Disability and Fatigue Can Be Objectively Measured in Multiple Sclerosis

Innovative multidimensional gait evaluation using IMU in multiple sclerosis: introducing the semiogram

Background

Quantifying gait using inertial measurement units has gained increasing interest in recent years. Highly degraded gaits, especially in neurological impaired patients, challenge gait detection algorithms and require specific segmentation and analysis tools. Thus, the outcomes of these devices must be rigorously tested for both robustness and relevancy in order to recommend their routine use. In this study, we propose a multidimensional score to quantify and visualize gait, which can be used in neurological routine follow-up. We assessed the reliability and clinical coherence of this method in a group of severely disabled patients with progressive multiple sclerosis (pMS), who display highly degraded gait patterns, as well as in an age-matched healthy subjects (HS) group.

Methods

Twenty-two participants with pMS and nineteen HS were included in this 18-month longitudinal follow-up study. During the follow-up period, all participants completed a 10-meter walk test with a U-turn and back, twice at M0, M6, M12, and M18. Average speed and seven clinical criteria (sturdiness, springiness, steadiness, stability, smoothness, synchronization, and symmetry) were evaluated using 17 gait parameters selected from the literature. The variation of these parameters from HS values was combined to generate a multidimensional visual tool, referred to as a semiogram.

Results

For both cohorts, all criteria showed moderate to very high test-retest reliability for intra-session measurements. Inter-session quantification was also moderate to highly reliable for all criteria except smoothness, which was not reliable for HS participants. All partial scores, except for the stability score, differed between the two populations. All partial scores were correlated with an objective but not subjective quantification of gait severity in the pMS population. A deficit in the pyramidal tract was associated with altered scores in all criteria, whereas deficits in cerebellar, sensitive, bulbar, and cognitive deficits were associated with decreased scores in only a subset of gait criteria.

Conclusions

The proposed multidimensional gait quantification represents an innovative approach to monitoring gait disorders. It provides a reliable and informative biomarker for assessing the severity of gait impairments in individuals with pMS. Additionally, it holds the potential for discriminating between various underlying causes of gait alterations in pMS.

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.

Fatigue Monitoring Through Wearables: A State-of-the-Art Review

The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems represent highly promising solutions for fatigue monitoring as they enable continuous, long-term monitoring of biomedical signals in unattended settings, with the required comfort and non-intrusiveness. This is a p rerequisite for the development of accurate models for fatigue monitoring in real-time. However, monitoring fatigue through wearable devices imposes unique challenges. To provide an overview of the current state-of-the-art in monitoring variables associated with fatigue via wearables and to detect potential gaps and pitfalls in current knowledge, a systematic review was performed. The Scopus and PubMed databases were searched for articles published in English since 2015, having the terms "fatigue," "drowsiness," "vigilance," or "alertness" in the title, and proposing wearable device-based systems for non-invasive fatigue quantification. Of the 612 retrieved articles, 60 satisfied the inclusion criteria. Included studies were mainly of short duration and conducted in laboratory settings. In general, researchers developed fatigue models based on motion (MOT), electroencephalogram (EEG), photoplethysmogram (PPG), electrocardiogram (ECG), galvanic skin response (GSR), electromyogram (EMG), skin temperature (T_sk), eye movement (EYE), and respiratory (RES) data acquired by wearable devices available in the market. Supervised machine learning models, and more specifically, binary classification models, are predominant among the proposed fatigue quantification approaches. These models were considered to perform very well in detecting fatigue, however, little effort was made to ensure the use of high-quality data during model development. Together, the findings of this review reveal that methodological limitations have hindered the generalizability and real-world applicability of most of the proposed fatigue models. Considerably more work is needed to fully explore the potential of wearables for fatigue quantification as well as to better understand the relationship between fatigue and changes in physiological variables.

Quantitative body symmetry assessment during neurological examination

BACKGROUND

A lack of movement coordination characterized by the undershoot or overshoot of the intended location with the hand, arm, or leg is often found in individuals with multiple sclerosis (MS). Standardized as Finger-to-Nose (FNT) and The Heel-to-Shin (HST) tests are the most frequently used tests for qualitative examination of upper and lower body coordination. Inertial sensors facilitate in performing quantitative motion analysis and by estimating body symmetry more accurately assess coordination lesion and imbalance.

