John K. Zao

Wedjat: A Mobile Phone Based Medicine In-take Reminder and Monitor

Out-patient medication administration has been identified as the most error-prone procedure in modern health¬care. Under or over doses due to erratic in-takes, drug-drug or drug-food interactions caused by un-reconciled prescriptions and the absence of in-take enforcement and monitoring mechanisms have caused medication errors to become the common cases of all medical errors. Most medication administration errors were made when patients bought different prescribed and over-the-counter medicines from several drug stores and use them at home without little or no guidance. Elderly or chronically ill patients are particularly susceptible to these mistakes. In this paper, we introduce Wedjat, a smart phone application designed to help patients avoiding these mistakes. Wedjat can remind its users to take the correct medicines on time and record the in-take schedules for later review by healthcare professionals. Wedjat has two distinguished features: (1) it can alert the patients about potential drug-drug/drug-food interactions and plan a proper in-take schedule to avoid these interactions; (2) it can revise the in-take schedule automatically when a dose was missed. In both cases, the software always tries to produce the simplest schedule with least number of in-takes. Wedjat is equipped with user friendly interfaces to help its users to recognize the proper medicines and obtain the correct instructions of taking these drugs. It can maintain the medicine in-take records on board, synchronize them with a data¬base on a host machine or upload them onto a Personal Heath Record (PHR) system. A proof-of-concept prototype of Wedjat has been implemented on Window Mobile platform and will be migrated onto Android for Google Phones. This paper introduces the system concept and design principles of Wedjat with emphasis on its medication scheduling algorithms and the modular implementation of mobile computing application.

On the optimization of degree distributions in LT code with covariance matrix adaptation evolution strategy

Luby Transform code (LT code) has been a popular and practical technique in the field of channel coding since its proposal. One of the key components of LT code is a degree distribution which is used to determine the relationship between source data and codewords. Luby in his proposal suggested two general methods to construct feasible degree distributions. Such general designs work appropriately in typical situations but not optimally in most cases. To explore the full potential of LT code, in this work, we make the first attempt to introduce evolutionary algorithms to optimize the degree distribution in LT code. Degree distributions are encoded as real-valued vectors and evaluated by numerical simulation of LT code. For applications of different natures, two objectives are implemented to search good degree distributions with different decoding behavior. Compared with the original design, the experimental results are quite promising and demonstrate that the degree distribution can be customized for different purposes. In addition to manually adjusting the degree distribution as the common practice, the work presented in this paper provides an efficient alternative approach to use and adapt LT code for both practitioners and researchers.

Optimizing degree distributions in LT codes by using the multiobjective evolutionary algorithm based on decomposition

Luby Transform code (LT code) is the first practical digital fountain code and has been widely used as basic components in many communication applications. The coding behavior of LT code is mainly decided by a probability distribution of codeword degrees. In order to customize a degree distribution for different purposes, multi-objective evolutionary algorithm is introduced to optimize degree distributions in this paper. Two critical performance indicators of LT code are considered in our experiments. Some applications hope to minimize the overhead of extra packets and some require to limit the computational cost of the coding system. To handle this problem, MOEA/D is applied to optimize two objectives simultaneously. We expect to obtain the Pareto front (PF) formed by partial optimal solutions and provide those available degree distributions to different LT code applications. Not only promising results are represented in this paper but also the behavior of LT code is thoroughly explored by optimizing the degree distribution according to multi-objectives.

Smart phone based medicine in-take scheduler, reminder and monitor

Out-patient medication administration was identified as the most error-prone procedure in modern healthcare. Most medication administration errors were made when patients ac-quired prescribed and over-the-counter medicines from several drug stores and use them at home without proper guidance. In this paper, we introduce Wedjat, a smart phone application that helps patients to avoid these mistakes. Wedjat can remind its users to take the correct medicines on time and keep an in-take record for later review by healthcare professionals. Wedjat has two distinguished features: (1) it can alert the patients about potential drug-drug/drug-food interactions and plan an in-take schedule that avoids these adverse interactions; (2) it can revise an in-take schedule automatically when a dose was missed. In both cases, the software always produces the simplest schedule with least number of in-takes. Wedjat works with the calendar application available on most smart phones to issue medicine and meal reminders. It also shows pictures of the medicine and pro-vides succinct in-take instructions. As a telemonitoring device, Wedjat can maintain medicine in-take records on board, syn-chronize them with a database on a host machine or upload them onto an electronic medical records (EMR) system. A prototype of Wedjat has been implemented on Window Mobile platform. This paper introduces the design concepts of Wedjat with emphasis on its medication scheduling and grouping algorithms.

iMAT: Intelligent medication administration tools

iMAT is a system of automatic medication dispensers and software tools. It is for people who take medications on long term basis at home to stay well and independent. The system helps its users to improve rigor in compliance by preventing misunderstanding of medication directions and making medication schedules more tolerant to tardiness and negligence. This paper presents an overview of the assumptions, models, architecture and implementation of the system.

