Automated gait and balance parameters diagnose and correlate with severity in Parkinson disease

Evaluation of the Parkinson's Remote Interactive Monitoring System in a Clinical Setting: Usability Study

BACKGROUND

The fastest-growing neurological disorder is Parkinson disease (PD), a progressive neurodegenerative disease that affects 10 million people worldwide. PD is typically treated with levodopa, an oral pill taken to increase dopamine levels, and other dopaminergic agonists. As the disease advances, the efficacy of the drug diminishes, necessitating adjustments in treatment dosage according to the patient's symptoms and disease progression. Therefore, remote monitoring systems that can provide more detailed and accurate information on a patient's condition regularly are a valuable tool for clinicians and patients to manage their medication. The Parkinson's Remote Interactive Monitoring System (PRIMS), developed by PragmaClin Research Inc, was designed on the premise that it will be an easy-to-use digital system that can accurately capture motor and nonmotor symptoms of PD remotely.

OBJECTIVE

We performed a usability evaluation in a simulated clinical environment to assess the ease of use of the PRIMS and determine whether the product offers suitable functionality for users in a clinical setting.

METHODS

Participants were recruited from a user sign-up web-based database owned by PragmaClin Research Inc. A total of 11 participants were included in the study based on the following criteria: (1) being diagnosed with PD and (2) not being diagnosed with dementia or any other comorbidities that would make it difficult to complete the PRIMS assessment safely and independently. Patient users completed a questionnaire that is based on the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale. Interviews and field notes were analyzed for underlying themes and topics.

RESULTS

In total, 11 people with PD participated in the study (female individuals: n=5, 45%; male individuals: n=6, 55%; age: mean 66.7, SD 7.77 years). Thematic analysis of the observer's notes revealed 6 central usability issues associated with the PRIMS. These were the following: (1) the automated voice prompts are confusing, (2) the small camera is problematic, (3) the motor test exhibits excessive sensitivity to the participant's orientation and position in relation to the cameras, (4) the system poses mobility challenges, (5) navigating the system is difficult, and (6) the motor test exhibits inconsistencies and technical issues. Thematic analysis of qualitative interview responses revealed four central themes associated with participants' perspectives and opinions on the PRIMS, which were (1) admiration of purpose, (2) excessive system sensitivity, (3) video instructions preferred, and (4) written instructions disliked. The average system usability score was calculated to be 69.2 (SD 4.92), which failed to meet the acceptable system usability score of 70.

CONCLUSIONS

Although multiple areas of improvement were identified, most of the participants showed an affinity for the overarching objective of the PRIMS. This feedback is being used to upgrade the current PRIMS so that it aligns more with patients' needs.

Scientometric Research and Critical Analysis of Gait and Balance in Older Adults

Gait and balance have emerged as a critical area of research in health technology. Gait and balance studies have been affected by the researchers' slow follow-up of research advances due to the absence of visual inspection of the study literature across decades. This study uses advanced search methods to analyse the literature on gait and balance in older adults from 1993 to 2022 in the Web of Science (WoS) database to gain a better understanding of the current status and trends in the field for the first time. The study analysed 4484 academic publications including journal articles and conference proceedings on gait and balance in older adults. Bibliometric analysis methods were applied to examine the publication year, number of publications, discipline distribution, journal distribution, research institutions, application fields, test methods, analysis theories, and influencing factors in the field of gait and balance. The results indicate that the publication of relevant research documents has been steadily increasing from 1993 to 2022. The United States (US) exhibits the highest number of publications with 1742 articles. The keyword "elderly person" exhibits a strong citation burst strength of 18.04, indicating a significant focus on research related to the health of older adults. With a burst factor of 20.46, Harvard University has made impressive strides in the subject. The University of Pittsburgh displayed high research skills in the area of gait and balance with a burst factor of 7.7 and a publication count of 103. The research on gait and balance mainly focuses on physical performance evaluation approaches, and the primary study methods include experimental investigations, computational modelling, and observational studies. The field of gait and balance research is increasingly intertwined with computer science and artificial intelligence (AI), paving the way for intelligent monitoring of gait and balance in the elderly. Moving forward, the future of gait and balance research is anticipated to highlight the importance of multidisciplinary collaboration, intelligence-driven approaches, and advanced visualization techniques.

Minimal clinically important differences of spatiotemporal gait variables in Parkinson disease

BACKGROUND

Assessment of gait function in People with Parkinson Disease (PwPD) is an important tool for monitoring disease progression in PD. While comprehensive gait analysis has become increasingly popular, only one study, Hass et al. (2014), has established minimal clinically important differences (MCID) for one spatiotemporal variable (velocity) in PwPD.

RESEARCH QUESTION

What are the MCIDs for velocity and additional spatiotemporal variables, including mean, variability, and asymmetry of step length, time, and width?

METHODS

As part of a larger clinic-based initiative, 382 medicated, ambulatory PwPD walked on an instrumented walkway during routine clinical visits. Distribution and anchor-based methods (Unified Parkinson's Disease Rating Scale-III, Modified Hoehn and Yahr, and the mobility subsection of the Parkinson Disease Questionnaire) were used to calculate MCIDs for variables of interest in a cross-sectional approach.

RESULTS

Distribution measures for all variables are presented. Of nine gait variables, four were significantly associated with every anchor and pooled to the following values: velocity (8.2 cm/s), step length mean (3.6 cm), step length variability (0.7%), and step time variability (0.67%).

SIGNIFICANCE

The finalized MCID for velocity (8.2 cm/s) was nearly half of the MCID of 15 cm/s reported by Hass et al., potentially due to differences in calculations. These results allow for evaluations of effectiveness of interventions by providing values that are specific to changes in gait for PwPD. Alterations of methodology including different versions of clinical or walking assessments, and/or different calculation and selection of gait variables necessitate careful reasoning when using presented MCIDs.

Digital biomarkers of mobility and quality of life in Parkinson's disease based on a wearable motion analysis LAB

BACKGROUND AND OBJECTIVE

Functional mobility, an indicator of the quality of life (QoL), requires fast and flexible changes during motion, which are limited in Parkinson's disease (PD). Recent body-worn sensors have emerged in the last decades as potential solutions to produce digital biomarkers able to quantify mobility outside routine consultations and during real-life scenarios for multiple days at a time. The proposed research aims to study the ability of a wearable motion analysis lab, developed by our team, to produce digital biomarkers of mobility and QoL levels in patients with PD.

METHODS

A cross-sectional study was followed, including 40 patients stratified into three subgroups according to a clinic motor examination and a QoL questionnaire.

RESULTS

The achieved outcomes demonstrate the ability of the proposed high-tech solution to measure prototypical gait impairments and discriminate motor condition (AUC=0,890) and patients' QoL levels (AUC=0,950). Also, from the measured multiple gait-associated parameters, we identified the variables with the most potential to be applied as digital biomarkers of mobility (67 % of the metrics) and QoL (72 % of the metrics) in PD.

CONCLUSIONS

Overall, we confirmed our hypothesis of using our body-worn sensor-based solution for passive or active monitoring of mobility and QoL in PD to produce objective, feasible, and continuous digital biomarkers.

Digital gait markers to potentially distinguish fragile X-associated tremor/ataxia syndrome, Parkinson's disease, and essential tremor

Background

Fragile X-associated tremor/ataxia syndrome (FXTAS), a neurodegenerative disease that affects carriers of a 55-200 CGG repeat expansion in the fragile X messenger ribonucleoprotein 1 (FMR1) gene, may be given an incorrect initial diagnosis of Parkinson's disease (PD) or essential tremor (ET) due to overlapping motor symptoms. It is critical to characterize distinct phenotypes in FXTAS compared to PD and ET to improve diagnostic accuracy. Fast as possible (FP) speed and dual-task (DT) paradigms have the potential to distinguish differences in gait performance between the three movement disorders. Therefore, we sought to compare FXTAS, PD, and ET patients using quantitative measures of functional mobility and gait under self-selected (SS) speed, FP, and DT conditions.

Methods

Participants with FXTAS (n = 22), PD (n = 23), ET (n = 20), and controls (n = 20) underwent gait testing with an inertial sensor system (APDM™). An instrumented Timed Up and Go test (i-TUG) was used to measure movement transitions, and a 2-min walk test (2MWT) was used to measure gait and turn variables under SS, FP, and DT conditions, and dual-task costs (DTC) were calculated. ANOVA and multinomial logistic regression analyses were performed.

