Gait pattern in patients with different multiple sclerosis phenotypes

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

Introduction: Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

Quantifying lower extremity inter-segmental coordination variability during walking in people with multiple sclerosis with high and low fear of falling

BACKGROUND

Fear of falling (FOF) is associated with gait disturbances in people with multiple sclerosis (PwMS). However, previous studies mostly assessed FOF-related changes in gait patterns of PwMS using spatio-temporal gait parameters. Considering the complex nature of gait control, investigation of the higher order properties of the human movement system, particularly inter-segmental coordination variability may provide valuable information about underlying deficits in motor control patterns in PwMS with different levels of FOF. Therefore, the purpose of this study was to clarify the differences in lower extremity inter-segmental coordination variability between healthy controls and PwMS with high and low FOF.

METHODS

This cross-sectional study examined gait patterns of 40 PwMS and 20 age-and-sex-matched healthy controls during treadmill walking at a preferred walking speed for 3 min. The falls efficacy scale-international questionnaire was used to stratify PwMS into high and low FOF subgroups. Variability in coordinative relationships between shank-thigh and foot-shank segments was determined using deviation phase (DP), which is the average standard deviation calculated from all points of the ensemble continuous relative phase (CRP) curve during the stance and swing phases of gait.

RESULTS

DP values for shank-thigh (p = 0.005 and p < 0.001, respectively) and foot-shank inter-segmental relationships (p < 0.001) during the stance phase as well as for foot-shank inter-segmental relationships during the swing phase (p = 0.03) were significantly greater in PwMS with high FOF compared to those with low FOF and healthy controls. In addition, both groups of PwMS with high and low FOF indicated greater shank-thigh DP values compared to healthy controls during the swing phase (p < 0.001 and p = 0.002, respectively).

CONCLUSION

The findings suggest unsteadiness in neuromuscular organization during walking in PwMS with high FOF. Rehabilitative interventions targeting impairments in lower extremity inter-segmental coordination and FOF may be useful to improve walking and reduce risk of falls in PwMS with high FOF.

Spatiotemporal gait changes in people with multiple sclerosis with different disease progression subtypes

BACKGROUND

Gait impairment is common in people with multiple sclerosis (MS), but less is known about gait differences between MS disease progression subtypes. The objective here was to examine differences in spatiotemporal gait in MS and between relapsing-remitting and progressive subtypes during the timed-25-ft-walk test. Our specific aims were to investigate (1) spatiotemporal, (2) spatiotemporal variability, and (3) gait modulation differences between healthy controls and MS subtypes at preferred and fast walking speed.

METHODS

This study included 27 controls, 18 relapsing-remitting MS, and 13 progressive MS participants. Participants wore six inertial sensors and walked overground without walking aids at preferred and fast-as-possible speeds.

FINDINGS

Both MS groups had significantly lower walking speed than controls, with a trend towards lower preferred gait speed in progressive compared to relapsing-remitting MS (ES = 0.502). Although most spatiotemporal gait parameters differed between controls and MS groups, differences were not significant between MS subtypes in these parameters and their variability, with low to moderate effect sizes during preferred and fast walking. Both MS groups showed reduced modulation in gait compared to controls and no significant differences between MS subtypes.

INTERPRETATION

Gait in MS is altered compared to controls. Although gait may change with progressive MS, the overall small differences in the gait parameters between the MS subtypes observed in this sample suggests that those with the progressive form of MS who are independently ambulatory and without further clinically meaningful changes in gait speed may not show gait decrements greater than the relapsing-remitting form of the disease.

Turning and multitask gait unmask gait disturbance in mild-to-moderate multiple sclerosis: Underlying specific cortical thinning and connecting fibers damage

Multiple sclerosis (MS) causes gait and cognitive impairments that are partially normalized by compensatory mechanisms. We aimed to identify the gait tasks that unmask gait disturbance and the underlying neural correlates in MS. We included 25 patients with MS (Expanded Disability Status Scale score: median 2.0, interquartile range 1.0-2.5) and 19 healthy controls. Fast-paced gait examinations with inertial measurement units were conducted, including straight or circular walking with or without cognitive/motor tasks, and the timed up and go test (TUG). Receiver operating characteristic curve analysis was performed to distinguish both groups by the gait parameters. The correlation between gait parameters and cortical thickness or fractional anisotropy values was examined by using three-dimensional T1-weighted imaging and diffusion tensor imaging, respectively (corrected p < .05). Total TUG duration (>6.0 s, sensitivity 88.0%, specificity 84.2%) and stride velocity during cognitive dual-task circular walking (<1.12 m/s, 84.0%, 84.2%) had the highest discriminative power of the two groups. Deterioration of these gait parameters was correlated with thinner cortical thickness in regional areas, including the left precuneus and left temporoparietal junction, overlapped with parts of the default mode network, ventral attention network, and frontoparietal network. Total TUG duration was negatively correlated with fractional anisotropy values in the deep cerebral white matter areas. Turning and multitask gait may be optimal to unveil partially compensated gait disturbance in patients with mild-to-moderate MS through dynamic balance control and multitask processing, based on the structural damage in functional networks.

Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data

One of the core problems for people with multiple sclerosis (pwMS) is the impairment of their ability to walk, which can be severely restrictive in everyday life. Therefore, monitoring of ambulatory function is of great importance to be able to effectively counteract disease progression. An extensive gait analysis, such as the Dresden protocol for multidimensional walking assessment, covers several facets of walking impairment including a 2-min walk test, in which the distance taken by the patient in two minutes is measured by an odometer. Using this approach, it is questionable how precise the measuring methods are at recording the distance traveled. In this project, we investigate whether the current measurement can be replaced by a digital measurement method based on accelerometers (six Opal sensors from the Mobility Lab system) that are attached to the patient’s body. We developed two algorithms using these data and compared the validity of these approaches using the results from 2-min walk tests from 562 pwMS that were collected with a gold-standard odometer. In 48.4% of pwMS, we detected an average relative measurement error of less than 5%, while results from 25.8% of the pwMS showed a relative measurement error of up to 10%. The algorithm had difficulties correctly calculating the walking distances in another 25.8% of pwMS; these results showed a measurement error of more than 20%. A main reason for this moderate performance was the variety of pathologically altered gait patterns in pwMS that may complicate the step detection. Overall, both algorithms achieved favorable levels of agreement (r = 0.884 and r = 0.980) with the odometer. Finally, we present suggestions for improvement of the measurement system to be implemented in the future.

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice.

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.

Muscle architecture and its relationship with lower extremity muscle strength in multiple sclerosis

This study was planned to determine the muscle architecture (pennation angle, muscle fiber length, and muscle thickness) and its relationship to lower extremity muscle strength in patients with Multiple Sclerosis (pwMS). The muscle architecture (pennation angle, muscle fiber length, and muscle thickness) and lower extremity muscle strength were assessed in 33 pwMS [13 Relapsing-Remitting MS (RRMS), 5 Primary Progressive MS (PPMS), 5 Secondary Progressive MS (SPMS), and 11 matched healthy controls (HC)]. Muscle architecture features were assessed with ultrasonography and muscle strength were assessed with a digital hand-held dynamometer. The rectus femoris muscle thickness and pennation angle, gastrocnemius muscle thickness, and the tibialis anterior pennation angle were significantly lower in pwMS compared to HC (p < 0.05). The strength of hip flexors, hip extensors, knee extensors, foot plantar, and foot dorsi flexors were lower in pwMS. In PPMS group, muscle strength of hip flexors was lower than RRMS and SPMS groups, and muscle strength of foot dorsi flexors was lower than RRMS (p < 0.05). In pwMS, positive correlations were found, between knee flexor strength and biceps femoris pennation angle. Also knee extensor strength and rectus femoris fiber length and muscle thickness were correlated positively (p < 0.05). According to our results the muscle architecture is affected in MS. The determination of architectural changes of lower extremity muscles may guide the arrangement of optimal strength exercises in functional rehabilitation programs.ClinicalTrials: NCT03766698.

Predicting Multiple Sclerosis From Gait Dynamics Using an Instrumented Treadmill: A Machine Learning Approach

OBJECTIVE

Multiple Sclerosis (MS) is a neurological condition which widely affects people 50-60 years of age. While clinical presentations of MS are highly heterogeneous, mobility limitations are one of the most frequent symptoms. This study examines a machine learning (ML) framework for identifying MS through spatiotemporal and kinetic gait features.

METHODS

In this study, gait data during self-paced walking on an instrumented treadmill from 20 persons with MS and 20 age, weight, height, and gender-matched healthy older adults (HOA) were obtained. We explored two strategies to normalize data and minimize dependence on subject demographics; size-normalization (standard body size-based normalization) and regress-normalization (regression-based normalization using scaling factors derived by regressing gait features on multiple subject demographics); and proposed an ML based methodology to classify individual strides of older persons with MS (PwMS) from healthy controls. We generalized both across different walking tasks and subjects.

