Repeatability of an off-the-shelf, full body inertial motion capture system during clinical gait analysis

Ground Contact Time Estimating Wearable Sensor to Measure Spatio-Temporal Aspects of Gait

Inpatient gait analysis is an essential part of rehabilitation for foot amputees and includes the ground contact time (GCT) difference of both legs as an essential component. Doctors communicate improvement advice to patients regarding their gait pattern based on a few steps taken at the doctor's visit. A wearable sensor system, called Suralis, consisting of an inertial measurement unit (IMU) and a pressure measuring sock, including algorithms calculating GCT, is presented. Two data acquisitions were conducted to implement and validate initial contact (IC) and toe-off (TO) event detection algorithms as the basis for the GCT difference determination for able-bodied and prosthesis wearers. The results of the algorithms show a median GCT error of -51.7 ms (IMU) and 14.7 ms (sensor sock) compared to the ground truth and thus represent a suitable possibility for wearable gait analysis. The wearable system presented, therefore, enables a continuous feedback system for patients and, above all, a remote diagnosis of spatio-temporal aspects of gait behaviour based on reliable data collected in everyday life.

The influence of sports practice, dominance and gender on the knee joint position sense

BACKGROUND

Physical activity, muscle fatigue or age have been suggested as factors that positively or negatively influence the knee joint position sense (KJPS). However, conflicting results about the influence of sports practice, limb dominance and gender are found in the literature. This study aimed to assess the influence of sports practice, limb dominance and gender on the KJPS of soccer players and untrained individuals.

METHODOLOGY

Sixty subjects participated in this study: 29 soccer players (SPs) and 31 untrained participants (UPs). KJPS was tested in a seated position, for the target angles of 20° and 45° of knee flexion, through an open kinetic chain technique and active repositioning method. Intergroup analysis was performed to compare KJPS between SPs and UPs and between gender, and intragroup analysis was performed to compare proprioceptive acuity between dominant and non-dominant limbs.

RESULTS

Knee repositioning errors were lower in SPs than in the UPs. Repositioning errors of the dominant and non-dominant limb were not significantly different in SPs (P > 0.05), but in UPs the dominant limb showed significantly lower repositioning errors, both for 20° (P = 0.046) and 45° target (P = 0.036). There were no gender differences in the KJPS in both groups (P > 0.05).

CONCLUSIONS

Proprioceptive acuity is higher in trained than in untrained participants. Dominance seems not to influence KJPS of SPs, but in UPs the dominant limb showed a higher accuracy. There were no differences in KJPS related to gender. These results suggest that sports practice, but neither gender nor limb dominance, may positively influence proprioceptive acuity.

Intra- and inter-rater reliability of joint range of motion tests using tape measure, digital inclinometer and inertial motion capturing

Background

In clinical practice range of motion (RoM) is usually assessed with low-cost devices such as a tape measure (TM) or a digital inclinometer (DI). However, the intra- and inter-rater reliability of typical RoM tests differ, which impairs the evaluation of therapy progress. More objective and reliable kinematic data can be obtained with the inertial motion capture system (IMC) by Xsens. The aim of this study was to obtain the intra- and inter-rater reliability of the TM, DI and IMC methods in five RoM tests: modified Thomas test (DI), shoulder test modified after Janda (DI), retroflexion of the trunk modified after Janda (DI), lateral inclination (TM) and fingertip-to-floor test (TM).

Methods

Two raters executed the RoM tests (TM or DI) in a randomized order on 22 healthy individuals while, simultaneously, the IMC data (Xsens MVN) was collected. After 15 warm-up repetitions, each rater recorded five measurements.

Findings

Intra-rater reliabilities were (almost) perfect for tests in all three devices (ICCs 0.886–0.996). Inter-rater reliability was substantial to (almost) perfect in the DI (ICCs 0.71–0.87) and the IMC methods (ICCs 0.61–0.993) and (almost) perfect in the TM methods (ICCs 0.923–0.961). The measurement error (ME) for the tests measured in degree (°) was 0.9–3.3° for the DI methods and 0.5–1.2° for the IMC approaches. In the tests measured in centimeters the ME was 0.5–1.3cm for the TM methods and 0.6–2.7cm for the IMC methods. Pearson correlations between the results of the DI or the TM respectively with the IMC results were significant in all tests except for the shoulder test on the right body side (r = 0.41–0.81).