Results

PD participants had reduced stride lengths compared to FXTAS and ET participants under SS and DT conditions, longer turn duration than ET participants during the FP task, and less arm symmetry than ET participants in SS gait. They also had greater DTC for stride length and velocity compared to FXTAS participants. On the i-TUG, PD participants had reduced sit-to-stand peak velocity compared to FXTAS and ET participants. Stride length and arm symmetry index during the DT 2MWT was able to distinguish FXTAS and ET from PD, such that participants with shorter stride lengths were more likely to have a diagnosis of PD and those with greater arm asymmetry were more likely to be diagnosed with PD. No gait or i-TUG parameters distinguished FXTAS from ET participants in the regression model.

Conclusion

This is the first quantitative study demonstrating distinct gait and functional mobility profiles in FXTAS, PD, and ET which may assist in more accurate and timely diagnosis.

Association between Self-reported Sleep Quality and Single-task Gait in Young Adults: A Study Using Machine Learning

Objective  The objective of the present study was to find biomechanical correlates of single-task gait and self-reported sleep quality in a healthy, young population by replicating a recently published study. Materials and Methods  Young adults ( n  = 123) were recruited and were asked to complete the Pittsburgh Sleep Quality Inventory to assess sleep quality. Gait variables ( n  = 53) were recorded using a wearable inertial measurement sensor system on an indoor track. The data were split into training and test sets and then different machine learning models were applied. A post-hoc analysis of covariance (ANCOVA) was used to find statistically significant differences in gait variables between good and poor sleepers. Results  AdaBoost models reported the highest correlation coefficient (0.77), with Support-Vector classifiers reporting the highest accuracy (62%). The most important features associated with poor sleep quality related to pelvic tilt and gait initiation. This indicates that overall poor sleepers have decreased pelvic tilt angle changes, specifically when initiating gait coming out of turns (first step pelvic tilt angle) and demonstrate difficulty maintaining gait speed. Discussion  The results of the present study indicate that when using traditional gait variables, single-task gait has poor accuracy prediction for subjective sleep quality in young adults. Although the associations in the study are not as strong as those previously reported, they do provide insight into how gait varies in individuals who report poor sleep hygiene. Future studies should use larger samples to determine whether single task-gait may help predict objective measures of sleep quality especially in a repeated measures or longitudinal or intervention framework.

Overview on wearable sensors for the management of Parkinson's disease

Parkinson's disease (PD) is affecting about 1.2 million patients in Europe with a prevalence that is expected to have an exponential increment, in the next decades. This epidemiological evolution will be challenged by the low number of neurologists able to deliver expert care for PD. As PD is better recognized, there is an increasing demand from patients for rigorous control of their symptoms and for therapeutic education. In addition, the highly variable nature of symtoms between patients and the fluctuations within the same patient requires innovative tools to help doctors and patients monitor the disease in their usual living environment and adapt treatment in a more relevant way. Nowadays, there are various body-worn sensors (BWS) proposed to monitor parkinsonian clinical features, such as motor fluctuations, dyskinesia, tremor, bradykinesia, freezing of gait (FoG) or gait disturbances. BWS have been used as add-on tool for patients' management or research purpose. Here, we propose a practical anthology, summarizing the characteristics of the most used BWS for PD patients in Europe, focusing on their role as tools to improve treatment management. Consideration regarding the use of technology to monitor non-motor features is also included. BWS obviously offer new opportunities for improving management strategy in PD but their precise scope of use in daily routine care should be clarified.

Identification of motor progression in Parkinson's disease using wearable sensors and machine learning

Wearable devices offer the potential to track motor symptoms in neurological disorders. Kinematic data used together with machine learning algorithms can accurately identify people living with movement disorders and the severity of their motor symptoms. In this study we aimed to establish whether a combination of wearable sensor data and machine learning algorithms with automatic feature selection can estimate the clinical rating scale and whether it is possible to monitor the motor symptom progression longitudinally, for people with Parkinson's Disease. Seventy-four patients visited the lab seven times at 3-month intervals. Their walking (2-minutes) and postural sway (30-seconds,eyes-closed) were recorded using six Inertial Measurement Unit sensors. Simple linear regression and Random Forest algorithms were utilised together with different routines of automatic feature selection or factorisation, resulting in seven different machine learning algorithms to estimate the clinical rating scale (Movement Disorder Society- Unified Parkinson's Disease Rating Scale part III; MDS-UPDRS-III). Twenty-nine features were found to significantly progress with time at group level. The Random Forest model revealed the most accurate estimation of the MDS-UPDRS-III among the seven models. The model estimations detected a statistically significant progression of the motor symptoms within 15 months when compared to the first visit, whereas the MDS-UPDRS-III did not capture any change. Wearable sensors and machine learning can track the motor symptom progression in people with PD better than the conventionally used clinical rating scales. The methods described in this study can be utilised complimentary to the clinical rating scales to improve the diagnostic and prognostic accuracy.

Objective measurement versus clinician-based assessment for Parkinson's disease

INTRODUCTION

Although clinician-based assessment through standardized clinical rating scales is currently the gold standard for quantifying motor impairment in Parkinson's disease (PD), it is not without limitations, including intra- and inter-rater variability and a degree of approximation. There is increasing evidence supporting the use of objective motion analyses to complement clinician-based assessment. Objective measurement tools hold significant potential for improving the accuracy of clinical and research-based evaluations of patients.

AREAS COVERED

The authors provide several examples from the literature demonstrating how different motion measurement tools, including optoelectronics, contactless and wearable systems allow for both the objective quantification and monitoring of key motor symptoms (such as bradykinesia, rigidity, tremor, and gait disturbances), and the identification of motor fluctuations in PD patients. Furthermore, they discuss how, from a clinician's perspective, objective measurements can help in various stages of PD management.

EXPERT OPINION

In our opinion, sufficient evidence supports the assertion that objective monitoring systems enable accurate evaluation of motor symptoms and complications in PD. A range of devices can be utilized not only to support diagnosis but also to monitor motor symptom during the disease progression and can become relevant in the therapeutic decision-making process.

Wearable sensors for assessing disease severity and progression in Progressive Supranuclear Palsy

INTRODUCTION

Progressive supranuclear palsy (PSP) is an atypical parkinsonism characterized by prominent gait and postural impairment. The PSP rating scale (PSPrs) is a clinician-administered tool to evaluate disease severity and progression. More recently, digital technologies have been used to investigate gait parameters. Therefore, object of this study was to implement a protocol using wearable sensors evaluating disease severity and progression in PSP.

METHODS

Patients were evaluated with the PSPrs as well as with three wearable sensors located on the feet and lumbar area. Spearman coefficient was used to assess the relationship between PSPrs and quantitative measurements. Furthermore, sensor parameters were included in a multiple linear regression model to assess their ability in predicting the PSPrs total score and sub-scores. Finally, differences between baseline and three-month follow-up were calculated for PSPrs and each quantitative variable. The significance level in all analyses was set at ≤ 0.05.

RESULTS

Fifty-eight evaluations from thirty-five patients were analyzed. Quantitative measurements showed multiple significant correlations with the PSPrs scores (r between 0.3 and 0.7; p < 0.05). Linear regression models confirmed the relationships. After three months visit, significant worsening from baseline was observed for cadence, cycle duration and PSPrs item 25, while PSPrs item 10 showed a significant improvement.

CONCLUSION

We propose wearable sensors can provide an objective, sensitive quantitative evaluation and immediate notification of gait changes in PSP. Our protocol can be easily introduced in outpatient and research settings as a complementary tool to clinical measures as well as an informative tool on disease severity and progression in PSP.

Intranasal Administration of Forskolin and Noopept Reverses Parkinsonian Pathology in PINK1 Knockout Rats

Parkinson's Disease (PD) is a brain-degenerative disorder characterized by a progressive loss of midbrain dopamine neurons. Current standard-of-care includes oral administration of Levodopa to address motor symptoms, but this treatment is not disease-modifying. A reduction in Protein Kinase A (PKA) signaling and neurotrophic support contributes to PD pathology. We previously showed that enhancing PKA activity in the brain via intraperitoneal administration of Forskolin in Parkinsonian rats (PINK1 knockout) abrogate motor symptoms and loss of midbrain dopamine neurons. Given that intraperitoneal administration is invasive, we hypothesized that intranasal administration of Forskolin and a second nootropic agent (Noopept) could reverse PD pathology efficiently. Results show that intranasal administration of a formulation (CNS/CT-001) containing Forskolin (10 µM) and Noopept (20 nM) significantly reversed motor symptoms, loss of hind limb strength, and neurodegeneration of midbrain dopamine neurons in PINK1-KO rats and is indistinguishable from wild-type (WT) rats; therapeutic effects associated with increased PKA activity and levels of BDNF and NGF in the brain. Intranasal administration of CNS/CT-001, but not Forskolin, significantly decreased the number of α-synuclein aggregates in the cortex of PINK1-KO rats, and is indistinguishable from WT rats. Overall, we show proof of concept that intranasal administration of CNS/CT-001 is a non-invasive, disease-modifying formulation for PD.

