Quantifying six-minute walk induced gait deterioration with inertial sensors in multiple sclerosis subjects

The measurement of fatigability severity in individuals with multiple sclerosis and healthy controls

BACKGROUND

Multiple Sclerosis (MS) is a chronic disease that substantially diminishes one's ability to undertake daily living activities. Fatigue has been reported by at least 80 % of persons with MS (PwMS). Yet, little is known concerning the quantification of fatigability using prolonged walking tests.

OBJECTIVES

To compare fatigability severity measures using the 10-minute walk test for PwMS against age- and gender-matched healthy controls (HCs).

METHODS

Participants included 53 ambulatory PwMS and 49 HCs. Perceived fatigability was measured by dividing a participant's change in self-reported tiredness by the number of meters walked. Performance fatigability was calculated by dividing the change in walking speed (at 2.5 and 10 min) by the total distance walked in meters.

RESULTS

There was a significant difference in perceived fatigability between PwMS and HCs (mean difference: 2.73 ± 0.83; p = 0.001) and in performance fatigability (mean difference: 0.24 ± 0.11; p = 0.01). Moreover, there were significant differences in speed and distance at all time points (p ≤ 0.05) between PwMS and HCs.

CONCLUSIONS

PwMS have significant walking deficits as reflected by greater fatigability in both perceived and performance measures. These methods can enhance therapeutic strategies that improve the walking performances of PwMS.

Between-Day Reliability of the Gait Characteristics and Their Changes During the 6-Minute Walking Test in People With Multiple Sclerosis

BACKGROUND

Gait characteristics and their changes during the 6-minute walking test (6MWT) in people with multiple sclerosis (pwMS) have been described in the literature, which one may refer to as walking fatigability in the body function level of the International Classification of Functioning, Disability, and Health. However, whether these metrics are reliable is unknown.

OBJECTIVE

To investigate the between-day reliability of the gait characteristics and their changes in pwMS and healthy controls (HCs).

METHODS

Forty-nine pwMS (EDSS 4.82 ± 1.22 and 54.7 ± 9.36 years) and 23 HCs (50.6 ± 6.1 years) performed the 6MWT, as fast as possible but safely while wearing Inertial Measurement Units. Gait characteristics were measured in the pace, rhythm, variability, asymmetry, kinematics, coordination, and postural control domains and were obtained in intervals of 1 minute during the 6MWT. In addition, gait characteristics change in the last minute compared with the first minute were calculated for all gait variables using a fatigability index (ie, distance walking index). The intraclass correlation coefficient (ICC), Bland-Altman Plots, and Standard error of measurement were applied to investigate reliability.

RESULTS

Reliability of gait characteristics, minute-by-minute, and for their changes (ie, using the fatigability index) ranged from poor to excellent (pwMS: ICC 0.46-0.96; HC: ICC 0.09-0.97 and pwMS: ICC 0-0.72; HC: ICC 0-0.77, respectively).

CONCLUSION

Besides coordination, at least 1 variable of each gait domain showed an ICC of moderate or good reliability for gait characteristics changes in both pwMS and HC. These metrics can be incorporated into future clinical trials and research on walking fatigability.Clinical Trial Registration: NCT05412043.

Maintaining Task Performance Levels Under Cognitive Load While Walking Requires Widespread Reallocation of Neural Resources

This study elucidates the neural mechanisms underlying increasing cognitive load while walking by employing 2 versions of a response inhibition task, the '1-back' version and the more cognitively demanding '2-back' version. By using the Mobile Brain/Body Imaging (MoBI) modality, electroencephalographic (EEG) activity, three-dimensional (3D) gait kinematics and task-related behavioral responses were collected while young adults (n = 61) performed either the 1-back or 2-back response inhibition task. Interestingly, increasing inhibitory difficulty from 1-back to 2-back during walking was not associated with any detectable costs in response accuracy, response speed, or gait consistency. However, the more difficult cognitive task was associated with distinct EEG component changes during both successful inhibitions (correct rejections) and successful executions (hits) of the motor response. During correct rejections, ERP changes were found over frontal regions, during latencies related to sensory gain control, conflict monitoring and working memory storage and processing. During hits, ERP changes were found over left-parietal regions during latencies related to orienting attention and subsequent selection and execution of the motor plan. The pattern of attenuation in walking-related EEG amplitude changes, during 2-back task performance, is thought to reflect more effortful recalibration of neural processes, a mechanism which might be a key driver of performance maintenance in the face of increased cognitive demands while walking. Overall, the present findings shed light on the extent of the neurocognitive capacity of young adults and may lead to a better understanding of how factors such as aging or neurological disorders could impinge on this capacity.