Interpretation

Measurement repetitions of either one or multiple trained raters can be considered reliable in all three devices.

The effect of a knee brace in dynamic motion-An instrumented gait analysis

Background

Osteoarthritis (OA) is a common problem in the older population. To reduce pain and stress in the affected knee joint compartment, a functional knee brace is often prescribed by physicians to protect it from high loads.

Objectives

An instrumented gait analysis should evaluate how the 4-point knee orthosis for varus or valgus load relief (M.4s OA) changes the kinematics of the knee, especially in the frontal plane.

Methods

17 healthy participants took part and were analyzed with an inertial sensor system (MyoMotion) giving continuous, objective information on the anatomical angles. The measurements were made both without wearing a knee brace and with the brace in different settings.

Results

The results show a significant reduction in the maximum knee abduction and raised knee adduction. The knee brace, with a strong adjustment in varus or valgus orientation, caused a shift of maximum ab-/adduction in the proposed direction in 69% and 75% of the dynamic tests, respectively. The knee motion in the frontal plane shows individual movement patterns.

Conclusion

The use of the brace leads to significant changes in the knee’s movement. Patient-specific movement patterns may explain different effects of functional knee braces on individual persons. Inertial sensors have been shown to be a low-cost, easy-to-use option for individual movement analysis and further personalized therapy.

Gait Analysis in a Box: A System Based on Magnetometer-Free IMUs or Clusters of Optical Markers with Automatic Event Detection

Gait analysis based on full-body motion capture technology (MoCap) can be used in rehabilitation to aid in decision making during treatments or therapies. In order to promote the use of MoCap gait analysis based on inertial measurement units (IMUs) or optical technology, it is necessary to overcome certain limitations, such as the need for magnetically controlled environments, which affect IMU systems, or the need for additional instrumentation to detect gait events, which affects IMUs and optical systems. We present a MoCap gait analysis system called Move Human Sensors (MH), which incorporates proposals to overcome both limitations and can be configured via magnetometer-free IMUs (MH-IMU) or clusters of optical markers (MH-OPT). Using a test-retest reliability experiment with thirty-three healthy subjects (20 men and 13 women, 21.7 ± 2.9 years), we determined the reproducibility of both configurations. The assessment confirmed that the proposals performed adequately and allowed us to establish usage considerations. This study aims to enhance gait analysis in daily clinical practice.

Functional movement assessment by means of inertial sensor technology to discriminate between movement behaviour of healthy controls and persons with knee osteoarthritis

BACKGROUND

Apart from biomechanical alterations in movement patterns, it is known that movement limitations in persons with knee osteoarthritis (PwKOA) are related to an individual's perception and belief regarding pain and disability. To gain more insights into the functional movement behaviour of PwKOA in a clinical setting, inertial sensor technology can be applied. This study first aims to evaluate the ability of inertial sensors to discriminate between healthy controls (HC) and PwKOA. Secondly, this study aims to determine the relationship between movement behaviour, pain-related factors and disability scores.

METHODS

Twelve HC and 19 PwKOA were included. Five repetitions of six functional movement tasks (walking, forward lunge, sideward lunge, ascent and descent stairs, single leg squat and sit-to-stand) were simultaneously recorded by the inertial sensor system and a camera-based motion analysis system. Statistically significant differences in angular waveforms of the trunk, pelvis and lower limb joints between HC and PwKOA were determined using one-dimensional statistical parametric mapping (SPM1D). The Knee injury and Osteoarthritis Outcome Score and TAMPA scale for Kinesiophobia were used to evaluate the relationship between discriminating joint motion, pain-related factors and disability using spearman's correlation coefficients.

RESULTS

PwKOA had significantly less trunk rotation, internal pelvis rotation and knee flexion ROM during walking. Additionally, the reduced knee flexion (i.e. at the end of the stance phase and swing phase) was related to increased level of perceived pain. During the sideward lunge, PwKOA had significantly less knee flexion, ankle plantarflexion and hip abduction. This decreased hip abduction (i.e. during stance) was related to higher fear of movement. Finally, PwKOA had significantly less knee flexion during the forward lunge, single leg squat and during ascent and descent stairs. No significant correlations were observed with disability.

