Marker-based Motion Analysis System Research Articles

Agreement between Azure Kinect and Marker-Based Motion Analysis during Functional Movements: A Feasibility Study.

(1) Background: The present study investigated the agreement between the Azure Kinect and marker-based motion analysis during functional movements. (2) Methods: Twelve healthy adults participated in this study and performed a total of six different tasks including front view squat, side view squat, forward reach, lateral reach, front view lunge, and side view lunge. Movement data were collected using an Azure Kinect and 12 infrared cameras while the participants performed the movements. The comparability between marker-based motion analysis and Azure Kinect was visualized using Bland-Altman plots and scatter plots. (3) Results: During the front view of squat motions, hip and knee joint angles showed moderate and high level of concurrent validity, respectively. The side view of squat motions showed moderate to good in the visible hip joint angles, whereas hidden hip joint angle showed poor concurrent validity. The knee joint angles showed variation between excellent and moderate concurrent validity depending on the visibility. The forward reach motions showed moderate concurrent validity for both shoulder angles, whereas the lateral reach motions showed excellent concurrent validity. During the front view of lunge motions, both the hip and knee joint angles showed moderate concurrent validity. The side view of lunge motions showed variations in concurrent validity, while the right hip joint angle showed good concurrent validity; the left hip joint showed poor concurrent validity. (4) Conclusions: The overall agreement between the Azure Kinect and marker-based motion analysis system was moderate to good when the body segments were visible to the Azure Kinect, yet the accuracy of tracking hidden body parts is still a concern.

A kinematic-geometric model based on ankles’ depth trajectory in frontal plane for gait analysis using a single RGB-D camera

The emergence of RGB-D cameras and the development of pose estimation algorithms offer opportunities in biomechanics. However, some challenges still remain when using them for gait analysis, including noise which leads to misidentification of gait events and inaccuracy.Therefore, we present a novel kinematic-geometric model for spatio-temporal gait analysis, based on ankles’ trajectory in the frontal plane and distance-to-camera data (depth). Our approach consists of three main steps: identification of the gait pattern and modeling via parameterized curves, development of a fitting algorithm, and computation of locomotive indices. The proposed fitting algorithm applies on both ankles’ depth data simultaneously, by minimizing through numerical optimization some geometric and biomechanical error functions.For validation, 15 subjects were asked to walk inside the walkway of the OptoGait, while the OptoGait and an RGB-D camera (Microsoft Azure Kinect) were both recording. Then, the spatio-temporal parameters of both feet were computed using the OptoGait and the proposed model. Validation results show that the proposed model yields good to excellent absolute statistical agreement (0.86 ≤ Rc ≤ 0.99).Our kinematic-geometric model offers several benefits: (1) It relies only on the ankles’ depth trajectory both for gait events extraction and spatio-temporal parameters’ calculation; (2) it is usable with any kind of RGB-D camera or even with 3D marker-based motion analysis systems in absence of toes’ and heels’ markers; and (3) it enables improving the results by denoising and smoothing the ankles’ depth trajectory. Hence, the proposed kinematic-geometric model facilitates the development of portable markerless systems for accurate gait analysis.

Reliability and agreement of Azure Kinect and Kinect v2 depth sensors in the shoulder joint range of motion estimation.

Depth sensor-based motion analysis systems are of interest to researchers with low cost, fast analysis capabilities, and portability; thus, their reliability is a matter of interest. Our study examined the agreement and reliability in estimating the basic shoulder movements of Azure Kinect, Microsoft's state-of-the-art depth sensor, and its predecessor, Kinect v2, by comparing them with the gold standard marker-based motion analysis system. In our study, the shoulder joint ranges of motion of 20 healthy individuals were analyzed during dominant-side flexion, abduction, and rotation movements. The reliability and agreement between methods were evaluated using the intraclass correlation coefficient (ICC) and the Bland-Altman method. Compared to the gold standard method, the old- and new-generation Kinect showed similar performance in terms of reliability in the estimation of flexion (ICC=0.86 vs. 0.82) and abduction (ICC=0.78 vs. 0.79) movements, respectively. In contrast, the new-generation sensor showed higher reliability than its predecessor in internal (ICC=0.49 vs. 0.75) and external rotation (ICC=0.38 vs. 0.67) movement. Compared to its predecessor, Kinect Azure has higher reliability in analyzing movements in a lower range and variability, thanks to its state-of-the-art hardware. However, the sensor should also be tested on multiaxial movements, such as combing hair, drinking water, and reaching back, which are the tasks that simulate extremity movements in daily life.

