Quantitative analysis of the morphing wing mechanism of raptors:IMMU-based motion capture system and its application on gestures of a Falco peregrinus

This paper presented a novel tinny motion capture system for measuring bird posture based on inertial and magnetic measurement units that are made up of micromachined gyroscopes, accelerometers, and magnetometers. Multiple quaternion-based extended Kalman filters were implemented to estimate the absolute orientations to achieve high accuracy.Under the guidance of ornithology experts, the extending/contracting motions and flapping cycles were recorded using the developed motion capture system, and the orientation of each bone was also analyzed. The captured flapping gesture of the Falco peregrinus is crucial to the motion database of raptors as well as the bionic design.

Kinematic calibration under the expectation maximization framework for exoskeletal inertial motion capture system

This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79%and 7.16%respectively in comparison to the traditional calibration method.

IMU-based motion capture system for rehabilitation applications: A systematic review

In recent years,the use of inertial measurement unit(IMU)-based motion capture(Mocap)systems in rehabilitation has grown significantly.This paper aimed to provide an overview of current IMUbased Mocap system designs in the field of rehabilitation,explore the specific applications and implementation of these systems,and discuss potential future developments considering sensor limitations.For this review,a systematic literature search was conducted using Scopus,IEEE Xplore,PubMed,and Web of Science from 2013 to 2022.A total of 65 studies were included and analyzed based on their rehabilitation application,target population,and system deployment and measurement.The proportion of rehabilitation assessment,training,and both were 82%,12%,and 6%respectively.The results showed that primary focus of the studies was stroke that was one of the most commonly studied pathological disease.Additionally,general rehabilitation without targeting a specific pathology was also examined widely,with a particular emphasis on gait analysis.The most common sensor configuration for gait analysis was two IMUs measuring spatiotemporal parameters of the lower limb.However,the lack of training applications and upper limb studies could be attributed to the limited battery life and sensor drift.To address this issue,the use of low-power chips and low-consumption transmission pathways was a potential way to extend usage time for long-term training.Furthermore,we suggest the development of a highly integrated multi-modal system with sensor fusion.

Differences between lower extremity joint running kinetics captured by marker-based and markerless systems were speed dependent

Background:The development of computer vision technology has enabled the use of markerless movement tracking for biomechanical analysis.Recent research has reported the feasibility of markerless systems in motion analysis but has yet to fully explore their utility for capturing faster movements,such as running.Applied studies using markerless systems in clinical and sports settings are still lacking.Thus,the present study compared running biomechanics estimated by marker-based and markerless systems.Given running speed not only affects sports performance but is also associated with clinical injury prevention,diagnosis,and rehabilitation,we aimed to investigate the effects of speed on the comparison of estimated lower extremity joint moments and powers between markerless and marker-based technologies during treadmill running as a concurrent validating study.Methods:Kinematic data from marker-based/markerless technologies were collected,along with ground reaction force data,from 16 young adults running on an instrumented treadmill at 3 speeds:2.24 m/s,2.91 m/s,and 3.58 m/s(5.0 miles/h,6.5 miles/h,and 8.0 miles/h).Sagittal plane moments and powers of the hip,knee,and ankle were calculated by inverse dynamic methods.Time series analysis and statistical parametric mapping were used to determine system differences.Results:Compared to the marker-based system,the markerless system estimated increased lower extremity joint kinetics with faster speed during the swing phase in most cases.Conclusion:Despite the promising application of markerless technology in clinical settings,systematic markerless overestimation requires focused attention.Based on segment pose estimations,the centers of mass estimated by markerless technologies were farther away from the relevant distal joint centers,which led to greater joint moments and powers estimates by markerless vs.marker-based systems.The differences were amplified by running speed.

Natural human–computer interaction control of multi operators in collaborative virtual maintenance based on optical human motion capture system

Aiming at the human–computer interaction control(HCIC)requirements of multi operators in collaborative virtual maintenance(CVM),real-time motion capture and simulation drive of multi operators with optical human motion capture system(HMCS)is proposed.The detailed realization process of real-time motion capture and data drive for virtual operators in CVM environment is presented to actualize the natural and online interactive operations.In order to ensure the cooperative and orderly interactions of virtual operators with the input operations of actual operators,collaborative HCIC model is established according to specific planning,allocating and decision-making of different maintenance tasks as well as the human–computer interaction features and collaborative maintenance operation features among multi maintenance trainees in CVM process.Finally,results of the experimental implementation validate the effectiveness and practicability of proposed methods,models,strategies and mechanisms.