CONCLUSIONS

Inertial sensors were able to discriminate between movement characteristics of PwKOA and HC. Additionally, significant relationships were found between joint motion, perceived pain and fear of movement. Since inertial sensors can be used outside the laboratory setting, these results are promising as they indicate the ability to evaluate movement deviations. Further research is required to enable measurements of small movement deviations in clinically relevant tasks.

Non-Linear Template-Based Approach for the Study of Locomotion

The automatic detection of gait events (i.e., Initial Contact (IC) and Final Contact (FC)) is crucial for the characterisation of gait from Inertial Measurements Units. In this article, we present a method for detecting steps (i.e., IC and FC) from signals of gait sequences of individuals recorded with a gyrometer. The proposed approach combines the use of a dictionary of templates and a Dynamic Time Warping (DTW) measure of fit to retrieve these templates into input signals. Several strategies for choosing and learning the adequate templates from annotated data are also described. The method is tested on thirteen healthy subjects and compared to gold standard. Depending of the template choice, the proposed algorithm achieves average errors from 0.01 to 0.03 s for the detection of IC, FC and step duration. Results demonstrate that the use of DTW allows achieving these performances with only one single template. DTW is a convenient tool to perform pattern recognition on gait gyrometer signals. This study paves the way for new step detection methods: it shows that using one single template associated with non-linear deformations may be sufficient to model the gait of healthy subjects.

The Effects of an Eight over Cricket Bowling Spell upon Pace Bowling Biomechanics and Performance within Different Delivery Lengths

Pace bowlers must often perform extended bowling spells with maximal ball release speed (BRS) while targeting different delivery lengths when playing a multi-day match. This study investigated the effect of an eight over spell upon pace bowling biomechanics and performance at different delivery lengths. Nine male bowlers (age = 18.8 ± 1.7 years) completed an eight over spell, while targeting different lengths (short: 7-10 m, good: 4-7 m, full: 0-4 m from the batter's stumps, respectively) in a randomized order. Trunk, knee and shoulder kinematics and ground reaction forces at front foot contact (FFC), as well as run-up velocity and BRS were measured. Paired sample t-tests (p ≤ 0.01), Hedges' g effect sizes, and statistical parametrical mapping were used to assess differences between mean variables from the first and last three overs. No significant differences (p = 0.05-0.98) were found in any discrete or continuous variables, with the magnitude of difference being trivial-to-medium (g = 0.00-0.73) across all variables. Results suggest pace bowlers sustain BRS through a single eight over spell while tolerating the repeatedly high whole-body biomechanical loads as suggested by maintaining the kinematics or technique at the assessed joints during FFC. Practically, the findings are advantageous for bowling performance and support current bowling load monitoring practices.

Sensitivity comparison of inertial to optical motion capture during gait: implications for tracking recovery

Wearable sensors provide a foundation for development of wearable robotic technology to be used in clinical applications. Inertial motion capture (IMC) has emerged as a viable alternative to more cumbersome, non-portable optical methods. Previous work has validated the accuracy of IMC for gait compared to optical motion capture (OMC). However, it is unclear how well IMC can measure the small changes in gait function needed to gauge recovery. In this study, we evaluate the sensitivity of IMC compared to OMC to small changes in gait on a cohort of unimpaired individuals during treadmill walking. Eight individuals walked on a split-belt treadmill in three-minute trials with five randomized conditions: right belt speed decrementing at 0.05 m/s from 1.0 m/s, all with left belt held at 1.0 m/s, simulating recovery of hemiparetic gait. We extracted the root mean square deviation (RMSD) of joint kinematics between limbs and within the limb with modulated gait speed as the main outcome measure. We used linear mixed models to identify differences in sensitivity to changes in gait asymmetry and gait speed. Based on these models, we estimated the minimal detectible interval in gait parameters. We found that IMC was capable of measuring a difference in gait speed of 0.08 m/s, roughly the equivalent of two weeks recovery progress. Statistically we could not conclude a difference of sensitivity between IMC and OMC, although there is a strong trend that IMC is more sensitive to changes in gait. We conclude that IMC is a valid tool to measure progress in gait kinematics over the course of recovery.