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

BACKGROUND

Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains.

OBJECTIVE

This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades.

METHODS

We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

RESULTS

Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good.

CONCLUSIONS

Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS.

TRIAL REGISTRATION

PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.

Paradoxical improvement of cognitive control in older adults under dual-task walking conditions is associated with more flexible reallocation of neural resources: A Mobile Brain-Body Imaging (MoBI) study

Combining walking with a demanding cognitive task is traditionally expected to elicit decrements in gait and/or cognitive task performance. However, it was recently shown that, in a cohort of young adults, most participants improved performance when walking was added to performance of a Go/NoGo response inhibition task. The present study aims to extend these previous findings to an older adult cohort, to investigate whether this improvement when dual-tasking is observed in healthy older adults. Mobile Brain/Body Imaging (MoBI) was used to record electroencephalographic (EEG) activity, three-dimensional (3D) gait kinematics and behavioral responses in the Go/NoGo task, during sitting or walking on a treadmill, in 34 young adults and 37 older adults. Increased response accuracy during walking, independent of age, was found to correlate with slower responses to stimuli (r = 0.44) and with walking-related EEG amplitude modulations over frontocentral regions (r = 0.47) during the sensory gating (N1) and conflict monitoring (N2) stages of inhibition, and over left-lateralized prefrontal regions (r = 0.47) during the stage of inhibitory control implementation. These neural activity changes are related to the cognitive component of inhibition, and they were interpreted as signatures of behavioral improvement during walking. On the other hand, aging, independent of response accuracy during walking, was found to correlate with slower treadmill walking speeds (r = -0.68) and attenuation in walking-related EEG amplitude modulations over left-dominant frontal (r = -0.44) and parietooccipital regions (r = 0.48) during the N2 stage, and over centroparietal regions (r = 0.48) during the P3 stage. These neural activity changes are related to the motor component of inhibition, and they were interpreted as signatures of aging. Older adults whose response accuracy 'paradoxically' improved during walking manifested neural signatures of both behavioral improvement and aging, suggesting that their flexibility in reallocating neural resources while walking might be maintained for the cognitive but not for the motor inhibitory component. These distinct neural signatures of aging and behavior can potentially be used to identify 'super-agers', or individuals at risk for cognitive decline due to aging or neurodegenerative disease.

Young adults who improve performance during dual-task walking show more flexible reallocation of cognitive resources: a mobile brain-body imaging (MoBI) study

INTRODUCTION

In young adults, pairing a cognitive task with walking can have different effects on gait and cognitive task performance. In some cases, performance clearly declines whereas in others compensatory mechanisms maintain performance. This study investigates the preliminary finding of behavioral improvement in Go/NoGo response inhibition task performance during walking compared with sitting, which was observed at the piloting stage.

MATERIALS AND METHODS

Mobile brain/body imaging (MoBI) was used to record electroencephalographic (EEG) activity, 3-dimensional (3D) gait kinematics and behavioral responses in the cognitive task, during sitting or walking on a treadmill.

RESULTS

In a cohort of 26 young adults, 14 participants improved in measures of cognitive task performance while walking compared with sitting. These participants exhibited walking-related EEG amplitude reductions over frontal scalp regions during key stages of inhibitory control (conflict monitoring, control implementation, and pre-motor stages), accompanied by reduced stride-to-stride variability and faster responses to stimuli compared with those who did not improve. In contrast, 12 participants who did not improve exhibited no EEG amplitude differences across physical condition.

DISCUSSION

The neural activity changes associated with performance improvement during dual tasking hold promise as cognitive flexibility markers that can potentially help assess cognitive decline in aging and neurodegeneration.

Semi-supervised clustering of quaternion time series: Application to gait analysis in multiple sclerosis using motion sensor data

Recent approaches in gait analysis involve the use of wearable motion sensors to extract spatio-temporal parameters that characterize multiple aspects of an individual's gait. In particular, the medical community could largely benefit from this type of devices as they could provide the clinicians with a valuable tool for assessing gait impairment. Motion sensor data are however complex and there is an urgent unmet need to develop sound statistical methods for analyzing such data and extracting clinically relevant information. In this article, we measure gait by following the hip rotation over time and the resulting statistical unit is a time series of unit quaternions. We explore the possibility to form groups of patients with similar walking impairment by taking into account their walking data and their global decease severity with semi-supervised clustering. We generalize a compromise-based method named hclustcompro to unit quaternion time series by combining it with the proper dissimilarity quaternion dynamic time warping. We apply this method on patients diagnosed with multiple sclerosis to form groups of patients with similar walking deficiencies while accounting for the clinical assessment of their overall disability. We also compare the compromise-based clustering approach with the method mergeTrees that falls into a sub-class of ensemble clustering named collaborative clustering. The results provide a first proof of both the interest of using wearable motion sensors for assessing gait impairment and the use of prior knowledge to guide the clustering process. It also demonstrates that compromise-based clustering is a more appropriate approach in this context.

