A Method to Analyse Generic Human Motion With Low-Cost Mocap Technologies

2018 ◽  
Author(s):  
Daniele Regazzoni ◽  
Andrea Vitali ◽  
Caterina Rizzi ◽  
Giorgio Colombo
Keyword(s):  
Low Cost ◽  
Sport Activity ◽  
Human Motion ◽  
The Body ◽  
Microsoft Kinect ◽  
Human Model ◽  
Digital Human Model ◽  
Working Volume ◽  
High Level ◽  
The Way

A number of pathologies impact on the way a patient can either move or control the movements of the body. Traumas, articulation arthritis or generic orthopedic disease affect the way a person can walk or perform everyday movements; brain or spine issues can lead to a complete or partial impairment, affecting both muscular response and sensitivity. Each of these disorder shares the need of assessing patient’s condition while doing specific tests and exercises or accomplishing everyday life tasks. Moreover, also high-level sport activity may be worth using digital tools to acquire physical performances to be improved. The assessment can be done for several purpose, such as creating a custom physical rehabilitation plan, monitoring improvements or worsening over time, correcting wrong postures or bad habits and, in the sportive domain to optimize effectiveness of gestures or related energy consumption. The paper shows the use of low-cost motion capture techniques to acquire human motion, the transfer of motion data to a digital human model and the extraction of desired information according to each specific medical or sportive purpose. We adopted the well-known and widespread Mocap technology implemented by Microsoft Kinect devices and we used iPisoft tools to perform acquisition and the preliminary data elaboration on the virtual skeleton of the patient. The focus of the paper is on the working method that can be generalized to be adopted in any medical, rehabilitative or sportive condition in which the analysis of the motion is crucial. The acquisition scene can be optimized in terms of size and shape of the working volume and in the number and positioning of sensors. However, the most important and decisive phase consist in the knowledge acquisition and management. For each application and even for each single exercise or tasks a set of evaluation rules and thresholds must be extracted from literature or, more often, directly form experienced personnel. This operation is generally time consuming and require further iterations to be refined, but it is the core to generate an effective metric and to correctly assess patients and athletes performances. Once rules are defined, proper algorithms are defined and implemented to automatically extract only the relevant data in specific time frames to calculate performance indexes. At last, a report is generated according to final user requests and skills.

Human Carrying Simulation With Symmetric and Asymmetric Loads

2012 ◽  
Author(s):  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Salam Rahmatalla ◽  
Hyun-Joon Chung ◽  
Rajan Bhatt ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Human Motion ◽  
Human Model ◽  
Physical Constraints ◽  
Digital Human Model ◽  
Load Carrying ◽  
Reaction Forces ◽  
Asymmetric Load ◽  
Optimization Schemes ◽  
Digital Human

Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Predictive dynamics approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joints dynamics using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion and ground reaction forces data during symmetric and asymmetric load carrying task. With such prediction capability the model could be used for biomedical and ergonomic studies.

Real-Time Motion Capture for a Human Body using Accelerometers

Robotica ◽  
2001 ◽  
Vol 19 (6) ◽  
pp. 601-610 ◽  
Author(s):  
Jihong Lee ◽  
Insoo Ha
Keyword(s):  
Real Time ◽  
Motion Capture ◽  
Human Body ◽  
Degrees Of Freedom ◽  
Low Cost ◽  
Human Motion ◽  
The Body ◽  
Sensor Data ◽  
Time Motion ◽  
Gravity Acceleration

In this paper we propose a set of techniques for a real-time motion capture of a human body. The proposed motion capture system is based on low cost accelerometers, and is capable of identifying the body configuration by extracting gravity-related terms from the sensor data. One sensor unit is composed of 3 accelerometers arranged orthogonally to each other, and is capable of identifying 2 rotating angles of joints with 2 degrees of freedom. A geometric fusion technique is applied to cope with the uncertainty of sensor data. A practical calibration technique is also proposed to handle errors in aligning the sensing axis to the coordination axis. In the case where motion acceleration is not negligible compared with gravity acceleration, a compensation technique to extract gravity acceleration from the sensor data is proposed. Experimental results not only for individual techniques but also for human motion capturing with graphics are included.

