A multi-sensors system for human motion measurement: Preliminary setup (original) (raw)
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International Journal on Advanced Science, Engineering and Information Technology, 2020
Inside clinical research, gait analysis is a fundamental part of the functional evaluation of the human body's movement. Its evaluation has been carried out through different methods and tools, which allow early diagnosis of diseases, and monitoring and assessing the effectiveness of therapeutic plans applied to patients for rehabilitation. The observational method is one of the most used in specialized centers in Colombia; however, to avoid any possible errors associated with the subjectivity observation, technological tools that provide quantitative data can support this method. This paper deals with the methodological process for developing a computational tool and hardware device for the analysis of gait, specifically on articular kinematics of the knee. This work develops a prototype based on the fusion of inertial measurement units (IMU) data as an alternative for the attenuation of errors associated with each of these technologies. A videogrammetry technique measured the same human gait patterns to validate the proposed system, in terms of accuracy and repeatability of the recorded data. Results showed that the developed prototype successfully captured the kneejoint angles of the flexion-extension motions with high consistency and accuracy in with the measurements obtained from the videogrammetry technique. Statistical analysis (ICC and RMSE) exhibited a high correlation between the two systems for the measures of the joint angles. These results suggest the possibility of using an IMU-based prototype in realistic scenarios for accurately tracking a patient's knee-joint kinematics during a human gait.
Fusion of Multi-sensor based Biomechanical Gait Analysis using Vision and Wearable Sensor
IEEE Sensors Journal , 2021
The purpose of this research work is to investigate the biomechanics of pelvis, hip, knee, and ankle joint motion using a Kinect sensor & inertial measurement unit (IMU) sensor during the normal walk. In this paper, a very cost-effective gait analysis system based on Microsoft Kinect v2 and Inertial Measurement Unit (IMU) device is presented. Kinect sensor is used for acquiring 3D skeleton data (camera (x, y, z), depth (x, y) orientation (x, y, z, w), color (x, y)) with 25 human body joints. For this analysis, the lower extremities joints i.e. spinal cord joint, hip, knee, and ankle joints of both left and right legs are being considered. The main contribution of this research work is the joint angle calculation of lower extremities of human gait based on Microsoft Kinect sensor V2 and IMU sensor. From the law of cosine, the joint angle is calculated between the two joints and plotted for a single subject. We came with the observation that the characteristics of the human knee joint and ankle joint are inversely related to each other. There are two sharp humps for knee and ankle joints during the normal walk. During the swing phase, the knee joint is highly activated while during toe-off and heel strike it is least activated. This analysis of clinical data is very useful for prosthesis limb and exoskeleton design. The stability of calculated joints trajectories is validated using the limit cycle curve. A system is designed for real-time analysis of biomechanics of different lower limbs joints using gait.
Wearable Human Body Joint and Posture Measuring System
Proceedings of the International Conference on Biomedical Electronics and Devices, 2011
In many medical applications, especially the orthopaedic setting, ambulatory, monitoring of human joint angles could be of substantial value to improving rehabilitation strategies and unravelling the pathomechanics of many degenerative joint diseases (e.g. knee osteoarthritis). With the ageing of the population and increasing incidence of obesity, the prevalence of degenerative joint diseases is increasing (e.g. knee osteoarthritis is the single most common cause of pain and disability in middle-aged and older adults. As an example, In case of osteoarthritis rehabilitation, it is critical to monitor the loading of the affected joint during activities of daily living (ADL). These measurements allow monitoring of daily activity patterns, joint angles and walking patterns, which could be of use in adjusting the applied therapy depending on the results measured.
Development and testing of a device for human kinematics measurement
WSEAS TRANSACTIONS on …, 2009
This paper presents a simple, inexpensive, and fast procedure for motion kinematics measurement and analysis . System developed in our laboratory is based on a high speed industrial camera, active LED markers and a PC for handling cameras video stream and data analysis. Active markers used in this work were assembled using small, lightweight and easily available white LEDs. Smaller LEDs allow larger density of markers to be placed on a subject in motion, tracking position and orientation of all segments relevant for motion kinematic analysis. Computer vision algorithm for marker detection and tracking was developed in-house, followed by an algorithm for computing and analyzing kinematics data of human locomotion . Procedures for camera calibration and sub pixel accuracy were also developed and integrated with the system. The accuracy and properties of our system were tested, and results were compared with the existing referent systems presently used in the field. Results of testing marker -camera properties suggest that the system could support work in larger volumes (distances from camera) and almost perpendicular rotations of marker against camera. This property allows building of a 3D kinematics tracking system with two or more cameras placed at different angels against the subject in setup. Proposed system has a few disadvantages; measurements and results that are representative in only one plane and use of battery powered active markers that could disturb subject during normal gait trial. The major advantage of our system is that it offers acceptable accuracy, high speed (up to 320Hz) and easy upgradeability at much lower price when compared with the other commercially available systems . Further development of our system will include additional cameras for 3D marker tracking and integration with an inertial sensor for full kinematics and kinetic measurement of human movement.