Data compensation based on the additional feature information for collaborative interactive operation with optical human motion capture system

As the effective capture region of optical motion capture system is limited by quantity,installation mode,resolution and focus of infrared cameras,the reflective markers on certain body parts(such as wrists,elbows,etc.)of multi-actual trainees may be obscured when they perform the collaborative interactive operation.To address this issue,motion data compensation method based on the additional feature information provided by the electromagnetic spatial position tracking equipment is proposed in this paper.The main working principle and detailed realization process of the proposed method are introduced step by step,and the practical implementation is presented to illustrate its validity and efficiency.The results show that the missing capture data and motion information of relevant obscured markers on arms can be retrieved with the proposed method,which can avoid the simulation motions of corresponding virtual operators being interrupted and deformed during the collaborative interactive operation process performed by multiactual trainees with optical human motion capture system in a limited capture range.

Application of Optical Motion Capture Technology in Power Safety Entitative Simulation Training System

The safety production is critical to stable development of Chinese electric power industry. With the development of electric power enterprises, the requirements of its employees are also becoming higher and higher. In this paper, an optical motion capture system based on the virtual reality technology is proposed to meet the requirements of the power enterprise for the qualified business ability. Electric power equipment, power equipment model entitative operating environment and the human model are established by electric power simulation unit, ZigBee technology and OpenGL graphics library. The problem of missing feature points is solved by applying the human model driven algorithm and the Kalman filtering algorithm. The experimental results show that it is more accurate to use Kalman filtering algorithm to extract the feature point in tracking process of actual motion capture and real-time animation display. The average absolute error of 3D coordinates is 1.61 mm and the average relative error is 2.23%. The system can improve trainees’ sense of experience and immersion.

Silk road dance exhibition system based on motion capture

Silk Road dance is an excellent traditional Chinese dance drama, which has high artistic values. This article introduces the virtual performance techniques of Silk Road based on motion capture. First, obtain the dance data using motion capture technique according to the features of dance itself, then establish figure model, finally combines these data to make 3-D animation system to perform Silk Road, meanwhile designs some interfaces to introduce it. This system excavates details of the dance, and can be reference of man-machine interaction and animation production.

Review of techniques for motion capture data processing

In order to high reality and efficiency, the technique computer animation. With the development of motion capture, a of motion capture （MoCap） has been widely used in the field of large amount of motion capture databases are available and this is significant for the reuse of motion data. But due to the high degree of freedoms and high capture frequency, the dimension of the mo- tion capture data is usually very high and this will lead to a low efficiency in data processing. So how to process the high dimension data and design an efficient and effective retrieval approach has become a challenge which we can＇t ignore. In this paper, first we lay out some problems about the key techniques in motion capture data processing. Then the existing approaches are analyzed and sum- marized. At last, some future work is proposed.

Fast Individual Facial Animation Framework Based on Motion Capture Data

Based upon motion capture,a semi-automatic technique for fast facial animation was implemented. While capturing the facial expressions from a performer,a camera was used to record her /his front face as a texture map. The radial basis function( RBF) technique was utilized to deform a generic facial model and the texture was remapped to generate a personalized face.Partitioning the personalized face into three regions and using the captured facial expression data,the RBF and Laplacian operator,and mean-value coordinates were implemented to deform each region respectively. With shape blending,the three regions were combined together to construct the final face model. Our results show that the technique is efficient in generating realistic facial animation.

An Adaptive Hand Exoskeleton for Teleoperation System

Teleoperation can assist people to complete various complex tasks in inaccessible or high-risk environments,in which a wearable hand exoskeleton is one of the key devices.Adequate adaptability would be available to enable the master hand exoskeleton to capture the motion of human fingers and reproduce the contact force between the slave hand and its object.This paper presents a novel finger exoskeleton based on the cascading four-link closed-loop kinematic chain.Each finger has an independent closed-loop kinematic chain,and the angle sensors are used to obtain the finger motion including the flexion/extension and the adduction/abduction.The cable tension is changed by the servo motor to transmit the contact force to the fingers in real time.Based on the finger exoskeleton,an adaptive hand exoskeleton is consequently developed.In addition,the hand exoskeleton is tested in a master-slave system.The experiment results show that the adaptive hand exoskeleton can be worn without any mechanical constraints,and the slave hand can follow the motions of each human finger.The accuracy and the real-time capability of the force reproduction are validated.The proposed adaptive hand exoskeleton can be employed as the master hand to remotely control the humanoid five-fingered dexterous slave hand,thus,enabling the teleoperation system to complete complex dexterous manipulation tasks.