Tracking Foot Drop Recovery Following Lumbar-Spine Surgery, Applying Multiclass Gait Classification Using Machine Learning Techniques

The ability to accurately perform human gait evaluation is critical for orthopedic foot and ankle surgeons in tracking the recovery process of their patients. The assessment of gait in an objective and accurate manner can lead to improvement in diagnoses, treatments, and recovery. Currently, visual inspection is the most common clinical method for evaluating the gait, but this method can be subjective and inaccurate. The aim of this study is to evaluate the foot drop condition in an accurate and clinically applicable manner. The gait data were collected from 56 patients suffering from foot drop with L5 origin gathered via a system based on inertial measurement unit sensors at different stages of surgical treatment. Various machine learning (ML) algorithms were applied to categorize the data into specific groups associated with the recovery stages. The results revealed that the random forest algorithm performed best out of the selected ML algorithms, with an overall 84.89% classification accuracy and 0.3785 mean absolute error for regression.

Classification of foot drop gait characteristic due to lumbar radiculopathy using machine learning algorithms

BACKGROUND

Recently, the study of walking gait has received significant attention due to the importance of identifying disorders relating to gait patterns. Characterisation and classification of different common gait disorders such as foot drop in an effective and accurate manner can lead to improved diagnosis, prognosis assessment, and treatment. However, currently visual inspection is the main clinical method to evaluate gait disorders, which is reliant on the subjectivity of the observer, leading to inaccuracies.

RESEARCH QUESTION

This study examines if it is feasible to use commercial off-the-shelf Inertial measurement unit sensors and supervised learning methods to distinguish foot drop gait disorder from the normal walking gait pattern.

METHOD

The gait data collected from 56 adults diagnosed with foot drop due to L5 lumbar radiculopathy (with MRI verified compressive pathology), and 30 adults with normal gait during multiple walking trials on a flat surface. Machine learning algorithms were applied to the inertial sensor data to investigate the feasibility of classifying foot drop disorder.

RESULTS

The best three performing results were 88.45%, 86.87% and 86.08% accuracy derived from the Random Forest, SVM, and Naive Bayes classifiers respectively. After applying the wrapper feature selection technique, the top performance was from the Random Forest classifier with an overall accuracy of 93.18%.

SIGNIFICANCE

It is demonstrated that the combination of inertial sensors and machine learning algorithms, provides a promising and feasible solution to differentiating L5 radiculopathy related foot drop from normal walking gait patterns. The implication of this finding is to provide an objective method to help clinical decision making.

Reliability and Agreement of 3D Trunk and Lower Extremity Movement Analysis by Means of Inertial Sensor Technology for Unipodal and Bipodal Tasks

This study evaluates the reliability and agreement of the 3D range of motion (ROM) of trunk and lower limb joints, measured by inertial measurement units (MVN BIOMECH Awinda, Xsens Technologies), during a single leg squat (SLS) and sit to stand (STS) task. Furthermore, distinction was made between movement phases, to discuss the reliability and agreement for different phases of both movement tasks. Twenty healthy participants were measured on two testing days. On day one, measurements were conducted by two operators to determine the within-session and between-operator reliability and agreement. On day two, measurements were conducted by the same operator, to determine the between-session reliability and agreement. The SLS task had lower within-session reliability and agreement compared with between-session and between-operator reliability and agreement. The reliability and agreement of the hip, knee, and ankle ROM in the sagittal plane were good for both phases of the SLS task. For both phases of STS task, within-session reliability and agreement were good, and between-session and between-operator reliability and agreement were lower in all planes. As both tasks are physically demanding, differences may be explained by inconsistent movement strategies. These results show that inertial sensor systems show promise for use in further research to investigate (mal)adaptive movement strategies.