OBJECTIVES

To assess the body symmetry of upper and lower limbs quantitatively, and to find the best body symmetry indices to discriminate MS from healthy individuals (CO).

METHODS

28 MS patients and 23 CO participated in the study. Spatiotemporal parameters obtained from six Inertial Measurement Units (IMUs) were placed on the upper and lower extremities during FNT and HST tests. All data were analyzed using statistical methods in MATLAB.

RESULTS

Asymmetry indices of temporal parameters showed a significant increase in upper body and lower body asymmetry of MS compared to CO. However, CO have a greater kinematic asymmetry compared to MS.

CONCLUSION

Temporal parameters are the most sensitive to body asymmetry evaluation. However, range of motion is completely inappropriate if it is calculated for one movement cycle.

Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis

Background

Multiple sclerosis (MS) is a disabling disease affecting the central nervous system and consequently the whole body’s functional systems resulting in different gait disorders. Fatigue is the most common symptom in MS with a prevalence of 80%. Previous research studied the relation between fatigue and gait impairment using stationary gait analysis systems and short gait tests (e.g. timed 25 ft walk). However, wearable inertial sensors providing gait data from longer and continuous gait bouts have not been used to assess the relation between fatigue and gait parameters in MS. Therefore, the aim of this study was to evaluate the association between fatigue and spatio-temporal gait parameters extracted from wearable foot-worn sensors and to predict the degree of fatigue.

Methods

Forty-nine patients with MS (32 women; 17 men; aged 41.6 years, EDSS 1.0–6.5) were included where each participant was equipped with a small Inertial Measurement Unit (IMU) on each foot. Spatio-temporal gait parameters were obtained from the 6-min walking test, and the Borg scale of perceived exertion was used to represent fatigue. Gait parameters were normalized by taking the difference of averaged gait parameters between the beginning and end of the test to eliminate inter-individual differences. Afterwards, normalized parameters were transformed to principle components that were used as input to a Random Forest regression model to formulate the relationship between gait parameters and fatigue.

Results

Six principal components were used as input to our model explaining more than 90% of variance within our dataset. Random Forest regression was used to predict fatigue. The model was validated using 10-fold cross validation and the mean absolute error was 1.38 points. Principal components consisting mainly of stride time, maximum toe clearance, heel strike angle, and stride length had large contributions (67%) to the predictions made by the Random Forest.

Conclusions

The level of fatigue can be predicted based on spatio-temporal gait parameters obtained from an IMU based system. The results can help therapists to monitor fatigue before and after treatment and in rehabilitation programs to evaluate their efficacy. Furthermore, this can be used in home monitoring scenarios where therapists can monitor fatigue using IMUs reducing time and effort of patients and therapists.

Associations Between Self-Reported Symptoms and Gait Parameters Using In-Home Sensors in Persons With Multiple Sclerosis

BACKGROUND AND PURPOSE

Multiple sclerosis (MS) is a progressive neurological disorder, characterized by exacerbations and remissions, often resulting in disability affecting multiple neurological functions. The purpose of this article was (1) to describe the frequencies of self-reported symptoms in a natural environment and (2) to determine characteristics and associations between self-reported symptoms and home gait parameters (speed, stride time, and stride length) at baseline and at 3 months in patients with MS.

METHODS

Participants completed the self-report MS-Related Symptom Scale to measure symptoms. A three-dimensional depth imaging system (Foresite Healthcare) was used to measure gait parameters in the home environment.

RESULTS

These data show significant correlations between the following symptoms: knee locking or collapsing, difficulty sleeping, depression, and anxiety with decreased number of average walks per day; however, the symptoms including trouble-making toilet: day and difficulty in starting urine were positively correlated with average walks per day. The symptom numbness was significantly correlated with decreased speed and decreased stride length.

DISCUSSION AND CONCLUSIONS

Our findings suggest that certain groups of symptoms were more frequently reported with certain gait parameters (stride time/speed) in persons with MS. Rehabilitation nurses can provide optimal care to prevent future decline in symptoms and gait.