Normalization and possibility of classification analysis using the optimal warping paths of dynamic time warping in gait analysis

The purpose of this study was to verify classification performance and the difference analysis between gender using optimal warping paths of dynamic time warping (DTW) and to examine the usefulness of root mean square error (RMSE) represented by the perpendicular distance from the optimal warping path to the diagonal. A 3-dimensional motion analysis experiment was performed with 24 healthy adults (male=12, female=12) in their 20s of age without gait-related diseases or injuries for the past 6 months to collect gait data. This study performed a DTW 132 times in total (male=62, female=62) for the flexion angle of the right leg's hip, knee, and ankle joints. Then, the global cost and the RMSE of the optimal warping paths were calculated and normalized. The difference analysis was performed by independent t-test. Machine learning was performed to test the classification performance using the neural network, support vector machine, and logistic regression model among the supervised models. Results analyzed using global cost and RMSE for hip, knee, and ankle joints showed a statistically significant difference between genders in global cost and RMSE for hip and knee joints but not for ankle joints using RMSE. Considering both area under the receiver operating characteristic curve and F1-score, the logistic regression model has been evaluated as the most suitable for gender classification using the global cost or RMSE. This study demonstrated that optimal warping paths could be used for statistical difference analysis and classification analysis.

Visit-to-visit systolic blood pressure variability is associated with increased fatigue symptoms in multiple sclerosis patients

OBJECTIVE

To evaluate the relationship between visit-to-visit systolic blood pressure variability (SBPv) and fatigue symptoms in Multiple Sclerosis (MS) patients.

METHODS

This is a cross-sectional study using data for MS patients who completed the Fatigue Subscale in the Performance Scales (PS), a validated, self-reported measure of MS-related disability, between 2011 and 2015 at an academic medical center. Those who had at least 3 available SBP measures within the prior 12 months of the survey were included in the analysis. Ordinal logistic regression was used to model fatigue as a function of SBP variability, adjusting for demographic factors and mean SBP.

RESULTS

Data for 91 MS subjects were analyzed. We found that, compared to those with the lowest SBP variability (Tertile 1), subjects in Tertile 2 had 2.2 times higher odds (OR = 2.19; 95% CI, 0.82-5.87; p = 0.120) and those in Tertile 3 (highest variability) 4.2 times higher odds (OR = 4.16; 95% CI, 1.56-11.13; p = 0.005) of being in a higher fatigue level group, independent of age, sex, race/ethnicity, and mean SBP.

CONCLUSIONS

Our data show that MS patients with higher SBP variability had a greater degree of fatigue. Future research is needed to further explore this relationship and the potential for therapeutic opportunities to improve fatigue.

Changes in Gait Characteristics During and Immediately After the 6-Minute Walk Test in Persons With Multiple Sclerosis: A Systematic Review

OBJECTIVE

There is limited information about gait patterns during prolonged walking in people with multiple sclerosis (PwMS). The aim of this review was to report on gait metrics during and immediately after the 6-Minute Walk Test (6MWT) in PwMS with different levels of disability.

METHODS

The systematic search was performed in 3 databases (PubMed, Web of Science, and SCOPUS) using keywords related to multiple sclerosis and 6MWT. Studies that reported on quantitative gait outcomes before and after the 6MWT or multiple time points during the 6MWT were included. The Hedges g effect size (ES) was calculated to determine the magnitude of change in each gait parameter.

RESULTS

Fourteen studies (n = 534 PwMS; n = 166 healthy controls) were eligible. Five studies investigated gait parameters prior to and immediately after the 6MWT. Nine studies collected gait measures during the 6MWT. Speed (ES = -0.43 to 0.19), cadence (ES = -0.46 to 0.16), step length (ES = -0.46 to 0.14), stability (ES = -0.35 to 0.33), and regularity (ES = -0.25 to -0.15) decreased in most studies. In the majority of included studies, step time (ES = 0 to 0.35), stance period (ES = 0.12 to 0.58), double support phase (ES = 0.03 to 0.62), variability (ES = -0.19 to 1.13), and asymmetry (ES = -0.79 to 0.62) increased following the 6MWT. The kinetic and kinematic (mainly in dorsiflexion angle [ES = -0.08 to -0.36]) features of gait were also negatively changed after 6 minutes of walking. Walking speed, cadence, step length, stride length, and stride time after 6MWT at a comfortable speed all increased. Changes in the majority of spatiotemporal parameters were more pronounced in PwMS with moderate-to-severe disability compared with PwMS with mild disability.