Can Gait Features Help in Differentiating Parkinson's Disease Medication States and Severity Levels? A Machine Learning Approach

Parkinson's disease (PD) is one of the most prevalent neurological diseases, described by complex clinical phenotypes. The manifestations of PD include both motor and non-motor symptoms. We constituted an experimental protocol for the assessment of PD motor signs of lower extremities. Using a pair of sensor insoles, data were recorded from PD patients, Elderly and Adult groups. Assessment of PD patients has been performed by neurologists specialized in movement disorders using the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS)-Part III: Motor Examination, on both ON and OFF medication states. Using as a reference point the quantified metrics of MDS-UPDRS-Part III, severity levels were explored by classifying normal, mild, moderate, and severe levels of PD. Elaborating the recorded gait data, 18 temporal and spatial characteristics have been extracted. Subsequently, feature selection techniques were applied to reveal the dominant features to be used for four classification tasks. Specifically, for identifying relations between the spatial and temporal gait features on: PD and non-PD groups; PD, Elderly and Adults groups; PD and ON/OFF medication states; MDS-UPDRS: Part III and PD severity levels. AdaBoost, Extra Trees, and Random Forest classifiers, were trained and tested. Results showed a recognition accuracy of 88%, 73% and 81% for, the PD and non-PD groups, PD-related medication states, and PD severity levels relevant to MDS-UPDRS: Part III ratings, respectively.

APDM gait and balance measures fail to predict symptom progression rate in Parkinson's disease

Parkinson's disease (PD) results in progressively worsening gait and balance dysfunction that can be measured using computerized devices. We utilized the longitudinal database of the Parkinson's Disease Biomarker Program to determine if baseline gait and balance measures predict future rates of symptom progression. We included 230, 222, 164, and 177 PD subjects with 6, 12, 18, and 24 months of follow-up, respectively, and we defined progression as worsening of the following clinical parameters: MDS-UPDRS total score, Montreal Cognitive Assessment, PDQ-39 mobility subscale, levodopa equivalent daily dose, Schwab and England score, and global composite outcome. We developed ridge regression models to independently estimate how each gait or balance measure, or combination of measures, predicted progression. The accuracy of each ridge regression model was calculated by cross-validation in which 90% of the data were used to estimate the ridge regression model which was then tested on the 10% of data left out. While the models modestly predicted change in outcomes at the 6-month follow-up visit (accuracy in the range of 66–71%) there was no change in the outcome variables during this short follow-up (median change in MDS-UPDRS total score = 0 and change in LEDD = 0). At follow-up periods of 12, 18, and 24 months, the models failed to predict change (accuracy in the held-out sets ranged from 42 to 60%). We conclude that this set of computerized gait and balance measures performed at baseline is unlikely to help predict future disease progression in PD. Research scientists must continue to search for progression predictors to enhance the performance of disease modifying clinical trials.

Association between Self-Reported Prior Night's Sleep and Single-Task Gait in Healthy, Young Adults: A Study Using Machine Learning

Failure to obtain the recommended 7−9 h of sleep has been associated with injuries in youth and adults. However, most research on the influence of prior night’s sleep and gait has been conducted on older adults and clinical populations. Therefore, the objective of this study was to identify individuals who experience partial sleep deprivation and/or sleep extension the prior night using single task gait. Participants (n = 123, age 24.3 ± 4.0 years; 65% female) agreed to participate in this study. Self-reported sleep duration of the night prior to testing was collected. Gait data was collected with inertial sensors during a 2 min walk test. Group differences (<7 h and >9 h, poor sleepers; 7−9 h, good sleepers) in gait characteristics were assessed using machine learning and a post-hoc ANCOVA. Results indicated a correlation (r = 0.79) between gait parameters and prior night’s sleep. The most accurate machine learning model was a Random Forest Classifier using the top 9 features, which had a mean accuracy of 65.03%. Our findings suggest that good sleepers had more asymmetrical gait patterns and were better at maintaining gait speed than poor sleepers. Further research with larger subject sizes is needed to develop more accurate machine learning models to identify prior night’s sleep using single-task gait.

Gait Analysis with Wearables Is a Potential Progression Marker in Parkinson's Disease

Gait disturbance is a prototypical feature of Parkinson's disease (PD), and the quantification of gait using wearable sensors is promising. This study aimed to identify gait impairment in the early and progressive stages of PD according to the Hoehn and Yahr (H-Y) scale. A total of 138 PD patients and 56 healthy controls (HCs) were included in our research. We collected gait parameters using the JiBuEn gait-analysis system. For spatiotemporal gait parameters and kinematic gait parameters, we observed significant differences in stride length (SL), gait velocity, the variability of SL, heel strike angle, and the range of motion (ROM) of the ankle, knee, and hip joints between HCs and PD patients in H-Y Ⅰ-Ⅱ. The changes worsened with the progression of PD. The differences in the asymmetry index of the SL and ROM of the hip were found between HCs and patients in H-Y Ⅳ. Additionally, these gait parameters were significantly associated with Unified Parkinson's Disease Rating Scale and Parkinson's Disease Questionnaire-39. This study demonstrated that gait impairment occurs in the early stage of PD and deteriorates with the progression of the disease. The gait parameters mentioned above may help to detect PD earlier and assess the progression of PD.

Dual task effect on upper and lower extremity skills in different stages of Parkinson's disease

BACKGROUND AND PURPOSE

Loss of automaticity and deteriorated executive function give rise to dual task deficits in Parkinson's disease (PD). This study aimed to compare single task and dual task upper and lower extremity skills in people with PD (PwPD) at different stages of PD and to examine the dual task effect (DTE) on upper and lower extremity skills in PwPD at different stages of PD. The second aim was to investigate the relationship between the DTE and the quality of life in PwPD.

METHODS

30 patients divided into 2 groups as mild PD group and moderate PD group according to the Modified Hoehn & Yahr Scale. 15 age matched healthy adults were recruited as the control group. The Unified Parkinson's Disease Rating Scale (UPDRS), the Purdue Pegboard Test (PPT), the Timed Up and Go Test (TUG), the 10 Meter Walk Test (10MWT), and the Parkinson's Disease Questionnaire (PDQ-8) were used for assessments.

RESULTS

Single task and dual task scores of all assessments of all groups were significantly different. The DTE on PPT was greater in mild and moderate PD groups than control group and significantly lower in mild PD group than moderate PD group. However, DTE on the TUG and 10MWT was not different in mild PD group than control group and DTE significantly lower in both groups than moderate PD group. Significant correlations between the DTE on PPT, TUG and 10MWT and the PDQ-8 in PwPD were observed.

CONCLUSION

Dual task has a worsening effect on upper and lower extremity skills in PwPD. This effect can be observed earlier in upper extremity skills than lower extremity skills. Also, the DTE and the QoL in PwPD are related.

Review-Emerging Portable Technologies for Gait Analysis in Neurological Disorders

The understanding of locomotion in neurological disorders requires technologies for quantitative gait analysis. Numerous modalities are available today to objectively capture spatiotemporal gait and postural control features. Nevertheless, many obstacles prevent the application of these technologies to their full potential in neurological research and especially clinical practice. These include the required expert knowledge, time for data collection, and missing standards for data analysis and reporting. Here, we provide a technological review of wearable and vision-based portable motion analysis tools that emerged in the last decade with recent applications in neurological disorders such as Parkinson's disease and Multiple Sclerosis. The goal is to enable the reader to understand the available technologies with their individual strengths and limitations in order to make an informed decision for own investigations and clinical applications. We foresee that ongoing developments toward user-friendly automated devices will allow for closed-loop applications, long-term monitoring, and telemedical consulting in real-life environments.