Strategies For Crowdsourcing ForDisaster Situation Information

When existing surveillance sensors used by a disaster warning and response system cannot provide adequate data for situation assessment purposes, crowdsourcing information collection can be an effective solution: People armed with wireless devices and social network services can be used as mobile human sensors. Eye-witness reports from them can complement data from in-situ physical sensors and provide the system with more extensive and detailed sensor coverage. The crowdsourcing strategy used by the system can be random, relying solely on mobility of individuals for coverage of the threatened area; or crowddriven, with the system providing situation updates as feedbacks to aid the crowd; or system-driven with individuals moving in response to directives from the system. The relative merits of the strategies clearly depend on the disaster scenario and the characteristics of the crowd. This paper presents a general crowd model for characterizing individuals within a crowd and the crowd as a whole and an abstract mobility model of crowd movements in the threatened area. The models can be specialized to characterize different disaster scenarios and crowds and used in simulation of the crowdsourcing strategies for evaluation purposes. Data on relative performance of different strategies for two types of disasters were thus obtained.

A rate-distortion optimization model for SVC inter-layer encoding and bitstream extraction

The Scalable Video Coding (SVC) standard enables viewing devices to adapt their video reception using bitstream extraction. Since SVC offers spatial, temporal, and quality combined scalability, extracting proper bitstreams for different viewing devices can be a non-trivial task, and naive choices usually produce poor playback quality. In this paper, we propose a two-prong approach to achieve rate-distortion (R-D) optimal extraction of SVC bitstreams. For SVC encoding, we developed a set of adaptation rules for setting the quantization parameters and the inter-layer dependencies among the SVC coding layers. A well-adapted SVC bitstream thus produced manifests good R-D trade-offs when its scalable layers are extracted along extraction paths consisting of successive refinement steps. For extracting R-D optimized bitstreams for different viewing devices, we formalized the notion of optimal and near-optimal extraction paths and devised computationally efficient strategies to search for the extraction paths. Experiment results demonstrated that our R-D optimized adaptation schemes and extraction strategies offer significant improvement in playback picture quality among heterogeneous viewing devices. Particularly, our adaptation rules promise R-D convexity along optimal extraction paths and permit the use of steepest-descent strategy to discover the optimal/near-optimal paths. This simple search strategy performs only half of the computation necessary for an exhaustive search.

Integrating Non-Repetitive LT Encoders With Modified Distribution to Achieve Unequal Erasure Protection

The performance of LT code is highly related to the code length. A decoder is more likely to deplete degree-1 encoding symbols and terminate during early stage when the code length is short. In this work, we modify the robust Soliton distribution (RSD) and increase the degree-1 proportion. More degree-1 encoding symbols can be generated to relieve early decoding termination. The proportion of low degrees, except for degree-1, is also reduced. Therefore, receivers collect less encoding symbols carrying redundant information. In addition, Non-Repetitive (NR) encoding scheme is proposed to avoid producing repeated degree-1 encoding symbols. To improve video transmission quality, previous studies redesign LT codes to provide Unequal Error Protection (UEP) for different Scalable Video Coding (SVC) layers. Unlike those studies to modify the code structure, we integrate multiple NR encoders to achieve UEP ability. Experimental results show that our UEP scheme outperforms previous studies in terms of the PSNR.

Polychromatic SSVEP stimuli with subtle flickering adapted to brain-display interactions

OBJECTIVE Interactive displays armed with natural user interfaces (NUIs) will likely lead the next breakthrough in consumer electronics, and brain-computer interfaces (BCIs) are often regarded as the ultimate NUI-enabling machines to respond to human emotions and mental states. Steady-state visual evoked potentials (SSVEPs) are a commonly used BCI modality due to the ease of detection and high information transfer rates. However, the presence of flickering stimuli may cause user discomfort and can even induce migraines and seizures. With the aim of designing visual stimuli that can be embedded into video images, this study developed a novel approach to induce detectable SSVEPs using a composition of red/green/blue flickering lights. APPROACH Based on the opponent theory of colour vision, this study used 32 Hz/40 Hz rectangular red-green or red-blue LED light pulses with a 50% duty cycle, balanced/equal luminance and 0°/180° phase shifts as the stimulating light sources and tested their efficacy in producing SSVEP responses with high signal-to-noise ratios (SNRs) while reducing the perceived flickering sensation. MAIN RESULTS The empirical results from ten healthy subjects showed that dual-colour lights flickering at 32 Hz/40 Hz with a 50% duty cycle and 180° phase shift achieved a greater than 90% detection accuracy with little or no flickering sensation. SIGNIFICANCE As a first step in developing an embedded SSVEP stimulus in commercial displays, this study provides a foundation for developing a combination of three primary colour flickering backlights with adjustable luminance proportions to create a subtle flickering polychromatic light that can elicit SSVEPs at the basic flickering frequency.

Design of optimal short-length LT codes using evolution strategies

Luby Transform (LT) and its companion Raptor codes are the most popular implementations of digital fountain codes. Performance of these rateless forward erasure correction codes is determined mainly by the degree distributions of their encoded symbols. Although the asymptotic behaviors of LT codes with large (>;105) symbol blocks have been deduced analytically, a proficient method for finding the optimal degree distributions of short length (<;103) LT codes is still absent. In this paper, we propose a practical approach to employ evolution strategies in finding the degree distributions of optimal short-length LT codes for different applications. Our approach begins with the development of a new performance model for LT codes based on three measurements: coding overhead ε, failure ratio r and failure occurrence probability p. Three evolution strategies (DE, CMA-ES and NES) were then employed to minimize these performance measurements separately with careful design of fitness functions and necessary transformations of decision variables. Throughout the evolution process, the performance of individual LT code in the population was evaluated with numerical simulations. Our experiments showed that the optimal degree distributions can be found using all three evolution strategies but with different convergence rates and the (r,p,ε) values of these optimized codes are all distributed on a smooth concave surface.