CONCLUSION

Most quantitative gait parameters deteriorated during the 6MWT, especially in PwMS with moderate-to-severe disability.

IMPACT

The deterioration of gait patterns should be considered when designing therapeutic interventions to increase sustained walking capacity.

The Role of Remote Monitoring in Evaluating Fatigue in Multiple Sclerosis: A Review

Fatigue is one of the most common multiple sclerosis (MS) symptoms. Despite this, monitoring and measuring fatigue (subjective lack of energy)- and fatigability (objectively measurable and quantifiable performance decline)- in people with MS have remained challenging. Traditionally, administration of self-report questionnaires during in-person visits has been used to measure fatigue. However, remote measurement and monitoring of fatigue and fatigability have become feasible in the past decade. Traditional questionnaires can be administered through the web in any setting. The ubiquitous availability of smartphones allows for momentary and frequent measurement of MS fatigue in the ecological home-setting. This approach reduces the recall bias inherent in many traditional questionnaires and demonstrates the fluctuation of fatigue that cannot be captured by standard measures. Wearable devices can assess patients' fatigability and activity levels, often influenced by the severity of subjective fatigue. Remote monitoring of fatigue, fatigability, and activity in real-world situations can facilitate quantifying symptom-severity in clinical and research settings. Combining remote measures of fatigue as well as objective fatigability in a single construct, composite score, may provide a more comprehensive outcome. The more granular data obtained through remote monitoring techniques may also help with the development of interventions aimed at improving fatigue and lowering the burden of this disabling symptom.

Exercise capacity in people with Parkinson's disease: which clinical characteristics are important?

BACKGROUND

People with Parkinson's (PwP) are suffering from reduced exercise capacity. However, little information is known about clinical correlates of exercise capacity in this population.

OBJECTIVE

This study aimed to evaluate correlations between motor and non-motor symptoms with exercise capacity in PwP.

METHODS

A total of 50 individuals with Parkinson's disease participated in the study. Exercise capacity was measured by 6 minutes' walk test (6MWT). Besides, the Movement Disorder Society-Unified Parkinson's Disease Rating Scale-Part III used to evaluate disease motor severity, Berg Balance Scale to assess balance, Montréal Cognitive Assessment to evaluate cognitive status, hospital anxiety and depression scale to assess depression and anxiety, Modified Fatigue Impact scale to evaluate fatigue, and the Pittsburgh Sleep Quality Index to evaluate sleep quality.

RESULTS

The results showed that exercise capacity, when measured by the 6MWT, can be significantly predicted by balance, disease motor severity, anxiety, and age (R² = 0.61 P < .0001).

CONCLUSION

These results suggest that exercise capacity in PwP is multifactorial and can potentially be predicted by balance, motor severity, anxiety, and age.

Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds

Spinal cord injury (SCI) patients suffer from diverse gait deficits depending on the severity of their injury. Gait assessments can objectively track the progress during rehabilitation and support clinical decision making, but a comprehensive gait analysis requires far more complex setups and time-consuming protocols that are not feasible in the daily clinical routine. As using inertial sensors for mobile gait analysis has started to gain ground, this work aimed to develop a sensor-based gait analysis for the specific population of SCI patients that measures the spatio-temporal parameters of typical gait laboratories for day-to-day clinical applications. The proposed algorithm uses shank-mounted inertial sensors and personalized thresholds to detect steps and gait events according to the individual gait profiles. The method was validated in nine SCI patients and 17 healthy controls walking on an instrumented treadmill while wearing reflective markers for motion capture used as a gold standard. The sensor-based algorithm (i) performed similarly well for the two cohorts and (ii) is robust enough to cover the diverse gait deficits of SCI patients, from slow (0.3 m/s) to preferred walking speeds.

Interpretable deep learning for the remote characterisation of ambulation in multiple sclerosis using smartphones