The timed up and go test in idiopathic normal pressure hydrocephalus: a Nationwide Study of 1300 patients

BACKGROUND

The aim of this study was to describe the outcome measure timed up and go (TUG) in a large, nationwide cohort of patients with idiopathic normal pressure hydrocephalus (iNPH) pre- and post-operatively. Furthermore, to compare the TUG test to the 10-m walk test (10MWT), the iNPH scale, the modified Rankin scale (mRS) and the Mini Mental State Examination (MMSE), which are commonly applied in clinical assessment of iNPH.

METHODS

Patients with iNPH (n = 1300), registered in the Swedish Hydrocephalus Quality Registry (SHQR), were included. All data were retrieved from the SHQR except the 10MWT, which was collected from patient medical records. Clinical scales were examined pre- and 3 months post-operatively. Data were dichotomised by sex, age, and preoperative TUG time.

RESULTS

Preoperative TUG values were 19.0 [14.0-26.0] s (median [IQR]) and 23 [18-30] steps. Post-operatively, significant improvements to 14.0 [11.0-20.0] s and 19 [15-25] steps were seen. TUG time and steps were higher in women compared to men (p < 0.001) but there was no sex difference in improvement rate. Worse preoperative TUG and younger age favoured improvement. TUG was highly correlated to the 10MWT, but correlations of post-operative changes were only low to moderate between all scales (r = 0.22-0.61).

CONCLUSIONS

This study establishes the distribution of TUG in iNPH patients and shows that the test captures important clinical features that improve after surgery independent of sex and in all age groups, confirming the clinical value of the TUG test. TUG performance is associated with performance on the 10MWT pre- and post-operatively. However, the weak correlations in post-operative change to the 10MWT and other established outcome measures indicate an additional value of TUG when assessing the effects of shunt surgery.

Rambling-trembling center-of-pressure decomposition reveals distinct sway responses to simulated somatosensory deficit

BACKGROUND

Falls in older adults are often multifactorial, but can be linked to diminished sensation capabilities from age-related neural degeneration. Rambling-trembling (RM-TR) decomposition may provide insight into the relation between sensorineural function and postural sway, with both research and clinical applications.

RESEARCH QUESTION

What are the effects of perturbed somatosensation on RM-TR-derived measures of center of pressure (COP) during quiet standing?

METHODS

Fifty-two healthy young adults (22.10 ± 1.88 years) participated in the study. Participants stood on two force plates with a standardized stance width and foot angle, with eyes open (EO) or eyes closed (EC). Foam with different thicknesses ranging from 1/8″ to 1″ (F1-F4) was placed under the feet to interfere with intact sensory input and simulate varying degrees of somatosensory deficit. Force and moment data were used to calculate COP, RM, and TR time series. Mean velocity, acceleration, and jerk in the anteroposterior (AP) and mediolateral direction (ML) were extracted for comparison.

RESULTS

The EO condition remained relatively constant regardless of foam thickness. The EC condition showed increasing changes from baseline to each of the foam conditions. COP captures the smallest change in foam thickness, but RM provides a robustness across parameters that is not found in COP or TR. RM jerk in the AP direction showed significantly greater changes from baseline to F4 than the COP or TR counterparts. In the ML direction, TR jerk showed a sharper contrast between foam conditions than COP and RM.

SIGNIFICANCE

Findings suggest that RM-TR-derived measures may act as a compliment to, or provide a greater degree of sensitivity than, traditional COP measures and aid in the initial detection and monitoring of fall risk in aging and pathological populations.

Normative database of postural sway measures using inertial sensors in typically developing children and young adults

OBJECTIVE

Reference values utilizing the APDM MobilityLab® inertial sensor system have not been established in children and young adults ages 5-30. These values are necessary for clinicians and researchers to compare to children with balance impairments.

METHODS

A group of 144 typically developing children and young adults from age 5-30 years completed the instrumented SWAY test during 6 test conditions: normal stance, firm surface, eyes open (EO) and closed (EC); normal stance, foam surface, EO and EC; and tandem stance, firm surface, EO and EC. Selected variables for normative outcomes included total sway area, and the mean, sagittal and coronal values for RMS sway, jerk, sway velocity and path length. Sex differences were examined within age groups via t tests. The effect of age on postural sway variables was analyzed using a one-way ANOVA for the mean values of total sway area, RMS sway, velocity and jerk, followed by post-hoc pairwise comparisons.

RESULTS

All sway parameters decreased significantly with age (p < 0.0001). Adult-like total sway area and jerk were achieved by ages 9-10 except for jerk during EC on foam. RMS sway and sway velocity reached adult levels by ages 11-13 during all EO and tandem stance conditions, and 14-21 with EC during normal stance on firm and foam surfaces for RMS sway and EC on firm surfaces for velocity. Females ages 5-6 performed more poorly during EO firm and EC foam for certain variables, but better during EO tandem and females ages 7-13 outperformed males when sex differences were found.

SIGNIFICANCE

These reference values can now be used by clinicians and researchers to evaluate abnormal postural sway and response to interventions in children and young adults.

A Systematic Review of Machine Learning Based Gait characteristics in Parkinson's disease

OBJECTIVE

Parkinson's disease is a pervasive neuro disorder that affects people's quality of life throughout the world. The unsatisfactory results of clinical rating scales open the door for more research. PD treatment using current biomarkers seems a difficult task. So automatic evaluation at an early stage may enhance the quality and time-period of life.

METHODS

Grading of Recommendations Assessment, Development, and Evaluation (GRADE) and Population, intervention, comparison, and outcome (PICO) search methodology schemes are followed to search the data and eligible studies for this survey. Approximate 1500 articles were extracted using related search strings. After the stepwise mapping and elimination of studies, 94 papers are found suitable for the present review.

RESULTS

After the quality assessment of extracted studies, nine inhibitors are identified to analyze people's gait with Parkinson's disease, where four are critical. This review also differentiates the various machine learning classification techniques with their PD analysis characteristics in previous studies. The extracted research gaps are described as future perspectives. Results can help practitioners understand the PD gait as a valuable biomarker for detection, quantification, and classification.

CONCLUSION

Due to less cost and easy recording of gait, gait-based techniques are becoming popular in PD detection. By encapsulating the gait-based studies, it gives an in-depth knowledge of PD, different measures that affect gait detection and classification.

Automated movement recognition to predict motor impairment in high-risk infants: a systematic review of diagnostic test accuracy and meta-analysis

AIM

To assess the sensitivity and specificity of automated movement recognition in predicting motor impairment in high-risk infants.

METHOD

We searched MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, and Scopus databases and identified additional studies from the references of relevant studies. We included studies that evaluated automated movement recognition in high-risk infants to predict motor impairment, including cerebral palsy (CP) and non-CP motor impairments. Two authors independently assessed studies for inclusion, extracted data, and assessed methodological quality using the Quality Assessment of Diagnostic Accuracy Studies-2. Meta-analyses were performed using hierarchical summary receiver operating characteristic models.

RESULTS

Of 6536 articles, 13 articles assessing 59 movement variables in 1248 infants under 5 months corrected age were included. Of these, 143 infants had CP. The overall sensitivity and specificity for motor impairment were 0.73 (95% confidence interval [CI] 0.68-0.77) and 0.70 (95% CI 0.65-0.75) respectively. Comparatively, clinical General Movements Assessment (GMA) was found to have sensitivity and specificity of 98% (95% CI 74-100) and 91% (95% CI 83-93) respectively. Sensor-based technologies had higher specificity (0.88, 95% CI 0.80-0.93).

INTERPRETATION

Automated movement recognition technology remains inferior to clinical GMA. The strength of this study is its meta-analysis to summarize performance, although generalizability of these results is limited by study heterogeneity.

Postural sway correlates with cognition and quality of life in Parkinson's disease

Background

The severity of Parkinson's disease (PD) is difficult to assess objectively owing to the lack of a robust biological marker of underlying disease status, with consequent implications for diagnosis, treatment and prognosis. The current standard tool is the Unified Parkinson's Disease Rating Scale (MDS-UPDRS), but this is hampered by variability between observers and within subjects. Postural sway has been shown to correlate with complex brain functioning in other conditions. This study aimed to investigate the relationship between postural sway, MDS-UPDRS and other non-motor measures of disease severity in patients with PD.

Method

25 patients with PD and 18 age-matched controls participated in the study. All participants underwent assessment of postural sway using a force plate, with eyes open and closed. In addition, participants underwent tests of cognition and quality of life: Montreal Cognitive Assessment (MoCA), Neuropsychiatry Unit Cognitive Assessment (NUCOG) and, for the patients, the Parkinson's Disease Questionnaire (PDQ-39-1), and assessment of clinical status using the motor component of the MDS-UPDRS.