RESULTS

We observed that regress-normalization improved the accuracy of identifying pathological gait using ML when compared to size-normalization. When generalizing from comfortable walking to walking while talking, gradient boosting machine achieved the optimal subject classification accuracy and AUC of 94.3 and 1.0, respectively and for subject generalization, a multilayer perceptron resulted in the best accuracy and AUC of 80% and 0.86, respectively, both with regression-normalized data.

CONCLUSION

The integration of gait data and ML may provide a viable patient-centric approach to aid clinicians in monitoring MS.

SIGNIFICANCE

The results of this study have future implications for the way regression normalized gait features may be clinically used to design ML-based disease prediction strategies and monitor disease progression in PwMS.

Kinematic Analysis of Lower Limb Joint Asymmetry During Gait in People with Multiple Sclerosis

The majority of people with Multiple Sclerosis (pwMS), report lower limb motor dysfunctions, which may relevantly affect postural control, gait and a wide range of activities of daily living. While it is quite common to observe a different impact of the disease on the two limbs (i.e., one of them is more affected), less clear are the effects of such asymmetry on gait performance. The present retrospective cross-sectional study aimed to characterize the magnitude of interlimb asymmetry in pwMS, particularly as regards the joint kinematics, using parameters derived from angle-angle diagrams. To this end, we analyzed gait patterns of 101 pwMS (55 women, 46 men, mean age 46.3, average Expanded Disability Status Scale (EDSS) score 3.5, range 1–6.5) and 81 unaffected individuals age- and sex-matched who underwent 3D computerized gait analysis carried out using an eight-camera motion capture system. Spatio-temporal parameters and kinematics in the sagittal plane at hip, knee and ankle joints were considered for the analysis. The angular trends of left and right sides were processed to build synchronized angle–angle diagrams (cyclograms) for each joint, and symmetry was assessed by computing several geometrical features such as area, orientation and Trend Symmetry. Based on cyclogram orientation and Trend Symmetry, the results show that pwMS exhibit significantly greater asymmetry in all three joints with respect to unaffected individuals. In particular, orientation values were as follows: 5.1 of pwMS vs. 1.6 of unaffected individuals at hip joint, 7.0 vs. 1.5 at knee and 6.4 vs. 3.0 at ankle (p < 0.001 in all cases), while for Trend Symmetry we obtained at hip 1.7 of pwMS vs. 0.3 of unaffected individuals, 4.2 vs. 0.5 at knee and 8.5 vs. 1.5 at ankle (p < 0.001 in all cases). Moreover, the same parameters were sensitive enough to discriminate individuals of different disability levels. With few exceptions, all the calculated symmetry parameters were found significantly correlated with the main spatio-temporal parameters of gait and the EDSS score. In particular, large correlations were detected between Trend Symmetry and gait speed (with rho values in the range of −0.58 to −0.63 depending on the considered joint, p < 0.001) and between Trend Symmetry and EDSS score (rho = 0.62 to 0.69, p < 0.001). Such results suggest not only that MS is associated with significantly marked interlimb asymmetry during gait but also that such asymmetry worsens as the disease progresses and that it has a relevant impact on gait performances.

Is there an association between multiple sclerosis and osteoarthritis in Germany? A retrospective cohort study of 8,600 patients from Germany

OBJECTIVES

The goal of this retrospective cohort study was to investigate the multiple sclerosis-osteoarthritis relationship in adults followed in general practices in Germany.

METHODS

Patients aged 18-70 years who were diagnosed for the first time with multiple sclerosis in one of 1,193 general practices in Germany between 2005 and 2018 (index date) were included in this retrospective cohort study. Patients without multiple sclerosis were matched (1:1) to those with multiple sclerosis by sex, age, index year, general practice, obesity, injuries, and other types of arthritis (index date: a randomly selected visit date). The association between multiple sclerosis and the 10-year incidence of osteoarthritis was analyzed using Cox regression models.

RESULTS

There were 4,300 patients with multiple sclerosis and 4,300 patients without multiple sclerosis included in this study. The proportion of women was 69.3% and mean (SD) age was 43.6 (12.6) years. There was no significant association between multiple sclerosis and incident osteoarthritis in the overall sample (HR = 0.95, 95% CI: 0.83-1.09) as well as sex and age subgroups.

CONCLUSIONS

Based on these findings, multiple sclerosis is not significantly associated with osteoarthritis. Further studies of longitudinal nature are warranted to corroborate or invalidate these results.

A Multifactorial Model of Multiple Sclerosis Gait and Its Changes Across Different Disability Levels

OBJECTIVE

Mobility assessment is critical in the clinical management of people with Multiple Sclerosis (pwMS). Instrumented gait analysis provides a plethora of metrics for quantifying concurrent factors contributing to gait deterioration. However, a gait model discriminating underlying features contributing to this deterioration is lacking in pwMS. This study aimed at developing and validating such a model.