Model of Soft Tissue Artifact Propagation to Joint Angles in Human Movement Analysis
Journal of Biomechanical Engineering, 2014
This work describes the kinematic laws that govern the transmission of soft tissue artifact errors to kinematic variables in the analysis of human movements. Artifacts are described as relative translations and rotations of the marker cluster over the bone, and a set of explicit expressions is defined to account for the effect of that relative motion on different representations of rotations: the rotation around the screw axis, or rotation vector, and three Euler angle sequences (XY′Z, YX′Y″, ZX′Y″). Although the error transmission is nonlinear in all cases, the effect of artifacts is greater on Euler sequences than on the rotation vector. Specifically, there are crosstalk effects in Euler sequences that amplify the errors near singular configurations. This fact is an additional source of variability in studies that describe artifacts by comparing the Euler angles obtained from skin markers, with the angles of an artifact-free gold standard. The transmission of errors to rotation ve...
Journal of biomechanics, 2017
Inertial sensor systems are becoming increasingly popular for gait analysis because their use is simple and time efficient. This study aimed to compare joint kinematics measured by the inertial sensor system RehaGait® with those of an optoelectronic system (Vicon®) for treadmill walking and running. Additionally, the test re-test repeatability of kinematic waveforms and discrete parameters for the RehaGait® was investigated. Twenty healthy runners participated in this study. Inertial sensors and reflective markers (PlugIn Gait) were attached according to respective guidelines. The two systems were started manually at the same time. Twenty consecutive strides for walking and running were recorded and each software calculated sagittal plane ankle, knee and hip kinematics. Measurements were repeated after 20min. Ensemble means were analyzed calculating coefficients of multiple correlation for waveforms and root mean square errors (RMSE) for waveforms and discrete parameters. After corr...
Technical Note: Three-dimensional Gait Analysis
Journal of Postgraduate Medicine, Education and Research
Quantitative gait analysis is the systematic measurement, description, and assessment of those quantities thought to characterize human locomotion. Optoelectronic motion capture system is a tool to conduct three-dimensional gait analysis and it helps us to acquire kinematic data, i.e., the angles and the kinetic data, i.e., forces along with spatiotemporal data which describe the fundamental gait characteristics. These are ultimately interpreted by the clinician(s) to form an assessment 1 which helps in identifying the pathology and developing rehabilitation strategies to restore normalcy of gait. Keeping in view the above evidence and the paucity of Indian normative gait data, our study was designed to create a gender-specific, region-specific, normative spatiotemporal, kinematic, and kinetic dataset. We present a technical note on our method of three-dimensional gait analysis. The gait lab at PGIMER is equipped with BTS SmartTM (BTS Bioengineering, Milan, Italy) Optoelectric system which was used to record and measure spatiotemporal, kinematic, and kinetic data. The gait lab has a walkway embedded with 16 force platforms with sufficient space for acceleration and deceleration coupled with 6 infrared cameras and two real-time cameras, enabling the recordings of left and right feet to be made simultaneously with each trial recording at least three complete gait cycles at a selfselected pace. The data were captured, processed, and analyzed with strict adherence to a standardized protocol. The data were recorded for transverse, sagittal, and axial planes.
Measurement, 2018
In recent years, the study of human body dynamics has been attracting a significant amount of attention. Currently there are many camera or active sensor based motion analysis systems available on the market. They have been extensively adopted and used by the film and animation or entertainment industries such as film and video game producers. More recently their potential in studying human dynamics / motion for medical purposes has been realised to the extent that they are now used to study full body human biomechanics in the form of gait analysis systems. Most orthopaedic surgeries are usually about joint repair or implants. According health line, revision surgery is usually due to infection, continued pain, joint stiffness, wear, instability, loosening. Apart from infection, the rest can be linked to the operation itself. Currently, surgical planning and placing implants is performed in a subjective manner, relying on the surgeon's experience and instinct, current systems to help the surgeon to place implant are also bulky, expensive, slow and not user friendly. The aim of this project is to develop an economic and portable motion assessment system which involves a wireless inertial measurement unit (IMU) dedicated to study and assess body joints. Through the data collected from the IMU, the system is capable real time measurement of relative position and orientation of the human joint. Several tests were conducted to validate the data extracted from gyroscope and accelerometer of the IMU. The joint motion results analysed using the device was compared with the results analysed using commercial video motion analysis software and it shows good correlation. It is found that the gyroscope of the IMU under DMP sensor fusion algorithm and calibration capability is able to give the angular velocity with less than 5% error. This has led to a more accurate orientation data which gives 7% error in average bending angle.