The emergence of digital technologies such as smartphones in healthcare applications have demonstrated the possibility of developing rich, continuous, and objective measures of multiple sclerosis (MS) disability that can be administered remotely and out-of-clinic. Deep Convolutional Neural Networks (DCNN) may capture a richer representation of healthy and MS-related ambulatory characteristics from the raw smartphone-based inertial sensor data than standard feature-based methodologies. To overcome the typical limitations associated with remotely generated health data, such as low subject numbers, sparsity, and heterogeneous data, a transfer learning (TL) model from similar large open-source datasets was proposed. Our TL framework leveraged the ambulatory information learned on human activity recognition (HAR) tasks collected from wearable smartphone sensor data. It was demonstrated that fine-tuning TL DCNN HAR models towards MS disease recognition tasks outperformed previous Support Vector Machine (SVM) feature-based methods, as well as DCNN models trained end-to-end, by upwards of 8-15%. A lack of transparency of "black-box" deep networks remains one of the largest stumbling blocks to the wider acceptance of deep learning for clinical applications. Ensuing work therefore aimed to visualise DCNN decisions attributed by relevance heatmaps using Layer-Wise Relevance Propagation (LRP). Through the LRP framework, the patterns captured from smartphone-based inertial sensor data that were reflective of those who are healthy versus people with MS (PwMS) could begin to be established and understood. Interpretations suggested that cadence-based measures, gait speed, and ambulation-related signal perturbations were distinct characteristics that distinguished MS disability from healthy participants. Robust and interpretable outcomes, generated from high-frequency out-of-clinic assessments, could greatly augment the current in-clinic assessment picture for PwMS, to inform better disease management techniques, and enable the development of better therapeutic interventions.

Instrumentally assessed gait quality is more relevant than gait endurance and velocity to explain patient-reported walking ability in early-stage multiple sclerosis

BACKGROUND AND PURPOSE

People with multiple sclerosis (PwMS) often report walking limitations even when the gold standard Expanded Disability Status Scale (EDSS) indicates normal walking endurance/autonomy. The present multicenter study on early-stage PwMS aims at analyzing which aspects are associated with patient-reported walking limitations measured with the 12-item Multiple Sclerosis Walking Scale (MSWS-12).

METHODS

Eighty-two PwMS (EDSS ≤ 2.5) were assessed using the Fullerton Advanced Balance Scale-short (FAB-s), the Fatigue Severity Scale (FSS) and the 6-min Walk Test (6MWT), the latter administered also to 21 healthy subjects. Participants performed the 6MWT wearing three inertial sensors on ankles and trunk. Instrumented metrics describing gait velocity (stride length and frequency) and quality (regularity, symmetry, instability) were computed from sensor data. Fatigue (FSS), balance (FAB-s), walking endurance (6MWT) and instrumented metrics were entered in a multiple regression model with MSWS-12 as dependent variable.

RESULTS

Gait symmetry, gait instability, fatigue and balance were significantly associated with self-rated walking ability, whilst walking endurance and velocity were not. Fatigue, balance, gait symmetry and instability were more impaired in participants reporting mild-to-moderate (MS_MM-PWL , 25 ≤ MSWS-12 < 75) compared to those reporting none-to-minimal (MS_nm-PWL , 0 ≤ MSWS-12 ≤ 25) perceived walking limitations. Compared to healthy subjects, gait symmetry and stability were reduced in MS_nm-PWL and MS_MM-PWL , even in those participants with EDSS ≤ 1.5.

CONCLUSION

Instrumentally assessed gait quality aspects (symmetry and instability) are associated with patient-reported walking ability in early-stage PwMS and seem sensitive biomarkers to detect subtle impairments even in the earliest stages of the disease (EDSS ≤ 1.5). Future studies should assess their ability to follow walking change due to MS progression or pharmacological/rehabilitation interventions.

Exercise-induced changes in gait kinematics in multiple sclerosis with minimal neurological disability

BACKGROUND

Exercise-induced gait deterioration is a frequently encountered symptom that limits ambulation throughout the clinical course, becoming more prominent with increasing neurological disability in people with MS (pwMS).

OBJECTIVE

We attempted to objectively document exercise-induced gait changes in pwMS with minimal neurological disability and stable disease.

METHODS

Gait kinematics and spatio-temporal parameters were recorded using 3D motion analysis before and after a 20-minute treadmill walk (Group A, n=15)/run (Group B, n=15) at a self-selected speed in pwMS and compared with healthy controls (n=15).

RESULTS

Gait analysis revealed a significant decrease in peak ankle dorsiflexion in swing of the most affected leg, post-exercise task, in both Group A (EDSS 2.5-3.5) and Group B (EDSS 1-2.5) and not in healthy controls. Fourteen out of 30 MS participants showed an exercise-induced gait deterioration, based on minimal detectable change. Pre-exercise gait parameters in Group A showed a significantly higher peak dorsiflexion in swing with shorter step length and higher cadence, whereas Group B was comparable to healthy controls.

CONCLUSION

The detection of exercise-induced gait deterioration (foot drop) in pwMS with minimal neurological disability and stable disease indicates the potential of gait kinematics, before and after an exercise task, to monitor subtle neurological deficits from an early stage of MS.