Accuracy measurement of different marker based motion analysis systems for biomechanical applications: A round robin study.

Multiple camera systems are widely used for 3D-motion analysis. Due to increasing accuracies these camera systems gained interest in biomechanical research areas, where high precision measurements are desirable. In the current study different measurement systems were compared regarding their measurement accuracy. Translational and rotational accuracy measurements as well as the zero offset measurements of seven different measurement systems were performed using two reference devices and two different evaluation algorithms. All measurements were performed in the same room with constant temperature at the same laboratory. Equal positions were measured with the systems according to a standardized protocol. Measurement errors were determined and compared. The highest measurement errors were seen for a measurement system using active ultrasonic markers, followed by another active marker measurement system (infrared) having measurement errors up to several hundred micrometers. The highest accuracies were achieved by three stereo camera systems, using passive 2D marker points having errors typically below 20 μm. This study can help to better assess the results obtained with different measurement systems. With the focus on the measurement accuracy, only one aspect in the selection of a system was considered. Depending on the requirements of the user, other factors like measurement frequency, the maximum analyzable volume, the marker type or the costs are important factors as well.

Dual-channel cascade pose estimation network trained on infrared thermal image and groundtruth annotation for real-time gait measurement.

Real-time spatiotemporal parameter measurement for gait analysis is challenging. Previous techniques for 3D motion analysis, such as inertial measurement units, marker based motion analysis or the use of depth cameras, require expensive equipment, highly skilled staff and limits feasibility for sustainable applications. In this paper a dual-channel cascaded network to perform contactless real-time 3D human pose estimation using a single infrared thermal video as an input is proposed. An algorithm to calculate gait spatiotemporal parameters is presented by tracking estimated joint locations. Additionally, a training dataset composed of infrared thermal images and groundtruth annotations has been developed. The annotation represents a set of 3D joint locations from infrared optical trackers, which is considered to be the gold standard in clinical applications. On the proposed dataset, our pose estimation framework achieved a 3D human pose mean error of below 21mm and outperforms state-of-the-art methods. The results reveal that the proposed system achieves competitive skeleton tracking performance on par with the other motion capture devices and exhibited good agreement with a marker-based three-dimensional motion analysis system (3DMA) over a range of spatiotemporal parameters. Moreover, the process is shown to distinguish differences in over-ground gait parameters of older adults with and without Hemiplegia's disease. We believe that the proposed approaches can measure selected spatiotemporal gait parameters and could be effectively used in clinical or home settings.

Optimizing Pitching Performance through Shoulder and Elbow Biomechanics

Shoulder injuries account for two-thirds of all injuries in overhead athletes. Maximizing pitching performance while mitigating injury risk requires an objective understanding of the complex biomechanics—both motion and loads—between the lower and upper extremity. Recent advances in both marker-based and marker-less motion capture systems have advanced our knowledge of shoulder biomechanics. Marker-based 3D motion analysis systems remain the gold-standard in sports performance analysis, but recent technical improvements in marker-less and IMU-based systems have provided new insights into pitching biomechanics both on and off the field. These research tools have identified that excessive shoulder external rotation and inefficient transfer of energy from the lower body through the kinetic chain during pitches leads to increased injury risk, particularly in youth and high school pitchers. These motion capture tools should be used to objectively measure cumulative pitching workload and identify the factors that can predispose pitchers to injury.