Automatic Key-Frame Extraction from Optical Motion Capture Data

Optical motion capture is an increasingly popular animation technique. In the last few years, plenty of methods have been proposed for key-frame extraction of motion capture data, and it is a common method to extract key-frame using quaternion. Here, one main difficulty is due to the fact that previous algorithms often need to manually set various parameters. In addition, it is problematic to predefine the appropriate threshold without knowing the data content. In this paper, we present a novel adaptive threshold-based extraction method. Key-frame can be found according to quaternion distance. We propose a simple and efficient algorithm to extract key-frame from a motion sequence based on adaptive threshold. It is convenient with no need to predefine parameters to meet certain compression ratio. Experimental results of many motion captures with different traits demonstrate good performance of the proposed algorithm. Our experiments show that one can typically cut down the process of extraction from several minutes to a couple of seconds.

Technological advancements in the analysis of human motion and posture management through digital devices

Technological development of motion and posture analyses is rapidly progressing,especially in rehabilitation settings and sport biomechanics.Consequently,clear discrimination among different measurement systems is required to diversify their use as needed.This review aims to resume the currently used motion and posture analysis systems,clarify and suggest the appropriate approaches suitable for specific cases or contexts.The currently gold standard systems of motion analysis,widely used in clinical settings,present several limitations related to marker placement or long procedure time.Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical studies,especially outside laboratories.Similarly,new posture analysis techniques are emerging,often driven by the need for fast and non-invasive methods to obtain high-precision results.These new technologies have also become effective for children or adolescents with non-specific back pain and postural insufficiencies.The evolutions of these methods aim to standardize measurements and provide manageable tools in clinical practice for the early diagnosis of musculoskeletal pathologies and to monitor daily improvements of each patient.Herein,these devices and their uses are described,providing researchers,clinicians,orthopedics,physical therapists,and sports coaches an effective guide to use new technologies in their practice as instruments of diagnosis,therapy,and prevention.

Marker-Based and Marker-Less Motion Capturing Video Data: Person and Activity Identification Comparison Based on Machine Learning Approaches

Biomechanics is the study of physiological properties of data and the measurement of human behavior.In normal conditions,behavioural properties in stable form are created using various inputs of subconscious/conscious human activities such as speech style,body movements in walking patterns,writing style and voice tunes.One cannot perform any change in these inputs that make results reliable and increase the accuracy.The aim of our study is to perform a comparative analysis between the marker-based motion capturing system(MBMCS)and the marker-less motion capturing system(MLMCS)using the lower body joint angles of human gait patterns.In both the MLMCS and MBMCS,we collected trajectories of all the participants and performed joint angle computation to identify a person and recognize an activity(walk and running).Using five state of the art machine learning algorithms,we obtained 44.6%and 64.3%accuracy in person identification using MBMCS and MLMCS respectively with an ensemble algorithm(two angles as features).In the second set of experiments,we used six machine learning algorithms to obtain 65.9%accuracy with the k-nearest neighbor(KNN)algorithm(two angles as features)and 74.6%accuracy with an ensemble algorithm.Also,by increasing features(6 angles),we obtained higher accuracy of 99.3%in MBMCS for person recognition and 98.1%accuracy in MBMCS for activity recognition using the KNN algorithm.MBMCS is computationally expensive and if we redesign the model of OpenPose with more body joint points and employ more features,MLMCS(low-cost system)can be an effective approach for video data analysis in a person identification and activity recognition process.

Reconfiguration of face expressions based on the discrete capture data of radial basis function interpolation

Compactly supported radial basis function can enable the coefficient matrix of solving weigh linear system to have a sparse banded structure, thereby reducing the complexity of the algorithm. Firstly, based on the compactly supported radial basis function, the paper makes the complex quadratic function （Multiquadric, MQ for short） to be transformed and proposes a class of compactly supported MQ function. Secondly, the paper describes a method that interpolates discrete motion capture data to solve the motion vectors of the interpolation points and they are used in facial expression reconstruction. Finally, according to this characteris- tic of the uneven distribution of the face markers, the markers are numbered and grouped in accordance with the density level, and then be interpolated in line with each group. The approach not only ensures the accuracy of the deformation of face local area and smoothness, but also reduces the time complexity of computing.

