Gait Analysis for Poststroke Rehabilitation

Inertial Sensor Gait Analysis of Trendelenburg Gait in Patients Who Have Hip Osteoarthritis

BACKGROUND

Gait abnormalities such as Trendelenburg gait (TG) in patients who have hip osteoarthritis (OA) have traditionally been evaluated using clinicians' visual assessment. Recent advances in portable inertial gait sensors offer more sensitive, quantitative methods for gait assessment in clinical settings. This study sought to compare sensor-derived metrics in a cohort of hip OA patients when stratified by clinical TG severity.

METHODS

There were 42 patients who had hip OA and were grouped by TG severity (mild, moderate, and severe) through visual assessment by a single arthroplasty surgeon who had > 30 years of experience. After informed consent, wireless inertial sensors placed at the midpoint of the intercristal line collected gait parameters including pelvic shift, support time, toe-off symmetry, impact, and cadence. Clinical data on hip strength, range of motion, and Kellgren-Lawrence grade were collected.

RESULTS

Worsening TG severity had a higher mean Kellgren-Lawrence grade (2.5 versus 3.2 versus 3.4; P = .014) and reduced passive hip abduction (P = .004). Severe TG group demonstrated predominantly contralateral pelvic shift (n = 9 of 10, 90.0%), while ipsilateral shift was more frequently detected in moderate (n = 10 of 18, 55.6%) and mild groups (n = 9 of 14, 64.3%; P = .021). Contralateral single support time bias was greatest in severe TG (35.7% versus 50.0 versus 90.0%; P = .027). Asymmetric toe-off, impact, and support times were observed in all groups.

CONCLUSIONS

Traditional understanding of TG is that truncal shift occurs to the ipsilateral side. Using sensor-based measurements, the present study demonstrates a shift of the weight-bearing axis toward the contralateral side with increasing TG severity, which has not been previously described. Inertial sensors are feasible, quantitative gait measuring tools, and may reveal subtle patterns not readily discernible by traditional methods.

AI in evaluating ambulation of stroke patients: severity classification with video and functional ambulation category scale

BACKGROUND

The evaluation of gait function and severity classification of stroke patients are important to determine the rehabilitation goal and the level of exercise. Physicians often qualitatively evaluate patients' walking ability through visual gait analysis using naked eye, video images, or standardized assessment tools. Gait evaluation through observation relies on the doctor's empirical judgment, potentially introducing subjective opinions. Therefore, conducting research to establish a basis for more objective judgment is crucial.

OBJECTIVE

To verify a deep learning model that classifies gait image data of stroke patients according to Functional Ambulation Category (FAC) scale.

METHODS

Gait vision data from 203 stroke patients and 182 healthy individuals recruited from six medical institutions were collected to train a deep learning model for classifying gait severity in stroke patients. The recorded videos were processed using OpenPose. The dataset was randomly split into 80% for training and 20% for testing.

RESULTS

The deep learning model attained a training accuracy of 0.981 and test accuracy of 0.903. Area Under the Curve(AUC) values of 0.93, 0.95, and 0.96 for discriminating among the mild, moderate, and severe stroke groups, respectively.

CONCLUSION

This confirms the potential of utilizing human posture estimation based on vision data not only to develop gait parameter models but also to develop models to classify severity according to the FAC criteria used by physicians. To develop an AI-based severity classification model, a large amount and variety of data is necessary and data collected in non-standardized real environments, not in laboratories, can also be used meaningfully.

The Reliability and Validity of the OneStep Smartphone Application for Gait Analysis among Patients Undergoing Rehabilitation for Unilateral Lower Limb Disability

An easy-to-use and reliable tool is essential for gait assessment of people with gait pathologies. This study aimed to assess the reliability and validity of the OneStep smartphone application compared to the C-Mill-VR+ treadmill (Motek, Nederlands), among patients undergoing rehabilitation for unilateral lower extremity disability. Spatiotemporal gait parameters were extracted from the treadmill and from two smartphones, one on each leg. Inter-device reliability was evaluated using Pearson correlation, intra-cluster correlation coefficient (ICC), and Cohen's d, comparing the application's readings from the two phones. Validity was assessed by comparing readings from each phone to the treadmill. Twenty-eight patients completed the study; the median age was 45.5 years, and 61% were males. The ICC between the phones showed a high correlation (r = 0.89-1) and good-to-excellent reliability (ICC range, 0.77-1) for all the gait parameters examined. The correlations between the phones and the treadmill were mostly above 0.8. The ICC between each phone and the treadmill demonstrated moderate-to-excellent validity for all the gait parameters (range, 0.58-1). Only 'step length of the impaired leg' showed poor-to-good validity (range, 0.37-0.84). Cohen's d effect size was small (d < 0.5) for all the parameters. The studied application demonstrated good reliability and validity for spatiotemporal gait assessment in patients with unilateral lower limb disability.

Biomechanical Analysis of Human Gait When Changing Velocity and Carried Loads: Simulation Study with OpenSim

Walking is one of the main activities of daily life and gait analysis can provide crucial data for the computation of biomechanics in many fields. In multiple applications, having reference data that include a variety of gait conditions could be useful for assessing walking performance. However, limited extensive reference data are available as many conditions cannot be easily tested experimentally. For this reason, a musculoskeletal model in OpenSim coupled with gait data (at seven different velocities) was used to simulate seven carried loads and all the combinations between the two parameters. The effects on lower limb biomechanics were measured with torque, power, and mechanical work. The results demonstrated that biomechanics was influenced by both speed and load. Our results expand the previous literature: in the majority of previous work, only a subset of the presented conditions was investigated. Moreover, our simulation approach provides comprehensive data that could be useful for applications in many areas, such as rehabilitation, orthopedics, medical care, and sports.

Biochemical, biomechanical and imaging biomarkers of ischemic stroke: Time for integrative thinking

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Measuring highly accurate foot position and angle trajectories with foot-mounted IMUs in clinical practice

BACKGROUND

Gait analysis using foot-mounted IMUs is a promising method to acquire gait parameters outside of laboratory settings and in everyday clinical practice. However, the need for precise sensor attachment or calibration, the requirement of environments with a homogeneous magnetic field, and the limited applicability to pathological gait patterns still pose challenges. Furthermore, in previously published work, the measurement accuracy of such systems is often only validated for specific points in time or in a single plane.

RESEARCH QUESTION

This study investigates the measurement accuracy of a gait analysis method based on foot-mounted IMUs in the acquisition of the foot motion, i.e., position and angle trajectories of the foot in the sagittal, frontal, and transversal plane over the entire gait cycle.

RESULTS

A comparison of the proposed method with an optical motion capture system showed an average RMSE of 0.67° for pitch, 0.63° for roll and 1.17° for yaw. For position trajectories, an average RMSE of 0.51 cm for vertical lift and 0.34 cm for lateral shift was found. The measurement error of the IMU-based method is found to be much smaller than the deviations caused by the shoes.

SIGNIFICANCE

The proposed method is found to be sufficiently accurate for clinical practice. It does not require precise mounting, special calibration movements, or magnetometer data, and shows no difference in measurement accuracy between normal and pathological gait. Therefore, it provides an easy-to-use alternative to optical motion capture and facilitates gait analysis independent of laboratory settings.

Interlimb Coordination during Double Support Phase of Gait in People with and without Stroke

This study aims to identify differences between participants with and without stroke regarding the ipsilesional and contralesional lower limbs kinematics, kinetics, muscle activity and their variability during double support phase of gait. Eleven post-stroke and thirteen healthy participants performed 10 gait trials at a self-selected speed while being monitored by an optoelectronic motion capture system, two force plates and an electromyographic system. The following outcomes were evaluated during the double support: the time and the joint position; the external mechanical work on the centre of mass; and the relative electromyographic activity. Both, contralesional/ipsilesional and dominant/non-dominant of participants with and without stroke, respectively, were evaluated during double support phase of gait in trailing or leading positions. The average value of each parameter and the coefficient of variation of the 10 trials were analysed. Post-stroke participants present bilateral decreased mechanical work on the centre of mass and increased variability, decreased contralesional knee and ankle flexion in trailing position, increased ipsilesional knee flexion in leading position and increased variability. Increased relative muscle activity was observed in post-stroke participants with decreased variability. Mechanical work on the centre of mass seems to be the most relevant parameter to identify interlimb coordination impairments in post-stroke subjects.