Results

Patients swayed significantly more than controls. This was most obvious in the eyes-closed condition. Sway path length showed strong correlations with PDQ-39-1, MoCA and the verbal fluency component of the NUCOG, and, to a lesser degree, with the UPDRS-III in patients with PD.

Conclusion

These results suggest that motor and non-motor symptoms of PD are associated in patients, and, in particular, that postural sway shows potential as a possible measure of underlying disease status in PD, either alone or in combination with other measures.

Cortical thickness as predictor of response to exercise in people with Parkinson's disease

We previously showed that dual-task cost (DTC) on gait speed in people with Parkinson's disease (PD) improved after 6 weeks of the Agility Boot Camp with Cognitive Challenge (ABC-C) exercise program. Since deficits in dual-task gait speed are associated with freezing of gait and gray matter atrophy, here we performed preplanned secondary analyses to answer two questions: (a) Do people with PD who are freezers present similar improvements compared to nonfreezers in DTC on gait speed with ABC-C? (b) Can cortical thickness at baseline predict responsiveness to the ABC-C? The DTC from 39 freezers and 43 nonfreezers who completed 6 weeks of ABC-C were analyzed. A subset of 51 participants (21 freezers and 30 nonfreezers) with high quality imaging data were used to characterize relationships between baseline cortical thickness and delta (Δ) DTC on gait speed following ABC-C. Freezers showed larger ΔDTC on gait speed than nonfreezers with ABC-C program (p < .05). Cortical thickness in visual and fronto-parietal areas predicted ΔDTC on gait speed in freezers, whereas sensorimotor-lateral thickness predicted ΔDTC on gait speed in nonfreezers (p < .05). When matched for motor severity, visual cortical thickness was a common predictor of response to exercise in all individuals, presenting the largest effect size. In conclusion, freezers improved gait automaticity even more than nonfreezers from cognitively challenging exercise. DTC on gait speed improvement was associated with larger baseline cortical thickness from different brain areas, depending on freezing status, but visual cortex thickness showed the most robust relationship with exercise-induced improvements in DTC.

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

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

Kinematic but not clinical measures predict falls in Parkinson-related orthostatic hypotension

OBJECTIVE

We sought to test the hypothesis that technology could predict the risk of falls in Parkinson's disease (PD) patients with orthostatic hypotension (OH) with greater accuracy than in-clinic assessment.

METHODS

Twenty-six consecutive PD patients with OH underwent clinical (including home-like assessments of activities of daily living) and kinematic evaluations of balance and gait as well as beat-to-beat blood pressure (BP) monitoring to estimate their association with the risk of falls. Fall frequency was captured by a diary collected prospectively over 6 months. When applicable, the sensitivity, specificity, and diagnostic accuracy were measured using the area under the receiver operating characteristics curve (AUC). Additional in-clinic assessments included the OH Symptom Assessment (OHSA), the OH Daily Activity Score (OHDAS), and the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS).

RESULTS

The prevalence of falls was 53.8% over six months. There was no association between the risk of falls and test of gait and postural stability (p ≥ 0.22) or home-like activities of daily living (p > 0.08). Conversely, kinematic data (waist sway during time-up-and-go, jerkiness, and centroidal frequency during postural sway with eyes-opened) predicted the risk of falls with high sensitivity and specificity (> 80%; AUC ≥ 0.81). There was a trend for higher risk of falls in patients with orthostatic mean arterial pressure ≤ 75 mmHg.

CONCLUSIONS

Kinematic but not clinical measures predicted falls in PD patients with OH. Orthostatic mean arterial pressure ≤ 75 mmHg may represent a hemodynamic threshold below which falls become more prevalent, supporting the aggressive deployment of corrective measures.

Automated Stage Discrimination of Parkinson’s Disease

Abstract Background: Treatment plans for Parkinson’s disease (PD) are based on a disease stage scale, which is generally determined using a manual, observational procedure. Automated, sensor-based discrimination saves labor and costs in clinical settings and may offer augmented stage determination accuracy. Previous automated devices were either cumbersome or costly and were not suitable for individuals who cannot walk without support.Methods: Since 2017, a device has been available that successfully detects PD and operates for people who cannot walk without support. In the present study, the suitability of this device for automated discrimination of PD stages was tested. The device consists of a walking frame fitted with sensors to simultaneously support walking and monitor patient gait. Sixty-five PD patients in Hoehn and Yahr (HY) stages 1 to 4 and 24 healthy controls were subjected to supported Timed Up and Go (TUG) tests, while using the walking frame. The walking trajectory, velocity, acceleration and force were recorded by the device throughout the tests. These physical parameters were converted into symptomatic spatiotemporal quantities that are conventionally used in PD gait assessment.Results: An analysis of variance (ANOVA) test extended by a confidence interval (CI) analysis indicated statistically significant separability between HY stages for the following spatiotemporal quantities: TUG time (p < 0.001), straight line walking time (p < 0.001), turning time (p < 0.001), and step count (p < 0.001). A negative correlation was obtained for mean step velocity (p < 0.001) and mean step length (p < 0.001). Moreover, correlations were established between these, as well as additional spatiotemporal quantities, and disease duration, L-dihydroxyphenylalanine-(L-DOPA) dose, motor fluctuation, dyskinesia and the mobile part of the Unified Parkinson Disease Rating Scale (UPDRS).Conclusions: We have proven that stage discrimination of PD can be automated, even to patients who cannot support themselves. A similar method might be successfully applied to other gait disorders.

Normative database of spatiotemporal gait parameters using inertial sensors in typically developing children and young adults

BACKGROUND

Inertial sensors are increasingly useful to clinicians and researchers to detect gait deficits. Reference values are necessary for comparison to children with gait abnormalities.

OBJECTIVE

To present a normative database of spatiotemporal gait and turning parameters in 164 typically developing children and young adults ages 5-30 utilizing the APDM Mobility Lab® system.

METHODS

Participants completed the i-WALK test at both self-selected (SS) and fast as possible (FAP) walking speeds. Spatiotemporal gait and turning parameters included stride length, stride length variability, gait speed, cadence, stance, swing, and double support times, and foot strike, toe-off, and toe-out angles, turn duration, peak turn velocity and number of steps to turn.

RESULTS

Absolute stride length and gait speed increased with age. Normalized gait speed, absolute and normalized cadence, and stride length variability decreased with age. Normalized stride length and all parameters of gait cycle phase and foot position remained unaffected by age except for greater FSA in children 7-8. Foot position parameters in children 5-6 were excluded due to aberrant values and high standard deviations. Turns were faster in children ages 5-13 and 7-13 in the SS and FAP conditions, respectively. There were no differences in number of steps to turn. Similar trends were observed in the FAP condition except: normalized gait speed did not demonstrate a relationship with age and children ages 5-8 demonstrated increased stance and double support times and decreased swing time compared to children 11-13 and young adults (ages 5-6 only). Females ages 5-6 demonstrated increased stride length variability in the SS condition; males ages 7-8 and 14-30 ha d increased absolute stride length in the FAP condition. Similarities and differences were found between our values and previous literature.

SIGNIFICANCE

This normative database can be used by clinicians and researchers to compare abnormal gait patterns and responses to interventions.

Prediction of Individual Progression Rate in Parkinson's Disease Using Clinical Measures and Biomechanical Measures of Gait and Postural Stability

Parkinson's disease (PD) is a common neurological disorder characterized by gait impairment. PD has no cure, and an impediment to developing a treatment is the lack of any accepted method to predict disease progression rate. The primary aim of this study was to develop a model using clinical measures and biomechanical measures of gait and postural stability to predict an individual's PD progression over two years. Data from 160 PD subjects were utilized. Machine learning models, including XGBoost and Feed Forward Neural Networks, were developed using extensive model optimization and cross-validation. The highest performing model was a neural network that used a group of clinical measures, achieved a PPV of 71% in identifying fast progressors, and explained a large portion (37%) of the variance in an individual's progression rate on held-out test data. This demonstrates the potential to predict individual PD progression rate and enrich trials by analyzing clinical and biomechanical measures with machine learning.