Music Control in an Interactive Conducting System Using Kinect

2013 ◽  
Vol 4 (4) ◽  
pp. 35-57
Author(s):  
Yi-Shin Chen ◽  
Leng-Wee Toh ◽  
Yi-Lan Liu
Keyword(s):  
Control Volume ◽  
Low Cost ◽  
Large Body ◽  
Microsoft Kinect ◽  
Conducting System ◽  
Practice Session ◽  
Musical Piece ◽  
Skill Levels ◽  
Training Tool ◽  
High Level

Music conducting is the art of directing musical ensembles with hand gestures to personalize and diversify a piece of music. Although the ability to successfully perform a musical piece demands intense training and coordination for the conductor and the orchestra, preparing a practice session is expensive and time-consuming. Hence, there is a genuine need for alternatives capable of providing adequate training for conductors at all skill levels. The potential use of virtual and augmented reality technology holds particular promise. The goal of this research is to examine the mechanics of music conducting and to develop a system capable of closely simulating the experience of conducting a piece of music. After extensive discussions with professional and nonprofessional conductors, in addition to wide-ranging research regarding music conducting materials, several key features of conducting were identified. A set of lightweight algorithms exploring these features was developed to enable tempo control, volume adjustment, and instrument emphasis, which are core components of conducting. Such a system would be a helpful training tool for students, an experiential tool allowing professional conductors and composers to shape music at a low cost, or an entertainment tool for nonprofessional music lovers. In this paper, we propose a real-time interactive conducting system using Microsoft Kinect. The proposed system overcomes the limitation of Kinect's design, which is generally designed for large body movements. In this system, delicate conducting signals can be correctly recognized without referencing any prior knowledge. Evaluation of the algorithms in real-world scenarios reveals promising results. The system was evaluated by conductors of all skill levels and provided a high level of accuracy and a low latency. Users of the final system expressed satisfaction with the virtual experience.

scholarly journals Human Body Simulation Within a Hybrid Operating Method for a Safe and Efficient Human-Robot Collaboration

2022 ◽  
pp. 191-202
Author(s):  
Kai Lemmerz ◽  
Bernd Kuhlenötter
Keyword(s):  
Production Systems ◽  
Separation Distance ◽  
Human Motion ◽  
Physical Contact ◽  
Human Model ◽  
Body Contact ◽  
Digital Human Model ◽  
Body Regions ◽  
And Performance ◽  
Human Robot Collaboration

AbstractThe planning and integration of production systems with a direct human-robot collaboration (HRC) is still associated with various technical challenges. This applies especially to the realization of the operation methods speed and separation monitoring (SSM) as well as power and force limiting (PFL). Due to the limited consideration of the human motion behaviour, the required dynamic separation distance in SSM is frequently oversized in practice. The main consequences are wasted space as well as cycle time and performance losses within the corresponding HRC application. In PFL a physical contact between the operator and robot is permissible, taking into account specified biomechanical thresholds. However, there is still a lack of suitable use-cases since the maximum permissible speeds are on a very low level. Moreover some thresholds regarding the transient contact case are still non-applicable for critical body areas (e.g. temple, middle of forehead). The study of this paper is related to a kinematic state determination of the human operator within a new hybrid collaborative operation. In this method the SSM type is extended regarding the description of the operator and coupled with the two-body contact model of the PFL. Using a planning and simulation tool for HRC, the kinematic states of different body regions are derived from an integrated and parameterized digital human model. Afterwards, these body regions are mapped to the characteristic body areas of the ISO/TS 15066, whereby the resulting information will be applied in an adaptive robot speed control. The performance of the presented concept will be evaluated using an exemplary simulated HRC scenario.

scholarly journals Functional Method for Joints Parameters Assessment in Human Body Modeling

2019 ◽  
Vol 8 (10) ◽  
pp. 1085-1089
Keyword(s):  
Gait Analysis ◽  
Sagittal Plane ◽  
Standard Technique ◽  
Optimization Method ◽  
Functional Method ◽  
Human Motion ◽  
The Body ◽  
Lower Limbs ◽  
Human Model ◽  
Biomechanical Models