Gait pattern after electromechanically-assisted gait training with the Hybrid Assistive Limb and conventional gait training in sub-acute stroke rehabilitation-A subsample from a randomized controlled trial

Introduction

Electromechanically-assisted gait training has been introduced in stroke rehabilitation as a means to enable gait training with a large number of reproducible and symmetrical task repetitions, i.e. steps. However, few studies have evaluated its impact on gait pattern functions. This study includes persons with no independent ambulation function at the start of a 4-week neurorehabilitation period in the sub-acute phase after stroke. The primary aim of the study was to evaluate whether the addition of electromechanically-assisted gait training to conventional training resulted in better gait pattern function than conventional training alone. The secondary aim was to identify correlations between overall gait quality and standardized clinical assessments.

Participants and methods

Seventeen patients with no independent ambulation function who participated in a Prospective Randomized Open Blinded End-point study in the sub-acute phase after stroke were randomized into two groups; one group (n = 7) to undergo conventional training only (CONV group) and the other group (n = 10) to undergo conventional training with additional electromechanically-assisted gait training (HAL group). All patients were assessed with 3D gait analysis and clinical assessments after the 4-week intervention period. Overall gait quality as per the Gait Profile Score (GPS), as well as kinematic, and kinetic and other spatiotemporal metrics were collected and compared between intervention groups. Correlations between biomechanical and clinical outcomes were evaluated.

Results

Both the CONV and HAL groups exhibited similar gait patterns with no significant differences between groups in any kinematic, kinetic parameters or other spatiotemporal metrics. The GPS for the paretic limb had a median (IQR) of 12.9° (7.8°) and 13.4° (4.3°) for the CONV and HAL groups, respectively (p = 0.887). Overall gait quality was correlated with independence in walking, walking speed, movement function and balance. We found no added benefit in gait pattern function from the electromechanically-assisted gait training compared to the conventional training alone.

Discussion

This finding raises new questions about how to best design effective and optimal post-stroke rehabilitation programs in patients with moderate to severe gait impairments to achieve both independent walking and optimal gait pattern function, and about which patients should be in focus in further studies on the efficacy of electromechanically-assisted gait training.

Clinical trial registration

The study was retrospectively registered at ClinicalTrials.gov, identifier (NCT02410915) on April 2015.

Adaptive Control Method for Gait Detection and Classification Devices with Inertial Measurement Unit

Cueing and feedback training can be effective in maintaining or improving gait in individuals with Parkinson's disease. We previously designed a rehabilitation assist device that can detect and classify a user's gait at only the swing phase of the gait cycle, for the ease of data processing. In this study, we analyzed the impact of various factors in a gait detection algorithm on the gait detection and classification rate (GDCR). We collected acceleration and angular velocity data from 25 participants (1 male and 24 females with an average age of 62 ± 6 years) using our device and analyzed the data using statistical methods. Based on these results, we developed an adaptive GDCR control algorithm using several equations and functions. We tested the algorithm under various virtual exercise scenarios using two control methods, based on acceleration and angular velocity, and found that the acceleration threshold was more effective in controlling the GDCR (average Spearman correlation -0.9996, p < 0.001) than the gyroscopic threshold. Our adaptive control algorithm was more effective in maintaining the target GDCR than the other algorithms (p < 0.001) with an average error of 0.10, while other tested methods showed average errors of 0.16 and 0.28. This algorithm has good scalability and can be adapted for future gait detection and classification applications.

Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review

Exoskeletons are a promising tool to support individuals with a decreased level of motor performance. Due to their built-in sensors, exoskeletons offer the possibility of continuously recording and assessing user data, for example, related to motor performance. The aim of this article is to provide an overview of studies that rely on using exoskeletons to measure motor performance. Therefore, we conducted a systematic literature review, following the PRISMA Statement guidelines. A total of 49 studies using lower limb exoskeletons for the assessment of human motor performance were included. Of these, 19 studies were validity studies, and six were reliability studies. We found 33 different exoskeletons; seven can be considered stationary, and 26 were mobile exoskeletons. The majority of the studies measured parameters such as range of motion, muscle strength, gait parameters, spasticity, and proprioception. We conclude that exoskeletons can be used to measure a wide range of motor performance parameters through built-in sensors, and seem to be more objective and specific than manual test procedures. However, since these parameters are usually estimated from built-in sensor data, the quality and specificity of an exoskeleton to assess certain motor performance parameters must be examined before an exoskeleton can be used, for example, in a research or clinical setting.

Repeatability and Temporal Consistency of Lower Limb Biomechanical Variables Expressing Interlimb Coordination during the Double-Support Phase in People with and without Stroke Sequelae

Reliable biomechanical methods to assess interlimb coordination during the double-support phase in post-stroke subjects are needed for assessing movement dysfunction and related variability. The data obtained could provide a significant contribution for designing rehabilitation programs and for their monitorisation. The present study aimed to determine the minimum number of gait cycles needed to obtain adequate values of repeatability and temporal consistency of lower limb kinematic, kinetic, and electromyographic parameters during the double support of walking in people with and without stroke sequelae. Eleven post-stroke and thirteen healthy participants performed 20 gait trials at self-selected speed in two separate moments with an interval between 72 h and 7 days. The joint position, the external mechanical work on the centre of mass, and the surface electromyographic activity of the tibialis anterior, soleus, gastrocnemius medialis, rectus femoris, vastus medialis, biceps femoris, and gluteus maximus muscles were extracted for analysis. Both the contralesional and ipsilesional and dominant and non-dominant limbs of participants with and without stroke sequelae, respectively, were evaluated either in trailing or leading positions. The intraclass correlation coefficient was used for assessing intra-session and inter-session consistency analysis. For most of the kinematic and the kinetic variables studied in each session, two to three trials were required for both groups, limbs, and positions. The electromyographic variables presented higher variability, requiring, therefore, a number of trials ranging from 2 to >10. Globally, the number of trials required inter-session ranged from 1 to >10 for kinematic, from 1 to 9 for kinetic, and 1 to >10 for electromyographic variables. Thus, for the double support analysis, three gait trials were required in order to assess the kinematic and kinetic variables in cross-sectional studies, while for longitudinal studies, a higher number of trials (>10) were required for kinematic, kinetic, and electromyographic variables.

Present and future of gait assessment in clinical practice: Towards the application of novel trends and technologies

Background

Despite being available for more than three decades, quantitative gait analysis remains largely associated with research institutions and not well leveraged in clinical settings. This is mostly due to the high cost/cumbersome equipment and complex protocols and data management/analysis associated with traditional gait labs, as well as the diverse training/experience and preference of clinical teams. Observational gait and qualitative scales continue to be predominantly used in clinics despite evidence of less efficacy of quantifying gait.

Research objective

This study provides a scoping review of the status of clinical gait assessment, including shedding light on common gait pathologies, clinical parameters, indices, and scales. We also highlight novel state-of-the-art gait characterization and analysis approaches and the integration of commercially available wearable tools and technology and AI-driven computational platforms.

Methods

A comprehensive literature search was conducted within PubMed, Web of Science, Medline, and ScienceDirect for all articles published until December 2021 using a set of keywords, including normal and pathological gait, gait parameters, gait assessment, gait analysis, wearable systems, inertial measurement units, accelerometer, gyroscope, magnetometer, insole sensors, electromyography sensors. Original articles that met the selection criteria were included.

Results and significance

Clinical gait analysis remains highly observational and is hence subjective and largely influenced by the observer's background and experience. Quantitative Instrumented gait analysis (IGA) has the capability of providing clinicians with accurate and reliable gait data for diagnosis and monitoring but is limited in clinical applicability mainly due to logistics. Rapidly emerging smart wearable technology, multi-modality, and sensor fusion approaches, as well as AI-driven computational platforms are increasingly commanding greater attention in gait assessment. These tools promise a paradigm shift in the quantification of gait in the clinic and beyond. On the other hand, standardization of clinical protocols and ensuring their feasibility to map the complex features of human gait and represent them meaningfully remain critical challenges.

Core Sets of Kinematic Variables to Consider for Evaluation of Gait Post-stroke

Background

Instrumented gait analysis post-stroke is becoming increasingly more common in research and clinics. Although overall standardized procedures are proposed, an almost infinite number of potential variables for kinematic analysis is generated and there remains a lack of consensus regarding which are the most important for sufficient evaluation. The current aim was to identify a discriminative core set of kinematic variables for gait post-stroke.

