Estimating Blood Pressure from Photoplethysmogram Signal and Demographic Features using Machine Learning Techniques

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the Blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based BP measurements are discrete and uncomfortable to the user. To address this need, a cuff-less, continuous and a non-invasive BP measurement system is proposed using Photoplethysmogram (PPG) signal and demographic features using machine learning (ML) algorithms. PPG signals were acquired from 219 subjects, which undergo pre-processing and feature extraction steps. Time, frequency and time-frequency domain features were extracted from the PPG and their derivative signals. Feature selection techniques were used to reduce the computational complexity and to decrease the chance of over-fitting the ML algorithms. The features were then used to train and evaluate ML algorithms. The best regression models were selected for Systolic BP (SBP) and Diastolic BP (DBP) estimation individually. Gaussian Process Regression (GPR) along with ReliefF feature selection algorithm outperforms other algorithms in estimating SBP and DBP with a root-mean-square error (RMSE) of 6.74 and 3.59 respectively. This ML model can be implemented in hardware systems to continuously monitor BP and avoid any critical health conditions due to sudden changes.Comment: Accepted for publication in Sensor, 14 Figures, 14 Table

Thermal Ageing Effect on Electro-Mechanical Properties of Work Hardened High Conductive Copper Based Material

High conductive materials may undergo work hardening in the process of manufacturing and utilization as machine parts. Moreover, these materials face various thermal conditions at operational environment. As a consequence, the electro-mechanical properties of these materials get changed, which in turn affect their operational ability as these materials need to maintain high conductivity along with desirable mechanical properties. It gratifies to investigate the effect of thermal ageing on the electro-mechanical properties and microstructure of high conductive copper based material. In this work, the samples are prepared from copper ingot and alloy collected from local market. From the bulk material, long bars are taken, and they are at first homogenized and solution treated, and then they have been work hardened at different level in two conditions i.e., at room temperature and near recrystallization temperature. Thereafter, a series of experiments are carried out to determine the changes in conductivity, micro-hardness, strength, elongation and microstructure of samples as a function of thermal ageing temperature. Most of the mechanical properties after thermal ageing are found to be influenced quite significantly by work hardening.  &nbsp

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Techniques of FECG signal analysis: detection and processing for fetal monitoring

Fetal heart rate monitoring is a technique for obtaining important information about the condition of a fetus during pregnancy and labor, by detecting the FECG signal generated by the heart of the fetus. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies is becoming a very important requirement in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature. A comparative study has been carried out to show the performance of various methods. This paper opens up a passage to biomedical researchers, physicians and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system by providing valuable information to help them in developing more dominant, flexible and resourceful application

EEG signal analysis and characterization for the aid of disabled people

The effectiveness of assistive devices for disabled people is often limited by the human machine interface. This research proposes an intelligent wheelchair system especially for severely disabled people based on analysing electroencephalographic signals by using discrete wavelet transform and higher order statistical methods. The system to be implemented in Field Programmable Gate Array enables an accurate and efficient system of processing signals to control the wheelchair, which makes an attractive option in the hardware realization.Full Tex

Wildlife net-gamekeepers using sensor network

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Electrical Grid interface for an Induction Motor

The 3-phase induction motor is the workhorse of modern industry and is widely regarded as a highly reliable electromechanical device. Two motor operational modes were of interest in this thesis work, motor starting and steady state operation when connected directly to the electrical grid and operating at the same grid frequency. Typical industrial applications include pumps, compressors and fan loads. Motor starting on isolated or weak grid systems is a highly dynamic process that can cause damage to the motor and load as well as grid voltage fluctuations. During steady-state operation, the induction motor draws reactive lagging currents and is exposed to variable grid voltages that reduce the motor operating efficiency and lifetime expectancy. Hence, the prime purpose of the thesis is to present power electronics that connect the induction motor to the grid and that can control the motor voltage above and below the grid voltage. As a result, the power electronics can provide a range of operational features such as: motor soft start, VAR compensation, improved power conversion efficiency, increased operational lifetime expectancy. The power electronics presented consists of a 3-phase floating H-bridge that is connected in series with the utility grid and a cage induction motor to provide series voltage compensation. By injecting a series voltage in each phase, the proposed system can be used to control the motor voltage during starting and hence limit the motor starting current. The voltage injection can provide a voltage sag ride through capability and operate with a leading grid power factor under steady state, hence generates VARs into the grid. The 3-phase H-bridges produce 5-level pwm motor line voltages with a pwm frequency up-to four times the switching. This compares with the 3-level line voltages produce in a standard VFD at twice the switching frequency, using larger voltage step sizes. The 3-phase H-bridge system therefore results in lower high frequency pwm induced iron losses and Cu losses in the motor. Besides soft start and reactive power generation capability, the proposed system has many other desirable operating features, such as; improved motor operating efficiencies, reduced motor losses. Floating capacitor converters can set the motor voltage at a fixed desired value, above or below the grid voltage, under transient or continuous steady-state conditions, and over the entire range of the motor load. This is useful when the motor is connected to a grid whose nominal voltage differs from the machine’s rated value or that may fluctuate over time (sag or swell). A variety of control options exist to lower the losses of an induction motor, the approach presented is based upon measuring the motor electrical input power and using readily available motor nameplate data to control the motor voltage. The conversion efficiencies of both the motor and the power electronics power can be improved over the entire motor load range. This results in lowering the motor’s operating temperature to improve lifetime expectancy, and avoids derating the motor power rating. The cooling requirements of the power electronics can be reduced, lowering their size, cost and weight. Motor voltage control with bridge voltage control is explained. Simulation and theoretical analysis is presented to predict operation of system as well as theoretical performance curves for the 3-phase H-bridge is presented for motor control modes. Relationship between motor winding temperature rise and motor loss is also established. A 5 HP experimental testbed is used to validate the concepts. Soft start, the grid voltage ride through capability feature and the reactive power generation characteristics are verified. Experimental results show that the proposed system can successfully soft start a standard squirrel cage induction machine under different modes and load conditions. Also the experimental performance of the power electronics, motor and total system is presented with respect to power losses, system efficiency and the motor output power. For applications where frequency control is not required, the proposed 3-phase H-bridge system is a viable cost effective solution