Wireless Motion Capture System Research Articles

Comparison of different techniques for prehospital cervical spine immobilization: Biomechanical measurements with a wireless motion capture system.

Various rescue techniques are used for the prehospital transport of trauma patients. This study compares different techniques in terms of immobilization of the cervical spine and the rescue time. A wireless motion capture system (Xsens Technologies, Enschede, The Netherlands) was used to record motion in three-dimensional space and the rescue time in a standardized environment. Immobilization was performed by applying different techniques through different teams of trained paramedics and physicians. All tests were performed on the set course, starting with the test person lying on the floor and ending with the test person lying on an ambulance cot ready to be loaded into an ambulance. Six different settings for rescue techniques were examined: rescue sheet with/without rigid cervical collar (P1S1, P1S0), vacuum mattress and scoop stretcher with/without rigid cervical collar (P2S1, P2S0), and long spinal board with/without rigid cervical collar (P3S1, P3S0). Four time intervals were defined: the time interval in which the rigid cervical collar is applied (T0), the time interval in which the test person is positioned on rescue sheet, vacuum mattress and scoop stretcher, or long spinal board (T1), the time interval in which the test person is carried to the ambulance cot (T2), and the time interval in which the ambulance cot is rolled to the ambulance (T3). An ANOVA was performed to compare the different techniques. During the simulated extrication procedures, a rigid cervical collar provided biomechanical stability at all angles with hardly any loss of time (mean angle ranges during T1: axial rotation P1S0 vs P1S1 p<0.0001, P2S0 vs P2S1 p<0.0001, P3S0 vs P3S1 p<0.0001; lateral bending P1S0 vs P1S1 p = 0.0263, P2S0 vs P2S1 p<0.0001, P3S0 vs P3S1 p<0.0001; flexion/extension P1S0 vs P1S1 p = 0.0023, P2S0 vs P2S1 p<0.0001). Of the three techniques examined, the scoop stretcher and vacuum mattress were best for reducing lateral bending in the frontal plane (mean angle ranges during T1: P2S1 vs P3S1 p = 0.0333; P2S0 vs P3S0 p = 0.0123) as well as flexion and extension in the sagittal plane (mean angle ranges during T2: P1S1 vs P2S1 p<0.0001; P1S0 vs P2S0 p<0.0001). On the other hand, the rescue sheet was clearly superior in terms of time (total duration P1S0 vs P2S0 p<0.001, P1S1 vs P2S1 p<0.001, P1S0 vs P3S0 p<0.001, P1S1 vs P3S1 p<0.001) but was always associated with significantly larger angular ranges of the cervical spine during the procedure. Therefore, the choice of technique depends on various factors such as the rescue time, the available personnel, as well as the severity of the suspected instability.

Wireless Motion Capture System for Upper Limb Rehabilitation

This work is devoted to the presentation of a Wireless Sensor System implementation for upper limb rehabilitation to function as a complementary system for a patient’s progress supervision during rehabilitation exercises. A cost effective motion capture sensor node composed by a 9 Degrees-of-Freedom (DoF) Inertial Measurement Unit (IMU) is mounted on the patient’s upper limb segments and sends wirelessly the corresponding measured signals to a base station. The sensor orientation and the upper limb individual segments movement in 3-Dimensional (3D) space are derived by processing the sensors’ raw data. For the latter purpose, a biomechanical model which resembles that of a kinematic model of a robotic arm based on the Denavit-Hartenberg (DH) configuration is used to approximate in real time the upper limb movements. The joint angles of the upper limb model are estimated from the extracted sensor node’s orientation angles. The experimental results of a human performing common rehabilitation exercises using the proposed motion capture sensor node are compared with the ones using an off-the-shelf sensor. This comparison results to very low error rates with the root mean square error (RMSE) being about 0.02 m.

Kinematic dataset of actors expressing emotions

Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emotions. Therefore, we aimed to produce a comprehensive dataset to assist in recognizing cues from all parts of the body that indicate six basic emotions (happiness, sadness, anger, fear, disgust, surprise) and neutral expression. The present dataset was created using a portable wireless motion capture system. Twenty-two semi-professional actors (half male) completed performances according to the standardized guidance and preferred daily events. A total of 1402 recordings at 125 Hz were collected, consisting of the position and rotation data of 72 anatomical nodes. To our knowledge, this is now the largest emotional kinematic dataset of the human body. We hope this dataset will contribute to multiple fields of research and practice, including social neuroscience, psychiatry, computer vision, and biometric and information forensics.

Effects of Developmental Task Constraints on Kinematic Synergies during Catching in Children with Developmental Delays

The aim of this study was to examine effects of a task intervention on kinematic synergies in catching. Participants were young children (5.58 ± 0.52 years) with the lowest scores on two-hand catching, according to assessments with the Test of Gross Motor Development-2 (TGMD-2) and were allocated into two groups. The constraints group took part in an 8-week intervention, whereas the control group experienced a typical physical education. Both groups were assessed with motor development and kinematic coordination measures with a catching task with a ball thrown from 2 m distance. Kinematic variables were recorded using a wireless motion capture system. A principal component analysis (PCA) was used to measure the kinematic synergies formed among active body parts. Two synergies that emerged in catching were mainly utilised for “reaching” and “catching” the ball. The control group tended to re-organise the majority of active body parts into two functional units in all phases, whereas the constraints group adapted their active parts into functional units according to the requirement of the novel movement in the transfer task. The findings of this study suggested that task constraints could facilitate object control by re-organisation of active body parts into functional synergies to achieve successful performance.