Methods

We applied a three-step process of statistical analysis on commonly used kinematic gait variables comprising the whole body, derived from 3D motion data on 31 persons post-stroke and 41 non-disabled controls. The process of identifying relevant core sets involved: (1) exclusion of variables for which there were no significant group differences; (2) systematic investigation of one, or combinations of either two, three, or four significant variables whereby each core set was evaluated using a leave-one-out cross-validation combined with logistic regression to estimate a misclassification rate (MR).

Results

The best MR for one single variable was shown for the Duration of single-support (MR 0.10) or Duration of 2nd double-support (MR 0.11) phase, corresponding to an 89–90% probability of correctly classifying a person as post-stroke/control. Adding Pelvis sagittal ROM to either of the variables Self-selected gait speed or Stride length, alternatively adding Ankle sagittal ROM to the Duration of single-stance phase, increased the probability of correctly classifying individuals to 93–94% (MR 0.06). Combining three variables decreased the MR further to 0.04, suggesting a probability of 96% for correct classification. These core sets contained: (1) a spatial (Stride/Step length) or a temporal variable (Self-selected gait speed/Stance time/Swing time or Duration of 2nd double-support), (2) Pelvis sagittal ROM or Ankle plantarflexion during push-off, and (3) Arm Posture Score or Cadence or a knee/shoulder joint angle variable. Adding a fourth variable did not further improve the MR.

Conclusion

A core set combining a few crucial kinematic variables may sufficiently evaluate post-stroke gait and should receive more attention in rehabilitation. Our results may contribute toward a consensus on gait evaluation post-stroke, which could substantially facilitate future diagnosis and monitoring of rehabilitation progress.

The gait profile score characterises walking performance impairments in young stroke survivors

BACKGROUND

The Gait Profile Score (GPS) provides a composite measure of the quality of joint movement during walking, but the relationship between this measure and metabolic cost, temporal (e.g. walking speed) and spatial (e.g. stride length) parameters in stroke survivors has not been reported.

RESEARCH QUESTION

The aims of this study were to compare the GPS (paretic, non-paretic, and overall score) of young stroke survivors to the healthy able-bodied control and determine the relationship between the GPS and metabolic cost, temporal (walking speed, stance time asymmetry) and spatial (stride length, stride width, step length asymmetry) parameters in young stroke survivors to understand whether the quality of walking affects walking performance in stroke survivors.

METHODS

Thirty-nine young stroke survivors aged between 18 and 65years and 15 healthy age-matched able-bodied controls were recruited from six hospital sites in Wales, UK. Joint range of motion at the pelvis, hip, knee and ankle, and temporal and spatial parameters were measured during walking on level ground at self-selected speed with calculation of the Gait Variable Score and then the GPS.

RESULTS

GPS for the paretic leg (9.40° (8.60-10.21) p < 0.001), non-paretic leg (11.42° (10.20-12.63) p < 0.001) and overall score (11.18° (10.26-12.09) p < 0.001)) for stroke survivors were significantly higher than the control (4.25° (3.40-5.10), 5.92° (5.11 (6.73)). All parameters with the exception of step length symmetry ratio correlated moderate to highly with the GPS for the paretic, non-paretic, and/or overall score (ρ = <-0.732 (p < 0.001)).

SIGNIFICANCE

The quality of joint movement during walking measured via the GPS is directly related to the speed and efficiency of walking, temporal (stance time symmetry) and spatial (stride length, stride width) parameters in young stroke survivors.

Optimized hip-knee-ankle exoskeleton assistance at a range of walking speeds

BACKGROUND

Autonomous exoskeletons will need to be useful at a variety of walking speeds, but it is unclear how optimal hip-knee-ankle exoskeleton assistance should change with speed. Biological joint moments tend to increase with speed, and in some cases, optimized ankle exoskeleton torques follow a similar trend. Ideal hip-knee-ankle exoskeleton torque may also increase with speed. The purpose of this study was to characterize the relationship between walking speed, optimal hip-knee-ankle exoskeleton assistance, and the benefits to metabolic energy cost.

METHODS

We optimized hip-knee-ankle exoskeleton assistance to reduce metabolic cost for three able-bodied participants walking at 1.0 m/s, 1.25 m/s and 1.5 m/s. We measured metabolic cost, muscle activity, exoskeleton assistance and kinematics. We performed Friedman's tests to analyze trends across walking speeds and paired t-tests to determine if changes from the unassisted conditions to the assisted conditions were significant.

RESULTS

Exoskeleton assistance reduced the metabolic cost of walking compared to wearing the exoskeleton with no torque applied by 26%, 47% and 50% at 1.0, 1.25 and 1.5 m/s, respectively. For all three participants, optimized exoskeleton ankle torque was the smallest for slow walking, while hip and knee torque changed slightly with speed in ways that varied across participants. Total applied positive power increased with speed for all three participants, largely due to increased joint velocities, which consistently increased with speed.

CONCLUSIONS

Exoskeleton assistance is effective at a range of speeds and is most effective at medium and fast walking speeds. Exoskeleton assistance was less effective for slow walking, which may explain the limited success in reducing metabolic cost for patient populations through exoskeleton assistance. Exoskeleton designers may have more success when targeting activities and groups with faster walking speeds. Speed-related changes in optimized exoskeleton assistance varied by participant, indicating either the benefit of participant-specific tuning or that a wide variety of torque profiles are similarly effective.

Establishing the Minimal Clinically Important Differences for Sagittal Hip Range of Motion in Chronic Stroke Patients

Many researchers have pointed out that decreased sagittal range of motion (ROM) in the affected hip joint is a common consequence of stroke, and it adversely affects walking performance and walking speed. Nevertheless, the minimal clinically important differences (MCID) in hip-related kinematic gait parameters post-stroke have not yet been determined. The present study aimed to define MCID values for hip ROM in the sagittal plane i.e., flexion-extension (FE), for the affected and unaffected sides at a chronic stage post-stroke. Fifty participants with hemiparesis due to stroke were enrolled for the study. Four statistical methods were used to calculate MCID. According to the anchor-based approach, the mean change in hip FE ROM achieved by the MCID group on the affected/unaffected side amounted to 5.81°/2.86° (the first MCID estimate). The distribution-based analyses established that the standard error of measurement in the no-change group amounted to 1.56°/1.04° (the second MCID estimate). Measurements based on the third method established that a change of 4.09°/0.61° in the hip ROM corresponded to a 1.85-point change in the Barthel Index. The optimum cutoff value, based on ROC curve analysis, corresponded to 2.9/2.6° of change in the hip sagittal ROM for the affected/unaffected side (the fourth MCID estimate). To our knowledge, this is the first study to use a comprehensive set of statistical methods to determine the MCID for hip sagittal ROM for the affected and unaffected sides at a chronic stage post-stroke. According to our findings, the MCID of the hip FE ROM for the affected side amounts to 5.81° and for the unaffected side to 2.86°, in patients with chronic stroke. This indicator is extremely important because it allows clinical practitioners to assess the effects of interventions administered to patients, and to interpret the significance of improvements in sagittal kinematic parameters of the hip; ultimately, it may facilitate the process of designing effective gait reeducation programs.

Validity Analysis of WalkerViewTM Instrumented Treadmill for Measuring Spatiotemporal and Kinematic Gait Parameters

The detection of gait abnormalities is essential for professionals involved in the rehabilitation of walking disorders. Instrumented treadmills are spreading as an alternative to overground gait analysis. To date, the use of these instruments for recording kinematic gait parameters is still limited in clinical practice due to the lack of validation studies. This study aims to investigate the performance of a multi-sensor instrumented treadmill (i.e., WalkerView^TM, WV) for performing gait analysis. Seventeen participants performed a single gait test on the WV at three different speeds (i.e., 3 km/h, 5 km/h, and 6.6 km/h). In each trial, spatiotemporal and kinematic parameters were recorded simultaneously by the WV and by a motion capture system used as the reference. Intraclass correlation coefficient (ICC) of spatiotemporal parameters showed fair to excellent agreement at the three walking speeds for steps time, cadence, and step length (range 0.502–0.996); weaker levels of agreement were found for stance and swing time at all the tested walking speeds. Bland–Altman analysis of spatiotemporal parameters showed a mean of difference (MOD) maximum value of 0.04 s for swing/stance time and WV underestimation of 2.16 cm for step length. As for kinematic variables, ICC showed fair to excellent agreement (ICC > 0.5) for total range of motion (ROM) of hip at 3 km/h (range 0.579–0.735); weaker levels of ICC were found at 5 km/h and 6.6 km/h (range 0.219–0.447). ICC values of total knee ROM showed poor levels of agreement at all the tested walking speeds. Bland–Altman analysis of hip ROM revealed a higher MOD value at higher speeds up to 3.91°; the MOD values of the knee ROM were always higher than 7.67° with a 60° mean value of ROM. We demonstrated that the WV is a valid tool for analyzing the spatiotemporal parameters of walking and assessing the hip’s total ROM. Knee total ROM and all kinematic peak values should be carefully evaluated, having shown lower levels of agreement.

Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis

Background: Gait dysfunction or impairment is considered one of the most common and devastating physiological consequences of stroke, and achieving optimal gait is a key goal for stroke victims with gait disability along with their clinical teams. Many researchers have explored post stroke gait, including assessment tools and techniques, key gait parameters and significance on functional recovery, as well as data mining, modeling and analyses methods.

Research Question: This study aimed to review and summarize research efforts applicable to quantification and analyses of post-stroke gait with focus on recent technology-driven gait characterization and analysis approaches, including the integration of smart low cost wearables and Artificial Intelligence (AI), as well as feasibility and potential value in clinical settings.

Methods: A comprehensive literature search was conducted within Google Scholar, PubMed, and ScienceDirect using a set of keywords, including lower extremity, walking, post-stroke, and kinematics. Original articles that met the selection criteria were included.

Results and Significance: This scoping review aimed to shed light on tools and technologies employed in post stroke gait assessment toward bridging the existing gap between the research and clinical communities. Conventional qualitative gait analysis, typically used in clinics is mainly based on observational gait and is hence subjective and largely impacted by the observer's experience. Quantitative gait analysis, however, provides measured parameters, with good accuracy and repeatability for the diagnosis and comparative assessment throughout rehabilitation. Rapidly emerging smart wearable technology and AI, including Machine Learning, Support Vector Machine, and Neural Network approaches, are increasingly commanding greater attention in gait research. Although their use in clinical settings are not yet well leveraged, these tools promise a paradigm shift in stroke gait quantification, as they provide means for acquiring, storing and analyzing multifactorial complex gait data, while capturing its non-linear dynamic variability and offering the invaluable benefits of predictive analytics.

Evaluation of Physical Interaction during Walker-Assisted Gait with the AGoRA Walker: Strategies Based on Virtual Mechanical Stiffness

Smart walkers are commonly used as potential gait assistance devices, to provide physical and cognitive assistance within rehabilitation and clinical scenarios. To understand such rehabilitation processes, several biomechanical studies have been conducted to assess human gait with passive and active walkers. Several sessions were conducted with 11 healthy volunteers to assess three interaction strategies based on passive, low and high mechanical stiffness values on the AGoRA Smart Walker. The trials were carried out in a motion analysis laboratory. Kinematic data were also collected from the smart walker sensory interface. The interaction force between users and the device was recorded. The force required under passive and low stiffness modes was 56.66% and 67.48% smaller than the high stiffness mode, respectively. An increase of 17.03% for the hip range of motion, as well as the highest trunk’s inclination, were obtained under the resistive mode, suggesting a compensating motion to exert a higher impulse force on the device. Kinematic and physical interaction data suggested that the high stiffness mode significantly affected the users’ gait pattern. Results suggested that users compensated their kinematics, tilting their trunk and lower limbs to exert higher impulse forces on the device.

Effect of robotic-assisted gait training on objective biomechanical measures of gait in persons post-stroke: a systematic review and meta-analysis

BACKGROUND

Robotic-Assisted Gait Training (RAGT) may enable high-intensive and task-specific gait training post-stroke. The effect of RAGT on gait movement patterns has however not been comprehensively reviewed. The purpose of this review was to summarize the evidence for potentially superior effects of RAGT on biomechanical measures of gait post-stroke when compared with non-robotic gait training alone.

METHODS

Nine databases were searched using database-specific search terms from their inception until January 2021. We included randomized controlled trials investigating the effects of RAGT (e.g., using exoskeletons or end-effectors) on spatiotemporal, kinematic and kinetic parameters among adults suffering from any stage of stroke. Screening, data extraction and judgement of risk of bias (using the Cochrane Risk of bias 2 tool) were performed by 2-3 independent reviewers. The Grading of Recommendations Assessment Development and Evaluation (GRADE) criteria were used to evaluate the certainty of evidence for the biomechanical gait measures of interest.

RESULTS

Thirteen studies including a total of 412 individuals (mean age: 52-69 years; 264 males) met eligibility criteria and were included. RAGT was employed either as monotherapy or in combination with other therapies in a subacute or chronic phase post-stroke. The included studies showed a high risk of bias (n = 6), some concerns (n = 6) or a low risk of bias (n = 1). Meta-analyses using a random-effects model for gait speed, cadence, step length (non-affected side) and spatial asymmetry revealed no significant differences between the RAGT and comparator groups, while stride length (mean difference [MD] 2.86 cm), step length (affected side; MD 2.67 cm) and temporal asymmetry calculated in ratio-values (MD 0.09) improved slightly more in the RAGT groups. There were serious weaknesses with almost all GRADE domains (risk of bias, consistency, directness, or precision of the findings) for the included outcome measures (spatiotemporal and kinematic gait parameters). Kinetic parameters were not reported at all.

CONCLUSION

There were few relevant studies and the review synthesis revealed a very low certainty in current evidence for employing RAGT to improve gait biomechanics post-stroke. Further high-quality, robust clinical trials on RAGT that complement clinical data with biomechanical data are thus warranted to disentangle the potential effects of such interventions on gait biomechanics post-stroke.

Biofeedback for Post-stroke Gait Retraining: A Review of Current Evidence and Future Research Directions in the Context of Emerging Technologies

Real-time gait biofeedback is a promising rehabilitation strategy for improving biomechanical deficits in walking patterns of post-stroke individuals. Because wearable sensor technologies are creating avenues for novel applications of gait biofeedback, including use in tele-health, there is a need to evaluate the state of the current evidence regarding the effectiveness of biofeedback for post-stroke gait training. The objectives of this review are to: (1) evaluate the current state of biofeedback literature pertaining to post-stroke gait training; and (2) determine future research directions related to gait biofeedback in context of evolving technologies. Our overall goal was to determine whether gait biofeedback is effective at improving stroke gait deficits while also probing why and for whom gait biofeedback may be an efficacious treatment modality. Our literature review showed that the effects of gait biofeedback on post-stroke walking dysfunction are promising but are inconsistent in methodology and therefore results. We summarize sources of methodological heterogeneity in previous literature, such as inconsistencies in feedback target, feedback mode, dosage, practice structure, feedback structure, and patient characteristics. There is a need for larger-sample studies that directly compare different feedback parameters, employ more uniform experimental designs, and evaluate characteristics of potential responders. However, as these uncertainties in existing literature are resolved, the application of gait biofeedback has potential to extend neurorehabilitation clinicians' cues to individuals with post-stroke gait deficits during ambulation in clinical, home, and community settings, thereby increasing the quantity and quality of skilled repetitions during task-oriented stepping training. In addition to identifying gaps in previous research, we posit that future research directions should comprise an amalgam of mechanism-focused and clinical research studies, to develop evidence-informed decision-making guidelines for gait biofeedback strategies that are tailored to individual-specific gait and sensorimotor impairments. Wearable sensor technologies have the potential to transform gait biofeedback and provide greater access and wider array of options for clinicians while lowering rehabilitation costs. Novel sensing technologies will be particularly valuable for telehealth and home-based stepping exercise programs. In summary, gait biofeedback is a promising intervention strategy that can enhance efficacy of post-stroke gait rehabilitation in both clinical and tele-rehabilitation settings and warrants more in-depth research.

Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration

Motor deficits are observed in Alzheimer's disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans.

[Kinematic parameters of gait in patients with supra- or subtentorial focus location during the early rehabilitation period after ischemic stroke]

OBJECTIVE

To study kinematic gait parameters during early rehabilitation period in patients with supra- or subtentorial ischemic stroke (IS).

MATERIAL AND METHODS

We examined 24 patients (11 women, 13 men, age 61.3±8.2) 4-6 weeks after stroke onset. 15 patients had supratentorial IS (middle cerebral artery location), 9 patients had subtentorial IS (brainstem and cerebellum). NIHSS score was 6.4±0.6/6.1±0.8, modified Ashwort scale score - 0.5±0.6/0.4±0.7, hand paresis - 3.4±0.9/3.7±0.7, leg paresis - 4.1±0.7/4.0±0.8 points. Kinematic gait parameters were recorded on video analysis system Physiomed Smart (Physiomed, Germany, Davis protocol).

