Using perceptive computing in multiple sclerosis - the Short Maximum Speed Walk test

Kinematic synergies show good consistency when extracted with a low-cost markerless device and a marker-based motion tracking system

Recently, markerless tracking systems, such as RGB-Depth cameras, have spread to overcome some of the limitations of the gold standard marker-based tracking systems. Although these systems are valuable substitutes for human motion analysis, as they guarantee higher flexibility, faster setup time and lower costs, their tracking accuracy is lower with respect to marker-based systems. Many studies quantified the error made by markerless systems in terms of body segment length estimation, articular angles, and biomechanics, concluding that they are appropriate for many clinical applications related to motion analysis. We propose an innovative approach to compare a markerless tracking system (Kinect V2) with a gold standard marker-based system (Vicon), based on motor control assessment. We quantified kinematic synergies from the tracking data of fifteen participants performing multi-directional upper limb movements. Kinematic synergy analysis decomposes the kinematic data into a reduced set of motor primitives that describe how the central nervous system coordinates motion at spatial and temporal level. Synergies were extracted with the recently released mixed-matrix factorization algorithm. Four synergies were extracted from both marker-based and markerless datasets and synergies were grouped in 6 clusters for each dataset. Cosine similarity in each cluster was ⩾0.60 in both systems, showing good consistency of synergies. Good matching was found between synergies extracted from markerless and from marker-based data, with a cosine similarity between matched synergies ⩾0.60 in 5 out 6 synergies. These results showed that the markerless sensor can be feasible for kinematic synergy analysis for gross movements, as it correctly estimates the number of synergies and in most cases also their spatial and temporal organization.

Digital Motor Biomarkers of Cerebellar Ataxia Using an RGB-Depth Camera-Based Motion Analysis System

This study aimed to identify quantitative biomarkers of motor function for cerebellar ataxia by evaluating gait and postural control using an RGB-depth camera-based motion analysis system. In 28 patients with degenerative cerebellar ataxia and 33 age- and sex-matched healthy controls, motor tasks (short-distance walk, closed feet stance, and stepping in place) were selected from a previously reported protocol, and scanned using Kinect V2 and customized software. The Clinical Assessment Scale for the Assessment and Rating of Ataxia (SARA) was also evaluated. Compared with the normal control group, the cerebellar ataxia group had slower gait speed and shorter step lengths, increased step width, and mediolateral trunk sway in the walk test (all P < 0.001). Lateral sway increased in the stance test in the ataxia group (P < 0.001). When stepping in place, the ataxia group showed higher arrhythmicity of stepping and increased stance time (P < 0.001). In the correlation analyses, the ataxia group showed a positive correlation between the total SARA score and arrhythmicity of stepping in place (r = 0.587, P = 0.001). SARA total score (r = 0.561, P = 0.002) and gait subscore (ρ = 0.556, P = 0.002) correlated with mediolateral truncal sway during walking. These results suggest that the RGB-depth camera-based motion analyses on mediolateral truncal sway during walking and arrhythmicity of stepping in place are useful digital motor biomarkers for the assessment of cerebellar ataxia, and could be utilized in future clinical trials.

RGB-Depth Camera-Based Assessment of Motor Capacity: Normative Data for Six Standardized Motor Tasks

BACKGROUND

Instrumental motion analysis constitutes a promising development in the assessment of motor function in clinical populations affected by movement disorders. To foster implementation and facilitate interpretation of respective outcomes, we aimed to establish normative data of healthy subjects for a markerless RGB-Depth camera-based motion analysis system and to illustrate their use.

METHODS

We recorded 133 healthy adults (56% female) aged 20 to 60 years with an RGB-Depth camera-based motion analysis system. Forty-three spatiotemporal parameters were extracted from six short, standardized motor tasks-including three gait tasks, stepping in place, standing-up and sitting down, and a postural control task. Associations with confounding factors, height, weight, age, and sex were modelled using a predictive linear regression approach. A z-score normalization approach was provided to improve usability of the data.

RESULTS

We reported descriptive statistics for each spatiotemporal parameter (mean, standard deviation, coefficient of variation, quartiles). Robust confounding associations emerged for step length and step width in comfortable speed gait only. Accessible normative data usage was lastly exemplified with recordings from one randomly selected individual with multiple sclerosis.

CONCLUSION

We provided normative data for an RGB depth camera-based motion analysis system covering broad aspects of motor capacity.

Healthcare applications of single camera markerless motion capture: a scoping review

Background

Single camera markerless motion capture has the potential to facilitate at home movement assessment due to the ease of setup, portability, and affordable cost of the technology. However, it is not clear what the current healthcare applications of single camera markerless motion capture are and what information is being collected that may be used to inform clinical decision making. This review aims to map the available literature to highlight potential use cases and identify the limitations of the technology for clinicians and researchers interested in the collection of movement data.

Survey Methodology

Studies were collected up to 14 January 2022 using Pubmed, CINAHL and SPORTDiscus using a systematic search. Data recorded included the description of the markerless system, clinical outcome measures, and biomechanical data mapped to the International Classification of Functioning, Disability and Health Framework (ICF). Studies were grouped by patient population.

Results

A total of 50 studies were included for data collection. Use cases for single camera markerless motion capture technology were identified for Neurological Injury in Children and Adults; Hereditary/Genetic Neuromuscular Disorders; Frailty; and Orthopaedic or Musculoskeletal groups. Single camera markerless systems were found to perform well in studies involving single plane measurements, such as in the analysis of infant general movements or spatiotemporal parameters of gait, when evaluated against 3D marker-based systems and a variety of clinical outcome measures. However, they were less capable than marker-based systems in studies requiring the tracking of detailed 3D kinematics or fine movements such as finger tracking.

Conclusions

Single camera markerless motion capture offers great potential for extending the scope of movement analysis outside of laboratory settings in a practical way, but currently suffers from a lack of accuracy where detailed 3D kinematics are required for clinical decision making. Future work should therefore focus on improving tracking accuracy of movements that are out of plane relative to the camera orientation or affected by occlusion, such as supination and pronation of the forearm.

Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development and Usability Study

Background

Instrumented assessment of motor symptoms has emerged as a promising extension to the clinical assessment of several movement disorders. The use of mobile and inexpensive technologies such as some markerless motion capture technologies is especially promising for large-scale application but has not transitioned into clinical routine to date. A crucial step on this path is to implement standardized, clinically applicable tools that identify and control for quality concerns.

Objective

The main goal of this study comprises the development of a systematic quality control (QC) procedure for data collected with markerless motion capture technology and its experimental implementation to identify specific quality concerns and thereby rate the usability of recordings.

Methods

We developed a post hoc QC pipeline that was evaluated using a large set of short motor task recordings of healthy controls (2010 recordings from 162 subjects) and people with multiple sclerosis (2682 recordings from 187 subjects). For each of these recordings, 2 raters independently applied the pipeline. They provided overall usability decisions and identified technical and performance-related quality concerns, which yielded respective proportions of their occurrence as a main result.

Results

The approach developed here has proven user-friendly and applicable on a large scale. Raters’ decisions on recording usability were concordant in 71.5%-92.3% of cases, depending on the motor task. Furthermore, 39.6%-85.1% of recordings were concordantly rated as being of satisfactory quality whereas in 5.0%-26.3%, both raters agreed to discard the recording.

Conclusions

We present a QC pipeline that seems feasible and useful for instant quality screening in the clinical setting. Results confirm the need of QC despite using standard test setups, testing protocols, and operator training for the employed system and by extension, for other task-based motor assessment technologies. Results of the QC process can be used to clean existing data sets, optimize quality assurance measures, as well as foster the development of automated QC approaches and therefore improve the overall reliability of kinematic data sets.

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.

Supporting the Assessment of Hereditary Transthyretin Amyloidosis Patients Based On 3-D Gait Analysis and Machine Learning

Hereditary Transthyretin Amyloidosis (vATTR-V30M) is a rare and highly incapacitating sensorimotor neuropathy caused by an inherited mutation (Val30Met), which typically affects gait, among other symptoms. In this context, we investigated the possibility of using machine learning (ML) techniques to build a model(s) that can be used to support the detection of the Val30Met mutation (possibility of developing the disease), as well as symptom onset detection for the disease, given the gait characteristics of a person. These characteristics correspond to 24 gait parameters computed from 3-D body data, provided by a Kinect v2 camera, acquired from a person while walking towards the camera. To build the model(s), different ML algorithms were explored: k-nearest neighbors, decision tree, random forest, support vector machines (SVM), and multilayer perceptron. For a dataset corresponding to 66 subjects (25 healthy controls, 14 asymptomatic mutation carriers, and 27 patients) and several gait cycles per subject, we were able to obtain a model that distinguishes between controls and vATTR-V30M mutation carriers (with or without symptoms) with a mean accuracy of 92% (SVM). We also obtained a model that distinguishes between asymptomatic and symptomatic carriers with a mean accuracy of 98% (SVM). These results are very relevant, since this is the first study that proposes a ML approach to support vATTR-V30M patient assessment based on gait, being a promising foundation for the development of a computer-aided diagnosis tool to help clinicians in the identification and follow-up of this disease. Furthermore, the proposed method may also be used for other neuropathies.

Speed but Not Smoothness of Gait Reacts to Rehabilitation in Multiple Sclerosis

Introduction

Improved gait is one of the leading therapy goals in multiple sclerosis. A plethora of clinical timed trials and state-of-the-art technology-based approaches are available to assess gait performance.

Objectives

To examine what aspects of gait react to inpatient rehabilitation in MS and which parameters should be best assessed.

Design

In this longitudinal study, we examined the performance of 76 patients with MS to shed further light on factors influencing gait, associations between tests, and the reaction to inpatient rehabilitation during an average time span of 16 d. Setting. Private specialist clinic for inpatient neurorehabilitation. Main Outcome Measures. Clinical walk tests (timed 25-foot walk test at normal pace, maximum pace over 10 m or 6 min) and IMU-based measures of movement smoothness.

Results

All gait parameters were strongly intercorrelated (all p < 0.05), and a model multiple linear regression for the 6MWT revealed short distance velocity (10 m) and movement smoothness as predictors in a strong model (R²_adjusted 0.75, p < 0.01). A second model with natural pace on short distance and movement smoothness was almost equally strong (R²_adjusted 0.71, p < 0.01). Patients improved their walking speed (p < 0.01), but not smoothness (p = 0.08–0.12), over the course of rehabilitation.

Conclusions

Since we were not able to observe improvements in smoothness of gait, we conclude that rehabilitation programs should be adapted to the patient's physiological capacities in order to allow for such improvements in smoothness of gait. Externally valid gait capacity (6MWT) could be predicted by a single walk for 10 s at natural pace.

Spatiotemporal Gait Measurement With a Side-View Depth Sensor Using Human Joint Proposals

We propose a method for calculating standard spatiotemporal gait parameters from individual human joints with a side-view depth sensor. Clinical walking trials were measured concurrently by a side-view Kinect and a pressure-sensitive walkway, the Zeno Walkway. Multiple joint proposals were generated from depth images by a stochastic predictor based on the Kinect algorithm. The proposals are represented as vertices in a weighted graph, where the weights depend on the expected and measured lengths between body parts. A shortest path through the graph is a set of joints from head to foot. Accurate foot positions are selected by comparing pairs of shortest paths. Stance phases of the feet are detected by examining the motion of the feet over time. The stance phases are used to calculate four gait parameters: stride length, step length, stride width, and stance percentage. A constant frame rate was assumed for the calculation of stance percentage because time stamps were not captured during the experiment. Gait parameters from 52 trials were compared to the ground truth walkway using Bland-Altman analysis and intraclass correlation coefficients. The large spatial parameters had the strongest agreements with the walkway (ICC(2, 1) = 1.00 and 0.98 for stride and step length with normal pace, respectively). The presented system directly calculates gait parameters from individual foot positions while previous side-view systems relied on indirect measures. Using a side-view system allows for tracking walking in both directions with one camera, extending the range in which the subject is in the field of view.

