Health monitoring of elderly in independent and assisted living

This paper aims to present a comprehensive solution for health monitoring of elderly in independent and assisted living. One mandatory requirement is on the provision of suitable medical devices and apparatus for regular health monitoring and data measurements of the elderly. Then, a user-friendly interface would help the upload of health-related data and measurements to a web portal in the Internet, which would provide a database and management service. The paper also discusses on the development of a Responsive Health Monitoring System which would provide automated data analysis and response to the collected data. The system is designed to provide real-time response to the needs of the elderly, as well as the regular health evaluation. It can deal with both emergency and routine events round the clock, with knowledge-based coordination and management. © 2012 IEEE.published_or_final_versionThe 2012 International Conference on Biomedical Engineering (ICoBE 2012), Perlis, Malaysia, 27-28 February 2012. In Proceedings of ICoBE, 2012, p. 553-55

Fabric inspection based on the Elo rating method

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Considerations and design on apps for elderly with mild-to-moderate dementia

Many elderly people suffer from dementia in their daily life. The symptoms of dementia include impairments in thinking, communicating and recalling things of the past. Dementia can be caused by brain damage incurred from stroke (brain infarct), injury or other diseases. Recently, research has indicated a potential rehabilitative role for touchscreen technology in dementia. Elders can use apps to aid recall in order to support activities of daily living. Memory and activity apps can be developed for people suffering from early dementia. This paper presents the current state of development in the field of cognitive tests. It has also presented the many considerations and design issues related to the development of apps for people with dementia. © 2015 IEEE.published_or_final_versio

An iteratively Reweighted Least Square algorithm for RSS-based sensor network localization

In this article, we give a new algorithm for localization based on RSS measurement. There are many measurement methods for localizing the unknown nodes in a sensor network. RSS is the most popular one due to its simple and cheap hardware requirement. However, accurate algorithm based on RSS is needed to obtain the positions of unknown nodes. Recent algorithms such as MDS(Multi-Dimensional Scaling)-MAP, PDM (Proximity Distance Matrix) cannot give accurate results based on RSS as the RSS signals always have large variations. Besides, recent algorithms on sensor network localization ignore the received signal strength (RSS) and thus get a disappointing accuracy. This is because they are mostly focused on the difference between the estimated distance and the real distance. This paper introduces a target function - signal-based maximum likelihood (SML), which uses the maximum likelihood based on the directly measured RSS signal. Inspired by the SMACOF (Scaling by Majorizing A COmplicated Function) algorithm, an iteration surrogate algorithm named IRLS (Iteratively Reweighted Least Square) is introduced to solve the SML. From the simulation results, the IRLS algorithm can give accurate results for RSS positioning. When compared with other popular algorithms such as MDS-MAP, PDM, and SMACOF, the error (distance between the estimated position and the actual position) calculated by IRLS is less than all the other algorithms. In anisotropic network, IRLS also has good performance. © 2011 IEEE.published_or_final_versionThe 2011 IEEE International Conference on Mechatronics and Automation (ICMA 2011), Beijing, China, 7-10 August 2011. In Proceedings of ICMA, 2011, p. 1085-109

Defect detection in textured materials using Gabor filters

Vision-based inspection of industrial materials such as textile webs, paper or wood requires the development of defect segmentation techniques based on texture analysis. In this work, a multi-channel filtering technique that imitates the early human vision process is applied to images captured online. This new approach uses Bernoulli's rule of combination for integrating images from different channels. Physical image size and yarn impurities are used as key parameters for tuning the sensitivity of the proposed algorithm. Several real fabric samples along with the result of segmented defects are presented. The results achieved show that the developed algorithm is robust, scalable and computationally efficient for detection of local defects in textured materials.published_or_final_versio

A Modified Differential Evolution with Heuristics Algorithm for Non-convex Optimization on Sensor Network Localization

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Human detection in crowded scenes

In this paper, our focus is to segment the foreground area for human detection. It is assumed that the foreground region has been detected. Accurate foreground contours are not required. The developed approach adopts a modified ISM (Implicit Shape Model) to collect some typical local patches of human being and their location information. Individuals are detected by grouping some local patches in the foreground area. The method can get good results in crowded scenes. Some examples based on CAVIAR dataset have been shown. A main contribution of the paper is that ISM model and joint occlusion analysis are combined for individual segmentation. There are mainly two advantages: First, with more sufficient information inside the foreground region, even the individuals inside a dense area can also be handled. Secondly, the method does not require an accurate foreground contour. A rough foreground area can be easily obtained in most situations. © 2010 IEEE.published_or_final_versionThe 17th IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, 26-29 September 2010. In Proceedings of the 17th ICIP, 2010, p. 721-72

Automated optical inspection of solder paste based on 2.5D visual images

In this paper, a special technique for the inspection of solder paste using directional LED lighting is presented. Conventional optical inspection method would depend on an image acquired from a camera mounted from the top. This 2D inspection of solder paste based on images is fast but is limited to defect such as bridge or no solder. Defects related to the volume of the printed solder paste or unevenness of the paste cannot be treated from a top image. The developed technique of this paper would involve the use of special directional side lighting to acquire two-and-a-half dimensional (2.5D) images from above the solder paste block. A sequence of three images is acquired and image processing is carried out for defect detection of the printed solder paste. The acquired images would highlight the geometrical features of the solder paste block. Solder paste inspection is then carried out based on the highlighted features. The proposed method can handle other types of defects that cannot be treated by conventional top light images. ©2009 IEEE.published_or_final_versio

Particle Filter for Targets Tracking with Motion Model

Real-time robust tracking for multiple non-rigid objects is a challenging task in computer vision research. In recent years, stochastic sampling based particle filter has been widely used to describe the complicated target features of image sequence. In this paper, non-parametric density estimation and particle filter techniques are employed to model the background and track the object. Color feature and motion model of the target are extracted and used as key features in the tracking step, in order to adapt to multiple variations in the scene, such as background clutters, object's scale change and partial overlap of different targets. The paper also presents the experimental result on the robustness and effectiveness of the proposed method in a number of outdoor and indoor visual surveillance scenes.published_or_final_versio

3-D measurement of solder paste using two-step phase shift profilometry

A two-step phase shift profilometry method (2-step PSP) with prefiltering and postfiltering stages is proposed to reconstruct the 3-D profile of solder paste. Two sinusoidal patterns which are π-out-of-phase are used in the 3-D reconstruction. The new method uses only two fringe patterns rather than four as the four-step phase shift profilometry (4-step PSP). In Fourier transform profilometry (FTP), a bandpass filter is required to extract the fundamental spectrum from the background and higher order harmonics due to camera noise and imperfectness of the pattern projector. By using two π-out-of-phase sinusoidal fringe patterns, the background term can be eliminated directly by taking the average of the two fringe patterns. The fringe pattern which is close to its ideal form can also be recovered from the averaging process. Prefiltering is utilized in filtering raw images to remove noise causing higher order harmonics. Hilbert transform is then used to obtain the in-quadrate component of the processed fringe pattern. Postfiltering is applied for reconstructing an appropriate 3-D profile. © 2008 IEEE.published_or_final_versio