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

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 141 ◽  
Author(s):  
Rob Van der Straaten ◽  
Amber K. B. D. Bruijnes ◽  
Benedicte Vanwanseele ◽  
Ilse Jonkers ◽  
Liesbet De Baets ◽  
...  
Keyword(s):  
Lower Limb ◽  
Sagittal Plane ◽  
Inertial Sensor ◽  
Movement Analysis ◽  
Sensor Technology ◽  
Inertial Measurement ◽  
Sit To Stand ◽  
Movement Strategies ◽  
Measurement Units ◽  
Healthy Participants

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.

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

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2638 ◽  
Author(s):  
Rob van der Straaten ◽  
Annick Timmermans ◽  
Amber K. B. D. Bruijnes ◽  
Benedicte Vanwanseele ◽  
Ilse Jonkers ◽  
...  
Keyword(s):  
Lower Limb ◽  
Inertial Sensor ◽  
Movement Analysis ◽  
Sensor Technology ◽  
Inertial Measurement ◽  
Closed Chain ◽  
Flexion Extension ◽  
Measurement Units ◽  
Healthy Participants ◽  
Better Than

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.

scholarly journals A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study

10.2196/17872 ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. e17872
Author(s):  
Riasat Islam ◽  
Mohamed Bennasar ◽  
Kevin Nicholas ◽  
Kate Button ◽  
Simon Holland ◽  
...  
Keyword(s):  
Acl Reconstruction ◽  
Joint Angle ◽  
Sagittal Plane ◽  
Cruciate Ligament ◽  
Movement Analysis ◽  
Joint Angles ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Anterior Cruciate ◽  
Healthy Participants

Background Movement analysis in a clinical setting is frequently restricted to observational methods to inform clinical decision making, which has limited accuracy. Fixed-site, optical, expensive movement analysis laboratories provide gold standard kinematic measurements; however, they are rarely accessed for routine clinical use. Wearable inertial measurement units (IMUs) have been demonstrated as comparable, inexpensive, and portable movement analysis toolkits. MoJoXlab has therefore been developed to work with generic wearable IMUs. However, before using MoJoXlab in clinical practice, there is a need to establish its validity in participants with and without knee conditions across a range of tasks with varying complexity. Objective This paper aimed to present the validation of MoJoXlab software for using generic wearable IMUs for calculating hip, knee, and ankle joint angle measurements in the sagittal, frontal, and transverse planes for walking, squatting, and jumping in healthy participants and those with anterior cruciate ligament (ACL) reconstruction. Methods Movement data were collected from 27 healthy participants and 20 participants with ACL reconstruction. In each case, the participants wore seven MTw2 IMUs (Xsens Technologies) to monitor their movement in walking, jumping, and squatting tasks. The hip, knee, and ankle joint angles were calculated in the sagittal, frontal, and transverse planes using two different software packages: Xsens’ validated proprietary MVN Analyze and MoJoXlab. The results were validated by comparing the generated waveforms, cross-correlation (CC), and normalized root mean square error (NRMSE) values. Results Across all joints and activities, for data of both healthy and ACL reconstruction participants, the CC and NRMSE values for the sagittal plane are 0.99 (SD 0.01) and 0.042 (SD 0.025); 0.88 (SD 0.048) and 0.18 (SD 0.078) for the frontal plane; and 0.85 (SD 0.027) and 0.23 (SD 0.065) for the transverse plane (hip and knee joints only). On comparing the results from the two different software systems, the sagittal plane was very highly correlated, with frontal and transverse planes showing strong correlation. Conclusions This study demonstrates that nonproprietary software such as MoJoXlab can accurately calculate joint angles for movement analysis applications comparable with proprietary software for walking, squatting, and jumping in healthy individuals and those following ACL reconstruction. MoJoXlab can be used with generic wearable IMUs that can provide clinicians accurate objective data when assessing patients’ movement, even when changes are too small to be observed visually. The availability of easy-to-setup, nonproprietary software for calibration, data collection, and joint angle calculation has the potential to increase the adoption of wearable IMU sensors in clinical practice, as well as in free living conditions, and may provide wider access to accurate, objective assessment of patients’ progress over time.