Cultural bias in motor function patterns: Potential relevance for predictive, preventive, and personalized medicine

Background

Quantification of motor performance has a promising role in personalized medicine by diagnosing and monitoring, e.g. neurodegenerative diseases or health problems related to aging. New motion assessment technologies can evolve into patient-centered eHealth applications on a global scale to support personalized healthcare as well as treatment of disease. However, uncertainty remains on the limits of generalizability of such data, which is relevant specifically for preventive or predictive applications, using normative datasets to screen for incipient disease manifestations or indicators of individual risks.

Objective

This study explored differences between healthy German and Japanese adults in the performance of a short set of six motor tests.

Methods

Six motor tasks related to gait and balance were recorded with a validated 3D camera system. Twenty-five healthy adults from Chiba, Japan, participated in this study and were matched for age, sex, and BMI to a sample of 25 healthy adults from Berlin, Germany. Recordings used the same technical setup and standard instructions and were supervised by the same experienced operator. Differences in motor performance were analyzed using multiple linear regressions models, adjusted for differences in body stature.

Results

From 23 presented parameters, five showed group-related differences after adjustment for height and weight (R ² between .19 and .46, p<.05). Japanese adults transitioned faster between sitting and standing and used a smaller range of hand motion. In stepping-in-place, cadence was similar in both groups, but Japanese adults showed higher knee movement amplitudes. Body height was identified as relevant confounder (standardized beta >.5) for performance of short comfortable and maximum speed walks. For results of posturography, regression models did not reveal effects of group or body stature.

Conclusions

Our results support the existence of a population-specific bias in motor function patterns in young healthy adults. This needs to be considered when motor function is assessed and used for clinical decisions, especially for personalized predictive and preventive medical purposes. The bias affected only the performance of specific items and parameters and is not fully explained by population-specific ethnic differences in body stature. It may be partially explained as cultural bias related to motor habits. Observed effects were small but are expected to be larger in a non-controlled cross-cultural application of motion assessment technologies with relevance for related algorithms that are being developed and used for data processing. In sum, the interpretation of individual data should be related to appropriate population-specific or even better personalized normative values to yield its full potential and avoid misinterpretation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-021-00236-3.

Standardization and digitization of clinical data in multiple sclerosis

Standardization is necessary to ensure the reliability of clinical data and to enable longitudinal and cross-sectional comparisons of data obtained in different centres and countries. In patients with multiple sclerosis (MS), standardized clinical data are needed for monitoring of disability and for collecting real-world evidence for use in research. This Perspective describes attempts to improve the standardization and digitization of clinical data in MS, including digital electronic health recording systems and applications that attempt to offer a comprehensive assessment of patients' neurological deficits and their effects on daily life. Despite the challenges raised by regulatory, ethical and data-privacy considerations, the standardization and digitization of clinical data in MS is expected to generate new insights into the pathophysiology of the disease and to contribute to personalized patient care.

The Dresden Protocol for Multidimensional Walking Assessment (DMWA) in Clinical Practice

Walking impairments represent one of the most debilitating symptom areas for people with multiple sclerosis (MS). It is important to detect even slightest walking impairments in order to start and optimize necessary interventions in time to counteract further progression of the disability. For this reason, a regular monitoring through gait analysis is highly necessary. At advanced stages of MS with significant walking impairment, this assessment is also necessary to optimize symptomatic treatment, choose the most suitable walking aid and plan individualized rehabilitation. In clinical practice, walking impairment is only assessed at higher levels of the disease using e.g., the Expanded Disability Status Scale (EDSS). In contrast to the EDSS, standardized functional tests such as walking speed, walking endurance and balance as well as walking quality and gait-related patient-reported outcomes allow a more holistic and sensitive assessment of walking impairment. In recent years, the MS Center Dresden has established a standardized monitoring procedure for the routine multidimensional assessment of gait and balance disorders. In the following protocol, we present the techniques and procedures for the analysis of gait and balance of people with MS at the MS Center Dresden. Patients are assessed with a multidimensional gait analysis at least once a year. This enables long-term monitoring of walking impairment, which allows early active intervention regarding further progression of disease and improves the current standard clinical practice.

Instrumental Assessment of Stepping in Place Captures Clinically Relevant Motor Symptoms of Parkinson's Disease

Fluctuations of motor symptoms make clinical assessment in Parkinson's disease a complex task. New technologies aim to quantify motor symptoms, and their remote application holds potential for a closer monitoring of treatment effects. The focus of this study was to explore the potential of a stepping in place task using RGB-Depth (RGBD) camera technology to assess motor symptoms of people with Parkinson's disease. In total, 25 persons performed a 40 s stepping in place task in front of a single RGBD camera (Kinect for Xbox One) in up to two different therapeutic states. Eight kinematic parameters were derived from knee movements to describe features of hypokinesia, asymmetry, and arrhythmicity of stepping. To explore their potential clinical utility, these parameters were analyzed for their Spearman's Rho rank correlation to clinical ratings, and for intraindividual changes between treatment conditions using standard response mean and paired t-test. Test performance not only differed between ON and OFF treatment conditions, but showed moderate correlations to clinical ratings, specifically ratings of postural instability (pull test). Furthermore, the test elicited freezing in some subjects. Results suggest that this single standardized motor task is a promising candidate to assess an array of relevant motor symptoms of Parkinson's disease. The simple technical test setup would allow future use by patients themselves.

Verification of reliability and validity of motion analysis systems during bilateral squat using human pose tracking algorithm

BACKGROUND

The human tracking algorithm called OpenPose can detect joint points and calculate joint angles. However, the reliability and validity of OpenPose have not been clarified yet.

RESEARCH QUESTION

Are there the enough reliability and validity of OpenPose based motion analysis?

METHODS

20 healthy young subjects participated in this study. The motion task was a bilateral squat. The joint angles of the trunk, hip, knee, and ankle were calculated using OpenPose and VICON. Kinematic measurements by three-dimensional motion analysis devices were recorded using VICON. Simultaneously, the images were taken with a digital camera from the right side. After the images were processed with OpenPose, joint angles were calculated from estimated joint points. To confirm the test-retest reliability within device, intraclass correlation coefficients [ICC (1, 3)] were calculated. To confirm the validity, linear regression analysis and ICC (2, 1) between the data obtained by OpenPose and VICON were calculated. Furthermore, the agreement between the data obtained by OpenPose and VICON was assessed by Bland-Altman analysis.

