Helmi Wasoh, Lee Yook Hengb, Fatimah Abu Bakar, Rahman Wagiran, Abu Bakar Salleh, Nor Azah Yusof, Norhisam Misrond and Fatin Hazimah Abdul Rahmane
The purpose of this paper is to describe a capacitive biosensor device consisting of an enzyme electrode and a simple detector which has been developed for histamine measurement.
Abstract
Purpose
The purpose of this paper is to describe a capacitive biosensor device consisting of an enzyme electrode and a simple detector which has been developed for histamine measurement.
Design/methodology/approach
In this analysis, degradation of histamine through enzymatic reaction produces signal that is monitored using a simple detector equipped with “astable” multivibrator operation circuit (in capacitor‐resistor circuit).
Findings
Different frequency (f) readings have been obtained for glucose, alcohol and histamine in different concentration levels, showing the ability of this simple device system to measure their dielectric constant (k) as formulated by the equation f=(1.44d)/ [kA (R1+2R2)]. The analysis using smaller electrode gap (d) produces higher value of f, indicating that d, is directly proportional to f. For histamine, by using immobilized enzyme electrode, the results show that the change of dielectric properties during the 300‐second reaction period could also be monitored. A linear relationship is obtained between concentration and frequency from 50 to 200 ppm.
Practical implications
Based on this result, an enzyme electrode and “astable” operation circuits have the potential to be used in the development of a simple capacitive biosensor device.
Originality/value
The paper is an outcome of experimental work carried out to observe capacitive sensing behavior using an immobilized enzyme, to measure biological samples, especially histamine.
Details
Keywords
Marzia Hoque Tania, M. Shamim Kaiser, Kamal Abu-Hassan and M. A. Hossain
The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals have created a demand for intelligent systems with the…
Abstract
Purpose
The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals have created a demand for intelligent systems with the least error-prone diagnosis results to be used by less medically trained persons and save clinical time. This paper aims at investigating the development of image-based colourimetric analysis. The purpose of recognising such tests is to support wider users to begin a colourimetric test to be used at homecare settings, telepathology and so on.
Design/methodology/approach
The concept of an automatic colourimetric assay detection is delivered by utilising two cases. Training deep learning (DL) models on thousands of images of these tests using transfer learning, this paper (1) classifies the type of the assay and (2) classifies the colourimetric results.
Findings
This paper demonstrated that the assay type can be recognised using DL techniques with 100% accuracy within a fraction of a second. Some of the advantages of the pre-trained model over the calibration-based approach are robustness, readiness and suitability to deploy for similar applications within a shorter period of time.
Originality/value
To the best of the authors’ knowledge, this is the first attempt to provide colourimetric assay type classification (CATC) using DL. Humans are capable to learn thousands of visual classifications in their life. Object recognition may be a trivial task for humans, due to photometric and geometric variabilities along with the high degree of intra-class variabilities, it can be a challenging task for machines. However, transforming visual knowledge into machines, as proposed, can support non-experts to better manage their health and reduce some of the burdens on experts.