Validation of a portable marker-based motion analysis system

BackgroundThe Opti_Knee system, a marker-based motion capture system, tracks and analyzes the 6 degrees of freedom (6DOF) motion of the knee joint. However, the validation of the accuracy of this gait system had not been previously reported. The objective of this study was to validate and the system. Two healthy subjects were recruited for the study.MethodsThe 6DOF kinematics of the knee during flexion–extension and level walking cycles of the knee were recorded by Opti_Knee and compared to those from a biplanar fluoroscopy system. The root mean square error (RMSE) of knee kinematics in flexion–extension cycles were compared between the two systems to validate the accuracy at which they detect basic knee motions. The RMSE of kinematics at key events of gait cycles (level walking) were compared to validate the accuracy at which the systems detect functional knee motion. Pearson correlation tests were conducted to assess similarities in knee kinematic trends between the two systems.ResultsIn flexion–extension cycles, the average translational accuracy (RMSE) was between 2.7 and 3.7 mm and the average rotational accuracy was between 1.7 and 3.8°. The Pearson correlation of coefficients for flexion–extension cycles was between 0.858 and 0.994 for translation and 0.995-0.999 for angles. In gait cycles, the RMSEs of angular knee kinematics were 2.3° for adduction/abduction, 3.2° for internal/external rotation, and 1.4° for flexion/extension. The RMSEs of translational kinematics were 4.2 mm for anterior/posterior translation, 3.3 mm for distal/proximal translation, and 3.2 mm for medial/lateral translation. The Pearson correlation of coefficients values was between 0.964 and 0.999 for angular kinematics and 0.883 and 0.938 for translational kinematics.ConclusionThe Opti_Knee gait system exhibited acceptable accuracy and strong correlation strength compared to biplanar fluoroscopy. The Opti _Knee may serve as a promising portable clinical system for dynamic functional assessments of the knee.

Midterm functional performance following open surgical repair of acute Achilles tendon rupture

IntroductionVarious impairments such as soleus atrophy and consecutive functional deficits in end-range plantarflexion have been described in surgical repair of acute Achilles tendon rupture. The aim of this study was to assess the functional performance at midterm following open surgical repair.Materials and MethodsThis cross-sectional study includes n = 52 patients which were tested on average 3.5 ± 1.4 years postoperatively using three different functional performance tests and patient-reported outcome measures. Two different surgical techniques (anatomical repair = AR vs. conventional repair = CR) were compared in a subanalysis. The testing included isokinetic strength testing, a novel setup of heel-rise testing using a marker-based 3D motion analysis system and a gait analysis.ResultsAt an average 3.5 years post-surgery, there is a persisting deficit in plantarflexion strength of 10.2%. Moreover, analysis of maximum peak torque angle and strength deficits according to the plantarflexion angle revealed that these deficits are not equally distributed across the range of motion. AR results in a significantly smaller deficit at 10° of plantarflexion compared to CR (13.9 vs. 29.9%, p < 0.05). This reflects into the functional performance during different modalities (static vs. dynamic) in this novel method of heel-rise testing.ConclusionIn summary, there are persisting functional deficits at > 3 years following Achilles tendon repair which range from strength deficits to specific impairments of functional performance e.g. during heel rise. Anatomical reconstruction is associated with an improved functional performance potentially due to a more symmetric strength during end-range plantarflexion which transfers into a higher satisfaction during athletic activities.Level of evidenceIII, retrospective cohort study

The Validity and Reliability of a Kinect v2-Based Gait Analysis System for Children with Cerebral Palsy.

The aim of this study is to evaluate if Kinect is a valid and reliable clinical gait analysis tool for children with cerebral palsy (CP), and whether linear regression and long short-term memory (LSTM) recurrent neural network methods can improve its performance. A gait analysis was conducted on ten children with CP, on two occasions. Lower limb joint kinematics computed from the Kinect and a traditional marker-based Motion Analysis system were investigated by calculating the root mean square errors (RMSE), the coefficients of multiple correlation (CMC), and the intra-class correlation coefficients (ICC2,k). Results showed that the Kinect-based kinematics had an overall modest to poor correlation (CMC—less than 0.001 to 0.70) and an angle pattern similarity with Motion Analysis. After the calibration, RMSE on every degree of freedom decreased. The two calibration methods indicated similar levels of improvement in hip sagittal (CMC—0.81 ± 0.10 vs. 0.75 ± 0.22)/frontal (CMC—0.41 ± 0.35 vs. 0.42 ± 0.37) and knee sagittal kinematics (CMC—0.85±0.07 vs. 0.87 ± 0.12). The hip sagittal (CMC—0.97±0.05) and knee sagittal (CMC—0.88 ± 0.12) angle patterns showed a very good agreement over two days. Modest to excellent reliability (ICC2,k—0.45 to 0.93) for most parameters renders it feasible for observing ongoing changes in gait kinematics.