Novel techniques for a wireless motion capture system for the monitoring and rehabilitation of disabled persons for application in smart buildings.

Due to the problem of aging societies, there is a need for smart buildings to monitor and support people with various disabilities, including rheumatoid arthritis. The aim of this paper is to elaborate on novel techniques for wireless motion capture systems for the monitoring and rehabilitation of disabled people for application in smart buildings. The proposed techniques are based on cross-verification of distance measurements between markers and transponders in an environment with highly variable parameters. To their verification, algorithms that enable comprehensive investigation of a system with different numbers of transponders and varying ambient parameters (temperature and noise) were developed. In the estimation of the real positions of markers, various linear and nonlinear filters were used. Several thousand tests were carried out for various system parameters and different marker locations. The results show that localization error may be reduced by as much as 90%. It was observed that repetition of measurements reduces localization error by as much as one order of magnitude. The proposed system, based on wireless techniques, offers a high commercial potential. However, it requires extensive cooperation between teams, including hardware and software design, system modelling, and architectural design.

A Portable Wireless Motion Capture System for Patients with Myotonic Dystrophy (P1.339)

A Portable Wireless Motion Capture System for Patients with Myotonic Dystrophy (P1.339)

Latent space segmentation for mobile gait analysis

An unsupervised learning algorithm is presented for segmentation and evaluation of motion data from the on-body Orient wireless motion capture system for mobile gait analysis. The algorithm is model-free and operates on the latent space of the motion, by first aggregating all the sensor data into a single vector, and then modeling them on a low-dimensional manifold to perform segmentation. The proposed approach is contrasted to a basic, model-based algorithm, which operates directly on the joint angles computed by the Orient sensor devices. The latent space algorithm is shown to be capable of retrieving qualitative features of the motion even in the face of noisy or incomplete sensor readings.

Design of Multi-User Aerobics Wireless Human Motion Capture System Based on MEMS

Main characteristics of recent human motion capture systems are analyzed in the paper firstly. Based on that, a new multi-user aerobics wireless human motion capture system based on MEMS is proposed. Design of its framework and core technology solutions including large-scale data obtain, multi-hop wireless sensor and high-frequency real-time transmission are put forward. Finally, three-dimensional real-time reconstructions of the multi-user aerobics wireless motion capture system are showed in the paper.

Numerical Study on the Improvement of Detection Accuracy for a Wireless Motion Capture System

A detection technique having an accuracy of better than 1 mm is required for body motion analysis in the field of medical treatment. A wireless magnetic motion capture system is one such effective detection technique. We propose a candidate system using an LC resonant magnetic marker (LC marker). Previous studies have showed that the system is capable of repeatable position detection accuracy of better than 1 mm if the system has an adequate signal-to-noise (S/N ratio). However, there are some cases in which the detection results include unignorable errors because some approximations, e.g. a magnetic dipole assumption of the LC marker, are applied to solve the inverse problem to determine the position and orientation of the LC marker. Therefore, a numerical analysis is employed to realize a motion capture system having a high detection accuracy. To elucidate the problem of detection error, the influence of variations in the sizes of the LC marker and the pick-up coil are considered in the numerical simulation. After studying the analysis, the main cause of detection error is determined to be the size of the pick-up coil rather than the size of the LC marker. It was also is found that a pick-up coil measuring 10 mm in diameter with a wound coil width of 1 mm achieves a detection accuracy of better than 0.1 mm.

1P1-A23 6軸モーションセンサの応用 : 姿勢センサモジュール(長野県におけるロボティクス・メカトロニクス)

Motion sensing technologies are continuously having developed for analyzing or controlling the actual dynamic robotic motions, which are getting quicker and more complex. In this paper, a new skew matrix operation shall be introduced to describe 3D dynamic high speed rotation. With this technology in combination with six-axis motion sensor, a tiny wireless motion capture system will be realized soon.

Development of real-time and highly accurate wireless motion capture system utilizing soft magnetic core

Highly accurate wireless motion capture system using LC resonant magnetic marker has been developed. The marker consists of soft magnetic core with wound coil and a chip capacitor without battery or electric wires, driven wirelessly by the action of electromagnetic induction. The system realized the position accuracy is less than 1 mm within the space of 150 mm from the pickup coil array. Compared with dc magnetic system, the proposed system is applicable for precision motion-capturing under optically isolated space without magnetic shielding because the system is not influenced very much by the earth field noise.

Wireless motion capture system using magnetically coupled LC resonant marker

A novel motion capture system using magnetically coupled LC resonant marker have been developed. This system composed from the LC marker, a driving coil and a pickup coil array. The marker consists only of an inductor and a capacitor without battery or electric wires, and driven wirelessly by the action of electromagnetic induction. The position accuracy was around 2 mm when the marker was located within the space of 50 mm apart from the pickup coil array. The system is applicable for highly accurate motion capturing without magnetic shielding because the system is free from the earth field. Additionally, it has a possibility of a multi-point motion capturing because the system allow markers to have an individual frequency band.