A method for estimating three-dimensional human arm movement with two electromagnetic sensors

A survey of human shoulder functional kinematic representations

In this survey, we review the field of human shoulder functional kinematic representations. The central question of this review is to evaluate whether the current approaches in shoulder kinematics can meet the high-reliability computational challenge. This challenge is posed by applications such as robot-assisted rehabilitation. Currently, the role of kinematic representations in such applications has been mostly overlooked. Therefore, we have systematically searched and summarised the existing literature on shoulder kinematics. The shoulder is an important functional joint, and its large range of motion (ROM) poses several mathematical and practical challenges. Frequently, in kinematic analysis, the role of the shoulder articulation is approximated to a ball-and-socket joint. Following the high-reliability computational challenge, our review challenges this inappropriate use of reductionism. Therefore, we propose that this challenge could be met by kinematic representations, that are redundant, that use an active interpretation and that emphasise on functional understanding.

Sensors on the humerus are not necessary for an accurate assessment of humeral kinematics in constrained movements

The measurement of humeral kinematics with a sensor on the humerus is susceptible to large errors due to skin motion artifacts. An alternative approach is to use data from a forearm sensor, combined with data from either a scapular or thoracic sensor. We used three tasks to assess the errors of these approaches: humeral elevation, elbow flexion and humeral internal rotation. Compared with the humeral method, the forearm methods (using either a scapular or thoracic sensor) demonstrated significantly smaller root mean square errors in humeral elevation and humeral internal rotation tasks. Although the errors of the forearm methods were significantly larger than those of the humeral method during elbow flexion, the errors of the forearm methods still were below 3°. Therefore, these forearm methods may be able to accurately measure humeral motion. In addition, since no difference was found between the forearm methods using the scapular or thoracic sensor, it may be possible to accurately assess both shoulder and elbow kinematics with only two sensors: one on the forearm and one on the scapula.

Accuracy and repeatability of parameter estimation methods from ambulatory data for the wrist joint

In this paper, as a preliminary study, we show that accuracy and repeatability in ambulatory measurements of wrist joint are related to movement conditions which are going to be used in a calibration procedure. We chose two representative in-vivo, non-invasive calibration methods of the human upper limb, from those available in literature, to estimate joint parameters. Developing an analytical model of wrist joint we used sets of synthetic data each of which containing different number of samples, joint covariations and noise to estimate the repeatability and accuracy of the methods in estimation. Afterwards, we used our mechanical mock-up to examine single joint motions as well as the rotation of both joints (i.e. flexion-extension rotation and radial-ulnar deviation) on accuracy and repeatability by calculating the mean and standard deviation of the relative errors. Finally, we show that the accuracy of adapted method (its relative error was less than 7%) is better than the other method in estimating the joint parameters.