Short Bouts of Gait Data and Body-Worn Inertial Sensors Can Provide Reliable Measures of Spatiotemporal Gait Parameters from Bilateral Gait Data for Persons with Multiple Sclerosis

Wearable devices equipped with inertial sensors enable objective gait assessment for persons with multiple sclerosis (MS), with potential use in ambulatory care or home and community-based assessments. However, gait data collected in non-controlled settings are often fragmented and may not provide enough information for reliable measures. This paper evaluates a novel approach to (1) determine the effects of the length of the walking task on the reliability of calculated measures and (2) identify digital biomarkers for gait assessments from fragmented data. Thirty-seven participants (37) diagnosed with relapsing-remitting MS (EDSS range 0 to 4.5) executed two trials, walking 20 m each, with inertial sensors attached to their right and left shanks. Gait events were identified from the medio-lateral angular velocity, and short bouts of gait data were extracted from each trial, with lengths varying from 3 to 9 gait cycles. Intraclass correlation coefficients (ICCs) evaluate the degree of agreement between the two trials of each participant, according to the number of gait cycles included in the analysis. Results show that short bouts of gait data, including at least six gait cycles of bilateral data, can provide reliable gait measurements for persons with MS, opening new perspectives for gait assessment using fragmented data (e.g., wearable devices, community assessments). Stride time variability and asymmetry, as well as stride velocity variability and asymmetry, should be further explored as digital biomarkers to support the monitoring of symptoms of persons with neurological diseases.

Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review

Wearable sensors are becoming increasingly popular for complementing classical clinical assessments of gait deficits. The aim of this review is to examine the existing knowledge by systematically reviewing a large number of papers focusing on the use of wearable inertial sensors for the assessment of gait during the 6-minute walk test (6MWT), a widely recognized, simple, non-invasive, low-cost and reproducible exercise test. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 28 full-text articles. Then, the available knowledge was summarized regarding study design, subjects enrolled (number of patients and pathological condition, if any, age, male/female ratio), sensor characteristics (type, number, sampling frequency, range) and body placement, 6MWT protocol and extracted parameters. Results were critically discussed to suggest future directions for the use of inertial sensor devices in the clinics.

Is a Wearable Sensor-Based Characterisation of Gait Robust Enough to Overcome Differences Between Measurement Protocols? A Multi-Centric Pragmatic Study in Patients with Multiple Sclerosis

Inertial measurement units (IMUs) allow accurate quantification of gait impairment of people with multiple sclerosis (pwMS). Nonetheless, it is not clear how IMU-based metrics might be influenced by pragmatic aspects associated with clinical translation of this approach, such as data collection settings and gait protocols. In this study, we hypothesised that these aspects do not significantly alter those characteristics of gait that are more related to quality and energetic efficiency and are quantifiable via acceleration related metrics, such as intensity, smoothness, stability, symmetry, and regularity. To test this hypothesis, we compared 33 IMU-based metrics extracted from data, retrospectively collected by two independent centres on two matched cohorts of pwMS. As a worst-case scenario, a walking test was performed in the two centres at a different speed along corridors of different lengths, using different IMU systems, which were also positioned differently. The results showed that the majority of the temporal metrics (9 out of 12) exhibited significant between-centre differences. Conversely, the between-centre differences in the gait quality metrics were small and comparable to those associated with a test-retest analysis under equivalent conditions. Therefore, the gait quality metrics are promising candidates for reliable multi-centric studies aiming at assessing rehabilitation interventions within a routine clinical context.

Deterioration of specific aspects of gait during the instrumented 6-min walk test among people with multiple sclerosis

Prolonged walking is typically impaired among people with multiple sclerosis (pwMS), however, it is unclear what the contributing factors are or how to evaluate this deterioration. We aimed to determine which gait features become worse during sustained walking and to examine the clinical correlates of gait fatigability in pwMS. Fifty-eight pwMS performed the 6-min walk test while wearing body-fixed sensors. Multiple gait domains (e.g., pace, rhythm, variability, asymmetry and complexity) were compared across each minute of the test and between mild- and moderate-disability patient groups. Associations between the decline in gait performance (i.e., gait fatigability) and patient-reported gait disability, fatigue and falls were also determined. Cadence, stride time variability, stride regularity, step regularity and gait complexity significantly deteriorated during the test. In contrast, somewhat surprisingly, gait speed and swing time asymmetry did not change. As expected, subjects with moderate disability (n = 24) walked more poorly in most gait domains compared to the mild-disability group (n = 34). Interestingly, a group × fatigue interaction effect was observed for cadence and gait complexity; these measures decreased over time in the moderate-disability group, but not in the mild group. Gait fatigability rate was significantly correlated with physical fatigue, gait disability, and fall history. These findings suggest that sustained walking affects specific aspects of gait, which can be used as markers for fatigability in MS. This effect on gait depends on the degree of disability, and may increase fall risk in pwMS. To more fully understand and monitor correlates that reflect everyday walking in pwMS, multiple domains of gait should be quantified.

