Majid A. Al-Taee

Remote Monitoring of Vehicle Diagnostics and Location Using a Smart Box with Global Positioning System and General Packet Radio Service

This paper presents a distributed system for remote monitoring of vehicle diagnostics and geographical position. This is achieved by using on-board microcomputer system, called on-board smart box (OBSB), general packet radio service (GPRS) and a remote server. The OBSB which is equipped with an integrated global positioning system (GPS) receiver is empowered by a software application that manages the processes of local data acquisition and transmission of the acquired data to the remote server via GPRS. When programmed with speed limits in a certain geographical region, the OBSB allows the traffic control authority to supervise violations of speed limits from inside vehicles rather than outside supervision via certain check points. Appropriate vocal and text warning messages are issued when a vehicle exceeds the permitted speed limit at a certain location. A prototype system is designed and implemented with a small number of sensors. On-road experiments have demonstrated the robustness, efficiency and applicability of the proposed system.

Audio-watermarking based ownership verification system using enhanced DWT-SVD technique

Audio watermarking has been proposed as an effective solution to solve or mitigate the new challenges of audio ownership verification. These challenges arose from easiness of copying and distributing of audio applications. This paper proposes important performance enhancements to a previously-reported audio ownership verification system based upon utilizing a combination of Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) techniques. A new audio signal framing, DWT matrix formation and embedding methods are proposed and successfully implemented to improve the minimum audio-cover period, quality of the watermarked audio and its robustness against various attacks. Performance evaluation of the developed system demonstrated improvements of 69% in the required minimum audio-cover period, 25% in the Signal-to-Noise Ratio (SNR), and improved robustness against various watermarking benchmark attacks.

Mobile health platform for diabetes management based on the Internet-of-Things

This paper presents a new Internet of Thing (IoT)-based platform to support self-management of diabetes. This mobile health (mHealth) approach allows for multiple care dimensions of diabetes by means of remote collection and monitoring of patient data and provision of personalized and customized feedback on a smartphone platform. Such support to self-management of diabetes enables real-time clinical interaction and feedback tailored to the personal needs of the patient, utilizing current and historical patient data. The platform understands to what extent the patients activities comply with their individual treatment plans, deriving rule-based health indicators, and generating appropriate warnings and support in terms of feedback advices. The physical layer of the platform incorporates wireless nodes; each of which encompasses a set of medical sensors linked wirelessly to a mobile device. The physical layer nodes are linked to a Web-based application layer through an existing telecommunication infrastructure. A fully functional prototype system is designed, implemented, and its end-to-end functionality is tested successfully, with high patient acceptability levels demonstrated by means of a clinician-led pilot study.

Web-of-Things inspired e-Health platform for integrated diabetes care management

Integration of physical objects (or things) within the Web has become a goal for current and future health care systems. In this paper, we propose a new e-Health platform driven by the needs of integrated diabetes care management. Architecture of this platform that is designed to be consistent with the concepts of Web-of-Things (WoT) comprises a physical sensors layer linked to a health Web-portal layer via an existing network infrastructure. The physical layer incorporates wireless nodes; each of which comprises a set of medical sensors linked wirelessly to a humanoid robot. Unlike existing e-Health systems, the proposed system is designed to support self-management of Type 1 diabetes mellitus (TIDM) not only through remote data collection and monitoring of patients data, but also through offering a support platform for real-time decisions and long-term social and behavioral change. These support services are delivered to the patients over a distance through daily patient-robot interactions that are either automatically generated be the system or assigned by specialist physicians. A prototype e-health platform which incorporates all these healthcare attributes is designed, implemented, and its end-to-end functionality is tested successfully with the aid of NHS collaborators.

Mobile‐based interpreter of arterial blood gases using knowledge‐based expert system

Purpose – An arterial blood gas (ABG) interpretation remains indispensable tool to assess and monitor critically ill patients in the intensive care unit or other critical care settings. This paper proposes a mobile‐based interpreter for ABG tests with the aim of providing accurate diagnosis in face of multiple acid‐base and oxygenation disorders. The paper aims to discuss these issues.Design/methodology/approach – A rule‐based expert system is designed and implemented using interpretation knowledge gathered from specialist physicians and peer‐reviewed medical literature. The gathered knowledge of ABG tests are organized into premise‐explanation pairs to deliver reliable evaluation with the appropriate differential in a timely manner.Findings – Performance of the developed interpreter prototype was assessed using a dataset of 74 ABG tests gathered from medical literature and clinical practice. The obtained results demonstrated that the identified acid‐base and oxygenation disorders and their differential d...

