Inertial and magnetic sensing of human movement near ferromagnetic materials

This paper describes a Kalman filter design to estimate orientation of human body segments by fusing gyroscope, accelerometer and magnetometer signals. Ferromagnetic materials near the sensor disturb the local magnetic field and therefore the orientation estimation. The magnetic disturbance can be detected by looking at the total magnetic density and a magnetic disturbance vector can be calculated. Results show the capability of this filter to correct for magnetic disturbances

3D motion analysis applying intertial sensing

Small inertial sensors like accelerometers and gyroscopes are more and more used in ambulatory motion analysis (Busseral. 1998; Baten et al. 2000; Veltink et al. 2003). Typically, angular orientation of a body segment is determined by integrating the output from the angular rate sensors strapped on the segment

Inertial and magnetic sensing of human motion

Movement and posture tracking of the human body is of great interest in many different disciplines such as monitoring of activities of daily living, assessment of working load in ergonomics studies, measurement of neurological disorders, computer animation, and virtual reality applications. This thesis deals with ambulatory position and orientation measurements of human body segments. Using inertial and magnetic sensing and actuation on the body, motion analysis can be performed anywhere, without the need for an expensive lab

Estimating Body Segment Orientation by Applying Inertial and Magnetic Sensing Near Ferromagnetic Materials

Inertial and magnetic sensors are very suitable for ambulatory monitoring of human posture and movements. However, ferromagnetic materials near the sensor disturb the local magnetic field and, therefore, the orientation estimation. A Kalman-based fusion algorithm was used to obtain dynamic orientations and to minimize the effect of magnetic disturbances. This paper compares the orientation output of the sensor fusion using three-dimensional inertial and magnetic sensors against a laboratory bound opto-kinetic system (Vicon) in a simulated work environment. With the tested methods, the difference between the optical reference system and the output of the algorithm was 2.6deg root mean square (rms) when no metal was near the sensor module. Near a large metal object instant errors up to 50deg were measured when no compensation was applied. Using a magnetic disturbance model, the error reduced significantly to 3.6deg rms

Ambulatory position and orientation tracking fusing magnetic and inertial sensing

This paper presents the design and testing of a portable magnetic system combined with miniature inertial sensors for ambulatory 6 degrees of freedom ( DOF) human motion tracking. The magnetic system consists of three orthogonal coils, the source, fixed to the body and 3-D magnetic sensors, fixed to remote body segments, which measure the fields generated by the source. Based on the measured signals, a processor calculates the relative positions and orientations between source and sensor. Magnetic actuation requires a substantial amount of energy which limits the update rate with a set of batteries. Moreover, the magnetic field can easily be disturbed by ferromagnetic materials or other sources. Inertial sensors can be sampled at high rates, require only little energy and do not suffer from magnetic interferences. However, accelerometers and gyroscopes can only measure changes in position and orientation and suffer from integration drift. By combing measurements from both systems in a complementary Kalman filter structure, an optimal solution for position and orientation estimates is obtained. The magnetic system provides 6 DOF measurements at a relatively low update rate while the inertial sensors track the changes position and orientation in between the magnetic updates. The implemented system is tested against a lab-bound camera tracking system for several functional body movements. The accuracy was about 5 mm for position and 3 degrees for orientation measurements. Errors were higher during movements with high velocities due to relative movement between source and sensor within one cycle of magnetic actuation

Compensation of Magnetic Disturbances Improves Inertial and Magnetic Sensing of Human Body Segment Orientation

This paper describes a complementary Kalman filter design to estimate orientation of human body segments by fusing gyroscope, accelerometer, and magnetometer signals from miniature sensors. Ferromagnetic materials or other magnetic fields near the sensor module disturb the local earth magnetic field and, therefore, the orientation estimation, which impedes many (ambulatory) applications. In the filter, the gyroscope bias error, orientation error, and magnetic disturbance error are estimated. The filter was tested under quasi-static and dynamic conditions with ferromagnetic materials close to the sensor module. The quasi-static experiments implied static positions and rotations around the three axes. In the dynamic experiments, three-dimensional rotations were performed near a metal tool case. The orientation estimated by the filter was compared with the orientation obtained with an optical reference system Vicon. Results show accurate and drift-free orientation estimates. The compensation results in a significant difference (p<0.01) between the orientation estimates with compensation of magnetic disturbances in comparison to no compensation or only gyroscopes. The average static error was 1.4/spl deg/ (standard deviation 0.4) in the magnetically disturbed experiments. The dynamic error was 2.6/spl deg/ root means square

Ambulatory human motion tracking by fusion of inertial and magnetic sensing with adaptive actuation