Determining the utility of a smartphone-based gait evaluation for possible use in concussion management

Objectives: Our was objectives were to (1) assess the validity of a smartphone-based application to obtain spatiotemporal gait variables relative to an established movement monitoring system used previously to evaluate post-concussion gait, and (2) determine the test-retest reliability of gait variables obtained with a smartphone.Methods: Twenty healthy participants (n = 14 females, mean age = 22.2, SD = 2.1 years) were assessed at two time points, approximately two weeks apart. Two measurement systems (inertial sensor system, smartphone application) acquired and analyzed single-task and dual-task spatio-temporal gait variables simultaneously. Our primary outcome measures were average walking speed (m/s), cadence (steps/min), and stride length (m) measured by the inertial sensor system and smartphone application.Results: Correlations between the systems were high to very high (Pearson r = 0.77-0.98) at both time points, with the exception of dual-task stride length at time 2 (Pearson r = 0.55). Bland-Altman analysis for average gait speed and cadence indicated the average disagreement between systems was close to zero, suggesting little evidence for systematic bias between acquisition systems. Test-retest consistency measures using the smartphone revealed high to very high reliability for all measurements (ICC = 0.81-0.95).Conclusions: Our results indicate that sensors within a smartphone are capable of measuring spatio-temporal gait variables similar to a validated three-sensor inertial sensor system in single-task and dual-task conditions, and that data are reliable across a two-week time interval. A smartphone-based application might allow clinicians to objectively evaluate gait in the management of concussion with high ease-of-use and a relatively low financial burden.

Gait asymmetry in glucocerebrosidase mutation carriers with Parkinson's disease

BACKGROUND

GBA mutation carriers with PD (PD-GBA) are at higher risk of cognitive decline, but there is limited data regarding whether there are differences in gait dysfunction between GBA mutation and non-mutation carriers with PD.

OBJECTIVES/METHODS

The primary aim of this study was to use quantitative inertial sensor-based gait analysis to compare gait asymmetry in 17 PD-GBA subjects, 17 non-mutation carriers with PD, and 15 healthy control subjects using parameters that had gait laterality and were markers of bradykinesia, in particular arm swing velocity and arm swing range of motion and stride length.

RESULTS

Arm swing velocity was more symmetric in PD-GBA subjects vs. non-mutation carriers in the OFF state (12.5 +/- 8.3 vs. 22.9 +/- 11.8%, respectively, p = 0.018). In the ON-medication state, non-mutation carriers with PD, but not PD-GBA subjects, exhibited arm swing velocity (16.8 +/- 8.6 vs. 22.9 +/- 11.8%, p = 0.006) and arm range of motion (26.7 +/- 16.3 vs. 33.4 +/- 18.6%, p = 0.02) that was more asymmetric compared with the OFF-medication state.

CONCLUSIONS

In the OFF medication state, arm swing velocity asymmetry may be a useful parameter in helping to distinguish GBA mutation carriers with PD from non-mutation carriers.

Use of Wearable Sensor Technology in Gait, Balance, and Range of Motion Analysis

More than 8.6 million people suffer from neurological disorders that affect their gait and balance. Physical therapists provide interventions to improve patient’s functional outcomes, yet balance and gait are often evaluated in a subjective and observational manner. The use of quantitative methods allows for assessment and tracking of patient progress during and after rehabilitation or for early diagnosis of movement disorders. This paper surveys the state-of-the-art in wearable sensor technology in gait, balance, and range of motion research. It serves as a point of reference for future research, describing current solutions and challenges in the field. A two-level taxonomy of rehabilitation assessment is introduced with evaluation metrics and common algorithms utilized in wearable sensor systems.

Gait Classification Using Mahalanobis–Taguchi System for Health Monitoring Systems Following Anterior Cruciate Ligament Reconstruction

In this paper, a gait patterns classification system is proposed, which is based on Mahalanobis–Taguchi System (MTS). The classification of gait patterns is necessary in order to ascertain the rehab outcome among anterior cruciate ligament reconstruction (ACLR) patients. (1) Background: One of the most critical discussion about when ACLR patients should return to work (RTW). The objective was to use Mahalanobis distance (MD) to classify between the gait patterns of the control and ACLR groups, while the Taguchi Method (TM) was employed to choose the useful features. Moreover, MD was also utilised to ascertain whether the ACLR group approaching RTW. The combination of these two methods is called as Mahalanobis-Taguchi System (MTS). (2) Methods: This study compared the gait of 15 control subjects to a group of 10 subjects with laboratory. Later, the data were analysed using MTS. The analysis was based on 11 spatiotemporal parameters. (3) Results: The results showed that gait deviations can be identified successfully, while the ACLR can be classified with higher precision by MTS. The MDs of the healthy group ranged from 0.560 to 1.180, while the MDs of the ACLR group ranged from 2.308 to 1509.811. Out of the 11 spatiotemporal parameters analysed, only eight parameters were considered as useful features. (4) Conclusions: These results indicate that MTS can effectively detect the ACLR recovery progress with reduced number of useful features. MTS enabled doctors or physiotherapists to provide a clinical assessment of their patients with more objective way.

Effects of Exergaming on Attentional Deficits and Dual-Tasking in Parkinson's Disease

Introduction: Impairment of dual-tasking, as an attention-based primary cognitive dysfunction, is frequently observed in Parkinson's Disease (PD). The Training-PD study investigated the efficiency of exergaming, as a novel cognitive-motor training approach, to improve attention-based deficits and dual-tasking in PD when compared to healthy controls.

Methods: Eighteen PD patients and 17 matched healthy controls received a 6-week home-based training period of exergaming. Treatment effects were monitored using quantitative motor assessment of gait and cognitive testing as baseline and after 6 weeks of training.

Results: At baseline PD patients showed a significantly worse performance in several quantitative motor assessment parameters and in two items of cognitive testing. After 6 weeks of exergames training, the comparison of normal gait vs. dual-tasking in general showed an improvement of stride length in the PD group, without a gait-condition specific improvement. In the direct comparison of three different gait conditions (normal gait vs. dual-tasking calculating while walking vs. dual-tasking crossing while walking) PD patients showed a significant improvement of stride length under the dual-tasking calculating condition. This corresponded to a significant improvement in one parameter of the D2 attention test.

Conclusions: We conclude, that exergaming, as an easy to apply, safe technique, can improve deficits in cognitive-motor dual-tasking and attention in PD.

Exploring the Parkinson patients' perspective on home-based video recording for movement analysis: a qualitative study

Background

Parkinson’s disease is a complex neurological disorder characterized by a variety of motor- as well as non-motor symptoms. Video-based technology (using continuous home monitoring) may bridge the gap between the fragmented in-clinic observations and the need for a comprehensive understanding of the progression and fluctuation of disease symptoms. However, continuous monitoring can be intrusive, raising questions about feasibility as well as potential privacy violation.

Methods

We used a grounded theory approach in which we performed semi-structured interviews to explore the opinion of Parkinson’s patients on home-based video recording used for vision-based movement analysis.

Results

Saturation was reached after sixteen interviews. Three first–level themes were identified that specify the conditions required to perform continuous video monitoring: Camera recording (e.g. being able to turn off the camera), privacy protection (e.g. patient’s behaviour, patient’s consent, camera location) and perceived motivation (e.g. contributing to science or clinical practice).

Conclusion

Our findings show that Parkinson patients’ perception of continuous, home-based video recording is positive, when a number of requirements are taken into account. This knowledge will enable us to start using this technology in future research and clinical practice in order to better understand the disease and to objectify outcomes in the patients’ own homes.

The Effects of Dual-Task Cognitive Interference and Environmental Challenges on Balance in Huntington's Disease

BACKGROUND

Huntington's disease (HD) is characterized by chorea, balance and gait impairments, and cognitive deficits, which increase fall risk. Dual task (DT) and environmentally challenging paradigms reflect balance related to everyday life. Furthermore, the impact of cognitive deficits on balance dysfunction and falls in HD is unknown.

OBJECTIVE

To determine the impact of DT interference, sensory feedback, and cognitive performance on balance and falls in HD.

METHODS

Seventeen participants with HD (55 ± 9.7 years) and 17 age-matched controls (56.5 ± 9.3 years) underwent quantitative balance testing with APDM inertial sensors. Postural sway was assessed during conditions of manipulated stance, vision, proprioception, and cognitive demand. The DT was a concurrent verbal fluency task. Neuropsychological assessments testing multiple cognitive domains were also administered.