Recognizing knee pathologies by using gait dynamics via kernel principal component analysis and deterministic learning theory

This study concentrates on dynamical motion characteristics of knees during treadmill walking, and describes the application of kernel principal component analysis and deterministic learning theory to the detection of abnormal gait dynamics induced by knee pathologies. First, twelve-dimensional knee joint rotation and translation parameters are measured by a marker-based motion analysis system during treadmill walking. Second, the dimension of the gait parameter signal is reduced based on kernel principal component analysis. Third, gait dynamics underlying time-varying gait parameter signal is captured by using localized radial basis function neural networks through deterministic learning mechanism. This kind of dynamics information represents the frame-to-frame temporal change of kinematics and kinetics modifications during treadmill walking, which is shown to be sensitive to the variance during knee pathologies. Gait patterns are represented as the gait dynamics underlying time-varying gait parameters. The training patters under different knee pathologies further constitute a uniform training dataset, containing all kinds of gait dynamics under different knee pathologies. By comparing the training patterns with a test knee gait pattern to be recognized, a set of recognition errors are generated. The average $$L_1$$ norms of the errors are taken as the classification measure between the dynamics of the training gait patterns and the dynamics of the test pattern. A rapid recognition scheme can be achieved according to the smallest error principle. Experimental results show that encouraging recognition accuracy can be achieved. The proposed method is sensitive for the detection of knee pathologies and is capable of discharge of patients without knee pathologies.

Knee kinematics of ACL-deficient patients: A development of a portable motion analysis system

This study is to compare the knee kinematic measurements between the novel portable skin marker-based motion analysis system (Opti-Knee®) and a conventional system (Vicon®). Nineteen subjects were recruited and asked to perform stair descent with lower limb placed with skin markers. Knee kinematic data was computed from the trajectories of the skin markers. Pearson’s correlation coefficient and Root-mean-square deviation (RMSD) were used to analyze the data. For the waveform, sagittal plane rotation is strongly positive correlated between systems, while for axial and coronal plane rotation, it was moderately to strongly positive correlated in both normal (ACLN) and ACL-deficient (ACLD) group. Substantial difference between two groups was found in correlation of abduction/adduction in both stance and swing phase, as well as in external/internal rotation in all selected regions of interest. Moreover, the RMSD was larger in ACLN than in ACLD in three planes of rotation. The capability of Opti-Knee® in tracking lower limb sagittal plane rotation was comparable to Vicon®. However, for coronal and axial plane rotation, although the correlation to Vicon® in kinematic waveforms was moderately high, their ROM and peak values substantially deviated from the values in Vicon®.

Kinect-based assessment of lower limb kinematics and dynamic postural control during the star excursion balance test

Assessments using dynamic postural control tests, like the Star Excursion Balance Test (SEBT), in combination with three-dimensional (3D) motion analysis can yield critical information regarding a subject’s lower limb movement patterns. 3D analysis can provide a clear understanding of the mechanisms that lead to specific outcome measures on the SEBT. Currently, the only technology for 3D motion analysis during such tests is expensive marker-based motion analysis systems, which are impractical for use in clinical settings. In this study we validated the use of the Microsoft Kinect as a cost-effective and marker-less alternative to more complex and expensive gold-standard motion analysis systems. Ten healthy subjects performed the SEBT while their lower limb kinematics were measured concurrently using a traditional motion capture system and a single Kinect v2 sensor. Analyses revealed errors in lower limb kinematics of less than 5°, except for the knee frontal-plane angle (5.7°) in the posterior-lateral direction. Ensemble curve analyses supported these findings, showing minimal between-system differences in all directions. Additionally, we found that the Kinect displayed excellent agreement (ICC3,k=0.99) and consistency (ICC2,k=0.99) when assessing reach distances in all directions. These results indicate that this low-cost and easy to implement technology may provide to clinicians a simple tool to simultaneously assess reach distances while developing a clearer understanding of the lower extremity movement patterns associated with SEBT performance in healthy and injured populations.