Walking endurance in multiple sclerosis: Meta-analysis of six-minute walk test performance

BACKGROUND

The 6-minute walk (6 MW) is the most commonly applied measure of endurance walking capacity in persons with multiple sclerosis (MS); however, we are not aware of a quantitative synthesis of 6 MW performance in MS.

RESEARCH QUESTION

We undertook a meta-analysis quantifying the overall magnitude of difference in 6 MW performance between MS and healthy controls (HCs), and then within MS as a function of disability status. We further examined possible moderator variables of 6 MW performance.

METHODS

The systematic search was conducted for articles that included the 6 MW in persons with MS and involved comparison groups (i.e., HCs or MS disability subgroups (i.e., mild vs moderate-to-severe disability status)). The mean and standard deviation of the distance traveled during the 6 MW as well as sample sizes were entered into Comprehensive Meta-Analysis software and we estimated the overall effect size (Cohen's d) using a random effects model and examined categorical variables as possible moderators (e.g., instruction protocol, provision of encouragement, method of distance measurement, and course description).

RESULTS

Thirty-four studies met inclusion criteria with a total sample size of 3204 persons (MS: 2683; HC: 521) yielding 42 total comparisons. Persons with MS walked a shorter distance than HCs (mean difference = -177.2 ± 19.1 m) with a large effect size (d = - 1.87). Persons with mild disability walked further than those with moderate-to-severe disability (mean difference = 185.19 ± 9.2 m) with a large effect (d = 1.83). The categorical variables of provision of encouragement and course layout moderated the effect of MS and course layout moderated the effect of disability status on 6 MW performance.

SIGNIFICANCE

This meta-analysis of 6 MW performance defines mean difference in 6 MW performance in MS compared with HCs and provides an estimate of the disease-related effect of MS on endurance walking capacity for application within clinical research and practice.

Novel technology for mobility and balance tracking in patients with multiple sclerosis: a systematic review

INTRODUCTION

Mobility and balance impairments in patients with multiple sclerosis (MS) are major factors for decreased quality of life. Novel sensing technologies have great potential to efficiently capture subtle changes in mobility and balance performance, and thus improve current practices by providing an easy-to-implement, objective, and continuous functional tracking in MS population. Areas covered: This review details the collective findings of novel technology utilization in mobility and balance tracking in patients with MS. Thirty-three were systematically identified and included in this review. Pertinent methodological features (participant demographics, sensing technology, study aims, functional assessment protocols, and outcome measures) were extracted from each article. The construct validity, reliability, clinical relevance, and discriminative ability of sensor-based assessment in the MS population were summarized. Expert commentary: Sensor-based balance and mobility assessment are valid in comparison with reference standard techniques and are reliable to measure performance in the MS population. Sensor-based measures are also associated with validated clinical outcomes and are sensitive to functional deficits in individuals with MS. Such technologies may greatly improve the likelihood of detecting mobility and balance dysfunctions in real-world environments, thus allowing healthcare professionals to monitor interventions and manage disease progression precisely and efficiently Abbreviations: PwMS: Patients with Multiple Sclerosis; BBS: Berg Balance Scale; DGI: Dynamic Gait Index; ABC: Activity-specific Balance Confidence; T25FW: Timed 25 Foot Walk; 6MWT: 6 minute walk test; TUG: Timed Up and Go test; EO: Eyes Open; EC: Eyes Closed; ICC: Intraclass Correlation Coefficient; EDSS: Expanded Disability Status Scale; MFIS: Modified Fatigue Impact Scale; MSWS: Multiple Sclerosis Walking Scale; MSIS: Mutliple Sclerosis Impact Scale; PPA: Physiological Profile Assessment; HC: Healthy Control; AP: Anterior-posterior direction; ML: Mediolateral direction.