RESULTS

ICCs (1, 3) of the data obtained by OpenPose and VICON were almost perfect. There were significant associations between the data obtained by OpenPose and VICON. ICCs (2, 1) between the data obtained by OpenPose and VICON were almost perfect or substantial for trunk, knee and ankle joints, and fair on the hip joint. There were fixed biases on knee and ankle joints, and proportional biases on trunk and hip joint.

SIGNIFICANCE

OpenPose based motion analysis is reliable and has the advantage of being low cost and easier to operate than conventional methods. In future, to consider the clinical utility of OpenPose, it is necessary to identify the error between the true values indicating actual joint movement and data obtained by OpenPose with its correction for fixed and proportional biases. (295 words).

Meaningful change: Defining the interpretability of changes in endpoints derived from interactive and mHealth technologies in healthcare and clinical research

Immersive, interactive and mHealth technologies are increasingly being used in clinical research, healthcare and rehabilitation solutions. Leveraging technology solutions to derive new and novel clinical outcome measures is important to the ongoing assessment of clinical interventions. While demonstrating statistically significant changes is an important element of intervention assessment, understanding whether changes detected reflect changes of a magnitude that are considered meaningful to patients is equally important. We describe methodologies used to determine meaningful change and recommend that these techniques are routinely included in the development and testing of clinical assessment and rehabilitation technology solutions.

Contactless recording of sleep apnea and periodic leg movements by nocturnal 3-D-video and subsequent visual perceptive computing

Contactless measurements during the night by a 3-D-camera are less time-consuming in comparison to polysomnography because they do not require sophisticated wiring. However, it is not clear what might be the diagnostic benefit and accuracy of this technology. We investigated 59 persons simultaneously by polysomnography and 3-D-camera and visual perceptive computing (19 patients with restless legs syndrome (RLS), 21 patients with obstructive sleep apnea (OSA), and 19 healthy volunteers). There was a significant correlation between the apnea hypopnea index (AHI) measured by polysomnography and respiratory events measured with the 3-D-camera in OSA patients (r = 0.823; p < 0.001). The receiver operating characteristic curve yielded a sensitivity of 90% for OSA with a specificity of 71.4%. In RLS patients 72.8% of leg movements confirmed by polysomnography could be detected by 3-D-video and a significant moderate correlation was found between PLM measured by polysomnography and by the 3-D-camera (RLS: r = 0.654; p = 0.004). In total, 95.4% of the sleep epochs were correctly classified by the machine learning approach, but only 32.5% of awake epochs. Further studies should investigate, if this technique might be an alternative to home sleep testing in persons with an increased pre-test probability for OSA.

Validation of a Single RGB-D Camera for Gait Assessment of Polyneuropathy Patients

Motion analysis systems based on a single markerless RGB-D camera are more suitable for clinical practice than multi-camera marker-based reference systems. Nevertheless, the validity of RGB-D cameras for motor function assessment in some diseases affecting gait, such as Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP), is yet to be investigated. In this study, the agreement between the Kinect v2 and a reference system for obtaining spatiotemporal and kinematic gait parameters was evaluated in the context of TTR-FAP. 3-D body joint data provided by both systems were acquired from ten TTR-FAP symptomatic patients, while performing ten gait trials. For each gait cycle, we computed several spatiotemporal and kinematic gait parameters. We then determined, for each parameter, the Bland Altman’s bias and 95% limits of agreement, as well as the Pearson’s and concordance correlation coefficients, between systems. The obtained results show that an affordable, portable and non-invasive system based on an RGB-D camera can accurately obtain most of the studied gait parameters (excellent or good agreement for eleven spatiotemporal and one kinematic). This system can bring more objectivity to motor function assessment of polyneuropathy patients, potentially contributing to an improvement of TTR-FAP treatment and understanding, with great benefits to the patients’ quality of life.

Full-body motion assessment: Concurrent validation of two body tracking depth sensors versus a gold standard system during gait

RGB-D cameras provide 3-D body joint data in a low-cost, portable and non-intrusive way, when compared with reference motion capture systems used in laboratory settings. In this contribution, we evaluate the validity of both Microsoft Kinect versions (v1 and v2) for motion analysis against a Qualisys system in a simultaneous protocol. Two different walking directions in relation to the Kinect (towards - WT, and away - WA) were explored. For each gait trial, measures related with all body parts were computed: velocity of all joints, distance between symmetrical joints, and angle at some joints. For each measure, we compared each Kinect version and Qualisys by obtaining the mean true error and mean absolute error, Pearson's correlation coefficient, and optical-to-depth ratio. Although both Kinect v1 and v2 and/or WT and WA data present similar accuracy for some measures, better results were achieved, overall, when using WT data provided by the Kinect v2, especially for velocity measures. Moreover, the velocity and distance presented better results than angle measures. Our results show that both Kinect versions can be an alternative to more expensive systems such as Qualisys, for obtaining distance and velocity measures as well as some angles metrics (namely the knee angles). This conclusion is important towards the off-lab non-intrusive assessment of motor function in different areas, including sports and healthcare.

Dual Kinect v2 system can capture lower limb kinematics reasonably well in a clinical setting: concurrent validity of a dual camera markerless motion capture system in professional football players

Objectives

To determine whether a dual-camera markerless motion capture system can be used for lower limb kinematic evaluation in athletes in a preseason screening setting.

Design

Descriptive laboratory study.

Setting

Laboratory setting.

Participants

Thirty-four (n=34) healthy athletes.

Main outcome measures

Three dimensional lower limb kinematics during three functional tests: Single Leg Squat (SLS), Single Leg Jump, Modified Counter-movement Jump. The tests were simultaneously recorded using both a marker-based motion capture system and two Kinect v2 cameras using iPi Mocap Studio software.

Results

Excellent agreement between systems for the flexion/extension range of motion of the shin during all tests and for the thigh abduction/adduction during SLS were seen. For peak angles, results showed excellent agreement for knee flexion. Poor correlation was seen for the rotation movements.

Conclusions

This study supports the use of dual Kinect v2 configuration with the iPi software as a valid tool for assessment of sagittal and frontal plane hip and knee kinematic parameters but not axial rotation in athletes.