La prothèse inversée d’épaule en chirurgie de reprise post-traumatique peut-elle rétablir les activités de la vie quotidienne ?

BackgroundFailed shoulder arthroplasty and failed internal fixation in fractures of the proximal humerus can benefit from implantation of a reverse total shoulder arthroplasty (RSA). While there is some evidence that RSA can improve function regarding range of motion (ROM), pain, satisfaction, and strength, there is sparse data how this translates into activities of daily living (ADLs). A marker-based 3D video motion analysis system has recently been designed that can measure changes of ROM in dynamic movements in every plane. The hypothesis was that a gain of maximum ROM also translates into the ability to perform ADLs and into a significant increase of ROM in ADLs. Materials and methodsSix consecutive patients, (5 women, 1 man; 2×failed arthroplasty, 4×failed open reduction and internal fixation) who received RSA were examined the day before and 1 year after shoulder replacement. A 3D motion analysis system using a novel upper extremity model measured active maximum values and ROM in four ADLs. ResultsComparing the pre- to the 1-year postoperative status, RSA resulted in a significant increase in mean maximum values for active flexion (humerus to thorax) of 37° (SD±23°), from 50° to 87° [P=0.005], and for active abduction averaging of 17° (SD±13°), from 52° to 69° [P=0.027]. The extension decreased significantly by about 8° (SD±16°), from a mean of 39° to 31° [P=0.009]. For active adduction and internal and external rotation there were trends for improvements, but no significant changes. Only three additional tasks of the ADL (out of 13/24 preoperatively) could be performed after revision surgery. Comparing the preoperative to the postoperative ROM in the ADLs in flexion/extension, ROM improved significantly in one (“tying an apron”) of four ADLs. There were no significant changes in the abduction-/adduction and internal/external rotation in any ADLs. ConclusionRSA in revision cases significantly improved maximum active flexion and abduction, but decreased extension in this series. However, the patients were only able to use this greater ROM to their benefit in one of four ADLs.

Can reverse shoulder arthroplasty in post-traumatic revision surgery restore the ability to perform activities of daily living?

BackgroundFailed shoulder arthroplasty and failed internal fixation in fractures of the proximal humerus can benefit from implantation of a reverse total shoulder arthroplasty (RSA). While there is some evidence that RSA can improve function regarding range of motion (ROM), pain, satisfaction, and strength, there is sparse data how this translates into activities of daily living (ADLs). A marker-based 3D video motion analysis system has recently been designed that can measure changes of ROM in dynamic movements in every plane. The hypothesis was that a gain of maximum ROM also translates into the ability to perform ADLs and into a significant increase of ROM in ADLs. Materials and methodsSix consecutive patients (5 women, 1 man; 2× failed arthroplasty, 4× failed open reduction and internal fixation) who received RSA were examined the day before and 1 year after shoulder replacement. A 3D motion analysis system using a novel upper extremity model measured active maximum values and ROM in four ADLs. ResultsComparing the pre- to the 1-year postoperative status, RSA resulted in a significant increase in mean maximum values for active flexion (humerus to thorax) of 37° (S.D. ±23°), from 50 to 87° [P=0.005], and for active abduction averaging of 17° (S.D. ±13°), from 52 to 69° [P=0.027]. The extension decreased significantly by about 8° (S.D. ±16°), from a mean of 39 to 31° [P=0.009]. For active adduction and internal and external rotation, there were trends for improvements, but no significant changes. Only three additional tasks of the ADL (out of 13/24 preoperatively) could be performed after revision surgery. Comparing the preoperative to the postoperative ROM in the ADLs in flexion/extension, ROM improved significantly in one (“tying an apron”) of four ADLs. There were no significant changes in the abduction/adduction and internal/external rotation in any ADLs. ConclusionRSA in revision cases significantly improved maximum active flexion and abduction, but decreased extension in this series. However, the patients were only able to use this greater ROM to their benefit in one of four ADLs.