Reliability and Repeatability Analysis of Indices to Measure Gait Deterioration in MS Patients during Prolonged Walking

Gait deterioration caused by prolonged walking represents one of the main consequences of multiple sclerosis (MS). This study aims at proposing quantitative indices to measure the gait deterioration effects. The experimental protocol consisted in a 6-min walking test and it involved nine patients with MS and twenty-six healthy subjects. Pathology severity was assessed through the Expanded Disability Status Scale. Seven inertial units were used to gather lower limb kinematics. Gait variability and asymmetry were assessed by coefficient of variation (CoV) and symmetry index (SI), respectively. The evolution of ROM (range of motion), CoV, and SI was computed analyzing data divided into six 60-s subgroups. Maximum difference among subgroups and the difference between the first minute and the remaining five were computed. The indices were analyzed for intra- and inter-day reliability and repeatability. Correlation with clinical scores was also evaluated. Good to excellent reliability was found for all indices. The computed standard deviations allowed us to affirm the good repeatability of the indices. The outcomes suggested walking-related fatigue leads to an always more variable kinematics in MS, in terms of changes in ROM, increase of variability and asymmetry. The hip asymmetry strongly correlated with the clinical disability.

Global Muscle Coactivation of the Sound Limb in Gait of People with Transfemoral and Transtibial Amputation

The aim of this study was to analyze the effect of the level of amputation and various prosthetic devices on the muscle activation of the sound limb in people with unilateral transfemoral and transtibial amputation. We calculated the global coactivation of 12 muscles using the time-varying multimuscle coactivation function method in 37 subjects with unilateral transfemoral amputation (10, 16, and 11 with mechanical, electronic, and bionic prostheses, respectively), 11 subjects with transtibial amputation, and 22 healthy subjects representing the control group. The results highlighted that people with amputation had a global coactivation temporal profile similar to that of healthy subjects. However, amputation increased the level of the simultaneous activation of many muscles during the loading response and push-off phases of the gait cycle and decreased it in the midstance and swing subphases. This increased coactivation probably plays a role in prosthetic gait asymmetry and energy consumption. Furthermore, people with amputation and wearing electronic prosthesis showed lower global coactivation when compared with people wearing mechanical and bionic prostheses. These findings suggest that the global lower limb coactivation behavior can be a useful tool to analyze the motor control strategies adopted and the ability to adapt to the prosthetic device.

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.

Reactive Postural Responses to Continuous Yaw Perturbations in Healthy Humans: The Effect of Aging

Maintaining balance stability while turning in a quasi-static stance and/or in dynamic motion requires proper recovery mechanisms to manage sudden center-of-mass displacement. Furthermore, falls during turning are among the main concerns of community-dwelling elderly population. This study investigates the effect of aging on reactive postural responses to continuous yaw perturbations on a cohort of 10 young adults (mean age 28 ± 3 years old) and 10 older adults (mean age 61 ± 4 years old). Subjects underwent external continuous yaw perturbations provided by the RotoBit^1D platform. Different conditions of visual feedback (eyes opened and eyes closed) and perturbation intensity, i.e., sinusoidal rotations on the horizontal plane at different frequencies (0.2 Hz and 0.3 Hz), were applied. Kinematics of axial body segments was gathered using three inertial measurement units. In order to measure reactive postural responses, we measured body-absolute and joint absolute rotations, center-of-mass displacement, body sway, and inter-joint coordination. Older adults showed significant reduction in horizontal rotations of body segments and joints, as well as in center-of-mass displacement. Furthermore, older adults manifested a greater variability in reactive postural responses than younger adults. The abnormal reactive postural responses observed in older adults might contribute to the well-known age-related difficulty in dealing with balance control during turning.

Validation of Novel Relative Orientation and Inertial Sensor-to-Segment Alignment Algorithms for Estimating 3D Hip Joint Angles

Wearable sensor-based algorithms for estimating joint angles have seen great improvements in recent years. While the knee joint has garnered most of the attention in this area, algorithms for estimating hip joint angles are less available. Herein, we propose and validate a novel algorithm for this purpose with innovations in sensor-to-sensor orientation and sensor-to-segment alignment. The proposed approach is robust to sensor placement and does not require specific calibration motions. The accuracy of the proposed approach is established relative to optical motion capture and compared to existing methods for estimating relative orientation, hip joint angles, and range of motion (ROM) during a task designed to exercise the full hip range of motion (ROM) and fast walking using root mean square error (RMSE) and regression analysis. The RMSE of the proposed approach was less than that for existing methods when estimating sensor orientation ( 12 . 32 ∘ and 11 . 82 ∘ vs. 24 . 61 ∘ and 23 . 76 ∘ ) and flexion/extension joint angles ( 7 . 88 ∘ and 8 . 62 ∘ vs. 14 . 14 ∘ and 15 . 64 ∘ ). Also, ROM estimation error was less than 2 . 2 ∘ during the walking trial using the proposed method. These results suggest the proposed approach presents an improvement to existing methods and provides a promising technique for remote monitoring of hip joint angles.

