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

Characterizing full-body reach duration across task and viewpoint modalities

The full-body control of virtual characters is a promising technique for application fields such as Virtual Prototyping. However it is important to assess to what extent the user full-body behavior is modified when immersed in a virtual environment. In the present study we have measured reach durations for two types of task (controlling a simple rigid shape vs. a virtual character) and two types of viewpoint (1st person vs. 3rd person). The paper first describes the architecture of the motion capture approach retained for the on-line full-body reach experiment. We then present reach measurement results performed in a non-virtual environment. They show that the target height parameter leads to reach duration variation of ∓25% around the average duration for the highest and lowest targets. This characteristic is highly accentuated in the virtual world as analyzed in the discussion section. In particular, the discrepancy observed for the first person viewpoint modality suggests to adopt a third person viewpoint when controling the posture of a virtual character in a virtual environment

Quantifying Antalgic Gait Knee Function Using Inertial Sensor Technology

The use of body-fixed inertial sensors to analyze human movement may prove useful in the medical field. Improving orthopaedic device design, diagnosing musculoskeletal disorders, and rehabilitation assessment could all benefit from a mobile gait analysis system based on inertial sensors. More specifically, patients recovering from lower limb corrective surgeries tend to adjust gait patterns to accommodate pain, a condition referred to as antalgic gait. Currently there is no quantitative method available to assess recovery for this patient population during post-operative management. A comparison of the inertial sensor system with the camera-based industry standard has confirmed it as a viable method for lower limb motion analysis during normal gait. The inertial sensors consist of multiple accelerometers, gyroscopes and magnetometers used to obtain raw data, which is manipulated to calculate dynamic parameters. By comparing kinematic parameters between affected and unaffected limbs, it is possible to deduce a set of unique knee functionality ratios for recovering fracture patients. A control population was used to verify no significant difference (p \u3e 0.05) of seven kinematic parameters between limbs during normal gait. Parameters included peak knee flexion-extension angles at 15±5% and 75±5% gait cycle. These parameters were then analyzed in a group of patients recovering from lower limb fractures, using the unaffected limb as a control/reference. The goal of this project is to use inertial sensor technology to pinpoint specific kinematic parameters of the lower limb that are clinically appropriate in assessing knee function of lower limb fracture patients during the post-operative time span critical in normal gait recovery

Full-body performance animation with Sequential Inverse Kinematics

In this paper, we present an analytic-iterative Inverse Kinematics (IK) method, called Sequential lK (SIK), that reconstructs 3D human full-body movements in real time. The input data for the reconstruction is the least possible (i.e., the positions of wrists, ankles, head and pelvis) in order to be usable within a low-cost human motion capture system that Would track only these six features. The performance of our approach is compared to other well-known IK methods in reconstruction quality and computation time obtaining satisfactory results for both. The paper first describes how we handle the spine and the clavicles before offering a simple joint limit model for ball-and-socket joints and a method to avoid self-collisions induced by the elbow. The second part focuses on the algorithms comparison study. (c) 2008 Elsevier Inc. All rights reserved

Analysis of gait and coordination for arthroplasty outcome evaluation using body-fixed sensors

The importance of evaluation of an orthopedic operation such as hip or knee arthroplasty has long been recognized. Many definitions of outcome and scoring questionnaires have been used in the past to assess the outcome of joint replacement. However, these assessments are subjective and not accurate enough. In addition, orthopedic surgeons require now more subtle comparisons between potentially efficacious treatments (e.g. two types of prostheses). Therefore, the use of objective instruments that have a better sensitivity and specificity than traditional scoring systems is needed. Gait analysis is one of the most currently used instrumented techniques in this respect. However, a gait analysis system is accessible only in a few specialized laboratories, as it is complex, expensive, need a lot of room space and fixed devices, and not convenient for the patient. In this thesis, we proposed an ambulatory system based on kinematic sensors attached on the lower limbs to overcome the limitations of the previously mentioned techniques. Technically the device is portable, easily mountable, non-invasive, and capable of continuously recording data in long term without hindrance to natural gait. The goal was to provide gait parameters as a new objective method to assess Total Knee Replacement (TKR). New solutions to fusing the data of accelerometers and gyroscopes were proposed to accurately measure lower limbs orientations and joint angles. The methods propose a minimal sensor configuration with one sensor module mounted on each segment. The models consider anatomical aspects and biomechanical constraints. In the proposed techniques, the angles are found without the need for integration, so absolute angles can be obtained which are free from any source of drift. These data were then used to develop a gait analysis system providing spatio-temporal parameters, kinematic curves, and a visualization tool to animate the motion data as synthetic skeletons performing the same actions as the subjects. Moreover, a new algorithm was proposed for assessing and quantification of inter-joint coordination during gait. The coordination model captures the whole dynamics of the lower limbs movements and shows the kinematic synergies at various walking speeds. The model imposes a relationship among lower limb joint angles (hips and knees) to parameterize the dynamics of locomotion for each individual. It provides a coordination score at various walking speeds which is ranged between 0 and 10. An integration of different analysis tools such as Harmonic Analysis, Principal Component Analysis, and Artificial Neural Network helped overcome high-dimensionality, temporal dependence, and non-linear relationships of the gait patterns. In order to show the effectiveness of the proposed methods in outcome evaluation, we have considered a clinical study where the outcomes of two types of knee prostheses were compared. We conducted a randomized controlled study, including 54 patients, to assess TKR outcome between patients with fixed bearing and mobile bearing tibial plates of implants. The patients were tested preoperatively and postoperatively at 6 weeks, 3 months, 6 months, and 1 year. Various statistical analyses were done to compare the outcomes of the two groups. Finally, we provided objective criteria, using ambulatory gait analysis, for assessing functional recovery following TKR procedure. We showed significant difference between the two groups where the standard clinical evaluation was unable to detect such a difference