RESULTS

Gait kinematic parameters in paretic and in unaffected leg were changed in both groups. Patients with supratentorial lesion had on paretic side exaggerated pelvic obliquity, an excessive internal rotation and amplitude of movements in the paretic hip joint, and an insufficient plantar extension on both sides. Patients with subtentorial stroke had exaggerated pelvic tilt forward, excessive flexion and insufficient extension of the hip joint, insufficient extension of the knee joint, excessive plantar flexion, and insufficient plantar extension on both sides.

CONCLUSION

Patients with supra- or subtentorial IS with muscle weakness less than 3-4 points and slightly changed or normal muscle tone differed in kinematic parameters in pelvic motions and in joints of paretic and unaffected lower extremity. These results highlight the importance of differentiating rehabilitation techniques according to supra- or subtentorial focus location and cerebellar involvement.

Gait analysis in neurological populations: Progression in the use of wearables

Gait assessment is an essential tool for clinical applications not only to diagnose different neurological conditions but also to monitor disease progression as it contributes to the understanding of underlying deficits. There are established methods and models for data collection and interpretation of gait assessment within different pathologies. This narrative review aims to depict the evolution of gait assessment from observation and rating scales to wearable sensors and laboratory technologies and provide limitations and possible future directions in the field of gait assessment. In this context, we first present an extensive review of current clinical outcomes and gait models. Then, we demonstrate commercially available wearable technologies with their technical capabilities along with their use in gait assessment studies for various neurological conditions. In the next sections, a descriptive knowledge for existing inertial and EMG based algorithms and a sign based guide that shows the outcomes of previous neurological gait assessment studies are presented. Finally, we state a discussion for the use of wearables in gait assessment and speculate the possible research directions by revealing the limitations and knowledge gaps in the literature.

Estimating Minimal Clinically Important Differences for Knee Range of Motion after Stroke

The importance of knee sagittal kinematic parameters, as a predictor of walking performance in post-stroke gait has been emphasised by numerous researchers. However, no studies so far were designed to determine the minimal clinically important differences (MCID), i.e., the smallest difference in the relevant score for the kinematic gait parameters, which are perceived as beneficial for patients with stroke. Studies focusing on clinically important difference are useful because they can identify the clinical relevance of changes in the scores. The purpose of the study was to estimate the MCID for knee range of motion (ROM) in the sagittal plane for the affected and unaffected side at a chronic stage post-stroke. Fifty individuals were identified in a database of a rehabilitation clinic. We estimated MCID values using: an anchor-based method, distribution-based method, linear regression analysis and specification of the receiver operating characteristic (ROC) curve. In the anchor-based study, the mean change in knee flexion/extension ROM for the affected/unaffected side in the MCID group amounted to 8.48°/6.81° (the first MCID estimate). In the distribution-based study, the standard error of measurement for the no-change group was 1.86°/5.63° (the second MCID estimate). Method 3 analyses showed 7.71°/4.66° change in the ROM corresponding to 1.85-point change in the Barthel Index. The best cut-off point, determined with ROC curve, was the value corresponding to 3.9°/3.8° of change in the knee sagittal ROM for the affected/unaffected side (the fourth MCID estimate). We have determined that, in chronic stroke, MCID estimates of knee sagittal ROM for the affected side amount to 8.48° and for the unaffected side to 6.81°. These findings will assist clinicians and researchers in interpreting the significance of changes observed in kinematic sagittal plane parameters of the knee. The data are part of the following clinical trial: Australian New Zealand Clinical Trials Registry: ACTRN12617000436370

Associations between changes in gait parameters, balance, and walking capacity during the first 3 months after stroke: a prospective observational study

BACKGROUND

Independent ambulation is a common rehabilitation goal after stroke, requiring adequate balance and efficiency of gait. Spatiotemporal gait parameters are expected to improve in the first 3 months and their association with balance and efficiency of gait may provide useful insights into the recovery of safe and independent mobility.

OBJECTIVE

Examine the associations between changes in spatiotemporal gait parameters, balance, and walking capacity during the first 3 months after stroke.

METHODS

This prospective observational study included participants diagnosed with stroke. Within the first 2 weeks after stroke onset and again 3 months (±2 weeks) later, gait was assessed using a GAITRite mat at self-selected gait speed, balance using the Berg Balance Scale (BBS), and walking capacity using the 6-minute walk test (6 MWT). Changes in gait parameters, balance, and walking capacity were assessed using paired sample t-tests, and linear regression analyses were used to assess associations between changes in spatiotemporal gait parameters, BBS, and 6MWT.

RESULTS

Seventy-nine participants (mean (SD) age 75.4 (8.5) years; 44 men) were included. Gait parameters, balance, and walking capacity all improved during follow-up. The bivariate regression analyses showed associations between improvements in all gait parameters, except walk ratio, with improvement in balance, and in all gait parameters with improvement in walking capacity. Only gait speed was associated with balance (13.8 points, 95% CI 0.5, 27.8, p = .0042) and walking capacity (256 m, 95% CI 173,340, p < .001) in the multivariate analyses.

CONCLUSION

Improved spatiotemporal gait parameters were associated with improved balance and walking capacity within the first 3 months after stroke.

Gait characteristics of post-stroke hemiparetic patients with different walking speeds

Hemiparesis resulting from stroke presents characteristic spatiotemporal gait patterns. This study aimed to clarify the spatiotemporal gait characteristics of hemiparetic patients by comparing them with height-, speed-, and age-matched controls while walking at various speeds. The data on spatiotemporal gait parameters of stroke patients and that of matched controls were extracted from a hospital gait analysis database. In total, 130 pairs of data were selected for analysis. Patients and controls were compared for spatiotemporal gait parameters and the raw value (RSI) and absolute value (ASI) of symmetry index and coefficient of variation (CV) of these parameters. Stroke patients presented with prolonged nonparetic stance (patients vs. controls: 1.01 ± 0.41 vs. 0.83 ± 0.25) and paretic swing time (0.45 ± 0.12 vs. 0.39 ± 0.07), shortened nonparetic swing phase (0.35 ± 0.07 vs. 0.39 ± 0.07), and prolonged paretic and nonparetic double stance phases [0.27 ± 0.13 (paretic)/0.27 ± 0.17 (nonparetic) vs. 0.22 ± 0.10]. These changes are especially seen in low-gait speed groups (<3.4 km/h). High RSIs of stance and swing times were also observed (-9.62 ± 10.32 vs. -0.79 ± 2.93, 24.24 ± 25.75 vs. 1.76 ± 6.43, respectively). High ASIs and CVs were more generally observed, including the groups with gait speed of ≥3.5 km/h. ASI increase of the swing phase (25.79 ± 22.69 vs. 4.83 ± 4.88) and CV of the step length [7.7 ± 4.9 (paretic)/7.6 ± 5.0 (nonparetic) vs. 5.3 ± 3.0] were observed in all gait speed groups. Our data suggest that abnormalities in the spatiotemporal parameters of hemiparetic gait should be interpreted in relation to gait speed. ASIs and CVs could be highly sensitive indices for detecting gait abnormalities.

Application of the Gait Deviation Index in the analysis of post-stroke hemiparetic gait

Due to the complexity and volume of kinematic data from 3-dimensional gait analysis, the Gait Deviation Index (GDI) was introduced as a summary measure providing a global picture of gait kinematic data, however previously it was not validated as an outcome measure in individuals after stroke. The present study investigated the concurrent validity of the GDI as an outcome measure of gait defects at a chronic stage of recovery post-stroke, through comparisons with conventional measures of gait. Those enrolled included 65 individuals after stroke and 65 healthy individuals without gait disorders, matched for age and gender. The kinematic gait parameters were measured using a movement analysis system. Walking speed, walking distance, number of steps, self-reliant mobility, cadence, step length, and single support time were evaluated. Strong correlation was found between cadence and mGDI as well as GDI for the affected leg (0.7 ≤ |R| < 0.9; p < 0.001). Moderate correlations were found between walking speed, number of steps, step length affected leg and mGDI as well as GDI for the affected leg (0.5 ≤ |R| < 0.7; p < 0.001). Low correlations were found between walking distance, self-reliant mobility, single support time affected leg and mGDI as well as GDI for the affected leg (0.3 ≤ |R| < 0.5; p < 0.001; p < 0.005). The findings confirm the concurrent validity of the GDI, but only for the affected leg and mGDI in post-stroke patients. On the other hand, the GDI for unaffected leg may be useful in efforts to identify any compensatory mechanisms developing in post-stroke gait patterns. Trial registration: anzctr.org.au, ID:ACTRN12617000436370. Registered 24 March 2017.