MRI Markers and Functional Performance in Patients With CIS and MS: A Cross-Sectional Study

Introduction: Brain atrophy is a widely accepted marker of disease severity with association to clinical disability in multiple sclerosis (MS). It is unclear to which extent this association reflects common age effects on both atrophy and function. Objective: To explore how functional performance in gait, upper extremities and cognition is associated with brain atrophy in patients with Clinically Isolated Syndrome (CIS) and relapsing-remitting MS (RRMS), controlling for effects of age and sex. Methods: In 27 patients with CIS, 59 with RRMS (EDSS ≤3) and 63 healthy controls (HC), 3T MRI were analyzed for T2 lesion count (T2C), volume (T2V) and brain volumes [normalized brain volume (NBV), gray matter volume (NGMV), white matter volume (NWMV), thalamic volume (NThalV)]. Functional performance was measured with short maximum walking speed (SMSW speed), 9-hole peg test (9HPT) and symbol digit modalities test (SDMT). Linear regression models were created for functional variables with stepwise inclusion of age, sex and MR imaging markers. Results: CIS differed from HC only in T2C and T2V. RRMS differed from HC in NBV, NGMV and NThalV, T2C and T2V, but not in NWMV. A strong association with age was seen in HC, CIS and RRMS groups for NBV (r = -0.5 to -0.6) and NGMV (r = -0.6 to -0.8). Associations with age were seen in HC and RRMS but not CIS for NThalV (r = -0.3; r = -0.5), T2C (rs = 0.3; rs = 0.2) and T2V (rs = 0.3; rs = 0.3). No effect of age was seen on NWMV. Correlations of functional performance with age in RRMS were seen for SMSW speed, 9HPTand SDMT (r = -0.27 to -0.46). Regression analyses yielded significant models only in the RRMS group for 9HPT, SMSW speed and EDSS. These included NBV, NGMV, NThalV, NWMV, logT2V, age and sex as predictors. NThalV was the only MRI variable predicting a functional measure (9HPTr) with a higher standardized beta than age and sex (R2 = 0.36, p < 1e-04). Conclusion: Thalamic atrophy was a stronger predictor of hand function (9HPT) in RRMS, than age and sex. This underlines the clinical relevance of thalamic atrophy and the relevance of hand function as a clinical marker even in mildly disabled patients.

Increases in fatigue do not change spasticity scores in persons with multiple sclerosis

AIM

Fatigue is a common finding in multiple sclerosis (MS) which may result in worsening of gait, function and other MS symptoms, like spasticity. Although the worsening of spasticity with fatigue has been reported by persons with MS, the effect of fatigue on spasticity has not been measured.

PURPOSE

The purpose of this study was to compare lower extremity Modified Ashworth Scale (MAS) scores of persons with mild-to-moderate MS symptoms before and after fatigued and unfatigued conditions.

METHODS

Using a randomized crossover design, MS subjects underwent 6-min walk to induce fatigue and 6-min supine rests, with lower extremity spasticity measured before and after each condition. Friedman tests gave paired comparisons of MAS before and after each condition.

RESULTS

16 subjects with mild-to-moderate MS completed the study (mean age = 56; standard deviation = 11.7). Friedman tests showed a significant decrease in mean rank for overall average MAS for both lower extremities (p = 0.031) when comparing fatigued to unfatigued conditions. This appeared to be driven by the right lower extremity average MAS (p = 0.002) and, more specifically, in post hoc pre to post-test comparisons for right knee flexor (p = 0.002 fatigued; p = 0.059 unfatigued) and right knee extensor (p = 0.001 fatigued; p = 0.020 unfatigued) MAS mean rank differences. Fatigue did not result in increased spasticity.

CONCLUSION

Spasticity in these subjects with MS was not worsened by fatigue suggesting that worsening of gait with fatigue may be due to causes other than spasticity.

Using a Somatosensory Controller to Assess Body Size for Size-Specific Dose Estimates in Computed Tomography

Computed tomography (CT) has been widely used in the healthcare environment. Presently, the radiation dose in CT is determined using the size-specific dose estimate (SSDE). Accurate assessment of individual's body size is essential for dose estimation. In this study, we integrated a somatosensory controller with a CT scanner to measure patient's anterior-posterior diameter (APD) and lateral diameter (LATD) and calculate the corresponding effective diameter (ED). A total of 108 individuals with an average age of 38.6 years were enrolled in this study. Microsoft Kinect was used to acquire the depth image of subjects. A grayscale-to-surface height conversion curve was created using acrylic sheets for APD estimation. The APD, LATD, and ED were measured and compared with the results obtained using F ruler and CT images. The mean absolute differences for APD, LATD, and ED between Kinect and F ruler measurements were 5.2%, 1.3%, and 2.5%, respectively, while those between Kinect and CT measurements were 8.8%, 2.6%, and 5.0%, respectively. Kinect can replace CT or F ruler for real-time body size measurements. The use of the somatosensory controller has the advantages of simple, low cost, no radiation, and automatic calculation. It can accurately estimate patient's APD, LATD, and ED for SSDE.

Walking speed measurement with an Ambient Measurement System (AMS) in patients with multiple sclerosis and walking impairment

BACKGROUND

Walking speed is an important measure of gait impairment in multiple sclerosis (MS). The clinical assessment of walking speed requires dedicated time, space, and personnel, and may not accurately gauge real-world performance. The term "Ambient Measurement System" (AMS) refers to a new class of device that passively measures walking speed at home, without the need for dedicated space or specialized setup. This study compared an AMS, Echo5D, versus in-clinic standard measures of walking speed on a straight path.

METHODS

Twenty participants with MS and walking impairment were recruited from the Cleveland Clinic Mellen Center for MS. Each participant traversed an electronic GAITRite CIRFace (GC) sensor mat four times (two at comfortable pace, two at fast pace). Each participant then performed the Timed 25-Foot Walk (T25FW) twice, measured by a manual stopwatch (SW). All traversals were simultaneously measured by an array of Echo5D devices. Echo5D speeds were correlated with the Patient-Determined Disease Steps and the MS Walking Scale-12 patient-reported outcomes.