scholarly journals A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study (Preprint)

2020 ◽  
Author(s):  
Riasat Islam ◽  
Mohamed Bennasar ◽  
Kevin Nicholas ◽  
Kate Button ◽  
Simon Holland ◽  
...  
Keyword(s):  
Acl Reconstruction ◽  
Joint Angle ◽  
Sagittal Plane ◽  
Cruciate Ligament ◽  
Movement Analysis ◽  
Joint Angles ◽  
Measurement Units ◽  
Anterior Cruciate ◽  
P Movement ◽  
Healthy Participants

BACKGROUND Movement analysis in a clinical setting is frequently restricted to observational methods to inform clinical decision making, which has limited accuracy. Fixed-site, optical, expensive movement analysis laboratories provide <i>gold standard</i> kinematic measurements; however, they are rarely accessed for routine clinical use. Wearable inertial measurement units (IMUs) have been demonstrated as comparable, inexpensive, and portable movement analysis toolkits. MoJoXlab has therefore been developed to work with generic wearable IMUs. However, before using MoJoXlab in clinical practice, there is a need to establish its validity in participants with and without knee conditions across a range of tasks with varying complexity. OBJECTIVE This paper aimed to present the validation of MoJoXlab software for using generic wearable IMUs for calculating hip, knee, and ankle joint angle measurements in the sagittal, frontal, and transverse planes for walking, squatting, and jumping in healthy participants and those with anterior cruciate ligament (ACL) reconstruction. METHODS Movement data were collected from 27 healthy participants and 20 participants with ACL reconstruction. In each case, the participants wore seven MTw2 IMUs (Xsens Technologies) to monitor their movement in walking, jumping, and squatting tasks. The hip, knee, and ankle joint angles were calculated in the sagittal, frontal, and transverse planes using two different software packages: Xsens’ validated proprietary MVN Analyze and MoJoXlab. The results were validated by comparing the generated waveforms, cross-correlation (CC), and normalized root mean square error (NRMSE) values. RESULTS Across all joints and activities, for data of both healthy and ACL reconstruction participants, the CC and NRMSE values for the sagittal plane are 0.99 (SD 0.01) and 0.042 (SD 0.025); 0.88 (SD 0.048) and 0.18 (SD 0.078) for the frontal plane; and 0.85 (SD 0.027) and 0.23 (SD 0.065) for the transverse plane (hip and knee joints only). On comparing the results from the two different software systems, the sagittal plane was very highly correlated, with frontal and transverse planes showing strong correlation. CONCLUSIONS This study demonstrates that nonproprietary software such as MoJoXlab can accurately calculate joint angles for movement analysis applications comparable with proprietary software for walking, squatting, and jumping in healthy individuals and those following ACL reconstruction. MoJoXlab can be used with generic wearable IMUs that can provide clinicians accurate objective data when assessing patients’ movement, even when changes are too small to be observed visually. The availability of easy-to-setup, nonproprietary software for calibration, data collection, and joint angle calculation has the potential to increase the adoption of wearable IMU sensors in clinical practice, as well as in free living conditions, and may provide wider access to accurate, objective assessment of patients’ progress over time.

scholarly journals Automatic pairing of inertial sensors to lower limb segments – a plug-and-play approach

2016 ◽  
Vol 2 (1) ◽  
pp. 715-718 ◽  
Author(s):  
David Graurock ◽  
Thomas Schauer ◽  
Thomas Seel
Keyword(s):  
Sensor Networks ◽  
Lower Limb ◽  
Healthy Subjects ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Lower Limbs ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
Correct Pairing ◽  
Measurement Units

AbstractInertial sensor networks enable realtime gait analysis for a multitude of applications. The usability of inertial measurement units (IMUs), however, is limited by several restrictions, e.g. a fixed and known sensor placement. To enhance the usability of inertial sensor networks in every-day live, we propose a method that automatically determines which sensor is attached to which segment of the lower limbs. The presented method exhibits a low computational workload, and it uses only the raw IMU data of 3 s of walking. Analyzing data from over 500 trials with healthy subjects and Parkinson’s patients yields a correct-pairing success rate of 99.8% after 3 s and 100% after 5 s.