Validation of the Microsoft Kinect as a Portable and Inexpensive Screening Tool for Identifying ACL Injury Risk

Objectives:A widespread screening tool to assess anterior cruciate ligament (ACL) injury risk should ideally be portable, inexpensive, markerless and easy to use. We hypothesize that our software program - for use with the Microsoft Kinect Motion Sensor - fulfills the above requirements. This study compares the measurements of knee abduction during a drop vertical jump (DVJ) between the Microsoft Kinect and the “gold standard” marker-based Vicon motion analysis system.Methods:Thirteen participants (10 male: 3 female; age 20-31) took part in this IRB approved study. Each participant performed between 5 and 7 DVJs, yielding a total of 84 DVJs. We simultaneously measured knee valgus motion (KVM) as measured from initial contact (IC) to the point of peak flexion (PF), frontal plane knee angle (FPKA) at both IC and PF, and knee-to-ankle separation (KASR) ratio measured at PF with the Kinect and Vicon systems. The intra-class correlation coefficient (ICC) (two-way, single measure, absolute agreement) was used to assess the degree of agreement between the Kinect and Vicon for each measure.Results:KVM had the lowest ICC value; 0.81 and 0.85 for the left and right leg, respectively. The other measures had similar ICC values of approximately 0.89 for both legs. Standard interpretations of the ICC suggest values above 0.75 indicate excellent agreement between the measurements (Table 1).Conclusion:This study demonstrates good correlation between the Microsoft Kinect and the Vicon system for measuring frontal plane knee kinematics during the DVJ. The DVJ test has been established as an ideal task for evaluating the motions that put athletes at risk for ACL injuries. Screening and early detection of ACL injury risk factors may lead to a relative risk reduction between 30% to 80% with an appropriate ACL injury prevention program. As compared to the “gold standard” Vicon system, the Microsoft Kinect is a portable, inexpensive, marker-less, and expedient system that likely has acceptable accuracy to become a practical means of mass screening of athletes for ACL injury risk factors. Further study will focus on validating the system with a larger and varied sample size and over a variety of functional tasks.

METHODOLOGICAL CONSIDERATION ON THIGH MARKER CLUSTERS ON KNEE VALGUS ANGLES IN SIDESTEP CUTTING AND VERTICAL DROP JUMPING

BackgroundRanking the athletes according to their knee valgus angle contributes to the development of screening tools for the risk of knee injury. However, studies used different thigh marker clusters to...

Concurrent validity of the Microsoft Kinect for assessment of spatiotemporal gait variables

Spatiotemporal characteristics of gait such as step time and length are often associated with overall physical function in clinical populations, but can be difficult, time consuming and obtrusive to measure. This study assessed the concurrent validity of overground walking spatiotemporal data recorded using a criterion reference – a marker-based three-dimensional motion analysis (3DMA) system – and a low-cost, markerless alternative, the automated skeleton tracking output from the Microsoft Kinect™ (Kinect). Twenty-one healthy adults performed normal walking trials while being monitored using both systems. The outcome measures of gait speed, step length and time, stride length and time and peak foot swing velocity were derived using supervised automated analysis. To assess the agreement between the Kinect and 3DMA devices, Bland–Altman 95% bias and limits of agreement, percentage error, relative agreement (Pearson's correlation coefficients: r) overall agreement (concordance correlation coefficients: rc) and landmark location linearity as a function of distance from the sensor were determined. Gait speed, step length and stride length from the two devices possessed excellent agreement (r and rc values >0.90). Foot swing velocity possessed excellent relative (r=0.93) but only modest overall (rc=0.54) agreement. Step time (r=0.82 and rc=0.23) and stride time (r=0.69 and rc=0.14) possessed excellent and modest relative agreement respectively but poor overall agreement. Landmark location linearity was excellent (R2=0.991). This widely available, low-cost and portable system could provide clinicians with significant advantages for assessing some spatiotemporal gait parameters. However, caution must be taken when choosing outcome variables as some commonly reported variables cannot be accurately measured.