RESULTS

Pearson correlations between Echo5D and clinical tests ranged from 0.89 to 0.98 (p < 0.0001). No statistically significant bias was found between Echo5D and GC. A small statistically significant bias was found between Echo5D and SW, with Echo5D reporting approximately 5% faster walking speeds in aggregate.

CONCLUSIONS

Among MS patients with walking impairments, the Echo5D AMS acquired walking speeds which were closely correlated with the standard measures of GC and SW. The strong agreement supports the use of Echo5D to assess in-home, real-world walking performance in MS.

Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis

Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease. This update critically evaluates advanced gait and balance analysis technologies and their applicability to identifying early lower limb dysfunction in people with MS. Non-wearable (motion capture systems, force platforms, and sensor-embedded walkways) and wearable (pressure and inertial sensors) biomechanical analysis systems have been developed to provide quantitative gait and balance assessments. Non-wearable systems are highly accurate, reliable and provide detailed outcomes, but require cumbersome and expensive equipment. Wearable systems provide less detail but can be used in community settings and can provide real-time feedback to patients and clinicians. Biomechanical analysis using advanced gait and balance analysis technologies can identify changes in gait and balance in early MS and consequently have the potential to significantly improve monitoring of mobility changes in MS.

Maximum walking speed in multiple sclerosis assessed with visual perceptive computing

BACKGROUND

Gait is often impaired in people with multiple sclerosis (PwMS), but detailed assessment of gait impairment in research and care remains challenging. In a previous pilot study we reported the feasibility of visual perceptive computing (VPC) for gait assessment in PwMS using the Short Maximum Speed Walk (SMSW), which assesses gait on recording distances confined to less than 4 meters.

OBJECTIVE

To investigate the equivalence of SMSW to rater-based timed 25ft. walk (T25FW) in a large cohort of PwMS, and to investigate the association of SMSW-derived gait parameters with clinical disability, as well as subjective and objective gait impairment, in order to validate the SMSW as a quick and objective measure of clinical relevance possibly superior to T25FW.

METHODS

95 PwMS and 60 healthy controls (HC) performed the SMSW using a VPC system with Microsoft Kinect. All participants received two immediate retests to establish test-retest-reliability. Both PwMS and HC performed the T25FW. PwMS were rated according to the Expanded Disability Status Scale (EDSS) and answered the 12-item Multiple Sclerosis Walking Scale (MSWS-12) as a measure of self-perceived walking impairment.

RESULTS

PwMS showed reduced average speed (p<0.001) and higher mediolateral deviation (p = 0.002) during SMSW than HC. Average speed was the most reliable SMSW parameter in PwMS and HC (intra-class correlation coefficient (ICC) in PwMS = 0.985, and in HC = 0.977). Average speed declined with age in PwMS and HC (r in PwMS = -0.648, and in HC = -0.452, both p<0.001). Correlation of SMSW average speed and T25FW speed was high in both groups (r in PwMS = 0.783, and in HC = 0.747, both p<0.001) and mean difference (0.0013 m/s) between methods was below smallest detectable change. Average speed correlated well with both clinical disability based on EDSS (r = -0.586, p<0.001) and self-perceived walking impairment based on MSWS-12 (r = -0.546, p<0.001).

CONCLUSION

VPC-assessed walking parameters during SMSW can reliably detect gait disturbance in PwMS over very short distance. Specifically, maximum gait speed can be obtained with high accuracy in this simple test set-up. Cross-sectional associations with disability and self-perceived walking impairment support clinical relevance. Given its objectivity in a simple test set-up, SMSW is superior to T25FW.

Evaluation of Clinical Gait Analysis parameters in patients affected by Multiple Sclerosis: Analysis of kinematics

BACKGROUND

Clinical Gait Analysis is commonly used to evaluate specific gait characteristics of patients affected by Multiple Sclerosis. The aim of this report is to present a retrospective cross-sectional analysis of the changes in Clinical Gait Analysis parameters in patients affected by Multiple Sclerosis.

METHODS

In this study a sample of 51 patients with different levels of disability (Expanded Disability Status Scale 2-6.5) was analyzed. We extracted a set of 52 parameters from the Clinical Gait Analysis of each patient and used statistical analysis and linear regression to assess differences among several groups of subjects stratified according to the Expanded Disability Status Scale and 6-Minutes Walking Test. The impact of assistive devices (e.g. canes and crutches) on the kinematics was also assessed in a subsample of patients.

FINDINGS

Subjects showed decreased range of motion at hip, knee and ankle that translated in increased pelvic tilt and hiking. Comparison between the two stratifications showed that gait speed during 6-Minutes Walking Test is better at discriminating patients' kinematics with respect to Expanded Disability Status Scale. Assistive devices were shown not to significantly impact gait kinematics and the Clinical Gait Analysis parameters analyzed.

INTERPRETATION

We were able to characterize disability-related trends in gait kinematics. The results presented in this report provide a small atlas of the changes in gait characteristics associated with different disability levels in the Multiple Sclerosis population. This information could be used to effectively track the progression of MS and the effect of different therapies.

The Berlin Treatment Algorithm: recommendations for tailored innovative therapeutic strategies for multiple sclerosis-related fatigue

More than 80% of multiple sclerosis (MS) patients suffer from fatigue. Despite this, there are few therapeutic options and evidence-based pharmacological treatments are lacking. The associated societal burden is substantial (MS fatigue is a major reason for part-time employment or early retirement), and at least one out of four MS patients view fatigue as the most burdensome symptom of their disease. The mechanisms underlying MS-related fatigue are poorly understood, and objective criteria for distinguishing and evaluating levels of fatigue and tiredness have not yet been developed. A further complication is that both symptoms may also be unspecific indicators of many other diseases (including depression, sleep disorders, anemia, renal failure, liver diseases, chronic obstructive pulmonary disease, drug side effects, recent MS relapses, infections, nocturia, cancer, thyroid hypofunction, lack of physical exercise). This paper reviews current treatment options of MS-related fatigue in order to establish an individualized therapeutic strategy that factors in existing comorbid disorders. To ensure that such a strategy can also be easily and widely implemented, a comprehensive approach is needed, which ideally takes into account all other possible causes and which is moreover cost efficient. Using a diagnostic interview, depressive disorders, sleep disorders and side effects of the medication should be identified and addressed. All MS patients suffering from fatigue should fill out the Modified Fatigue Impact Scale, Epworth Sleepiness Scale, the Beck Depression Inventory (or a similar depression scale), and the Pittsburgh Sleep Quality Index (or the Insomnia Severity Index). In some patients, polygraphic or polysomnographic investigations should be performed. The treatment of underlying sleep disorders, drug therapy with alfacalcidol or fampridine, exercise therapy, and cognitive behavioral therapy-based interventions may be effective against MS-related fatigue. The objectives of this article are to identify the reasons for fatigue in patients suffering from multiple sclerosis and to introduce individually tailored treatment approaches. Moreover, this paper focuses on current knowledge about MS-related fatigue in relation to brain atrophy and lesions, cognition, disease course, and other findings in an attempt to identify future research directions.