Smart Bolus Estimation Taking into Account the Amount of Insulin on Board

Self-management blood glucose (SMBG) and bolus calculations are pivotal components of evidence-based standard of care for young diabetics receiving multiple daily insulin injections. This paper aims at developing a smart bolus estimator that takes into account the amount of insulin on board (IoB), i.e. Insulin remaining in the patients body, to reduce fear of hypoglycemia and achieve goals of glycemic control. Design of the proposed bolus estimator follows the feed-forward multi-perceptron artificial neural network (ANN) with an input represents the time shift from last injection of quick acting (QA) insulin. The network output represents the amount of IoB. Calculation of the bolus required for a meal/snack is then carried out normally deducing the estimated IoB and thus the possibility of excess insulin administration and the risk of hypoglycemia can be averted. A functional prototype of the proposed system is developed and tested successfully on various mobile devices (i.e smartphones and tablet computers).

Automated electrical stimulation and physical activity monitoring of zebrafish larvae

Zebrafish (Danio rerio) is accepted as an efficient model to aid in research over a broad range of human diseases and drug discovery. However, obtaining evidences of pain perception similarity between adults and larvae is still a considerable scientific challenge. This paper presents an automated test-bed for electrical stimulation and physical activity monitoring of zebrafish larvae. It comprises of infrared digital camera and 25 test arenas along with the required software and hardware circuitry. Unlike existing systems, the developed system is fully automatic and does not require any manual adjustments. In addition, it is capable of estimating and monitoring physical activity of multiple larvae at various levels of painful stimulation. Performance of the developed testbed is assessed experimentally using various stimulation levels for numerous test batches of zebrafish larvae. The obtained results demonstrated accurate tracking and monitoring of multiple larvae responses for various levels of painful stimulation.

Biometric based audio ownership verification using discrete wavelet transform and SVD techniques

The digital revolution in audio industry has brought new ownership verification challenges, as a recording can be copied and distributed easily. Audio watermarking has been proposed as an effective solution to solve or mitigate the impact of these challenges. This paper investigates a previously-reported digital audio watermarking algorithm with the aim of improving its features and performance. The modified algorithm is then used to develop an audio ownership verification system. This is achieved by comgining the advantages of Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) techniques along with utilizing biometric features (thumbprint) of the owner as a digital watermark. A fully functional ownership verification system is developed and its performance is assessed experimentally. When compared to the original algorithm, the suggested system show significant improvements in terms of minimizing the required minimum period of original audio signal, improving quality of watermarked audio signal, and detecting the applied attacks.

Robot Assistant in Management of Diabetes in Children Based on the Internet of Things

This paper presents a new eHealth platform incorporating humanoid robots to support an emerging multidimensional care approach for the treatment of diabetes. The architecture of the platform extends the Internet of Things to a Web-centric paradigm through utilizing existing Web standards to access and control objects of the physical layer. This incorporates capillary networks, each of which encompasses a set of medical sensors linked wirelessly to a humanoid robot linked (via the Internet) to a Web-centric disease management hub. This provides a set of services for both patients and their caregivers that support the full continuum of the multidimensional care approach of diabetes. The platform’s software architecture pattern enables the development of various applications without knowing low-level details of the platform. This is achieved through unifying the access interface and mechanism of handling service requests through a layered approach based on object virtualization and automatic service delivery. A fully functional prototype is developed, and its end-to-end functionality and acceptability are tested successfully through a clinician-led pilot study, providing evidence that both patients and caregivers are receptive to the introduction of the proposed platform.

Development of improved automatic music transcription system for the arabian flute (NAY)

The accuracy and reliability of automatic music transcription plays and important role in music information retrieval applications. This paper investigates a previously reported Automatic Music Transcription (AMT) system for the Arabian flute (Nay)with the aim of extending its features and improving its performance. Several critical design factors are considered in the new extension. A hybrid pitch detection method that utilizes both the autocorrelation and Fast Fourier Transform (FFT) is suggested and implemented in the improved AMT system. The signal power is also used to detect octave falls and to perform mapping from intensity to MIDI velocity. Experimental evaluation of the developed system has shown better transcription results when compared to original system.