Co-Contraction of Lower Limb Muscles Contributes to Knee Stability During Stance Phase in Hemiplegic Stroke Patients

Background

Knee stability has an important role in the gait of hemiplegic stroke patients. However, factors affecting knee stability have not been assessed concerning gait. The purpose of this study was to explore whether co-contraction of the lower limb muscles contributes to the knee stability during the stance phase of the gait cycle in hemiplegic stroke patients.

Material/Methods

A total of 30 hemiplegic stroke patients, ages 36–79 years, were instructed to walk at their natural speed. The root mean square of surface electromyography was used to measure activities of the biceps femoris and rectus femoris muscles, while the co-contraction ratio was computed based on the root mean squares. The peak angle of knee extension was acquired in the stance phase by 3D kinematic analyses. Lower limb function was evaluated using the Fugl-Meyer scale for lower limb motor assessment.

Results

A statistically significant increase of the muscle co-contraction ratio of the involved extremity was observed compared with that of the uninvolved extremity (t=−4.066, P<0.05). The muscle co-contraction ratio was significantly correlated with the peak angle of knee extension (r=0.387, P=0.035), Fugl-Meyer scale (r=−0.522, P=0.003), and Modified Ashworth Scale (r=0.404, P=0.027) during the stance phase of the gait cycle.

Conclusions

Our results showed that co-contraction of the rectus femoris muscle contributes to the stability of the knee and lower limb function in hemiplegic stroke patients, and suggests that co-contraction should be considered in the rehabilitation of knee stability during gait in hemiplegic stroke patients. Appropriate rehabilitation assessment planning with hemiplegic stroke patients, such as muscle co-contraction or knee stability of, might be created based on our results.

Return to Employment After Stroke in Young Adults: How Important Is the Speed and Energy Cost of Walking?

Supplemental Digital Content is available in the text.

A quarter of individuals who experience a stroke are under the age of 65 years (defined as young adults), and up to 44% will be unable to return to work poststroke, predominantly because of walking difficulties. No research study has comprehensively analyzed walking performance in young adult’s poststroke. The primary aim of this study is to investigate how a stroke in young adults affects walking performance (eg, walking speed and metabolic cost) compared with healthy age-matched controls. The secondary aim is to determine the predictive ability of walking performance parameters for return to employment poststroke.

Fore-aft resistance applied at the center of mass using a novel robotic interface proportionately increases propulsive force generation in healthy nonimpaired individuals walking at a constant speed

Background

Past studies have utilized external interfaces like resistive bands and motor-generated pulling systems to increase limb propulsion during walking on a motorized treadmill. However, assessing changes in limb propulsion against increasing resistance demands during self-controlled walking has not been undertaken.

Purpose

We assessed limb propulsion against increasing fore-aft loading demands by applying graded fore-aft (FA) resistance at the center of mass during walking in a novel, intent-driven treadmill environment that allowed participants to control their walking speeds. We hypothesized that to maintain a target speed against progressively increasing resistance, participants would proportionately increase their limb propulsion without increasing vertical force production, with accompanying increases in trailing limb angle and positive joint work.

Methods

Seventeen healthy-nonimpaired participants (mean age 52 yrs., SD = 11) walked at a target, self-controlled speed of 1.0 m/s against 10, 15, 20, and 25% (% body weight) FA resistance levels. We primarily assessed linear slope values across FA resistance levels for mean propulsive force and impulse and vertical impulse of the dominant limb using one-sample t-tests. We further assessed changes in trailing and leading limb angles and joint work using one-way ANOVAs.

Results

Participants maintained their target velocity within an a priori defined acceptable range of 1.0 m/s ± 0.2. They significantly increased propulsion proportional to FA resistance (propulsive force mean slope = 2.45, SD = 0.7, t (16) =14.44, p < 0.01; and propulsive impulse mean slope = 0.7, SD = 0.25, t (16) = 11.84, p < 0.01), but had no changes in vertical impulse (mean slope = − 0.04, SD =0.17, p > 0.05) across FA resistance levels. Mean trailing limb angle increased from 24.3° at 10% resistance to 27.4° at 25% (p < 0.05); leading limb angle decreased from − 18.4° to − 12.6° (p < 0.05). We also observed increases in total positive limb work (F (1.7, 26) = 16.88, p ≤ 0.001, η² = 0.5), primarily attributed to the hip and ankle joints.

Conclusions

FA resistance applied during self-driven walking resulted in increased propulsive-force output of healthy-nonimpaired individuals with accompanying biomechanical changes that facilitated greater limb propulsion. Future rehabilitation interventions for neurological populations may be able to utilize this principle to design task-specific interventions like progressive strength training and workload manipulation during aerobic training for improving walking function.

Electronic supplementary material

The online version of this article (10.1186/s12984-019-0577-x) contains supplementary material, which is available to authorized users.

Inertial sensors versus standard systems in gait analysis: a systematic review and meta-analysis

INTRODUCTION

The increasing popularity of inertial sensors in clinical practice is not supported by precise information on their reliability or guidelines for their use in rehabilitation. The authors investigated the state of the literature concerning the use of inertial sensors for gait analysis in both healthy and pathological adults comparing traditional systems. Furthermore, trying to define directions for clinicians.

EVIDENCE ACQUISITION

In accordance with the PRISMA statement, authors searched in PubMed, Web of Science and Scopus all paper published from January 1st, 2005 until December 31st, 2017. They included both healthy and pathological adults' subjects as population, wearable or inertial sensors used for gait analysis and compared with classical gait analysis performed in a Motion Lab as intervention and comparison, gait parameters as outcomes. Considering the methodological quality, authors focused on: sample; description of the study; type of gait analysis used for comparison; type of sensor; sensor placement on the body; gait task requested.

EVIDENCE SYNTHESIS

From a total of 888 articles, 16 manuscripts were selected and 7 of them were considered for meta-analysis for different gait parameters. Demographic data, tested devices, reference systems, test procedures and outcomes were analyzed.

CONCLUSIONS

Our results show a good agreement between inertial sensors and classical gait analysis for some gait parameters, supporting their use as a solution for capturing kinematic information over an extended space and time and even outside a laboratory in real-life conditions. Authors can support the use of portable inertial sensors for a practical gait analysis in clinical setting with good reliability. It will then be the experience of the clinician to direct the decision-making process.

Validity of the Microsoft Kinect™ in assessing spatiotemporal and lower extremity kinematics during stair ascent and descent in healthy young individuals

Stair negotiation is one of the most challenging, yet frequently encountered, locomotor tasks in daily life. This study is the first attempt to investigate the capacity of the Kinect^™ sensor to assess stair negotiation spatiotemporal and sagittal plane kinematic variables. The goal of this study was to examine the validity of the Kinect^™ v2 sensor in assessing lower extremity kinematics and spatiotemporal parameters in healthy young individuals; and to demonstrate its potential as a low-cost stair gait analysis tool. Twelve healthy participants ascended and descended a 3-step custom-built staircase at their preferred speed, as spatiotemporal parameters and kinematics were extracted simultaneously using the Kinect^™ and a three-dimensional motion analysis. Spatiotemporal measures included gait speed, swing phase time, and double stance time. Kinematic outcomes included hip, knee, and ankle joint angles in the sagittal plane. Consistency (ICC_2,1) and absolute agreement (ICC_3,1) between the two systems were assessed using separate interclass correlations coefficients. In addition, ensemble curves and associated 90% confidence intervals (CI90) were generated for the hip, knee, and ankle kinematics to enable between system comparisons throughout the gait cycle. Results showed that the Kinect^™ has the potential to be an effective clinical assessment device for sagittal plane hip and knee joint kinematics and for some spatiotemporal parameters during the stair gait negotiation.

An assessment of the relationship between the items of the observational Wisconsin Gait Scale and the 3-dimensional spatiotemporal and kinematic parameters in post-stroke gait

BACKGROUND

There are few reports in the literature investigating the relationship between observational gait scales used to assess individuals after a stroke and objective data acquired from 3-dimensional gait analysis (3DGA).

RESEARCH QUESTION

The objective of this study was to compare the relationship between the specific items of the Wisconsin Gait Scale (WGS) and the matching 3-dimensional (3D) spatiotemporal and kinematic gait parameters in individuals after a stroke. In this way we evaluated whether using the simple, inexpensive, easy-to-use, observational WGS can fully substitute for the very costly and time-consuming 3DGA.