Accuracy and Reliability of the Kinect Version 2 for Clinical Measurement of Motor Function

Background

The introduction of low cost optical 3D motion tracking sensors provides new options for effective quantification of motor dysfunction.

Objective

The present study aimed to evaluate the Kinect V2 sensor against a gold standard motion capture system with respect to accuracy of tracked landmark movements and accuracy and repeatability of derived clinical parameters.

Methods

Nineteen healthy subjects were concurrently recorded with a Kinect V2 sensor and an optical motion tracking system (Vicon). Six different movement tasks were recorded with 3D full-body kinematics from both systems. Tasks included walking in different conditions, balance and adaptive postural control. After temporal and spatial alignment, agreement of movements signals was described by Pearson’s correlation coefficient and signal to noise ratios per dimension. From these movement signals, 45 clinical parameters were calculated, including ranges of motions, torso sway, movement velocities and cadence. Accuracy of parameters was described as absolute agreement, consistency agreement and limits of agreement. Intra-session reliability of 3 to 5 measurement repetitions was described as repeatability coefficient and standard error of measurement for each system.

Results

Accuracy of Kinect V2 landmark movements was moderate to excellent and depended on movement dimension, landmark location and performed task. Signal to noise ratio provided information about Kinect V2 landmark stability and indicated larger noise behaviour in feet and ankles. Most of the derived clinical parameters showed good to excellent absolute agreement (30 parameters showed ICC(3,1) > 0.7) and consistency (38 parameters showed r > 0.7) between both systems.

Conclusion

Given that this system is low-cost, portable and does not require any sensors to be attached to the body, it could provide numerous advantages when compared to established marker- or wearable sensor based system. The Kinect V2 has the potential to be used as a reliable and valid clinical measurement tool.

Accuracy and repeatability of two methods of gait analysis - GaitRite™ und Mobility Lab™ - in subjects with cerebellar ataxia

Instrumental gait analysis is increasingly recognized as a useful tool for the evaluation of movement disorders. The various assessment devices available to date have mostly been evaluated in healthy populations only. We aimed to explore whether reliability and validity seen in healthy subjects can also be assumed in subjects with cerebellar ataxic gait. Gait was recorded simultaneously with two devices - a sensor-embedded walkway and an inertial sensor based system - to explore test accuracy in two groups of subjects: one with mild to moderate cerebellar ataxia due to a subtype of autosomal-dominantly inherited neurodegenerative disorder (SCA14), the other were healthy subjects matched for age and height (CTR). Test precision was assessed by retest within session for each device. In conclusion, accuracy and repeatability of gait measurements were not compromised by ataxic gait disorder. The accuracy of spatial measures was speed-dependent and a direct comparison of stride length from both devices will be most reliably made at comfortable speed. Measures of stride variability had low agreement between methods in CTR and at retest in both groups. However, the marked increase of stride variability in ataxia outweighs the observed amount of imprecision.

Ranking of Dystonia Severity by Pairwise Video Comparison

Background

Reviewers of dystonia rating scales agree on the need to assess symptoms more comprehensively. During the development of a quantitative dystonia assessment by video-perceptive computing, we devised a video-based severity ranking as a procedure to create a validation standard without the use of clinical scales.

Methods

Thirty-four patients with dystonia (17 with dystonic tremor) and 2 controls were assessed with clinical scales and video-recordings of 24 short movement tasks. Two to 4 raters compared multiple permutations of videos from 22 subjects, including 2 healthy controls, until a complete rank order was achieved. Inter-rater agreement was expressed as normalized Kendall tau distance. Spearman correlations of video rank order with clinical scales and self-rating were repeated for tremor/nontremor subgroups.

Results

Normalized Kendall tau distances were <0.3 for 15 items. The video rank order for sitting and head movements correlated with clinical scales for the whole group (rho 0.52-0.87) and in the subgroup without tremor. In the tremor subgroup such correlation was perceived in the 2 items involving sitting. Video rank order correlated with quality of life self-rating only in 1 item (arms held in front, palm down).

Conclusions

The agreement of video rankings between raters is remarkable. The lack of correlation in the tremor subgroup in several items may be interpreted as tremor being considered in video comparisons but not in clinical scales. This supports video-based ranking as a more comprehensive rating of dystonia and as a possible validation instrument applicable in situations in which no reference standard is available.

Disability and Fatigue Can Be Objectively Measured in Multiple Sclerosis

Background

The available clinical outcome measures of disability in multiple sclerosis are not adequately responsive or sensitive.

Objective

To investigate the feasibility of inertial sensor-based gait analysis in multiple sclerosis.

Methods

A cross-sectional study of 80 multiple sclerosis patients and 50 healthy controls was performed. Lower-limb kinematics was evaluated by using a commercially available magnetic inertial measurement unit system. Mean and standard deviation of range of motion (mROM, sROM) for each joint of lower limbs were calculated in one minute walking test. A motor performance index (E) defined as the sum of sROMs was proposed.

Results

We established two novel observer-independent measures of disability. Hip mROM was extremely sensitive in measuring lower limb motor impairment, being correlated with muscle strength and also altered in patients without clinically detectable disability. On the other hand, E index discriminated patients according to disability, being altered only in patients with moderate and severe disability, regardless of walking speed. It was strongly correlated with fatigue and patient-perceived health status.

Conclusions

Inertial sensor-based gait analysis is feasible and can detect clinical and subclinical disability in multiple sclerosis.