METHODS

The gait of 24 healthy controls and 114 pwMS with mild, moderate, or severe disability was measured with inertial sensors on the shanks and lower trunk while walking for 6 minutes along a hospital corridor. Twenty out of thirty-six initially explored metrics computed from the sensor data met the quality criteria for exploratory factor analysis. This analysis provided the sought model, which underwent a confirmatory factor analysis before being used to characterize gait impairment across the three disability groups.

RESULTS

A gait model consisting of five domains (rhythm/variability, pace, asymmetry, and forward and lateral dynamic balance) was revealed by the factor analysis, which was able to highlight gait abnormalities across the disability groups: significant alterations in rhythm/variability-, asymmetry-, and pace-based features were present in the mild group, but these were more profound in the moderate and severe groups. Deterioration in dynamic balance-based features was only noted in pwMS with a moderate and severe disability.

CONCLUSION

A conceptual model of gait for disease-specific mobility assessment in pwMS was successfully developed and tested.

SIGNIFICANCE

The new model, built with metrics that represent gait impairment in pwMS, highlighted clinically relevant changes across different disability levels, including those with no clinically observable walking disability. This shows the clear potential as a monitoring biomarker in pwMS.

Influence of Multiple Sclerosis on Spatiotemporal Gait Parameters: A Systematic Review and Meta-Regression

OBJECTIVE

To quantify the effect of multiple sclerosis (MS) on spatiotemporal gait characteristics accounting for disability severity and fall classification.

DATA SOURCES

MEDLINE (1946-August 2018), Allied and Complementary Medicine Database (1985-2018 August), and PsycINFO (1806-August 2018) were searched for terms on MS and gait.

STUDY SELECTION

Dual independent screening was conducted to identify observational, cross-sectional studies that compared adults with MS grouped according to Expanded Disability Status Scale (EDSS) level or fall history, reported on spatiotemporal gait characteristics, and were published in English. The search retrieved 5891 results, of which 12 studies satisfied the inclusion criteria.

DATA EXTRACTION

Two authors worked independently to extract and verify data on publication details, study methodology, participant characteristics, gait outcomes, conclusions, and limitations. Risk of bias was assessed using the QualSyst critical appraisal tool. A random-effects meta-regression and meta-analysis were conducted on pooled data.

DATA SYNTHESIS

All studies received quality ratings of very good to excellent and collectively examined 1513 individuals with MS. With every 1-point increase in EDSS, significant changes (P<.05) were observed in gait speed (-0.12 m/s; 95% confidence interval (CI), 0.08-0.15), step length (-0.04 m; 95% CI, 0.03-0.05), step time (+0.04 seconds; 95% CI, 0.02-0.06), step time variability (+0.009 seconds; 95% CI, 0.003-0.016), stride time (+0.08 seconds; 95% CI, 0.03-0.12), cadence (-4.4 steps per minute; 95% CI, 2.3-6.4), stance phase duration (+0.8% gait cycle; 95% CI, 0.1-1.5), and double support time (+3.5% gait cycle; 95% CI, 1.5-5.4). Recent fallers exhibited an 18% (95% CI, 13%-23%) reduction in gait speed compared with nonfallers (P<.001).

CONCLUSIONS

This review provides the most accurate reference values to-date that can be used to assess the effectiveness of MS gait training programs and therapeutic techniques for individuals who differ on disability severity and fall classification. Some gait adaptations could be part of adopting a more cautious gait strategy and should be factored into the design of future interventions.

Long-term unsupervised mobility assessment in movement disorders

Mobile health technologies (wearable, portable, body-fixed sensors, or domestic-integrated devices) that quantify mobility in unsupervised, daily living environments are emerging as complementary clinical assessments. Data collected in these ecologically valid, patient-relevant settings can overcome limitations of conventional clinical assessments, as they capture fluctuating and rare events. These data could support clinical decision making and could also serve as outcomes in clinical trials. However, studies that directly compared assessments made in unsupervised and supervised (eg, in the laboratory or hospital) settings point to large disparities, even in the same parameters of mobility. These differences appear to be affected by psychological, physiological, cognitive, environmental, and technical factors, and by the types of mobilities and diagnoses assessed. To facilitate the successful adaptation of the unsupervised assessment of mobility into clinical practice and clinical trials, clinicians and researchers should consider these disparities and the multiple factors that contribute to them.

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.