Reliability of 3D Lower Extremity Movement Analysis by Means of Inertial Sensor Technology during Transitional Tasks

This study assesses the reliability and agreement of trunk and lower limb joints’ 3D kinematics, measured by inertial measurement units, during walking and more demanding movement tasks. For data analysis, tasks were divided in open and closed chain phases. Twenty healthy participants were included. On day one, measurements were conducted by “Operator 1” and “Operator 2” to determine between-operator reliability/agreement. On day two, the measurements were conducted by Operator 1, in order to determine within-session reliability/agreement. Furthermore, between-session reliability/agreement was assessed based on data from Operator 1, captured on day one and two. Within-session reliability/agreement was high, and better than between-session and between-operator results for all tasks. The results for walking were generally better than for other movement tasks, for all joint kinematics, and for both open and closed chain phases. Only for the ab/adduction and flexion/extension angles during forward and sideward lunge, reliability and agreement results were comparable to walking, for both the open and closed chain phases. The fact that lunges show similar reliability results than walking for open and closed chain phases, but require more motor control to perform, indicates that the performance of lunges might be interesting to use in further research aiming to identify kinematic differences between populations.

Validation of foot pitch angle estimation using inertial measurement unit against marker-based optical 3D motion capture system

Gait analysis is relevant to a broad range of clinical applications in areas of orthopedics, neurosurgery, rehabilitation and the sports medicine. There are various methods available for capturing and analyzing the gait cycle. Most of gait analysis methods are computationally expensive and difficult to implement outside the laboratory environment. Inertial measurement units, IMUs are considered a promising alternative for the future of gait analysis. This study reports the results of a systematic validation procedure to validate the foot pitch angle measurement captured by an IMU against Vicon Optical Motion Capture System, considered the standard method of gait analysis. It represents the first phase of a research project which aims to objectively evaluate the ankle function and gait patterns of patients with dorsiflexion weakness (commonly called a "drop foot") due to a L5 lumbar radiculopathy pre- and post-lumbar decompression surgery. The foot pitch angle of 381 gait cycles from 19 subjects walking trails on a flat surface have been recorded throughout the course of this study. Comparison of results indicates a mean correlation of 99.542% with a standard deviation of 0.834%. The maximum root mean square error of the foot pitch angle measured by the IMU compared with the Vicon Optical Motion Capture System was 3.738° and the maximum error in the same walking trail between two measurements was 9.927°. These results indicate the level of correlation between the two systems.

Accuracy of Base of Support Using an Inertial Sensor Based Motion Capture System

The potential of miniature inertial sensors for human balance and gait analysis appears promising. Base of support (BOS), together with its interaction with center of mass, is a critical indicator in above mentioned research fields. This study aims to evaluate the accuracy of Xsens MVN BIOMECH, a commercial widely used inertial sensor-based motion capture system, for measuring static BOS and examine the effect of different task complexity on the accuracy. Eleven young males participated in this study and went through eleven different experimental tasks. Results showed there were considerable errors in estimating BOS area (error ranged from −12.6% to +64.6%) from Xsens MVN and a large error in foot separation distance when there was knee flexion. The estimated BOS area from MVN was smaller than the ground truth from footprint when there was no knee flexion, and larger when there was knee flexion, and it increased monotonically along with the knee flexion angles. Wrongly estimated foot separations, mainly caused by knee flexion, and the initial system estimation error on BOS, were two major reasons for error and instability of BOS estimation. The findings suggested that caution should be taken when using Xsens MVN BIOMECH to estimate BOS and foot position-related measurements, especially for postures/motions with knee flexion.

Octopus: A Design Methodology for Motion Capture Wearables

Human motion capture (MoCap) is widely recognised for its usefulness and application in different fields, such as health, sports, and leisure; therefore, its inclusion in current wearables (MoCap-wearables) is increasing, and it may be very useful in a context of intelligent objects interconnected with each other and to the cloud in the Internet of Things (IoT). However, capturing human movement adequately requires addressing difficult-to-satisfy requirements, which means that the applications that are possible with this technology are held back by a series of accessibility barriers, some technological and some regarding usability. To overcome these barriers and generate products with greater wearability that are more efficient and accessible, factors are compiled through a review of publications and market research. The result of this analysis is a design methodology called Octopus, which ranks these factors and schematises them. Octopus provides a tool that can help define design requirements for multidisciplinary teams, generating a common framework and offering a new method of communication between them.