Validity of the Kinect for Gait Assessment: A Focused Review

Gait analysis may enhance clinical practice. However, its use is limited due to the need for expensive equipment which is not always available in clinical settings. Recent evidence suggests that Microsoft Kinect may provide a low cost gait analysis method. The purpose of this report is to critically evaluate the literature describing the concurrent validity of using the Kinect as a gait analysis instrument. An online search of PubMed, CINAHL, and ProQuest databases was performed. Included were studies in which walking was assessed with the Kinect and another gold standard device, and consisted of at least one numerical finding of spatiotemporal or kinematic measures. Our search identified 366 papers, from which 12 relevant studies were retrieved. The results demonstrate that the Kinect is valid only for some spatiotemporal gait parameters. Although the kinematic parameters measured by the Kinect followed the trend of the joint trajectories, they showed poor validity and large errors. In conclusion, the Kinect may have the potential to be used as a tool for measuring spatiotemporal aspects of gait, yet standardized methods should be established, and future examinations with both healthy subjects and clinical participants are required in order to integrate the Kinect as a clinical gait analysis tool.

Validity of visual perceptive computing for static posturography in patients with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) patients frequently have postural control impairment but quantitative posturography is difficult to perform in clinical care. Recent technology facilitates new posturography approaches.

OBJECTIVE

To evaluate construct validity of visual perceptive computing (VPC) for static posturography to study postural control in MS patients.

METHODS

A total of 90 MS patients and 59 healthy controls (HCs) performed three stance tests: open, closed and tandem stance. Static posturography was performed using a VPC system with Microsoft Kinect. Clinical assessments included Expanded Disability Status Scale (EDSS), Timed-25-Foot-Walk, Short-Maximum-Speed-Walk and 12-item MS Walking Scale (MSWS-12) questionnaire. Reliability was assessed with intra-class correlation coefficients at retest.

RESULTS

As a group, MS patients performed worse than HCs in all tests. The closed stance test showed best applicability and reliability. With closed eyes, in 36.7% of patients, the three-dimensional mean angular sway velocity (MSV-3D) was above HCs' 95th percentile. Higher MSV-3D was associated with decreased walking speed (p < 0.001); worse clinical scores, mainly attributable to the cerebellar functional system score (p < 0.001); and reflected in self-reported walking disability (MSWS-12, p < 0.001).

CONCLUSION

Postural control can be reliably assessed by VPC-based static posturography in patients with MS. Abnormal postural control seems to predominantly reflect involvement of cerebellar circuits with impact on gait and walking disability.

Automated extraction and validation of children's gait parameters with the Kinect

BACKGROUND

Gait analysis for therapy regimen prescription and monitoring requires patients to physically access clinics with specialized equipment. The timely availability of such infrastructure at the right frequency is especially important for small children. Besides being very costly, this is a challenge for many children living in rural areas. This is why this work develops a low-cost, portable, and automated approach for in-home gait analysis, based on the Microsoft Kinect.

METHODS

A robust and efficient method for extracting gait parameters is introduced, which copes with the high variability of noisy Kinect skeleton tracking data experienced across the population of young children. This is achieved by temporally segmenting the data with an approach based on coupling a probabilistic matching of stride template models, learned offline, with the estimation of their global and local temporal scaling. A preliminary study conducted on healthy children between 2 and 4 years of age is performed to analyze the accuracy, precision, repeatability, and concurrent validity of the proposed method against the GAITRite when measuring several spatial and temporal children's gait parameters.

RESULTS

The method has excellent accuracy and good precision, with segmenting temporal sequences of body joint locations into stride and step cycles. Also, the spatial and temporal gait parameters, estimated automatically, exhibit good concurrent validity with those provided by the GAITRite, as well as very good repeatability. In particular, on a range of nine gait parameters, the relative and absolute agreements were found to be good and excellent, and the overall agreements were found to be good and moderate.

CONCLUSION

This work enables and validates the automated use of the Kinect for children's gait analysis in healthy subjects. In particular, the approach makes a step forward towards developing a low-cost, portable, parent-operated in-home tool for clinicians assisting young children.

Self-selected gait speed--over ground versus self-paced treadmill walking, a solution for a paradox

Background

The study of gait at self-selected speed is important. Traditional gait laboratories being relatively limited in space provide insufficient path length, while treadmill (TM) walking compromises natural gait by imposing speed variables. Self-paced (SP) walking can be realized on TM using feedback-controlled belt speed. We compared over ground walking vs. SP TM in two self-selected gait speed experiments: without visual flow, and while subjects were immersed in a virtual reality (VR) environment inducing natural visual flow.

Methods

Young healthy subjects walked 96 meters at self-selected comfortable speed, first over ground and then on the SP TM without (n=15), and with VR visual flow (n=11). Gait speed was compared across conditions for four 10 m long segments (7.5 – 17.5, 30.5 – 40.5, 55.5 – 65.5 and 78.5-88.5 m).

Results

During over ground walking mean (± SD) gait speed was equal for both experimental groups (1.50 ± 0.13 m/s). Without visual flow, gait speed over SP TM was smaller in the first and second epochs as compared to over ground (first: 1.15 ±0.18 vs. second: 1.53 ± 0.13 m/s; p<0.05), and was comparable in the third and fourth (1.45 ± 0.19 vs. 1.49 ± 0.15 m/s; p>0.3). With visual flow, gait speed became comparable to that of over ground performance already in the first epoch (1.43 ± 0.22 m/s; p>0.17). Curve fitting analyses estimated that steady state velocity in SP TM walking is reached after shorter distanced passed with visual flow (24.6 ± 14.7 m) versus without (36.5 ± 18.7 m, not statistically significant; p=0.097). Steady state velocity was estimated to be higher in the presence of visual flow (1.61 ± 0.17 m/s) versus its absence (1.42 ± 1.19 m/s; p<0.05).

Conclusions

The SP TM walking is a reliable method for recording typical self-selected gait speed, provided that sufficient distance is first passed for reaching steady state. Seemingly, in the presence of VR visual flow, steady state of gait speed is reached faster. We propose that the gait research community joins forces to standardize the use of SP TMs, e.g., by unifying protocols or gathering normative data.