The integration of proper algorithms and computer graphics-based systems seems promising for the design of biomechanical models and the relative motion analysis. Thus, consequences on research fields as gait analysis are gathered, focusing on joints kinematics. Human motion patterns are indeed directly influenced from human model and associated joints parameters, such as centers and axes of rotation. These, as a matter of fact, determine the body segments coordinates systems. Joints parameters are estimated with several methods. The aim of this research is to evaluate the consistency of a functional approach versus a the predictive one. A validation of the algorithm used to estimate the lower limbs joints centers in gait analysis is provided with a proper subject-specific multibody model implemented in OpenSim space. Joints angles are estimated using a global optimization method and a comparison with the gold standard technique is also discussed. Overall the obtained results are consistent for the two different methodologies. The correlation of the curves is excellent in the sagittal plane, and very good in the coronal and transversal plane.

Development of 3D Equipment Interaction With Predictive Dynamics in Human Motion Simulation

2016 ◽  
Author(s):  
Hyun-Joon Chung ◽  
Yujiang Xiang
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Reaction Force ◽  
Human Motion ◽  
The Body ◽  
Joint Torque ◽  
Human Model ◽  
Motion Simulation ◽  
Predictive Dynamics ◽  
Human Motion Simulation

3D equipment interaction module in human motion simulation is developed in this paper. A predictive dynamics method is used to simulate human motion, and a helmet is modeled as the equipment that is attached to the human body. We then implement this method using the predictive dynamics task of walking. A mass-spring-damper system is attached at the top of the head as a helmet model. The equations of motion for the helmet are also derived in a recursive Lagrangian formulation within the same inertial reference frame as the human model’s. The total number of degrees of freedom for the human model is 55 — 6 degrees of freedom for global translation and rotation, and 49 degrees of freedom for the body. The helmet has 7 degrees of freedom, but 6 of them are dependent to the human model. The movement of the helmet is analyzed due to the human motion. Then, the reaction force between the human body and the equipment is calculated. Once the reaction force is obtained, it is applied to the human body as an external force in the predictive dynamics optimization process. Results include the motion of equipment, the force acting on body at the attachment point, the joint torque profiles, and the ground reaction force profiles at the foot contacting point.

The Hybrid Predictive Dynamics Method for Analysis, Simulation and Prediction of Human Motion

2016 ◽  
Author(s):  
Mahdiar Hariri
Keyword(s):  
Motion Capture ◽  
Degrees Of Freedom ◽  
Human Motion ◽  
Human Model ◽  
Coordinate Frame ◽  
Optimization Approach ◽  
Predictive Dynamics ◽  
Digital Human Model ◽  
Digital Human ◽  
Dynamics Method

The ‘Hybrid Predictive Dynamics Method for Digital Human Modeling’ is analyzed in this work. The ‘Hybrid’ prefix mentioned in the literature recently [1], refers to the use of motion capture data for improving human motion simulations. This use of motion capture compensates for the inherent weaknesses of purely theoretical motion prediction due to deficiencies in computational power or available theoretical backgrounds. In this work, it is shown that while using the ‘Hybrid’ the more precisely and finely the human motion is modeled (if computational and theoretical limitations allow), the less will be the need for the ‘Hybrid’ method and the more will the human model be able to change the prediction if the inputs are varied (cause and effect). Several human motion scenarios are mentioned in this work. These motion tasks are: “Jogging around Markers”, “Rolling Over”, “Getting up from Prone”, “Vertical Jumping” and “Kneeling and Aiming”. The digital human model is a full-body, three dimensional model with 55 degrees of freedom. Six degrees of freedom specify the global position and orientation of the coordinate frame attached to the pelvic point of the digital human and 49 degrees of freedom represent the revolute joints which model the human joints and determine the kinematics of the entire digital human. Motion is generated by a multi-objective optimization approach. The optimization problem is subject to constraints which represent the limitations of the environment, the digital human model and the motion task. Design variables are the joint angle profiles. All the forces, inertial, gravitational as well as external, are known, except the ground reaction forces. The feasibility of the generation of that arbitrary motion by using the given ground contact areas is ensured by using the well-known Zero Moment Point (ZMP) constraint.

