Assessment of human kinematic performance with non-contact measurements for tele-rehabilitation

 Aging of population is challenging the traditional rehabilitation services for various movement disorders. In the foreseeable future, tele-rehabilitation will be a contributive factor for the well-being of the older generation. This research has tackled a series of problems in developing an automated assessment tool for human kinematic performance in tele-rehabilitation with optoelectronic bio-kinematic motion capture devices and preliminarily confirmed its applicability.

E-Simulations for educating the professions in blended learning environments

This chapter introduces digital, role-based simulations as an emerging and powerful educational approach for the professions and for broader workforce development purposes. It is acknowledged that simulations used for education, professional development, and training, have a long history of development and use. The focus is on digital simulations (e-simulations) situated in blended learning environments and the improved affordances of the newer digital media used via the web to enhance the value of their contribution to learning and teaching in professional and vocationally-oriented fields. This is an area which has received less attention in the whole “e-learning” literature compared with the voluminous body of knowledge and practice on computer-mediated communication, online community building, social networking, and various forms of online (usually automated) assessment. A framework of blended e-simulation design is outlined. The chapter concludes by examining what the future might hold for simulations in further and higher education, and ongoing work-based learning.

Signal processing for automated EEG quality assessment

An automated signal quality assessment method was proposed for the EEG signals, which will help in testing new BCI algorithms so that the testing can be made on high quality signals only. This research includes the development of novel feature extraction technique and a new clustering algorithm for EEG signals.

Objective assessment of pilling of nonwoven fabrics using the two dimensional discrete wavelet transform

Fabric pilling is a serious problem for the apparel industry, causing an unsightly appearance and premature wear. Woolen products are particularly prone to pilling. Recently, a process for production of woolen nonwoven apparel fabrics has been commercialized in Australia, and may lead to new markets for Australian wool. However, the success of such nonwoven fabrics will partly rely on their propensity to pill. A key element in the control of fabric pilling is the evaluation of resistance to pilling by testing. Resistance to pilling is normally tested in the laboratory by processes that simulate accelerated wear, followed by a manual assessment of the degree of pilling by an expert based on a visual comparison of the sample to a set of test images. To bring more objectivity into the pilling rating process, a number of automated systems based on image analysis have been developed. The authors previously proposed a new method of image analysis based on the two-dimensional discrete wavelet transform to objectively measure the pilling intensity for woven fabrics. This paper presents preliminary work in extending this method to nonwoven fabrics.