Transient waveform matching based on ascending multi-wavelets for diagnostics and prognostics of bearing deterioration.

Run-to-failure experiment is efficient and effective to investigate bearing deterioration process. Periodic transient waveform carries rich information of health conditions of bearings but the transient waveform matching is a challenging problem for evaluating bearing fatigue life because the shapes and parameters of the waveform vary with the evolution of the bearing degradation. A wavelet function such as a Morlet wavelet is able to extract essential features from the transient waveform but limited to a single transient component.

Automatic classification of pathological gait patterns using ground reaction forces and machine learning algorithms.

An automated gait classification method is developed in this study, which can be applied to analysis and to classify pathological gait patterns using 3D ground reaction force (GRFs) data. The study involved the discrimination of gait patterns of healthy, cerebral palsy (CP) and multiple sclerosis subjects. The acquired 3D GRFs data were categorized into three groups.

Formation of an internal model of environment dynamics during upper limb reaching movements: a fuzzy approach.

This paper presents the development and simulation of a fuzzy logic based learning mechanism to emulate human motor learning. In particular, fuzzy inference was used to develop an internal model of a novel dynamic environment experienced during planar reaching movements with the upper limb. A dynamic model of the human arm was developed and a fuzzy if-then rule base was created to relate trajectory movement and velocity errors to internal model update parameters.