Immediate effects of rhythmic auditory stimulation on gait kinematics in Parkinson's disease ON/OFF medication

OBJECTIVE

Gait impairment is a highly disabling symptom for Parkinson's disease (PD) patients. Rhythmic auditory stimulation (RAS), has shown to improve spatio-temporal gait parameters in PD, but only a few studies have focused on their effects on gait kinematics, and the ideal stimulation frequency has still not been identified.

METHODS

We enrolled 30 PD patients and 18 controls. Patients were evaluated under two conditions (with (ON), and without (OFF) medications) with three different RAS frequencies (90%, 100%, and 110% of the patient's preferred walking cadence). Spatial-temporal parameters, joint angles and gait phases distribution were evaluated. A novel global index (GPQI) was used to quantify the difference in gait phase distribution.

RESULTS

Along with benefits in spatial-temporal parameters, GPQI improved significantly with RAS at a frequency of 110% for both ON and OFF medication conditions. In the most severe patients, the same result was observed also with RAS at 100%.

CONCLUSIONS

RAS administration, at a frequency of 110% of the preferred walking frequency, can be beneficial in improving the gait pattern in PD patients.

SIGNIFICANCE

When rhythmic auditory stimulation is provided to patients with PD, the selection of an adequate frequency of stimulation can optimize their effects on gait pattern.

Comparing Gait Trials with Greedy Template Matching

Gait assessment and quantification have received an increased interest in recent years. Embedded technologies and low-cost sensors can be used for the longitudinal follow-up of various populations (neurological diseases, elderly, etc.). However, the comparison of two gait trials remains a tricky question as standard gait features may prove to be insufficient in some cases. This article describes a new algorithm for comparing two gait trials recorded with inertial measurement units (IMUs). This algorithm uses a library of step templates extracted from one trial and attempts to detect similar steps in the second trial through a greedy template matching approach. The output of our method is a similarity index (SId) comprised between 0 and 1 that reflects the similarity between the patterns observed in both trials. Results on healthy and multiple sclerosis subjects show that this new comparison tool can be used for both inter-individual comparison and longitudinal follow-up.

Thigh-Derived Inertial Sensor Metrics to Assess the Sit-to-Stand and Stand-to-Sit Transitions in the Timed Up and Go (TUG) Task for Quantifying Mobility Impairment in Multiple Sclerosis

Introduction: Inertial sensors generate objective and sensitive metrics of movement disability that may indicate fall risk in many clinical conditions including multiple sclerosis (MS). The Timed-Up-And-Go (TUG) task is used to assess patient mobility because it incorporates clinically-relevant submovements during standing. Most sensor-based TUG research has focused on the placement of sensors at the spine, hip or ankles; an examination of thigh activity in TUG in multiple sclerosis is wanting. Methods: We used validated sensors (x-IMU by x-io) to derive transparent metrics for the sit-to-stand (SI-ST) transition and the stand-to-sit (ST-SI) transition of TUG, and compared effect sizes for metrics from inertial sensors on the thighs to effect sizes for metrics from a sensor placed at the L3 level of the lumbar spine. Twenty-three healthy volunteers were compared to 17 ambulatory persons with MS (PwMS, HAI ≤ 2). Results: During the SI-ST transition, the metric with the largest effect size comparing healthy volunteers to PwMS was the Area Under the Curve of the thigh angular velocity in the pitch direction-representing both thigh and knee extension; the peak of the spine pitch angular velocity during SI-ST also had a large effect size, as did some temporal measures of duration of SI-ST, although less so. During the ST-SI transition the metric with the largest effect size in PwMS was the peak of the spine angular velocity curve in the roll direction. A regression was performed. Discussion: We propose for PwMS that the diminished peak angular velocity during SI-ST directly represents extensor weakness, while the increased roll during ST-SI represents diminished postural control. Conclusions: During the SI-ST transition of TUG, angular velocities can discriminate between healthy volunteers and ambulatory PwMS better than temporal features. Sensor placement on the thighs provides additional discrimination compared to sensor placement at the lumbar spine.

