Biomedical subjects

ChunMei Lu

Publications and source records attributed to ChunMei Lu.

3 recordsLinked to original sources

PubMed2004

A digital video system for the automated measurement of repetitive joint motion.

Automated measurement and analysis of human motion during performance of workplace tasks are desirable for ergonomic studies. While numerous technologies exist for accurate measurement of biomechanical data, their use is often not feasible in the workplace environment. We present a digital-video based system suitable for measuring human motion of repetitive workplace tasks. Due to practical considerations, a single-camera solution is exploited by adding some control over the environment. We present an analysis of experiments demonstrating the accuracy of our system.

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PubMed2004

Repetitive motion analysis: segmentation and event classification.

Acquisition, analysis, and classification of repetitive human motion for the assessment of postural stress is of central importance to ergonomics practitioners. We present a two-threshold, multidimensional segmentation algorithm to automatically decompose a complex motion into a sequence of simple linear dynamic models. No a priori assumptions were made about the number of models that comprise the full motion or about the duration of the task cycle. A compact motion representation is obtained for each segment using parameters of a damped harmonic dynamic model. Event classification was performed using cluster analysis with the model parameters as input. Experiments demonstrate the technique on complex motion.

Algorithms↗

PubMed2003

Automated analysis of repetitive joint motion.

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.

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