibited (i) reduced intermuscular zero-lag coherence in the beta/gamma frequency band during end-of-stance and (ii) enhanced forward as well as reverse directed coherence in the alpha and beta/gamma frequency bands around toe-off.

CONCLUSIONS

PD patients had a reduced common cortical drive to upper and lower limb muscles during gait, possibly contributing to disturbed interlimb coordination. Enhanced bidirectional coupling between upper and lower limb muscles on subcortical and transcortical levels in PD patients suggests a mechanism of compensation.

SIGNIFICANCE

These findings provide support for the facilitating effect of arm swing instructions in PD gait.