Biosensors & Bioelectronics

A natural phosphate electrode modified with antibiotic (amoxivillin) was employed for the detection and quantification of Staphylococcus aureus from aqueous solutions. The new electrode (AMX-NPE) revealed interesting electroanalytical detection of Staphylococcus aureus based on the adsorption of these bacteria onto antibiotic under open circuit conditions. The bacteria redox peaks were operated by square wave voltammetry in 0.1 mol/L NaCl solution. The response depends on the concentration of bacteria in the bulk solution as well as the parameters involved in the preconcentration, pH and the measurement steps

Parkinson’s disease (PD) is the second highest neurodegenerative disease that impairs speech besides causing bodykinesia, postural instability, rigidity and tremor. From the present research works it is understood that the disease is the result of lack of dopamine in brain cells. However, its real cause is yet to be established satisfactorily. In this paper we review the present state of the art of the PD including the nature of disease, its characteristics, the treatment, algorithms or techniques available to diagnose or monitor the patients with the disease, sensors and wearable devices being used to help PD patients and physicians. We also explored many speech based solutions to the disease. The essence of our review is that this neurodegenerative disorder needs further research and development of wearable devices that can help patients to lead a normal life. In this paper we provide the summary of findings which leads to continue our research to develop a wearable device with state of the art software that can help PD patients to have better lives.

This work presents a 2D quantification of strain field caused due to the motion artifact in an Electrocardiogram (ECG) measurement. The objective of this work is to estimate the skin stretch induced motion artifact in an ECG signal. An ECG measurement was obtained from a subject for 10 seconds using standard Ag/AgCl electrodes by continuously moving the arm back and forth during the measurement. A Poly dimethyl siloxane (PDMS) patch of dimensions 40 mm × 45 mm × 0.254 mm was adhered to the arm during motion. The movement of the PDMS patch during the ECG measurement was recorded in a video and motion artifact was quantified in terms of normal and shear strain components εx, εy and εxy. These values were derived using feature detection and Euclidean distance feature mapping. The motion artifact was eliminated from the ECG signal using Extended Kalman Filtering (EKF).

Hydroacoustic method has been used in various field of marine research. Use hydroacoustic method is a method developed to obtain information about the mangrove crab (Scylla sp.). This study analyses the value Target Strength (TS), Power Spectral Density (PSD), and Fast Fourier Transform (FFT) used the instrument hidroakustik. Data collection was performed at the Laboratory of Marine Acoustics using instruments CruzPro PCFF-80 operated with a frequency of 200 kHz. Results of detection of the target by looking at the value of Target strength, strongest TS value can be seen at a depth of 0.6 meters from the transducer with estimations it is the result of target detection. The target strength (TS) of the mangrove crab (Scylla sp.) ranged between –50 and –54 dB. TS value at ping number of 0-500 have a greater value is the value of -55 dB, TS value at that time have in common with TS value at ping number 2500-3000. SV value is no different than the value of TS is caused using 1 target. Echo level (EL) value versus time has highest peak in the range of 115 dB with the lapse ping number is 15-25, with values that are at the end of the echo of ping number of 70 with value is 132 dB rated Power Spectral Density (PSD) is actually located at 2900 s, and depth of a pool is not affect the value of backscatter targets.

This work presents a parametric electrical modelling of the electrical response of human forearm tissues through a simulation of Multi-frequency Electrical Bioimpedance analysis (MF-EBIA). The objective is to estimate an electrical equivalent representation for tissue response in terms of resistance and capacitance values for three tissue layers in the forearm – the fat, muscle and artery, using parametric fitting analysis. Following up from a simulation study of the human forearm model using Ansys® High Frequency Structure Simulator (HFSS), this work assumes an electrical model of the human forearm section for every tissue and calculates the electrical parameters. The tissue model was considered to be isotropic with regards to the dielectric properties and the consideration of blood flow was realised by taking three instances of radial artery diameter. The proposed model was validated by using the obtained values of model components to reproduce the overall response. The obtained values of resistance and capacitance for every tissue domain provide an insight into their significant contribution to the overall electrical response, which can be important while analysing their individual electrical behaviour and also helpful in various pre-experimental studies related to dielectric characterization of living tissues.

