Assessment of a three-dimensional robotic model for biomechanical-data acquisition of human movement

Objective evaluation of shoulder function using body-fixed sensors: a new way to detect early treatment failures?

BACKGROUND

Variable definitions of outcome (Constant score, Simple Shoulder Test [SST]) have been used to assess outcome after shoulder treatment, although none has been accepted as the universal standard. Physicians lack an objective method to reliably assess the activity of their patients in dynamic conditions. Our purpose was to clinically validate the shoulder kinematic scores given by a portable movement analysis device, using the activities of daily living described in the SST as a reference. The secondary objective was to determine whether this device could be used to document the effectiveness of shoulder treatments (for glenohumeral osteoarthritis and rotator cuff disease) and detect early failures.

METHODS

A clinical trial including 34 patients and a control group of 31 subjects over an observation period of 1 year was set up. Evaluations were made at baseline and 3, 6, and 12 months after surgery by 2 independent observers. Miniature sensors (3-dimensional gyroscopes and accelerometers) allowed kinematic scores to be computed. They were compared with the regular outcome scores: SST; Disabilities of the Arm, Shoulder and Hand; American Shoulder and Elbow Surgeons; and Constant.

RESULTS

Good to excellent correlations (0.61-0.80) were found between kinematics and clinical scores. Significant differences were found at each follow-up in comparison with the baseline status for all the kinematic scores (P < .015). The kinematic scores were able to point out abnormal patient outcomes at the first postoperative follow-up.

CONCLUSION

Kinematic scores add information to the regular outcome tools. They offer an effective way to measure the functional performance of patients with shoulder pathology and have the potential to detect early treatment failures.

A markerless sub-pixel motion estimation technique to reconstruct kinematics and estimate the centre of mass in posturography

A novel method to evaluate postural sway is presented: balance strategies are identified by applying a markerless image processing algorithm to video sequences obtained from commercially available systems. The motion estimation technique for the analysis of video sequences is a coarse to fine procedure based on the block matching algorithm (BMA). The method makes it possible to estimate the movement of selected elements on the scene with a sub-pixel precision. It has been done by applying a bicubic spline interpolation to the coarse results obtained by the BMA. Results achieved through the analysis of synthetic video tests make it possible to determine the accuracy of the proposed sub-pixel algorithm. Figures show how the proposed method can be confidently applied to evaluate postural sway. The proposed method has been applied to videos recorded during orthostatic posture trials in different conditions, and to combined tests where signals from a balance plate have been acquired simultaneously to the video sequence. The results show the usefulness of the proposed approach in order to evaluate balance strategies in posturography.

Handling missing marker coordinates in 3D analysis

The use of mathematical formulations to retrieve missing data is not usually implemented as an automated computer procedure. The purpose of this paper is to present a simple mathematical formulation that can be used to retrieve the coordinates of markers hidden during a task. A strategy based on the smoothness of the variation of distance between points is devised, which leads to an automated computer procedure for retrieving hidden skin markers or missing joint coordinates (missing 3D points). This approach has the advantage of not being restricted to the usual rigid-body assumption.