Wearable technology reveals gait compensations, unstable walking patterns and fatigue in people with multiple sclerosis

OBJECTIVE

People with multiple sclerosis (PwMS) often experience a decline in gait performance, which can compromise their independence and increase falls. Ankle joint contractures in PwMS are common and often result in compensatory gait patterns to accommodate reduced ankle range of motion (ROM).

APPROACH

Using advances in wearable technology, the aim of this study was to quantify head and pelvis movement patterns that occur in PwMS with disability and determine how these secondary gait compensations impact on gait stability. Twelve healthy participants and 12 PwMS participated in the study. Head and pelvis movements were measured using two tri-axial accelerometers. Measures of gait compensation, mobility, variability, asymmetry, stability and fatigue were assessed during a 6 min walking test.

MAIN RESULTS

Compared to healthy controls, PwMS had greater vertical asymmetry in their head and pelvic movements (Cohen's d  =  1.85 and 1.60). Lower harmonic ratios indicated that PwMS were more unstable than controls (Cohen's d  =  -1.61 to  -3.06), even after adjusting for their slower walking speeds. In the PwMS, increased compensatory movements were correlated with reduced ankle active ROM (r  =  -0.71), higher disability (EDSS) scores (r  =  0.58), unstable gait (r  =  -0.76), reduced mobility (r  =  -0.76) and increased variability (r  =  0.83).

SIGNIFICANCE

Wearable device technology provides an efficient and reliable way to screen for excessive compensatory movements often present in PwMS and provides clinically important information that impacts on mobility, stride time variability and gait stability. This information may help clinicians identify PwMS at high risk of falling and develop better rehabilitation interventions that, in addition to improving mobility, may help target the underlying causes of unstable gait.

Measuring Gait Quality in Parkinson's Disease through Real-Time Gait Phase Recognition

Monitoring gait quality in daily activities through wearable sensors has the potential to improve medical assessment in Parkinson’s Disease (PD). In this study, four gait partitioning methods, two based on thresholds and two based on a machine learning approach, considering the four-phase model, were compared. The methods were tested on 26 PD patients, both in OFF and ON levodopa conditions, and 11 healthy subjects, during walking tasks. All subjects were equipped with inertial sensors placed on feet. Force resistive sensors were used to assess reference time sequence of gait phases. Goodness Index (G) was evaluated to assess accuracy in gait phases estimation. A novel synthetic index called Gait Phase Quality Index (GPQI) was proposed for gait quality assessment. Results revealed optimum performance (G < 0.25) for three tested methods and good performance (0.25 < G < 0.70) for one threshold method. The GPQI resulted significantly higher in PD patients than in healthy subjects, showing a moderate correlation with clinical scales score. Furthermore, in patients with severe gait impairment, GPQI was found higher in OFF than in ON state. Our results unveil the possibility of monitoring gait quality in PD through real-time gait partitioning based on wearable sensors.

In Memoriam: Paolo Cappa

Prof. Paolo Cappa passed away on 26 August 2016, at the age of 59, after a long and courageous fight against cancer. Paolo Cappa was a Professor in Mechanical and Thermal Measurements and Experimental Biomechanics in the Department of Mechanical and Aerospace Engineering of Sapienza University of Rome, where he had also served as the Head of the Department, and a Research Professor in the Department of Mechanical and Aerospace Engineering of New York University Tandon School of Engineering. During his intense, yet short, career, he made several significant scientific contributions within the discipline of Mechanical and Thermal Measurements, pioneering fundamental applications to Biomechanics. He co-founded the Motion Analysis and Robotics Laboratory (MARLab) within the Neurorehabilitation Division of IRCCS Pediatric Hospital “Bambino Gesu”, in Rome, to fuel transitional research from the laboratory to clinical practice. Through collaboration with neurologists and physiatrists at MARLab, Prof. Cappa led the development of a powerful array of novel mechanical solutions to wearable robotics for pediatric patients, addressing dramatic needs for children’s health and contributing to the training of an entire generation of Mechanical Engineering students.

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.

Instrumented balance and walking assessments in persons with multiple sclerosis show strong test-retest reliability

BACKGROUND

There is a need for objective movement assessment for clinical research trials aimed at improving gait and balance in persons with multiple sclerosis (PwMS). Wireless inertial sensors can accurately measure numerous walking and balance parameters but these measures require evaluation of reliability in PwMS. The current study determined the test-retest reliability of wireless inertial sensor measures obtained during an instrumented standing balance test and an instrumented Timed Up and Go test in PwMS.