Understanding the Physiological Significance of Four Inertial Gait Features in Multiple Sclerosis

Gait impairment in multiple sclerosis (MS) can result from muscle weakness, physical fatigue, lack of coordination, and other symptoms. Walking speed, as measured by a number of clinician-administered walking tests, is the primary measure of gait impairment used by clinical researchers, but inertial gait features from body-worn sensors have been proven to add clinical value. This paper seeks to understand and differentiate the physiological significance of four such features with proven value in MS to facilitate adoption by clinical researchers and incorporation in gait monitoring and analysis systems. In addition, this information can be used to select features that might be appropriate in other forms of disability. Two of the four features are computed using the dynamic time warping (DTW) algorithm: The "DTW Score" is based on the usual DTW distance, and the "Warp Score" is based on the warping length. The third feature, based on kernel density estimation (KDE), is the "KDE Peak" value. Finally, the "Causality Index" is based on the phase slope index between inertial signals from different body parts. Relationships between these measures and the aforementioned gait-related symptoms are determined by applying factor analysis to three common, clinical walking outcomes, then correlating the inertial measures as well as walking speed to each extracted factor. Statistically significant differences in correlation coefficients to the three extracted clinical factors support their distinct physiological meaning and suggest they may have complimentary roles in the analysis of MS-related walking disability.

Gait

Gait is one of the keys to functional independence. For a long-time, walking was considered an automatic process involving minimal higher-level cognitive input. Indeed, walking does not take place without muscles that move the limbs and the "lower-level" control that regulates the timely activation of the muscles. However, a growing body of literature suggests that walking can be viewed as a cognitive process that requires "higher-level" cognitive control, especially during challenging walking conditions that require executive function and attention. Two main locomotor pathways have been identified involving multiple brain areas for the control of posture and gait: the dorsal pathway of cognitive locomotor control and the ventral pathway for emotional locomotor control. These pathways may be distinctly affected in different pathologies that have important implications for rehabilitation and therapy. The clinical assessment of gait should be a focused, simple, and cost-effective process that provides both quantifiable and qualitative information on performance. In the last two decades, gait analysis has gradually shifted from analysis of a few steps in a restricted space to long-term monitoring of gait using body fixed sensors, capturing real-life and routine behavior in the home and community environment. The chapter also describes this evolution and its implications.

Relationship between perceived fatigue and performance fatigability in people with multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

Perceived fatigue (i.e., subjective perception of reduced capacity) is one of the most common and disabling symptoms for people with multiple sclerosis (MS). Perceived fatigue may also be related to performance fatigability (i.e., decline in physical performance over time), although study findings have been inconsistent.

OBJECTIVE

To locate all studies reporting the relationship between perceived fatigue and fatigability in people with MS, determine the population correlation, and examine moderating variables of the correlation size.

METHODS

In accordance with PRISMA guidelines, systematic searches were completed in Medline, PsychInfo, Google Scholar, and the Cochrane Library for peer-reviewed articles published between March 1983 and August 2016. Included articles measured perceived fatigue and performance fatigability in people with MS and provided a correlation between measures. Moderator variables expected to influence the relationship were also coded. Searches located 19 studies of 848 people with MS and a random-effects model was used to pool correlations.

RESULTS

The mean correlation between fatigue and fatigability was positive, "medium" in magnitude, and statistically significant, r=0.31 (95% CI=0.21, 0.42), p<0.001. Despite moderate between-study heterogeneity (I²=46%) no statistically significant moderators were found, perhaps due to the small number of studies per moderator category.

CONCLUSION

There is a significant relationship between perceived fatigue and fatigability in MS, such that people reporting elevated fatigue also are highly fatigable. The size of the relationship is not large enough to suggest fatigue and fatigability are the same construct, and both should continue to be assessed independently.

The Assessment of Motor Fatigability in Persons With Multiple Sclerosis: A Systematic Review

Background. Persons with multiple sclerosis (PwMS) are often characterized by increased motor fatigability, which is a performance change on an objectively measured criterion after any type of voluntary muscle contractions. This review summarizes the existing literature to determine which protocols and outcome measures are best to detect or study motor fatigability and the underlying mechanisms in MS. Methods. Two electronic databases, PubMed and Web of Science, were searched for relevant articles published until August 2016 with a combination of multiple sclerosis, fatigability, muscle fatigue, and motor fatigue. Results. A total of 48 articles were retained for data extraction. A variety of fatigability protocols were reported; protocols showed differences in type (isometric vs concentric), duration (15 to 180 s), and number of contractions (fixed or until exhaustion). Also, 12 articles reported motor fatigability during functional movements, predominantly assessed by changes in walking speed; 11 studies evaluated the mechanisms underlying motor fatigability, using additional electrical nerve or transcranial magnetic stimulation. Three articles reported psychometrics of the outcomes. Conclusions. The disparity of protocols and outcome measures to study different aspects of motor fatigability in PwMS impedes direct comparison between data. Most protocols use maximal single-joint isometric contractions, with the advantage of high standardization. Because there is no head-to-head comparison of the different protocols and only limited information on psychometric properties of outcomes, there is currently no gold standard to assess motor fatigability. The disability level, disease phenotype, and studied limb may influence the assessment of motor fatigability in PwMS.