Walking while Performing Working Memory Tasks Changes the Prefrontal Cortex Hemodynamic Activations and Gait Kinematics

BACKGROUND

Increasing evidence suggests that walking while performing a concurrent task negatively influences gait performance. However, it remains unclear how higher-level cognitive processes and coordination of limb movements are altered in challenging walking environments. This study investigated the influence of cognitive task complexity and walking road condition on the neutral correlates of executive function and postural control in dual-task walking.

METHODS

Twenty-four healthy young adults completed a series of overground walks with three walking road conditions (wide, narrow, with obstacles) with and without the concurrent n-back working memory tasks of two complexity levels (1-back and 3-back). Prefrontal brain activation was assessed by functional near-infrared spectroscopy. A three-dimensional motion analysis system was used simultaneously to measure gait performance and lower-extremity kinematics. Repeated measures analysis of variance were performed to examine the differences between the conditions.

RESULTS

In comparison with standing still, participants showed lower n-back task accuracy while walking, with the worst performance from the road with obstacles. Spatiotemporal gait parameters, lower-extremity joint movements, and the relative changes in oxygenated hemoglobin (HbO) concentration levels were all significantly different across the task complexity and walking path conditions. While dual-tasking participants were found to flex their hips and knees less, leading to a slower gait speed, longer stride time, shorter step length, and greater gait variability than during normal walking. For narrow-road walking, smaller ankle dorsiflexion and larger hip flexion were observed, along with a reduced gait speed. Obstacle negotiation was mainly characterized by increased gait variability than other conditions. HbO levels appeared to be lower during dual-task walking than normal walking. Compared to wide and obstacle conditions, walking on the narrow road was found to elicit a smaller decrement in HbO levels.

CONCLUSION

The current study provided direct evidence that, in young adults, neural correlates of executive function and dynamic postural control tend to be altered in response to the cognitive load imposed by the walking environment and the concurrent task during ambulation. A shift of brain activation patterns between functionally connected networks may occur when facing challenging cognitive-motor interaction.

A portable inertial sensing-based spinal motion measurement system for low back pain assessment

Spinal motion measurement during dynamic conditions may help identify differences between individuals with and without low back pain (LBP). The purpose of this paper is to demonstrate the feasibility of an inertial sensing based, portable spinal motion measurement system for investigating the differences of the spinal motions between an LBP group and a healthy control group. During a fast flexion/extension test, we measured 3D angular motions of the pelvis, lumbar spine and thoracic spine of the two groups using the inertial sensing based system. Range of motions (ROM) and peak angular velocities were investigated to determine which variables have significant differences between the two groups (p < 0.05). Also, a logistic regression analysis was carried out to see the classifying ability of the LBP patients from controls using the proposed system. The result shows that LBP was particularly associated with significant decreases in peak velocities of the lumbar spinal extension motion, having the maximum 90% sensitivity and 80% specificity in the classification according to the regression analysis. The result demonstrates the possibility of the proposed inertial sensing-based system to be served as an efficient tool in providing an accurate and continuous measurement of the spinal kinematics.

Inertial motion capture in conjunction with an artificial neural network can differentiate the gait patterns of hemiparetic stroke patients compared with able-bodied counterparts

Clinical gait analysis has proven to reduce uncertainties in selecting the appropriate quantity and type of treatment for patients with neuromuscular disorders. However, gait analysis as a clinical tool is under-utilised due to the limitations and cost of acquiring and managing data. To overcome these obstacles, inertial motion capture (IMC) recently emerged to counter the limitations attributed to other methods. This paper investigates the use of IMC for training and testing a back-propagation artificial neural network (ANN) for the purpose of distinguishing between hemiparetic stroke and able-bodied ambulation. Routine gait analysis was performed on 30 able-bodied control subjects and 28 hemiparetic stroke patients using an IMC system. An ANN was optimised to classify the two groups, achieving a repeatable network accuracy of 99.4%. It is concluded that an IMC system and appropriate computer methods may be useful for the planning and monitoring of gait rehabilitation therapy of stroke victims.