METHODS

The study group comprised 50 participants who had experienced a stroke and were in the chronic stage of recovery. The study participants' gait was evaluated by means of the WGS; spatiotemporal and kinematic gait parameters were examined in the Gait Laboratory with the use of the BTS Smart system. The 3D recording of gait was performed using 2 video cameras positioned in such a way that it was possible to obtain images in the frontal and the sagittal plane.

RESULTS

The findings show strong (0.7 ≤ |R| < 0.9; p < 0.001) or very strong (0.9≤ |R| < 1; p < 0.001) correlation between the specific items of the WGS and the matching 3D gait parameters.

SIGNIFICANCE

The WGS is a diagnostic tool useful for conducting observational gait analysis in people with post-stroke hemiparesis and in situations when the costly objective methods of gait assessment cannot be applied for various reasons, the scale may be an effective tool enabling the assessment of gait. The WGS may be particularly useful in the subacute period of stroke as video recording of walking takes considerably less time than 3DGA. The study has been registered at the ClinicalTrials.gov, ID: ACTRN12617000436370.

Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

Three-dimensional gait analysis (3DGA) is shown to be a useful clinical tool for the evaluation of gait abnormality due to movement disorders. However, the use of 3DGA in actual clinics remains uncommon. Possible reasons could include the time-consuming measurement process and difficulties in understanding measurement results, which are often presented using a large number of graphs. Here we present a clinician-friendly 3DGA method developed to facilitate the clinical use of 3DGA. This method consists of simplified preparation and measurement processes that can be performed in a short time period in clinical settings and intuitive results presentation to facilitate clinicians' understanding of results. The quick, simplified measurement procedure is achieved by the use of minimum markers and measurement of patients on a treadmill. To facilitate clinician understanding, results are presented in figures based on the clinicians' perspective. A Lissajous overview picture (LOP), which shows the trajectories of all markers from a holistic viewpoint, is used to facilitate intuitive understanding of gait patterns. Abnormal gait pattern indices, which are based on clinicians' perspectives in gait evaluation and standardized using the data of healthy subjects, are used to evaluate the extent of typical abnormal gait patterns in stroke patients. A graph depicting the analysis of the toe clearance strategy, which depicts how patients rely on normal and compensatory strategies to achieve toe clearance, is also presented. These methods could facilitate implementation of 3DGA in clinical settings and further encourage development of measurement strategies from the clinician's point of view.

Comparing the effects of adapting to a weight on one leg during treadmill and overground walking: A pilot study

BACKGROUND

Locomotor adaptation has been suggested as a way to improve gait symmetry in individuals post-stroke. Most perturbation methods utilize costly, specialized equipment. The use of a unilateral leg weight may provide a low cost, clinically translatable alternative. Furthermore, previous studies have suggested that adaptation context may affect movement outcomes. The purpose of this study was to assess the ability of a unilaterally applied ankle weight to drive locomotor adaptation and determine the effect of context (treadmill versus overground) in young, non-disabled participants.

METHODS

Eighteen young non-disabled adults were randomly assigned to receive 10min of walking on a treadmill with a weight (TG), overground with a weight (OG) or as a control on a treadmill/overground without a weight (CG). Outcomes measured before, during and after adaptation were: step length symmetry, single limb support symmetry and gait speed.

RESULTS

After adding the weight, single limb support immediately became asymmetrical for all participants without changes in step length symmetry. After walking for 10min, TG step length became asymmetrical. After weight removal, both TG and OG had increased step length asymmetry. TG decreased single limb support asymmetry while OG did not. After walking overground without the weight, walking parameters eventually returned to baseline in both weighted groups. The control group showed no changes.

CONCLUSION

A unilaterally applied ankle weight appears able to cause gait adaptation in young, non-disabled participants. However different adaptive changes in the gait pattern are made by the nervous system when the perturbation is applied in different contexts.

Stroke

Stroke, or cerebrovascular accident, involves injury to the central nervous system as a result of a vascular cause, and is a leading cause of disability worldwide. People with stroke often experience sensory, cognitive, and motor sequelae that can lead to difficulty walking, controlling balance in standing and voluntary tasks, and reacting to prevent a fall following an unexpected postural perturbation. This chapter discusses the interrelationships between stroke-related impairments, problems with control of balance and gait, fall risk, fear of falling, and participation in daily physical activity. Rehabilitation can improve balance and walking function, and consequently independence and quality of life, for those with stroke. This chapter also describes effective interventions for improving balance and walking function poststroke, and identifies some areas for further research in poststroke rehabilitation.

Effect of ankle foot orthosis on gait parameters and functional ambulation in patients with stroke

Objectives

This study aims to investigate the effect of ankle foot orthosis (AFO) on temporospatial parameters, ankle kinematics, and functional ambulation level in patients with stroke.

Patients and methods

Records of 286 adult patients with stroke assessed in the gait and motion analysis laboratory between April 2005 and January 2013 were reviewed. The data of 28 patients (16 males, 12 females; mean age 43.2±15.9 years; range 20 to 72 years) who were analyzed with and without AFO during the same session were selected for the study. Temporospatial parameters (walking speed, cadence, opposite foot contact, double support time, single support time, step time, and step length) and ankle kinematics (ankle dorsiflexion at initial contact and midswing) were measured using the Vicon 512 motion analysis system. The video and medical records of patients were examined to determine their ambulation level according to Functional Ambulation Category.

Results

Walking speed, cadence, and ankle dorsiflexion at initial contact and midswing were significantly increased while walking with AFO compared to walking barefoot (p<0.05). There were significant reduction in step time and significant increase in step length and opposite foot contact with AFO on the affected side (p<0.05). Single support time reduced significantly with AFO on the unaffected side (p<0.05). Functional Ambulation Category score improved significantly with use of AFO (p<0.05).

Conclusion

The use of AFO has positive effects on gait parameters and functional ambulation in patients with stroke.

A systematic review of mechanisms of gait speed change post-stroke. Part 1: spatiotemporal parameters and asymmetry ratios

BACKGROUND

In walking rehabilitation trials, self-selected walking speed (SSWS) has emerged as the dominant outcome measure to assess walking ability. However, this measure cannot differentiate between recovery of impaired movement and compensation strategies. Spatiotemporal variables and asymmetry ratios are frequently used to quantify gait deviations and are hypothesized markers of recovery.

OBJECTIVES

The purpose of this review is to investigate spatiotemporal variables and asymmetry ratios as mechanistic recovery measures in physical therapy intervention studies post-stroke.

METHODS

A systematic literature search was performed to identify physical therapy intervention studies with a statistically significant change in SSWS post intervention and concurrently collected spatiotemporal variables. Methodological quality was assessed using the Cochrane Collaboration's tool. Walking speed, spatiotemporal, and intervention data were extracted.

RESULTS

46 studies met the inclusion criteria, 41 of which reported raw spatiotemporal measures and 19 reported asymmetry ratio calculations. Study interventions included: aerobic training (n = 2), functional electrical stimulation (n = 5), hippotherapy (n = 2), motor dual task training (n = 2), multidimensional rehabilitation (n = 4), robotics (n = 4), sensory stimulation training (n = 8), strength/resistance training (n = 4), task specific locomotor rehabilitation (n = 9), and visually guided training (n = 6).

CONCLUSIONS

Spatiotemporal variables help describe gait deviations, but scale to speed, so consequently, may not be an independent factor in describing functional recovery and gains. Therefore, these variables are limited in explaining mechanistic changes involved in improving gait speed. Use of asymmetry measures provides additional information regarding the coordinative requirements for gait and can potentially indicate recovery. Additional laboratory-based mechanistic measures may be required to truly understand how walking speed improves.

A systematic review of mechanisms of gait speed change post-stroke. Part 2: exercise capacity, muscle activation, kinetics, and kinematics

BACKGROUND

Regaining locomotor ability is a primary goal in stroke rehabilitation and is most commonly measured using changes in self-selected walking speed. However, walking speed cannot identify the mechanisms by which an individual recovers. Laboratory-based mechanistic measures such as exercise capacity, muscle activation, force production, and movement analysis variables may better explain neurologic recovery.

OBJECTIVES

The objectives of this systematic review are to examine changes in mechanistic gait outcomes and describe motor recovery as quantified by changes in laboratory-based mechanistic variables in rehabilitation trials.

