Magnetic DNA detection sensor for point-of-care diagnostics

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonThis thesis focuses on inductive base sensor design at MHz range frequency. The background theory, design, experiments and results for a new magnetic particles sensor is presented. A new magnetic sensor based on a planar coil was investigated for DNA pathogen detection. Change in inductance of the planar coil due to the presence of magnetic particles with varying mass was measured. The experimental set-up consisted of different sized planar coil with associated electronics for inductance measurements. The best sensor performance was accomplished using two different inductors while oscillating at frequencies 2.4MHz using 9.5μH inductor and 7.2MHz with 85μH inductor. The sensor has very large signal to noise ratio (580×103), while the average amount of frequency drift was 0.58. This sensor was tested with various types of magnetic particles. In addition, iron-oxide nanoparticles were synthesized through water in oil microemulsion method and with an average size of 25nm. The best sensitivity achieved for detection of 50μg iron-oxide particles was with the bead size of 10nm. 81Hz frequency shift was attained in regard to that amount of particles. This research shows that increasing the resonance frequency to 7.2MHz can cause the larger output signal difference (frequency shift) in the presence of magnetic particles; however, the sensor stability is the most important factor for determining the detection resolution and sensitivity. The sensitivity is better if the sensor can detect smaller amount of magnetic sample. The results of this research demonstrate that while the sample consists of smaller size particles, the sensor can detect the lower amount of sample. This is due to the heating effect of nanoparticles. On the other hand the sample distance from the sensor has a major impact on the sensitivity too; the shorter the distance, the higher the sensitivity. This technique can potentially be extended to detect several different types of bacterial pathogens and can be modified for multiplex quantitative detection. This sensing technique will be incorporated into a handheld, disposable microfluidic chip for point-of-care diagnostics for sexually transmitted diseases. Key words: Point of care diagnostics, Magnetic particle Detection, Molecular detection, Inductive sensin

Development of a vibration measurement device based on a MEMS accelerometer

© 2017 by SCITEPRESS. Published under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence (CC BY-NC-ND 4.0: https://creativecommons.org/licenses/by-nc-nd/4.0/)This paper proposes a portable and low cost vibration detection device. Enhanced vibration calculation, reduction of error and low storage memory are complementary accomplishments of this research. The device consists of a MEMS capacitive accelerometer sensor and microcontroller unit, which operates based on a novel algorithm designed to obtained vibration velocity, bypassing the usual time-based integration process. The proposed algorithm can detect vibrations within 15Hz-1000Hz frequencies. Vibration in this frequency range cannot be easily and accurately evaluated with conventional low cost digital sensors. The proposed technique is assessed and validated by comparing results with an industrial grade vibration meter

Power Efficient FFT Implementation for a Real Time Spectrum Analyser

Peer reviewe

Improving Displacement Measurement for Evaluating Longitudinal Road Profiles

2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper introduces a half-wavelength peak matching (HWPM) model, which improves the accuracy of vehicle based longitudinal road profilers used in evaluating road unevenness and mega-textures. In this application, the HWPM model is designed for profilers which utilize a laser displacement sensor with an accelerometer for detecting surface irregularities. The process of converting acceleration to displacement by double integration (which is used in most rofilers) is error-prone, and although there are techniques to minimize the effect of this error, this paper proposes a novel approach for improving the generated road profile results. The technique amends the vertical displacement derived from the accelerometer samples, by using data from the laser displacement sensor as a reference. The vehicle based profiler developed for this experiment (which uses the HWPM model) shows a huge improvement in detected longitudinal irregularities when compared with pre-processed results, and uses a 3-m rolling straight edge as a benchmark.Peer reviewe

Embedded Trusted Monitoring and Management Modules for Smart Solar Panels

This paper investigates developing a prototype of smart solar panels. This architecture consists of a panel monitoring module and the central management unit. The monitoring module is to be embedded inside each PV panel making it secure to transfer the trusted data via Wi-Fi to the central Management unit (which can accommodate an array of PV panels in an installation). This module is required for data storage and provides the ability to upload secure data to the cloud. This platform presents the ability to securely manage large numbers of rooftop solar panels in a distributed ledger by implementing block chain algorithm. For achieving this purpose, Module 400 is envisaged to be turned into a Blockchain node as it provides the infrastructure to implement this technology