scholarly journals Inertial measurement units for the detection of the effects of simulated leg length inequalities

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Hannah Lena Siebers ◽  
Jörg Eschweiler ◽  
Valentin M. Quack ◽  
Markus Tingart ◽  
Marcel Betsch
Keyword(s):  
Stance Phase ◽  
Inertial Sensor ◽  
Knee Extension ◽  
Inertial Measurement Units ◽  
Leg Length ◽  
Joint Angles ◽  
Inertial Measurement ◽  
Hip Abduction ◽  
Measurement Units ◽  
Healthy Participants

Abstract Background Leg length inequalities (LLI) are a common condition that can be associated with detrimental effects like low back pain and osteoarthritis. Inertial measurement units (IMUs) offer the chance to analyze daily activities outside a laboratory. Analyzing the kinematic effects of (simulated) LLI on the musculoskeletal apparatus using IMUs will show their potentiality to improve the comprehension of LLI. Methods Twenty healthy participants with simulated LLI of 0-4 cm were analyzed while walking with an inertial sensor system (MyoMotion). Statistical evaluation of the peak anatomical angles of the spine and legs were performed using repeated measurement (RM) ANOVA or their non-parametric test versions (Friedman test). Results Lumbar lateral flexion and pelvic obliquity increased during the stance phase of the elongated leg and decreased during its swing phase. The longer limb was functionally shortened by higher hip and knee flexion, higher hip adduction, dorsiflexion, and lower ankle adduction. Finally, the shorter leg was lengthened by higher hip and knee extension, hip abduction, ankle plantarflexion, and decreased hip adduction. Conclusion We found differing compensation strategies between the different joints, movement planes, gait phases, and amounts of inequality. Overall the shorter leg is lengthened and the longer leg is shortened during walking, to retain the upright posture of the trunk. IMUs were helpful and precise in the detection of anatomical joint angles and for the analysis of the effects of LLI.

scholarly journals Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results

2021 ◽  
Vol 32 (4) ◽  
Author(s):  
Luigi D’Alfonso ◽  
Emanuele Garone ◽  
Pietro Muraca ◽  
Paolo Pugliese
Keyword(s):  
Pose Estimation ◽  
Good Accuracy ◽  
Inertial Sensor ◽  
Experimental Tests ◽  
Inertial Measurement Units ◽  
Magnetic Vector ◽  
Inertial Measurement ◽  
The Earth ◽  
Measurement Units ◽  
Position And Orientation

AbstractIn this work, we face the problem of estimating the relative position and orientation of a camera and an object, when they are both equipped with inertial measurement units (IMUs), and the object exhibits a set of n landmark points with known coordinates (the so-called Pose estimation or PnP Problem). We present two algorithms that, fusing the information provided by the camera and the IMUs, solve the PnP problem with good accuracy. These algorithms only use the measurements given by IMUs’ inclinometers, as the magnetometers usually give inaccurate estimates of the Earth magnetic vector. The effectiveness of the proposed methods is assessed by numerical simulations and experimental tests. The results of the tests are compared with the most recent methods proposed in the literature.

scholarly journals Effect of Functional Electrical Stimulation of the Gluteus Medius during Gait in Patients following a Stroke

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Sota Araki ◽  
Masayuki Kawada ◽  
Takasuke Miyazaki ◽  
Yuki Nakai ◽  
Yasufumi Takeshita ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Lower Limb ◽  
Stride Length ◽  
Gluteus Medius ◽  
Gait Velocity ◽  
Inertial Measurement Units ◽  
Stroke Patients ◽  
Inertial Measurement ◽  
Motion Range ◽  
Measurement Units