Over the last years, inertial sensing has proven to be a suitable ambulatory alternative to traditional human motion tracking based on optical position measurement systems, which are generally restricted to a laboratory environment. Besides many advantages, a major drawback is the inherent drift caused by integration of acceleration and angular velocity to obtain position and orientation. In addition, inertial sensing cannot be used to estimate relative positions and orientations of sensors with respect to each other. In order to overcome these drawbacks, this study presents an Extended Kalman Filter for fusion of inertial and magnetic sensing that is used to estimate relative positions and orientations. In between magnetic updates, change of position and orientation are estimated using inertial sensors. The system decides to perform a magnetic update only if the estimated uncertainty associated with the relative position and orientation exceeds a predefined threshold. The filter is able to provide a stable and accurate estimation of relative position and orientation for several types of movements, as indicated by the average rms error being 0.033 m for the position and 3.6 degrees for the orientation

Assessment of hand kinematics using inertial and magnetic sensors

Background:\ud Assessment of hand kinematics is important when evaluating hand functioning. Major drawbacks ofcurrent sensing glove systems are lack of rotational observability in particular directions, labourintensive calibration methods which are sensitive to wear and lack of an absolute hand orientationestimate.\ud \ud Methods:\ud We propose an ambulatory system using inertial sensors that can be placed on the hand, fingers andthumb. It allows a full 3D reconstruction of all finger and thumb joints as well as the absoluteorientation of the hand. The system was experimentally evaluated for the static accuracy, dynamicrange and repeatability.\ud \ud Results:\ud The RMS position norm difference of the fingertip compared to an optical system was 5±0.5 mm(mean ± standard deviation) for flexion-extension and 12.4±3.0 mm for combined flexion-extensionabduction-adduction movements of the index finger. The difference between index and thumb tipsduring a pinching movement was 6.5±2.1 mm. The dynamic range of the sensing system and filterwas adequate to reconstruct full 80 degrees movements of the index finger performed at 116 timesper minute, which was limited by the range of the gyroscope. Finally, the reliability study showed amean range difference over five subjects of 1.1±0.4 degrees for a flat hand test and1.8±0.6 degrees for a plastic mold clenching test, which is smaller than other reported data gloves.\ud \ud Conclusion:\ud Compared to existing data gloves, this research showed that inertial and magnetic sensors are of interest for ambulatory analysis of the human hand and finger kinematics in terms of static accuracy, dynamic range and repeatability. It allows for estimation of multi-degree of freedom joint movements using low-cost sensors

Gait analysis using ultrasound and inertial sensors

Introduction and past research:\ud Inertial sensors are great for orientation estimation, but they cannot measure relative positions of human body segments directly. In previous work we used ultrasound to estimate distances between body segments [1]. In [2] we presented an easy to use system for gait analysis in clinical practice but also in-home situations. Ultrasound range estimates were fused with data from foot-mounted inertial sensors, using an extended Kalman filter, for 3D (relative) position and orientation estimation of the feet.\ud \ud Validation:\ud From estimated 3D positions we calculated step lengths and stride widths and compared this to an optical reference system for validation. Mean (±standard deviation) of absolute differences was 1.7 cm (±1.8 cm) for step lengths and 1.2 cm (±1.2 cm) for stride widths when comparing 54 walking trials of three healthy subjects.\ud \ud Clinical application:\ud Next, the system presented in [2] was used in the INTERACTION project, for measuring eight stroke subjects during a 10 m walk test [3]. Step lengths, stride widths and stance and swing times were compared with the Berg balance scale score. The first results showed a correlation between step lengths and Berg balance scale scores. To draw real conclusions, more patients and also different activities will be investigated next.\ud \ud Future work:\ud In future work we will extend the system with inertial sensors on the upperand lower legs and the pelvis, to be able to calculate a closed loop and improve the estimation of joint angles compared with systems containing only inertial sensors

A preliminary investigation of the use of inertial sensing technology for the measurement of hip rotation asymmetry in horse riders

This study investigated the use of inertial sensing technology as an indicator of asymmetry in horse riders, evidenced by discrepancies in the angle of external rotation of the hip joint. Twelve horse and rider combinations were assessed with the rider wearing the XsensTM MVN inertial motion capture suit. Asymmetry (left vs right) was revealed in mean hip external rotation of all riders, with values ranging from 1° to 27°, and 83% showed greater external rotation of the right hip. This study represents novel use of inertial sensing equipment in its application to the measurement of rider motion patterns. The technique is non-invasive, is capable of recording rider hip rotation asymmetry whilst performing a range of movements unhindered and was found to be efficient and practical, with potential to further advance the analysis of horse and rider interactions