Repetitive Motion Analysis: Segmentation and Event Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Indexing 3-D human motion repositories for content-based retrieval
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
| Hi-index | 0.00 |
Automated measurement, analysis, and comparison of human motion during performance of workplace tasks or exercise therapy are core competencies required to realize many telemedicine applications. Ergonomic studies and telemonitoring of patients performing rehabilitation exercises are examples of applications that would benefit from a representation of complex human motion in a form amenable to comparison. We present a representation of joint motion suitable for the analysis of multidimensional angular joint motion time series data. Complex motion is reduced to a concatenation motion segments, where simple dynamic models approximate the observed motion on each segment. This compact representation still enables measurement of statistics familiar to ergonomics practitioners such as cycle length and task duration. An algorithm to obtain this representation from observed motion data (time series) is given. We introduce a metric, based on a kinetic energy-like measure, to compare motions. Experiments are presented to demonstrate the representation, its relationship to previous measures and the applicability of the kinetic energy metric for motion comparison.