Mohd Alauddin Mohd Ali

A Review of Smart Homes—Past, Present, and Future

A smart home is an application of ubiquitous computing in which the home environment is monitored by ambient intelligence to provide context-aware services and facilitate remote home control. This paper presents an overview of previous smart home research as well as the associated technologies. A brief discussion on the building blocks of smart homes and their interrelationships is presented. It describes collective information about sensors, multimedia devices, communication protocols, and systems, which are widely used in smart home implementation. Special algorithms from different fields and their significance are explained according to their scope of use in smart homes. This paper also presents a concrete guideline for future researchers to follow in developing a practical and sustainable smart home.

Surface Electromyography Signal Processing and Classification Techniques

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.

Real-time signal processing for fetal heart rate monitoring

An algorithm based on digital filtering, adaptive thresholding, statistical properties in the time domain, and differencing of local maxima and minima has been developed for the simultaneous measurement of the fetal and maternal heart rates from the maternal abdominal electrocardiogram during pregnancy and labor for ambulatory monitoring. A microcontroller-based system has been used to implement the algorithm in real-time. A Doppler ultrasound fetal monitor was used for statistical comparison on five volunteers with low risk pregnancies, between 35 and 40 weeks of gestation. Results showed an average percent root mean square difference of 5.32% and linear correlation coefficient from 0.84 to 0.93. The fetal heart rate curves remained inside a /spl plusmn/5-beats-per-minute limit relative to the reference ultrasound method for 84.1% of the time.

SPEED: An Inhabitant Activity Prediction Algorithm for Smart Homes

This paper proposes an algorithm, called sequence prediction via enhanced episode discovery (SPEED), to predict inhabitant activity in smart homes. SPEED is a variant of the sequence prediction algorithm. It works with the episodes of smart home events that have been extracted based on the on -off states of home appliances. An episode is a set of sequential user activities that periodically occur in smart homes. The extracted episodes are processed and arranged in a finite-order Markov model. A method based on prediction by partial matching (PPM) algorithm is applied to predict the next activity from the previous history. The result shows that SPEED achieves an 88.3% prediction accuracy, which is better than LeZi Update, Active LeZi, IPAM, and C4.5.

Hardware prototyping of an intelligent current dq PI controller for FOC PMSM drive

Field Oriented Control (FOC) Permanent Magnet Synchronous Motor (PMSM) is a commutator less servo drive which provides high controllability, greater efficiency, superior torque to inertia ratio and high power density. However, the performance of FOC-PMSM depends on the driver circuits, which requires expensive computing elements. Besides, an intelligent current regulator is desired for a highly precise driver. This research proposed a hardwire prototype of current dq PI controller as a part of real-time hardwired motion intelligent driver which was previously solved using software and firmware dependent modules. The outcome will be a single chip current dq PI controller for FOC-PMSM drive.

CMOS Differential Ring Oscillators: Review of the Performance of CMOS ROs in Communication Systems

The integrated differential ring oscillator (DRO) in complementary metal oxide semiconductor (CMOS) technology has been used in numerous products for a long time. Its presence has been extended to high-speed clock and data recovery (CDR) circuits for optical communication, analog and digitally controlled oscillators, frequency dividers of high-frequency synthesizers, clock generators of digital circuits, analog-to-digital converters (ADCs), and many more applications [1]-[5]. Implementations of these ring oscillators are seen in emerging technologies such as ultrawideband (UWB) and radio frequency identification (RFID) as well as wireless sensor networks (WSNs) and short-range communication devices [6], [7]. The DRO is a good design choice for integrated circuit (IC)designers because of its continued use in different bulk CMOS technologies. This article presents implementation techniques and performance comparisons of the DRO as a CMOS voltage-controlled oscillator (VCO) in low radio frequency (RF) bands, along with presentation and discussion of a number of circuit approaches.

Finger photoplethysmogram pulse amplitude changes induced by flow-mediated dilation

This study was conducted to investigate the utility and efficacy of finger photoplethysmogram pulse amplitude (PPG-AC) in comparison with the standard Doppler ultrasound in assessing an endothelial function via flow-mediated dilation (FMD). High-resolution B-mode scanning of the right brachial artery (BA) of 31 healthy subjects aged 39.7 +/- 11.3 (range 22-64) years and 52 risk subjects aged 47.7 +/- 10.8 (range 30-65) years were performed before and after 4 min of upper arm occlusion. Concurrent with the ultrasound measurement (where color Doppler imaging was used to enhance arterial boundary detection), PPG signals were recorded from both index fingers for cross evaluation and comparison. Our results show that the finger PPG-AC exhibits a similar response to that of the well-known BA dilation: following the release of pressure (cuff around the BA), the PPG-AC increases abruptly before slowly decreasing toward the baseline. The peak PPG-AC is reached significantly faster than the peak FMD measured by ultrasound among healthy and risk groups (P < 0.001). The proposed technique using a finger photoplethysmogram can be applied in a rapid and non-invasive assessment of peripheral vascular functions as an alternative low-cost and less operator-dependent tool compared to ultrasound.

A Review on the Applications of Petri Nets in Modeling, Analysis, and Control of Urban Traffic

Urban traffic systems that possess system states that are distributed, parallel, deterministic, stochastic, discrete, and continuous are well suited for a Petri net (PN) approach. The literature survey conducted in this paper shows the vast applications of PNs in modeling and simulation, analyzing and evaluating performances, intelligent control and optimization, and congestion management in urban traffic systems. This paper outlines the related works conducted using PNs and discusses its viability, such as its contributions and limitations. Extendibility and future research potential to further the successful applications of PNs in traffic systems are discussed and proposed in this paper.

The application of empirical mode decomposition for the enhancement of cardiotocograph signals.

Cardiotocograph (CTG) is widely used in everyday clinical practice for fetal surveillance, where it is used to record fetal heart rate (FHR) and uterine activity (UA). These two biosignals can be used for antepartum and intrapartum fetal monitoring and are, in fact, nonlinear and non-stationary. CTG recordings are often corrupted by artifacts such as missing beats in FHR, high-frequency noise in FHR and UA signals. In this paper, an empirical mode decomposition (EMD) method is applied on CTG signals. A recursive algorithm is first utilized to eliminate missing beats. High-frequency noise is reduced using EMD followed by the partial reconstruction (PAR) method, where the noise order is identified by a statistical method. The obtained signal enhancement from the proposed method is validated by comparing the resulting traces with the output obtained by applying classical signal processing methods such as Butterworth low-pass filtering, linear interpolation and a moving average filter on 12 CTG signals. Three obstetricians evaluated all 12 sets of traces and rated the proposed method, on average, 3.8 out of 5 on a scale of 1(lowest) to 5 (highest).

FPGA realization of multipurpose FIR filter

A multipurpose FIR filter has been designed and realized by field programmable gate arrays (FPGA) for real-time filtering applications. The design can accomplish an arbitrary filter frequency response and variable filter order up to 127. The coefficients are computed through the Hamming windowing technique. The model is capable of performing filtering operations, like lowpass, highpass, bandpass and bandstop based on selection that is embedded into the design. The filter is set to 8-bit signed data processing. Linear constant coefficient difference equation (LCCDE) has been used to filter the input data in time domain. The design is coded with VHDL to cope with the parallelism of digital hardware. Simulation, compilation and synthesis have been done to verify the validity of the design outputs. To test the correctness of the design the observed output is compared with the calculated output results from MATLAB implementation that confirms the effectiveness of the design.