METHODS

Fifteen PwMS and 15 healthy control subjects (HC) performed an instrumented standing balance and instrumented Timed Up and Go (TUG) test on two separate days. Ten instrumented standing balance measures and 18 instrumented TUG measures were computed from the wireless sensor data. Intraclass correlation coefficients (ICC) were calculated to determine test-retest reliability of all instrumented standing balance and instrumented TUG measures. Correlations were evaluated between the instrumented standing balance and instrumented TUG measures and self-reported walking and balance performance, fall history, and clinical disability.

RESULTS

For both groups, ICCs for instrumented standing balance measures were best for spatio-temporal measures, while frequency measures were less reliable. All instrumented TUG measures exhibited good to excellent (ICCs > 0.60) test-retest reliability in PwMS and in HC. There were no correlations between self-report walking and balance scores and instrumented TUG or instrumented standing balance metrics, but there were correlations between instrumented TUG and instrumented standing balance metrics and fall history and clinical disability status.

CONCLUSIONS

Measures from the instrumented standing balance and instrumented TUG tests exhibit good to excellent reliability, demonstrating their potential as objective assessments for clinical trials. A subset of the most reliable measures is recommended for measuring walking and balance in clinical settings.

Neuromuscular fatigue during exercise: Methodological considerations, etiology and potential role in chronic fatigue

The term fatigue is used to describe a distressing and persistent symptom of physical and/or mental tiredness in certain clinical populations, with distinct but ultimately complex, multifactorial and heterogenous pathophysiology. Chronic fatigue impacts on quality of life, reduces the capacity to perform activities of daily living, and is typically measured using subjective self-report tools. Fatigue also refers to an acute reduction in the ability to produce maximal force or power due to exercise. The classical measurement of exercise-induced fatigue involves neuromuscular assessments before and after a fatiguing task. The limitations and alternatives to this approach are reviewed in this paper in relation to the lower limb and whole-body exercise, given the functional relevance to locomotion, rehabilitation and activities of daily living. It is suggested that under some circumstances, alterations in the central and/or peripheral mechanisms of fatigue during exercise may be related to the sensations of chronic fatigue. As such, the neurophysiological correlates of exercise-induced fatigue are briefly examined in two clinical examples where chronic fatigue is common: cancer survivors and people with multiple sclerosis. This review highlights the relationship between objective measures of fatigability with whole-body exercise and perceptions of fatigue as a priority for future research, given the importance of exercise in relieving symptoms of chronic fatigue and/or overall disease management. As chronic fatigue is likely to be specific to the individual and unlikely to be due to a simple biological or psychosocial explanation, tailored exercise programmes are a potential target for therapeutic intervention.

Clinical assessment of gait in individuals with multiple sclerosis using wearable inertial sensors: Comparison with patient-based measure

BACKGROUND

This study aims to verify the feasibility of use of wearable accelerometers in an ambulatory environment to assess spatiotemporal parameters of gait in people with Multiple Sclerosis (pwMS), as well as the correlation of objective data with patient-reported outcomes.

METHODS

One hundred and five pwMS (Expanded Disability Status Scale, EDSS in the range 0-6.5) classified in three sub-groups (EDSS 0-1.5, EDSS 2-4, EDSS 4.5-6.5) and 47 healthy controls (HC) participated in the study. All the subjects were evaluated with the timed 25-foot walking test (T25FW) while wearing a commercially available accelerometer. PwMS also rated the impact of the disease on their walking abilities using the 12-item MS walking scale (MSWS-12).

RESULTS

All parameters objectively measured, except stride length, were significantly modified in pwMS with higher EDSS, with respect to HC and lower disability participants. Moderate to high correlations (r =0.57-0.79) were observed between gait parameters and MSWS-12 for pwMS of higher EDSS. The correlation was found moderate for the intermediate EDSS category (r =0.42-0.62).

CONCLUSION

Wearable accelerometers are a useful tool for assessing gait performance for pwMS in a clinical setting, especially in cases of mild to moderate disability. Compared with other quantitative techniques, these devices allow patient testing under realistic conditions (i.e., fully dressed, with their usual shoes) using a simple procedure with immediate availability of data.