METHODS

Following a systematic literature search (in PubMed, Ovid, and CINAHL), we included rehabilitation trials with a statistically significant change in self-selected walking speed post-intervention that concurrently collected mechanistic variables. Methodological quality was assessed using Cochrane Collaboration's tool. Walking speed changes, mechanistic variables, and intervention data were extracted.

RESULTS

Twenty-five studies met the inclusion criteria and examined: cardiorespiratory function (n = 5), muscle activation (n = 5), force production (n = 11), and movement analysis (n = 10). Interventions included: aerobic training, functional electrical stimulation, multidimensional rehabilitation, robotics, sensory stimulation training, strength/resistance training, task-specific locomotor rehabilitation, and visually-guided training.

CONCLUSIONS

Following this review, no set of outcome measures to mechanistically explain changes observed in walking speed were identified. Nor is there a theoretical basis to drive the complicated selection of outcome measures, as many of these outcomes are not independent of walking speed. Since rehabilitation literature is yet to support a causal, mechanistic link for functional gains post-stroke, a systematic, multimodal approach to stroke rehabilitation will be necessary in doing so.

Improved kinect-based spatiotemporal and kinematic treadmill gait assessment

A cost-effective, clinician friendly gait assessment tool that can automatically track patients' anatomical landmarks can provide practitioners with important information that is useful in prescribing rehabilitative and preventive therapies. This study investigated the validity and reliability of the Microsoft Kinect v2 as a potential inexpensive gait analysis tool. Ten healthy subjects walked on a treadmill at 1.3 and 1.6m·s^-1, as spatiotemporal parameters and kinematics were extracted concurrently using the Kinect and three-dimensional motion analysis. Spatiotemporal measures included step length and width, step and stride times, vertical and mediolateral pelvis motion, and foot swing velocity. Kinematic outcomes included hip, knee, and ankle joint angles in the sagittal plane. The absolute agreement and relative consistency between the two systems were assessed using interclass correlations coefficients (ICC2,1), while reproducibility between systems was established using Lin's Concordance Correlation Coefficient (rc). Comparison of ensemble curves and associated 90% confidence intervals (CI90) of the hip, knee, and ankle joint angles were performed to investigate if the Kinect sensor could consistently and accurately assess lower extremity joint motion throughout the gait cycle. Results showed that the Kinect v2 sensor has the potential to be an effective clinical assessment tool for sagittal plane knee and hip joint kinematics, as well as some spatiotemporal temporal variables including pelvis displacement and step characteristics during the gait cycle.

Analysis of consistency between temporospatial gait parameters and gait assessment with the use of Wisconsin Gait Scale in post-stroke patients

INTRODUCTION

Due to the increasing incidence and social effects of stroke there is a growing interest in finding methods enabling gait analysis in this group of patients. Observational techniques are predominantly applied in clinical practice; on the other hand advanced quantitative methods allow in-depth multidimensional gait assessment. The present study was designed to assess the consistency between temporospatial gait parameters acquired through 3-dimensional gait analysis and the results of gait assessment with the use of observational WGS in post stroke hemiparetic patients.

MATERIAL AND METHOD

The study was performed in a group of 30 post-stroke patients, over 6 months from the onset of ischaemic stroke, who were able to walk unassisted. Gait assessment based on WGS was performed by an experienced physiotherapist, with the use of video recordings. Assessment of temporospatial parameters was based on gait analysis performed with BTS Smart system.

RESULTS

The findings show moderate correlation between WGS based gait assessment and gait velocity (r=-0.39; p=0.0316). Similar relationship was identified between gait cycle duration and score in WGS for both unaffected (r=-0.36; p=0.0477) and affected side (r=-0.37; p=0.0426). Higher correlation level was demonstrated for stance phase on the unaffected side and gait assessment based on WGS (r=0.58; p=0.0009).

CONCLUSIONS

Gait assessments with the use of temporospatial parameters and with observational WGS were found to produce moderate and good consistent results. WSG is a useful, simple tool for assessing gait in post stroke hemiparetic patients.

Feasibility of a Simplified, Clinically Oriented, Three-dimensional Gait Analysis System for the Gait Evaluation of Stroke Patients

Objective

Although previous studies have evidenced the value of three-dimensional gait analysis (3DGA) for evaluating gait disorder, the time-consuming measurement process and space requirement has hampered its use in the clinical setting. The aim of this study was to examine the feasibility of a simplified 3DGA system for stroke patients.

Methods

Thirteen pairs of stroke patients and age- (± 1 year), gender-, and gait speed- (± 0.5 m/s) matched controls were drawn from the Fujita Health University gait analysis database. 3DGA was performed using the KinemaTracer^® treadmill gait analysis system. Comparisons of the spatiotemporal and kinematic parameters were performed between stroke patients and matched controls. The correlations between items from the Wisconsin Gait Scale (WGS) and 3DGA data in stroke patients were also investigated.

Results

3DGA measurements clearly showed reduced toe clearance, hip flexion, and knee flexion in stroke patients compared with the matched controls. In contrast, significant increases were observed in hip elevation, shoulder elevation, shoulder lateral shift, and step width in stroke patients. For the four items drawn from the WGS, a significant correlation with three 3DGA parameters was observed: stance time on the impaired side, stance width, and knee flexion from toe off to midswing.

Conclusions

In this study, significant differences in gait parameters of stroke patients and age-, gender-, and speed-matched controls were found using a simplified 3DGA system. A significant correlation with WGS was also observed. These results support the validity of the clinical measurement of gait parameters using a simplified 3DGA system.

Influence of Spinal Cord Integrity on Gait Control in Human Spinal Cord Injury

Background Clinical trials in spinal cord injury (SCI) primarily rely on simplified outcome metrics (ie, speed, distance) to obtain a global surrogate for the complex alterations of gait control. However, these assessments lack sufficient sensitivity to identify specific patterns of underlying impairment and to target more specific treatment interventions. Objective To disentangle the differential control of gait patterns following SCI beyond measures of time and distance. Methods The gait of 22 individuals with motor-incomplete SCI and 21 healthy controls was assessed using a high-resolution 3-dimensional motion tracking system and complemented by clinical and electrophysiological evaluations applying unbiased multivariate analysis. Results Motor-incomplete SCI patients showed varying degrees of spinal cord integrity (spinal conductivity) with severe limitations in walking speed and altered gait patterns. Principal component (PC) analysis applied on all the collected data uncovered robust coherence between parameters related to walking speed, distortion of intralimb coordination, and spinal cord integrity, explaining 45% of outcome variance (PC 1). Distinct from the first PC, the modulation of gait-cycle variables (step length, gait-cycle phases, cadence; PC 2) remained normal with respect to regained walking speed, whereas hip and knee ranges of motion were distinctly altered with respect to walking speed (PC 3). Conclusions In motor-incomplete SCI, distinct clusters of discretely controlled gait parameters can be discerned that refine the evaluation of gait impairment beyond outcomes of walking speed and distance. These findings are specifically different from that in other neurological disorders (stroke, Parkinson) and are more discrete at targeting and disentangling the complex effects of interventions to improve walking outcome following motor-incomplete SCI.

Stroke rehabilitation: clinical picture, assessment, and therapeutic challenge

This chapter reviews the evolution of stroke rehabilitation in the last 20 years. It begins by describing the different types of stroke that can occur in adults, their potential consequences on a person's capacity to function in daily life and statistics on the number of strokes and their burden on families and the economy. The assessment of stroke severity, recovery of function over time, and the impact of initial stroke severity and age on potential recovery are then addressed as well as the concept of rehabilitation to enhance recovery. Fueled by the synthesis of an ever-increasing research knowledge base and the creation of stroke rehabilitation recommendations for optimal delivery of rehabilitation services and of therapeutic interventions, stroke rehabilitation has changed dramatically. Examples of improvements in stroke rehabilitation in Canada are given with emphasis on the "best practices" inspired stroke rehabilitation continuum recently recommended for the Province of Quebec. The need for an improved community-based rehabilitation approach that includes regular follow-ups and community-based programs promoting reintegration is emphasized. The importance of knowledge translation strategies to promote the uptake of best-practice recommendations is illustrated by describing the activities of the Sensorimotor Rehabilitation Research Team. Over the past 3 years, the researchers of this team and clinicians in three rehabilitation centers, two in Montreal and one in Quebec City, have collaborated to adopt standardized assessment tools, create a common stroke registry, a best-practice recommended approach to interventions and the participation of clinicians in the research process.