RESULTS

HD participants exhibited significantly greater total sway area, jerk, and variability under single-task (ST) and DT conditions compared to controls (P = 0.0002 - < 0.0001). They also demonstrated greater DT interference with vision removed for total sway area (P = 0.01) and variability (P = 0.02). Significantly worse postural control was observed in HD with vision removed and reduced proprioception (P = 0.001 - 0.01). Decreased visuospatial performance correlated with greater total sway and jerk (P = 0.01; 0.009). No balance parameters correlated with retrospective falls in HD.

CONCLUSIONS

HD participants have worse postural control under DT, limited proprioception/vision, and greater DT interference with a narrowed base and no visual input. These findings may have implications for designing motor and cognitive strategies to improve balance in HD.

Effect of PI3K/Akt/mTOR signaling pathway on JNK3 in Parkinsonian rats

Effect of PI3K/Akt/mTOR signaling pathway on the expression of JNK3 in Parkinsonian rats was investigated. A total of 200 rats were used for Parkinson's disease (PD) modeling and 180 models were successfully established. Rats were randomly divided into four groups including A, B, C, and D, 45 in each group. Group A was control group and no inhibitor was given. Group B was given PI3K inhibitor LY294002. Group C was given rapamycin inhibitor rapamycin; and group D was given inhibitor LY294002 and inhibitor rapamycin. JNK3 mRNA expression was detected by RT-qPCR and expression of p-mTOR protein and JNK3 protein was detected by western blot analysis. Expression level of JNK3 mRNA and protein in groups C and D was significantly lower than that in group B (P<0.01). Expression level of JNK3 mRNA and protein in group D was significantly lower than that in group C (P<0.01). Relative expression level of p-mTOR protein in groups C and D was significantly lower than that in group B (P<0.01). Relative expression level of JNK3 protein in group D was significantly lower than that in group C (P<0.01). Pearson's correlation analysis showed that expression of JNK3 mRNA was positively correlated with the expression of JNK3 protein and Pearson's correlation coefficient was 0.98 (P<0.01). There was also a positive correlation between the expression of JNK3 mRNA and the expression of p-mTOR protein and Pearson's correlation coefficient was 0.95 (P<0.01). Expression of JNK3 protein was positively correlated with the expression of p-mTOR protein, and the Pearson's correlation coefficient was 0.93 (P<0.01). Inhibition of PI3K/Akt/mTOR signaling pathway is negatively correlated with the expression of JNK3. Inhibition of PI3K-Akt-mTOR signaling pathway leads to a decrease in the expression of JNK3, which protects dopaminergic neurons and improves PD.

Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data

As the collection of mobile health data becomes pervasive, missing data can make large portions of datasets inaccessible for analysis. Missing data has shown particularly problematic for remotely diagnosing and monitoring Parkinson's disease (PD) using smartphones. This contribution presents multi-source ensemble learning, a methodology which combines dataset deconstruction with ensemble learning and enables participants with incomplete data (i.e., where not all sensor data is available) to be included in the training of machine learning models and achieves a 100% participant retention rate. We demonstrate the proposed method on a cohort of 1513 participants, 91.2% of which contributed incomplete data in tapping, gait, voice, and/or memory tests. The use of multi-source ensemble learning, alongside convolutional neural networks (CNNs) capitalizing on the amount of available data, increases PD classification accuracy from 73.1% to 82.0% as compared to traditional techniques. The increase in accuracy is found to be partly caused by the use of multi-channel CNNs and partly caused by developing models using the large cohort of participants. Furthermore, through bootstrap sampling we reveal that feature selection is better performed on a large cohort of participants with incomplete data than on a small number of participants with complete data. The proposed method is applicable to a wide range of wearable/remote monitoring datasets that suffer from missing data and contributes to improving the ability to remotely monitor PD via revealing novel methods of accounting for symptom heterogeneity.

Quantification of discrete behavioral components of the MDS-UPDRS

INTRODUCTION

The Movement Disorder Society's Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is the current gold standard means of assessing disease state in Parkinson's disease (PD). Objective measures in the form of wearable sensors have the potential to improve our ability to monitor symptomology in PD, but numerous methodological challenges remain, including integration into the MDS-UPDRS. We applied a structured video coding scheme to temporally quantify clinical, scripted, motor tasks in the MDS-UPDRS for the alignment and integration of objective measures collected in parallel.

METHODS

25 PD subjects completed two video-recorded MDS-UPDRS administrations. Visual cues of task performance reliably identifiable in video recordings were used to construct a structured video coding scheme. Postural transitions were also defined and coded. Videos were independently coded by two trained non-expert coders and a third expert coder to derive indices of inter-rater agreement.

RESULTS

50 videos of MDS-UPDRS performance were fully coded. Non-expert coders achieved a high level of agreement (Cohen's κ > 0.8) on all postural transitions and scripted motor tasks except for Postural Stability (κ = 0.617); this level of agreement was largely maintained even when more stringent thresholds for agreement were applied. Durations coded by non-expert coders and expert coders were significantly different (p < 0.05) for only Postural Stability and Rigidity, Left Upper Limb.

CONCLUSIONS

Non-expert coders consistently and accurately quantified discrete behavioral components of the MDS-UPDRS using a structured video coding scheme; this represents a novel, promising approach for integrating objective and clinical measures into unified, longitudinal datasets.

Cognitive function impacts gait, functional mobility and falls in fragile X-associated tremor/ataxia syndrome

BACKGROUND

Executive function and information processing speed deficits occur in fragile X premutation carriers (PMC) with and without fragile X-associated tremor/ataxia syndrome (FXTAS). Gait is negatively impacted by cognitive deficits in many patient populations resulting in increased morbidity and falls but these relationships have not been studied in FXTAS.

RESEARCH QUESTION

We sought to investigate the associations between executive function and information processing speed and gait, turning and falls in PMC with and without FXTAS compared to healthy controls.

METHODS

Global cognition and the cognitive domains of information processing speed, attention, response inhibition, working memory and verbal fluency were tested with a neuropsychological test battery in 18 PMC with FXTAS, 15 PMC without FXTAS, and 27 controls. An inertial sensor based instrumented Timed Up and Go was employed to test gait, turns and functional mobility.

RESULTS

Lower information processing speed was significantly associated with shorter stride length, reflecting slower gait speed, in PMC with FXTAS (p = 0.0006) but not PMC without FXTAS or controls. Lower response inhibition was also significantly associated with slower turn-to-sit times in PMC with FXTAS (p = 0.034) but not in those without FXTAS or controls. Lower information processing speed (p = 0.012) and working memory (p = 0.004), were significantly correlated with a greater number of self-reported falls in the past year in FXTAS participants.

SIGNIFICANCE

This is the first study demonstrating that worse executive function and slower information processing speed is associated with reduced gait speed and functional mobility, as well as with a higher retrospective fall history in participants with FXTAS. This information may be important in the design of cognitive and motor interventions for this neurodegenerative disorder.

Accuracy of Markerless 3D Motion Capture Evaluation to Differentiate between On/Off Status in Parkinson's Disease after Deep Brain Stimulation

Background

Body motion evaluation (BME) by markerless systems is increasingly being considered as an alternative to traditional marker-based technology because they are faster, simpler, and less expensive. They are increasingly used in clinical settings in patients with movement disorders; however, the wide variety of systems available makes results conflicting.

Research Question

The objective of this study was to determine whether a markerless 3D motion capture system is a useful instrument to objectively differentiate between PD patients with DBS in On and Off states and controls and its correlation with the evaluation by means of MDS-UPDRS.

Methods

Six PD patients who underwent deep brain stimulation (DBS) bilaterally in the subthalamic nucleus were evaluated using BME and the Unified Parkinson's Disease Rating Scale (UPDRS-III) with DBS turned On and Off. BME of 16 different movements in six controls paired by age and sex was compared with that in PD patients with DBS in On and Off states.

Results

A better performance in the BME was correlated with a lower UPDRS-III score. There was no statistically significant difference between patients in Off and On states of DBS regarding BME. However, some items such as left shoulder flexion (p=0.038), right shoulder rotation (p=0.011), and left trunk rotation (p=0.023) were different between Off patients and healthy controls.

Significance

Kinematic data obtained with this markerless system could contribute to discriminate between PD patients and healthy controls. This emerging technology may help to clinically evaluate PD patients more objectively.