Temperature sensitivity in multiple sclerosis: An overview of its impact on sensory and cognitive symptoms

Multiple sclerosis (MS) is an autoimmune neurodegenerative disease characterized by demyelination of the central nervous system (CNS). The exact cause of MS is still unknown; yet its incidence and prevalence rates are growing worldwide, making MS a significant public health challenge. The heterogeneous distribution of demyelination within and between MS patients translates in a complex and varied array of autonomic, motor, sensory and cognitive symptoms. Yet a unique aspect of MS is the highly prevalent (60-80%) temperature sensitivity of its sufferers, where neurological symptoms are temporarily exacerbated by environmental- or exercise-induced increases (or decreases) in body temperature. MS temperature sensitivity is primarily driven by temperature-dependent slowing or blocking of neural conduction within the CNS due to changes in internal (core) temperature; yet changes in skin temperature could also contribute to symptom exacerbation (e.g. during sunlight and warm ambient exposure). The impact of temperature sensitivity, and particularly of increases in core temperature, on autonomic (e.g. thermoregulatory/cardiovascular function) and motor symptoms (e.g. fatigue) is well described. However, less attention has been given to how increases (and decreases) in core and skin temperature affect sensory and cognitive symptoms. Furthermore, it remains uncertain whether changes in skin temperature alone could also trigger worsening of symptoms. Here we review the impact of temperature sensitivity on MS sensory and cognitive function and discuss additional factors (e.g. changes in skin temperature) that potentially contribute to temperature-induced worsening of symptoms in the absence of alteration in core temperature.

Do spatiotemporal parameters and gait variability differ across the lifespan of healthy adults? A systematic review

BACKGROUND

Aging is often associated with changes in the musculoskeletal system, peripheral and central nervous system. These age-related changes often result in mobility problems influencing gait performance. Compensatory strategies are used as a way to adapt to these physiological changes.

RESEARCH QUESTION

The aim of this review is to investigate the differences in spatiotemporal and gait variability measures throughout the healthy adult life.

METHODS

This systematic review was conducted according to the PRISMA guidelines and registered in the PROSPERO database (no. CRD42017057720). Databases MEDLINE (Pubmed), Web of Science (Web of Knowledge), Cochrane Library and ScienceDirect were systematically searched until March 2018.

RESULTS

Eighteen of the 3195 original studies met the eligibility criteria and were included in this review. The majority of studies reported spatiotemporal and gait variability measures in adults above the age of 65, followed by the young adult population, information of middle-aged adults is lacking. Spatiotemporal parameters and gait variability measures were extracted from 2112 healthy adults between 18 and 98 years old and, in general, tend to deteriorate with increasing age. Variability measures were only reported in an elderly population and show great variety between studies.

SIGNIFICANCE

The findings of this review suggest that most spatiotemporal parameters significantly differ across different age groups. Elderly populations show a reduction of preferred walking speed, cadence, step and stride length, all related to a more cautious gait, while gait variability measures remain stable over time. A preliminary framework of normative reference data is provided, enabling insights into the influence of aging on spatiotemporal parameters, however spatiotemporal parameters of middle-aged adults should be investigated more thoroughly.

Effects of cognitive versus motor dual-task on spatiotemporal gait parameters in healthy controls and multiple sclerosis patients with and without fall history

BACKGROUND

The purpose of the current study was to compare the effects of cognitive or motor tasks on gait performance between healthy controls and multiple sclerosis (MS) patients with and without fall history.

METHODS

The investigation included MS patients with fall history (n = 25) and without fall history (n = 25) and matched healthy controls (n = 25). Participants walked at their preferred speed on a motorized treadmill under three walking conditions in a randomized order: walking only, walking while performing a concurrent cognitive task (counting backward aloud by 3s), and walking while performing a concurrent motor task (carrying a tray with glasses).

RESULTS

The findings showed that in patients with MS, regardless of fall history, spatiotemporal gait parameters were different compared to healthy controls. In contrast to average gait parameters, variability in stride length and stride time could discriminate between MS fallers and non-fallers. Simultaneous performance of cognitive task and walking resulted in higher dual-task costs (DTC) in gait performance compared to the motor dual-task. However, the pattern of change was not different among the three groups. All participants responded to the cognitive task challenges by increasing stride length and decreasing cadence and stride length variability while maintaining cognitive task performance.

CONCLUSIONS

The findings may reflect successful adaptation of locomotor system to preserve cognitive task performance under cognitive dual-task condition. Future studies should examine more complex concurrent cognitive and motor tasks to better understand the dual-task-related gait changes and their contribution to falls in patients with MS.