A Platform for Mechanical Assembly Education Using the Microsoft Kinect

2014 ◽  
Author(s):  
Yizhe Chang ◽  
El-Sayed Aziz ◽  
Zhou Zhang ◽  
Mingshao Zhang ◽  
Sven Esche ◽  
...  
Keyword(s):  
Undergraduate Students ◽  
Computer Aided Design ◽  
Motion Tracking ◽  
Low Cost ◽  
Financial Burden ◽  
Human Motion ◽  
Microsoft Kinect ◽  
Input Device ◽  
Mechanical Assembly ◽  
Mechanical Parts

Mechanical assembly activities involve multiple factors including humans, mechanical parts, tools and assembly environments. In order to simulate assembly processes by computers for educational purposes, all these factors should be considered. Virtual reality (VR) technology, which aims to integrate natural human motion into real-world scenarios, provides an ideal simulation medium. Novel VR devices such as 3D glasses, motion-tracking gloves, haptic sensors, etc. are able to fulfill fundamental assembly simulation needs. However, most of these implementations focus on assembly simulations for computer-aided design, which are geared toward professionals rather than students, thus leading to complicated assembly procedures not suitable for students. Furthermore, the costs of these novel VR devices and specifically designed VR platforms represent an untenable financial burden for most educational institutions. In this paper, a virtual platform for mechanical assembly education based on the Microsoft Kinect sensor and Garry’s Mod (GMod) is presented. With the help of the Kinect’s body tracking function and voice recognition technology in conjunction with the graphics and physics simulation capabilities of GMod, a low-cost VR platform that enables educators to author their own assembly simulations was implemented. This platform utilizes the Kinect as the sole input device. Students can use voice commands to navigate their avatars inside of a GMod powered virtual laboratory as well as use their body’s motions to integrate pre-defined mechanical parts into assemblies. Under this platform, assembly procedures involving the picking, placing and attaching of parts can be performed collaboratively by multiple users. In addition, the platform allows collaborative learning without the need for the learners to be co-located. A pilot study for this platform showed that, with the instructor’s assistance, mechanical engineering undergraduate students are able to complete basic assembly operations.

scholarly journals Validity of Pendant-Based IMU Assessment of Postural Stability Under Varying Balance Conditions Compared to a Sensor Positioned on the Lower Back

2019 ◽  
Vol 63 (1) ◽  
pp. 1159-1163 ◽  
Author(s):  
Shubo Lyu ◽  
Stephen Piazza ◽  
Danielle Symons Downs ◽  
Andris Freivalds
Keyword(s):  
Postural Stability ◽  
Low Cost ◽  
Center Of Mass ◽  
Roc Curves ◽  
The Body ◽  
Anova Analysis ◽  
Inertial Measurement ◽  
Lower Back ◽  
Measurement Units ◽  
High Level

Body-worn inertial measurement units (IMUs) have been widely used in postural stability and balance studies because of their low cost and high level of convenience. In most studies, single IMU sensors are put on the lower back attached to a belt, placing the sensor near the body’s center of mass (COM). For some populations, such as pregnant women, wearing the sensor on a belt over the lower back presents challenges in terms of fit and comfort. Thus, it may be necessary to identify a better location for the sensor and a more comfortable means for attaching the sensor to the body. This study aims to implement and test a novel pendant IMU sensor hanging from the subject’s neck and placed over the sternum. Three standing tasks (double-leg, tandem, and single-leg standing) were performed under open- and closed-eye conditions for preliminary assessments of the ability of the new sensor to discriminate between balance conditions. Standard deviations were analyzed in different conditions, along with ROC curves and ANOVA analysis. The results showed that the pendant sensor can detect the signals as good as the sensor on the waist.

Human Stair Ascent and Descent Simulations

2014 ◽  
Author(s):  
Yujiang Xiang ◽  
Joo H. Kim ◽  
Hyun-Joon Chung ◽  
James Yang ◽  
Hyun-Jung Kwon
Keyword(s):  
Degrees Of Freedom ◽  
Human Motion ◽  
Stair Climbing ◽  
Human Model ◽  
Physical Constraints ◽  
Digital Human Model ◽  
Stair Ascent ◽  
Reaction Forces ◽  
Optimization Schemes ◽  
Digital Human

Human stair ascent and descent are simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Hybrid predictive dynamics approach is used to predict the stair climbing motion with weapons and backpacks. In this process, the model predicts joints dynamics using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion and ground reaction forces data during stair climbing tasks. This can be used in human health domain such as leg prosthesis design.

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