Model-based approach for human kinematics reconstruction from markerless and marker-based motion analysis systems

Modeling tools related to the musculoskeletal system have been previously developed. However, the integration of the real underlying functional joint behavior is lacking and therefore available kinematic models do not reasonably replicate individual human motion. In order to improve our understanding of the relationships between muscle behavior, i.e. excursion and motion data, modeling tools must guarantee that the model of joint kinematics is correctly validated to ensure meaningful muscle behavior interpretation. This paper presents a model-based method that allows fusing accurate joint kinematic information with motion analysis data collected using either marker-based stereophotogrammetry (MBS) (i.e. bone displacement collected from reflective markers fixed on the subject's skin) or markerless single-camera (MLS) hardware. This paper describes a model-based approach (MBA) for human motion data reconstruction by a scalable registration method for combining joint physiological kinematics with limb segment poses. The presented results and kinematics analysis show that model-based MBS and MLS methods lead to physiologically-acceptable human kinematics. The proposed method is therefore available for further exploitation of the underlying model that can then be used for further modeling, the quality of which will depend on the underlying kinematic model.

Validity of the Microsoft Kinect for providing lateral trunk lean feedback during gait retraining

Gait retraining programs are prescribed to assist in the rehabilitation process of many clinical conditions. Using lateral trunk lean modification as the model, the aim of this study was to assess the concurrent validity of kinematic data recorded using a marker-based 3D motion analysis (3DMA) system and a low-cost alternative, the Microsoft Kinect™ (Kinect), during a gait retraining session. Twenty healthy adults were trained to modify their gait to obtain a lateral trunk lean angle of 10°. Real-time biofeedback of the lateral trunk lean angle was provided on a computer screen in front of the subject using data extracted from the Kinect skeletal tracking algorithm. Marker coordinate data were concurrently recorded using the 3DMA system, and the similarity and equivalency of the trunk lean angle data from each system were compared. The lateral trunk lean angle data obtained from the Kinect system without any form of calibration resulted in errors of a high (>2°) magnitude (mean error=3.2±2.2°). Performing global and individualized calibration significantly (P<0.001) improved this error to 1.7±1.5° and 0.8±0.8° respectively. With the addition of a simple calibration the anatomical position coordinates of the Kinect can be used to create a real-time biofeedback system for gait retraining. Given that this system is low-cost, portable and does not require any sensors to be attached to the body, it could provide numerous advantages when compared to laboratory-based gait retraining systems.

Wrist and shoulder posture and muscle activity during touch-screen tablet use: Effects of usage configuration, tablet type, and interacting hand

Due to its rapid growth in popularity, there is an imminent need for ergonomic evaluation of the touch-screen tablet computing form-factor. The aim of this study was to assess postures of the shoulders and wrists and their associated muscle activity during touch-screen tablet use. Fifteen experienced adult tablet users completed a set of simulated software tasks on two media tablets in a total of seven user configurations. Configurations consisted of a combination of a support condition (held with one hand, two hands or in a case), a location (on the lap or table surface), and a software task (web browsing, email, and game). Shoulder postures were measured by using an infra-red LED marker based motion analysis system, wrist postures by electro-goniometry, and shoulder (upper trapezius and anterior deltoid) and forearm (flexor carpi radialis, flexor carp ulnaris, and extensor radialis) muscle activity by surface electromyography. Postures and muscle activity for the wrist significantly varied across configurations and between hands, but not across the two tablets tested. Wrist extension was high for all configurations and particularly for the dominant hand when a tablet was placed on the lap (mean=38°). Software tasks involving the virtual keyboard (e-mailing) corresponded to higher wrist extensor muscle activity (50th percentile=9.5% MVC) and wrist flexion/extension acceleration (mean=322°/s2). High levels of wrist radial deviation were observed for the non-dominant hand when it was used to tilt and hold the tablet (mean=13°). Observed differences in posture and muscle activity of the shoulder were driven by tablet location. Touch-screen tablet users are exposed to extreme wrist postures that are less neutral than other computing technologies and may be at greater risk of developing musculoskeletal symptoms. Tablets should be placed in cases or stands that adjust the tilt of the screen rather than supporting and tilting the tablet with only one hand.