Many stroke patients rely on cane or ankle-foot orthosis during gait rehabilitation. The purpose of this study was to investigate the immediate effect of functional electrical stimulation (FES) to the gluteus medius (GMed) and tibialis anterior (TA) on gait performance in stroke patients, including those who needed assistive devices. Fourteen stroke patients were enrolled in this study (mean poststroke duration: 194.9 ± 189.6   d ; mean age: 72.8 ± 10.7   y ). Participants walked 14 m at a comfortable velocity with and without FES to the GMed and TA. After an adaptation period, lower-limb motion was measured using magnetic inertial measurement units attached to the pelvis and the lower limb of the affected side. Motion range of angle of the affected thigh and shank segments in the sagittal plane, motion range of the affected hip and knee extension-flexion angle, step time, and stride time were calculated from inertial measurement units during the middle ten walking strides. Gait velocity, cadence, and stride length were also calculated. These gait indicators, both with and without FES, were compared. Gait velocity was significantly faster with FES ( p = 0.035 ). Similarly, stride length and motion range of the shank of the affected side were significantly greater with FES (stride length: p = 0.018 ; motion range of the shank: p = 0.02 6). Meanwhile, cadence showed no significant difference ( p = 0.238 ) in gait with or without FES. Similarly, range of motion of the affected hip joint, knee joint, and thigh did not differ significantly depending on FES condition ( p = 0.115 ‐ 0.529 ). FES to the GMed and TA during gait produced an improvement in gait velocity, stride length, and motion range of the shank. Our results will allow therapists to use FES on stroke patients with varying conditions.

scholarly journals Technology in Rehabilitation: Evaluating the Single Leg Squat Exercise with Wearable Inertial Measurement Units

2017 ◽  
Vol 56 (02) ◽  
pp. 88-94 ◽  
Author(s):  
Tomás E. Ward ◽  
Eamonn Delahunt ◽  
Brian Caulfield ◽  
Darragh F. Whelan ◽  
Martin A. O'Reilly
Keyword(s):  
Lumbar Spine ◽  
Lower Limb ◽  
Low Cost ◽  
Objective Evaluation ◽  
Inertial Measurement Units ◽  
Lower Limb Injury ◽  
Inertial Measurement ◽  
Increased Risk ◽  
Measurement Units ◽  
Single Leg Squat

SummaryBackground: The single leg squat (SLS) is a common lower limb rehabilitation exercise. It is also frequently used as an evaluative exercise to screen for an increased risk of lower limb injury. To date athlete/patient SLS technique has been assessed using expensive laboratory equipment or subjective clinical judgement; both of which are not without shortcomings. Inertial measurement units (IMUs) may offer a low cost solution for the objective evaluation of athlete/patient SLS technique.Objectives: The aims of this study were to determine if in combination or in isolation IMUs positioned on the lumbar spine, thigh and shank are capable of: (a) distinguishing between acceptable and aberrant SLS technique; (b) identifying specific deviations from acceptable SLS technique.Methods: Eighty-three healthy volunteers participated (60 males, 23 females, age: 24.68 +/− 4.91 years, height: 1.75 +/− 0.09 m, body mass: 76.01 +/− 13.29 kg). All participants performed 10 SLSs on their left leg. IMUs were positioned on participants’ lumbar spine, left shank and left thigh. These were utilized to record tri-axial accelerometer, gyroscope and magnetometer data during all repetitions of the SLS. SLS technique was labelled by a Chartered Physiotherapist using an evaluation framework. Features were extracted from the labelled sensor data. These features were used to train and evaluate a variety of random-forests classifiers that assessed SLS technique.Results: A three IMU system was moderately successful in detecting the overall quality of SLS performance (77% accuracy, 77% sensitivity and 78% specificity). A single IMU worn on the shank can complete the same analysis with 76% accuracy, 75% sensitivity and 76% specificity. Single sensors also produce competitive classification scores relative to multi-sensor systems in identifying specific deviations from acceptable SLS technique.Conclusions: A single IMU positioned on the shank can differentiate between acceptable and aberrant SLS technique with moderate levels of accuracy. It can also capably identify specific deviations from optimal SLS performance. IMUs may offer a low cost solution for the objective evaluation of SLS performance. Additionally, the classifiers described may provide useful input to an exercise biofeed-back application.

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