Bioacoustics is a combination between biology and acoustic study which usually refers to a study on sound production, dispersion through elastic media, and reception in animals, including humans. Bio sonar signals dolphin radiated along the beam axis of an Atlantic bottlenose dolphin resemble short transient oscillations. The purpose of this research is to measure, analyse, distinguish dolphin sound characteristics and detect the click sound by the dolphins. Indo-pacific bottlenose dolphins, maintained in captivity, Indonesia, had the lowest intensity of 18.76 dB while the highest were 32.02 dB with 100% percentage. Sound frequency range of Indo-pacific bottlenose dolphins in captivity, Indonesia was between 13.211 – 15.245 Hz. The percentage maximum intensity in the frequency is 14 kHz can be seen the percentage shown in the amount of 100% and minimum percentage of 75% in frequency 13 kHz sounds are probably produced by air movements in the nasal plugs. Sub frequency of 10 kHz has a value of 649.89 × 103, and 14 kHz with anti-log value of 782.82 × 103. Frequency of the sounds produced by a bottlenose dolphin ranges from 0.2 to 150 kHz. The lower frequency vocalizations (0.2 to 50 kHz) are likely used in social communication. Social signals have their most energy at frequencies less than 40 kHz. Higher frequency clicks (40 to 150 kHz) are primarily used for echolocation.

Signal processing with passive acoustic in fisheries and marine science learn the sound frequency range of fish, the intensity of the sound amplitude, sound fluctuations, and shape the sound patterns of the fish. Application of passive acoustic filed for marine fisheries and science detects the sound frequency range of fish, the intensity of the sound amplitude, sound fluctuations, and shape the sound patterns of the fish. Passive acoustic methods used to monitor marine mammals expressed. In general, the signal obtained from the ranimal record sounds is poor and difficult to determine from which directions it is produced, therefore it requires that require amplification/ strengthening. Bioacoustic research is needed to identify the communication language (acoustic communication) in mammals. Bioacoustic detect mammal-produced frequency ranges of sound, amplitude intensity of sound, voice fluctuation, and form sound patterns of mammals. Studying bioacoustic is inseparable from the science of underwater acoustics, biology of mammals, and the study of mammalian behavior. Generally bioacoustic include physiology of mammals organ that produce sound, earnings voice mechanism, sound characteristics of mammals, mammals sound-approaching mechanism, the hearing capacity of fish, and the evolution of the auditory system, and to obtain the frequency range of each sound produced by the dolphins (mammals). Environmental conditions and parameters (salinity and temperature) will greatly affect the value of the intensity and frequency generated from the target, the more extreme the environmental conditions, the lower value of the intensity and frequency generated

Integrated-optical (bio) chemical sensors are more and more commercialized, mainly because of their high intrinsic sensitivity in combination with the possibilities they offer for integration in optofluidic devices. The microring resonator (MRR), for example, is a very feasible structure to be used as microarray sensor element for multiplex biosensing. Fabrication of MRRs has been described in the case of the TriPleX platform employing well-defined stacks of stoichiometric Si3N4 and SiO2 material. This platform allows for a wide variety of applications, due to its intrinsic low loss and its transparency for the VIS/NIR wavelength range. In the present paper, we describe the recent achievements in the characterization of arrays of these MRRs regarding temperature sensitivity, refractive index sensitivity and protein immobilization performance. Furthermore, the use of a reference channel/reference MRR is demonstrated in order to show the advantage of compensation of unintended change in temperature or sample composition. The refractive index sensitivity was determined to be 104 nm/RIU and the limit of detection was about 2 × 10-6 RIU. MRRs appeared to behave very comparable (expressed as the coefficient of (intra-array) variation (CV)) regarding the response to temperature (CV≈0.3%) as well as refractive index (CV<0.1%). Furthermore, it is shown that protein immobilization onto the different MRRs of the same arrays can be realized in a comparable way (CV<3%). A good comparability (i.e., a low variation) in these aspects allows for the use of internal referencing in order to compensate for unintended change in temperature or refractive index and also helps to attain a high assay precision in the ultimate biosensing application. Ongoing research is focused on the integration of more functionality on chip and further miniaturization in order to allow for fabrication of complex, though affordable, sensor devices.

Face detection and recognition has been prevalent with research scholars and diverse approaches have been incorporated till date to serve purpose. The rampant advent of biometric analysis systems, which may be full body scanners, or iris detection and recognition systems and the finger print recognition systems, and surveillance systems deployed for safety and security purposes have contributed to inclination towards same. Advances has been made with frontal view, lateral view of the face or using facial expressions such as anger, happiness and gloominess, still images and video image to be used for detection and recognition. This led to newer methods for face detection and recognition to be introduced in achieving accurate results and economically feasible and extremely secure. Techniques such as Principal Component analysis (PCA), Independent component analysis (ICA), Linear Discriminant Analysis (LDA), have been the predominant ones to be used. But with improvements needed in the previous approaches Neural Networks based recognition was like boon to the industry. It not only enhanced the recognition but also the efficiency of the process. Choosing Backpropagation as the learning method was clearly out of its efficiency to recognize nonlinear faces with an acceptance ratio of more than 90% and execution time of only few seconds.