Automated analysis of gait and modified timed up and go using the Microsoft Kinect in people with Parkinson's disease: associations with physical outcome measures

Instrumenting physical assessments in people with Parkinson's disease can provide valuable and sensitive information. This study aimed to investigate whether variables derived from a Kinect-based system can provide incremental value over standard habitual gait speed (HGS) and timed up and go (TUG) variables by evaluating associations with (1) motor and (2) postural instability and gait difficulty (PIGD) subscales of the Unified Parkinson's Disease Rating Scale (UPDRS). Sixty-two individuals with Parkinson's disease (age 66 ± 7 years; 74% male) undertook an instrumented HGS and modified TUG tests, in addition to the UPDRS. Multivariable regression models were used to evaluate the associations of the Kinect measures with UPDRS motor and PIGD scores. First step length during the TUG and average step length and vertical pelvic displacement during the HGS were significantly associated with the PIGD subscale (P < 0.05). The only Kinect-derived variable showing additive benefits over the standard measures for the PIGD association was HGS vertical pelvic displacement. The only standard or Kinect-derived variable significantly associated with the motor subscale was first step length during the TUG (P < 0.01). This study provides preliminary evidence to support the use of a low-cost, non-invasive method of instrumenting gait and TUG tests in people with Parkinson's disease. Graphical abstract ᅟ.

Predictive ability of functional tests for postural instability and gait difficulty in Parkinson's disease

The objective of this study is to identify clinical determinants for postural instability and gait difficulty in persons with Parkinson's disease (PD). Ninety-one persons (68 males; 74.7%) with PD were studied. Their mean age was 68.73 ± 8.74 years. The average time since diagnosis was 7.69 ± 5.23 years. The average Hoehn and Yahr stage was 2.43 ± 0.44. Age, gender, disease duration, disease severity and motor impairment were recorded. Participants were asked to perform timed clinical mobility tests that included a 5-step test, turns, forward walk, backward walk, and a sideways walk. The mobility tests were investigated for their contribution to predict the postural instability and gait difficulty (PIGD) score (falling, freezing, walking, gait and postural stability) of the Unified Parkinson Disease Rating Scale (UPDRS). PIGD score was significantly correlated with age, disease duration, Hoehn and Yahr score, comorbidity, UPDRS motor score, gait speed of forward, backward and sideways walks, and time to turn. PIGD score was marginally significantly correlated with timed 5-step test. After controlling for age, disease duration, disease severity, comorbidity, and motor impairment, sideway gait speed (β = - 0.335; p = 0.024), timed 5-step test (β = - 0.397; p = 0.003) and time to turn (β = 0.289; p = 0.028) significantly predicted postural instability and gait difficulty. Walking sideways, 5-step test, and turning are significant predictors of PIGD score. These simple mobility tests can be quickly applied in clinical practice to determine postural instability and gait problems in persons with PD.

Wearable sensors objectively measure gait parameters in Parkinson's disease

Distinct gait characteristics like short steps and shuffling gait are prototypical signs commonly observed in Parkinson’s disease. Routinely assessed by observation through clinicians, gait is rated as part of categorical clinical scores. There is an increasing need to provide quantitative measurements of gait, e.g. to provide detailed information about disease progression. Recently, we developed a wearable sensor-based gait analysis system as diagnostic tool that objectively assesses gait parameter in Parkinson’s disease without the need of having a specialized gait laboratory. This system consists of inertial sensor units attached laterally to both shoes. The computed target of measures are spatiotemporal gait parameters including stride length and time, stance phase time, heel-strike and toe-off angle, toe clearance, and inter-stride variation from gait sequences. To translate this prototype into medical care, we conducted a cross-sectional study including 190 Parkinson’s disease patients and 101 age-matched controls and measured gait characteristics during a 4x10 meter walk at the subjects’ preferred speed. To determine intraindividual changes in gait, we monitored the gait characteristics of 63 patients longitudinally. Cross-sectional analysis revealed distinct spatiotemporal gait parameter differences reflecting typical Parkinson’s disease gait characteristics including short steps, shuffling gait, and postural instability specific for different disease stages and levels of motor impairment. The longitudinal analysis revealed that gait parameters were sensitive to changes by mirroring the progressive nature of Parkinson’s disease and corresponded to physician ratings. Taken together, we successfully show that wearable sensor-based gait analysis reaches clinical applicability providing a high biomechanical resolution for gait impairment in Parkinson’s disease. These data demonstrate the feasibility and applicability of objective wearable sensor-based gait measurement in Parkinson’s disease reaching high technological readiness levels for both, large scale clinical studies and individual patient care.

Balance training in individuals with Parkinson's disease: Therapist-supervised vs. home-based exercise programme

BACKGROUND

Poor locomotion and balance in Parkinson's disease (PD) often diminishes independence. Accordingly, gait is considered one of the most relevant rehabilitation outcomes, and home-based balance exercises might be a viable mode of exercise delivery for individuals with PD. However, research on PD interventions rarely indicate best practices to deliver exercises. Therefore, this study endeavoured to compare the efficacy of a home-based and therapist-supervised balance programme on gait parameters, dynamic balance, balance confidence and motivation in individuals diagnosed with PD.

METHODS

An experimental study design, including a cluster randomized convenience sample, of 40 participants with idiopathic PD (Hoehn and Yahr stage I-III; age: 65.0±7.7years). Participants were divided into a therapist-supervised (n=24) and home-based group (n=16). Groups received either eight weeks of balance training with an exercise therapist or a DVD. Outcome measures include the instrumented Timed-Up-and-Go, Functional Gait Analysis (FGA), Activity-specific Balance confidence (ABC) scale and Intrinsic Motivation Inventory (IMI).

RESULTS

Both groups improved in stride length (p<0.05). Similar FGA improved by 9% and 16% in the therapist-supervised and home-based group, respectively (p<0.01). Only the therapist-supervised group showed improvements in ABC (p=0.051), stride velocity (p=0.0006) and cadence (p=0.046) over the intervention; the latter two were also better compared to home-based (p<0.05). Furthermore the therapist-supervised group were more motivated (p=002).

CONCLUSION

The home-based balance programme was effective in improving some aspects of gait, albeit the programme supervised by an exercise therapist included somewhat more benefits after the intervention i.e. stride velocity and cadence in individuals with mild to moderate PD.

Quantitative Analysis of Motor Status in Parkinson's Disease Using Wearable Devices: From Methodological Considerations to Problems in Clinical Applications

Long-term and objective monitoring is necessary for full assessment of the condition of patients with Parkinson's disease (PD). Recent advances in biotechnology have seen the development of various types of wearable (body-worn) sensor systems. By using accelerometers and gyroscopes, these devices can quantify motor abnormalities, including decreased activity and gait disturbances, as well as nonmotor signs, such as sleep disturbances and autonomic dysfunctions in PD. This review discusses methodological problems inherent in wearable devices. Until now, analysis of the mean values of motion-induced signals on a particular day has been widely applied in the clinical management of PD patients. On the other hand, the reliability of these devices to detect various events, such as freezing of gait and dyskinesia, has been less than satisfactory. Quantification of disease-specific changes rather than nonspecific changes is necessary.

Dual-task gait differences in female and male adolescents following sport-related concussion

Concussion may affect females and males differentially. Identification of gender-related differences after concussion, therefore, may help clinicians with individualized evaluations. We examined potential differences in dual-task gait between females and males after concussion. Thirty-five participants diagnosed with a concussion (49% female, mean age=15.0±2.1 years, 7.5±3.0 days post-injury) and 51 controls (51% female, mean age=14.4±2.1 years) completed a symptom inventory and single/dual-task gait assessment. The primary outcome variable, the dual-task cost, was calculated as the percent change between single-task and dual-task conditions to account for individual differences in spatio-temporal gait variables. No significant differences in symptom severity measured by the post-concussion symptom scale were observed between females (32.0±18.0) and males (27.8±18.2). Compared with males, adolescent females walked with significantly decreased cadence dual-task costs after concussion (-19.7%±10.0% vs. -11.3%±9.2%, p=0.007) when adjusted for age, height, and prior concussion history. No significant differences were found between female and male control groups on other dual-task cost gait measures. Females and males with concussion also walked with significantly shorter stride lengths than controls during single-task (females: 1.13±0.11m vs. 1.26±0.11m, p=0.001; males: 1.14±0.14m vs. 1.22±0.15m, p=0.04) and dual-task gait (females: 0.99±0.10m vs. 1.10±0.11m, p=0.001; males: 1.00±0.13m vs. 1.08±0.14m, p=0.04). Females demonstrated a significantly greater amount of cadence change between single-task and dual-task gait than males after a sport-related concussion. Thus, differential alterations may exist during gait among those with a concussion; gender may be one prominent factor affecting dual-task gait.

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.