Methodical Approach to Integrate Human Movement Diversity in Real-Time into a Virtual Test Field for Highly Automated Vehicle Systems

Recently, virtual realities and simulations play important roles in the development of automated driving functionalities. By an appropriate abstraction, they help to design, investigate and communicate real traffic scenario complexity. Especially, for edge cases investigations of interactions between vulnerable road users (VRU) and highly automated driving functions, valid virtual models are essential for the quality of results. The aim of this study is to measure, process and integrate real human movement behaviour into a virtual test environment for highly automated vehicle functionalities. The overall system consists of a georeferenced virtual city model and a vehicle dynamics model, including probabilistic sensor descriptions. By motion capture hardware, real humanoid behaviour is applied to a virtual human avatar in the test environment. Through retargeting methods, which enable the independency of avatar and person under test (PuT) dimensions, the virtual avatar diversity is increased. To verify the biomechanical behaviour of the virtual avatars, a qualitative study is performed, which funds on a representative movement sequence. The results confirm the functionality of the used methodology and enable PuT independence control of the virtual avatars in real-time.

An error-based micro-sensor capture system for real-time motion estimation

A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities.In the proposed filter algorithm,the gyroscope bias error,orientation error and magnetic disturbance error are estimated and compensated,significantly reducing the orientation estimation error due to sensor noise and drift.Displacement estimation,especially for activities such as jumping,has been the challenge in micro-sensor motion capture.An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities.The performance of this system is benchmarked with respect to the results of VICON optical capture system.The experimental results have demonstrated effectiveness of the system in daily activities tracking,with estimation error 0.16 ± 0.06m for normal walking and 0.13 ± 0.11m for jumping motions.

PESTA: An Elastic Motion Capture Data Retrieval Method

Prevalent use of motion capture(MoCap)produces large volumes of data and MoCap data retrieval becomes crucial for efficient data reuse.MoCap clips may not be neatly segmented and labeled,increasing the difficulty of retrieval.In order to effectively retrieve such data,we propose an elastic content-based retrieval scheme via unsupervised posture encoding and strided temporal alignment(PESTA)in this work.It retrieves similarities at the sub-sequence level,achieves robustness against singular frames and enables control of tradeoff between precision and efficiency.It firstly learns a dictionary of encoded postures utilizing unsupervised adversarial autoencoder techniques and,based on which,compactly symbolizes any MoCap sequence.Secondly,it conducts strided temporal alignment to align a query sequence to repository sequences to retrieve the best-matching sub-sequences from the repository.Further,it extends to find matches for multiple sub-queries in a long query at sharply promoted efficiency and minutely sacrificed precision.Outstanding performance of the proposed scheme is well demonstrated by experiments on two public MoCap datasets and one MoCap dataset captured by ourselves.

Experimental hydrodynamic assessment of a cylindrical-type floating solar system exposed to waves

In this paper,an experimental investigation on the wave loads and structural motions of two semi-fixed semi-immersed horizontal cylinders type rafts in the free surface zone is conducted.The physical mod-els are tested at the 1:4.5 scale and exposed to a range of regular and irregular waves in a wave flume at Queen’s University Belfast.The physical models and experimental setup are discussed alongside an in-vestigation of the hydrodynamic phenomena,surge forces,and dynamic responses that each structure ex-hibits in the coastal wave climates.Furthermore,an investigation into the wave attenuation by both mod-els is carried out.The results show that the surge forces have a positive correlation with wave steepness for both models.Hydrodynamic phenomena such as wave runup and overtopping,radiative damping and reflected waves,constructive interference,diffraction and flow separation were identified during the ex-periments.A negative mean heave displacement is observed during the monochromatic sea states which could result in impact loading and submergence of the superstructure components and photovoltaic pan-els at full-scale.The results presented in this paper may be used to calibrate and verify numerical models that calculate the global responses and hydrodynamic forces.It may also benefit the design processes of geometrically similar floating solar technologies by providing data on surge loads,motion responses and hydrodynamic observations.

Experimental investigation on single person's jumping load model

This paper presents a modified half-sine-squared load model of the jumping impulses for a single person. The model is based on a database of 22,921 experimentally measured single jumping load cycles from 100 test subjects. Threedimensional motion capture technology in conjunction with force plates was employed in the experiment to record jumping loads. The variation range and probability distribution of the controlling parameters for the load model such as the impact factor, jumping frequency and contact ratio, are discussed using the experimental data. Correlation relationships between the three parameters are investigated. The contact ratio and jumping frequency are identified as independent model parameters, and an empirical frequency-dependent function is derived for the impact factor. The feasibility of the proposed load model is established by comparing the simulated load curves with measured ones, and by comparing the acceleration responses of a single-degree-of-freedom system to the simulated and measured jumping loads. The results show that a realistic individual jumping load can be generated by the proposed method. This can then be used to assess the dynamic response of assembly structures.