Development of a mechatronic sorting system for removing contaminants from wool

Automated visual inspection (AVI) systems have been extended to many fields, such as agriculture and the food, plastic and textile industries. Generally, most visual systems only inspect product defects, and then analyze and grade them due to the lack of any sorting function. This main reason rests with the difficulty of using the image data in real time. However, it is increasingly important to either sort good products from bad or grade products into separate groups usingAVI systems. This article describes the development of a mechatronic sorting system and its integration with a vision system for automatically removing contaminants from wool in real time. The integration is implemented by a personal computer, which continuously processes live images under the Windows 2000 operating system. The developed real-time sorting approach is also applicable to many other AVI systems

L_(p)-error estimates for radial basis function interpolation on the sphere

In this paper we review the variational approach to radial basis function interpolation on the sphere and establish new Lp-error bounds, for p[1,∞]. These bounds are given in terms of a measure of the density of the interpolation points, the dimension of the sphere and the smoothness of the underlying basis function

A System in the Wild: Deploying a Two Player Arm Rehabilitation System for Children With Cerebral Palsy in a School Environment

This paper outlines a system for arm rehabilitation for children with upper-limb hemiplegia resulting from cerebral palsy. Our research team designed a two-player, interactive (competitive or collaborative) computer play therapy system that provided powered assistance to children while they played specially designed games that promoted arm exercises. We designed the system for a school environment. To assess the feasibility of deploying the system in a school environment, the research team enlisted the help of teachers and staff in nine schools. Once the system was set up, it was used to deliver therapy without supervision from the research team. Ultimately, the system was found to be suitable for use in schools. However, the overriding need for schools to focus on academic activities meant that children could not use the system enough to achieve the amount of use desired for therapeutic benefit. In this paper, we identify the key challenges encountered during this study. For example, there was a marked reluctance to report system issues (which could have been fixed) that prevented children from using the system. We also discuss future implications of deploying similar studies with this type of system

A Hand-Held Device Presenting Haptic Directional Cues for the Visually Impaired

Haptic information is essential in everyday activities, especially for visually impaired people in terms of real-world navigation. Since human haptic sensory processing is nonlinear, asymmetric vibrations have been widely studied to create a pulling sensation for the delivery of directional haptic cues. However, the design of an input control signal that generates asymmetric vibrations has not yet been parameterised. In particular, it is unclear how to quantify the asymmetry of the output vibrations to create a better pulling sensation. To better understand the design of an input control signal that generates haptic directional cues, we evaluated the effect of the pulling sensations corresponding to the three adjustable parameters (i.e., delay time, ramp-down step length, and cut-off voltage) in a commonly applied step-ramp input signal. The results of a displacement measurement and a psychophysical experiment demonstrate that when the quantified asymmetry ratio is in a range of 0.3430–0.3508 with an optimised cut-off voltage for our hand-held device, the haptic directional cues are better perceived by participants. Additionally, the results also showed a superior performance in haptic delivery by shear forces than normal forces

What is Hiding in Medicine's Dark Matter? Learning with Missing Data in Medical Practices

Electronic patient records (EPRs) produce a wealth of data but contain significant missing information. Understanding and handling this missing data is an important part of clinical data analysis and if left unaddressed could result in bias in analysis and distortion in critical conclusions. Missing data may be linked to health care professional practice patterns and imputation of missing data can increase the validity of clinical decisions. This study focuses on statistical approaches for understanding and interpreting the missing data and machine learning based clinical data imputation using a single centre's paediatric emergency data and the data from UK's largest clinical audit for traumatic injury database (TARN). In the study of 56,961 data points related to initial vital signs and observations taken on children presenting to an Emergency Department, we have shown that missing data are likely to be non-random and how these are linked to health care professional practice patterns. We have then examined 79 TARN fields with missing values for 5,791 trauma cases. Singular Value Decomposition (SVD) and k-Nearest Neighbour (kNN) based missing data imputation methods are used and imputation results against the original dataset are compared and statistically tested. We have concluded that the 1NN imputer is the best imputation which indicates a usual pattern of clinical decision making: find the most similar patients and take their attributes as imputation.Comment: 8 page

Feasibility of school-based computer-assisted robotic gaming technology for upper limb rehabilitation of children with cerebral palsy

We investigated the feasibility of using computer-assisted arm rehabilitation (CAAR) computer games in schools. Outcomes were children's preference for single player or dual player mode, and changes in arm activity and kinematics. Method: Nine boys and two girls with cerebral palsy (6-12 years, mean 9 years) played assistive technology computer games in single-user mode or with school friends in an AB-BA design. Preference was determined by recording the time spent playing each mode and by qualitative feedback. We used the ABILHAND-kids and Canadian Occupational Performance Measure to evaluate activity limitation, and a portable laptop-based device to capture arm kinematics. Results: No difference was recorded between single-user and dual-user modes (median daily use 9.27 versus 11.2 min, p = 0.214). Children reported dual-user mode was preferable. There were no changes in activity limitation (ABILHAND-kids, p = 0.424; COPM, p = 0.484) but we found significant improvements in hand speed (p = 0.028), smoothness (p = 0.005) and accuracy (p = 0.007). Conclusion: School timetables prohibit extensive use of rehabilitation technology but there is potential for its short-term use to supplement a rehabilitation program. The restricted access to the rehabilitation games was sufficient to improve arm kinematics but not arm activity