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  • Open access
  • 55 Reads
Kinematic characteristics of national and college level weightlifters during snatch technique using wearable inertial sensors

Weightlifting performance is strongly dependent on technique, explosive strength, and flexibility. There are two major lifts involved in competition: the snatch and the clean and jerk, where the snatch is the most technical component of the weightlifting competition. Most of the technical analyses have been done using either video analysis or conventional optical camera systems. However, few studies have investigated the kinematic characteristics of the weightlifters using the inertial measurement unit (IMU) sensors. In this study, we investigated the joints kinematics of the trunk, shoulder, elbow, hip, and knee as well as the main phases during the snatch technique for national and college level weightlifters using multiple IMU sensors. Seven female Mongolian weightlifters (3-national level and 4-college level) participated. Each participant performed three snatch attempts at 70 % of one-repetition maximum. The joints angles were calculated using 3-axis acceleration and 3-axis gyroscope data from the IMU sensors based on the Madwick filtering. The six main phases of the snatch technique were defined based on knee flexion. All parameters were compared between the national and college level weightlifters. The national team showed a higher elbow range of motion and a greater extension of the hip and knee joints at the second pull than college-level athletes. In addition, the college team does not exhibit the transition phase and the proportion of the turnover phase was larger. This study provides a kinematic difference between the two different level weightlifters, which may help coaches and athletes to improve training strategy and weightlifting performance.

  • Open access
  • 66 Reads
Towards a multi-interdigital transducer configuration to combine focusing and trapping of microparticles within a microfluidic platform: a 3D numerical analysis.

In lab-on-chip devices, the separation and manipulation of micro-particles within microfluidic channels are important operations in the process of biological analyses. In this study, the microfluidic flow is coupled with acoustic waves through a 3D multi-physics numerical solution in order to generate optimized acoustic pressure pattern. Exploiting interdigital transducers (IDTs), surface acoustic waves (SAWs) are generated on the surface of a piezoelectric substrate (lithium niobate). These waves interfere constructively to generate a standing pressure field within a fluid contained in a microchannel placed between them. Several studies and applications have been reported exploiting two facing IDTs, effective in particle focusing due to the acoustic radiation force developed by the acoustic pressure. In this work, a configuration made by four IDTs is investigated to enhance the focusing effect and provide trapping capabilities. A complex matrix of pressure wave nodes (zero wave amplitude) and antinodes (maximum wave amplitude) is generated and optimized to get the right acoustic pressure pattern. Results obtained show particle focusing effects but also trapping on specific sites depending on the distribution of waves. These innovative results, based on multiphysics 3D numerical analysis, highlight the versatility and the efficiency of this configuration depending on the design of the microfluidic structure implemented in the SAW-based platform. Applications towards biological cell sorting and assembling can be considered based on this principle.

  • Open access
  • 39 Reads
Determination of Chemical Oxygen Demand (COD) Using Nanoparticle-Modified Voltammetric Sensors and Electronic Tongue Principles
Published: 01 November 2021 by MDPI in 8th International Electronic Conference on Sensors and Applications session Posters

Chemical Oxygen Demand (COD) is a widely used parameter in analyzing and controlling the degree of pollution in water. COD is defined as the amount of molecular oxygen (in milligrams of O2) required to decompose all the organic compounds in 1 L of aqueous solution to carbon dioxide and water. Electro-oxidizing the organic contaminants to completely transform them into CO2 and H2O using sensors is considered the best method for COD estimation. In this sense, copper electrodes have been reported based on the fact that copper in alkaline media acts as a powerful electrocatalyst for oxidation of aminoacids and carbohydrates, which are believed to be the major culprits for organic pollutions.

In this work, four electrodes were studied for COD analysis employing the cyclic voltammetry technique: Nafion film covered electrodeposited CuO/Cu nanoparticle electrode (E1), Cu nanoparticle-graphite-epoxy composite electrode (E2), CuO nanoparticle-graphite-epoxy composite electrode (E3) and Ni Cu alloy nanoparticle-graphite-epoxy composite electrode (E4). Glucose, glycine, potassium hydrogen phthalate (KHP) and ethylene glycol, which show different reducibilities, were chosen to be the standard substances to play the role of organic contaminants with different degradation difficulties. It was observed from the obtained cyclic voltammograms that glucose is very easy to be oxidized by those four electrodes and electrode E1 shows the best performance, with a linear range of 19.2~1120.8 mg/L and limit of detection of 27.5 mg/L. Besides, KHP is very difficult to be oxidized by these four electrodes. Water samples were also analyzed with the electronic tongue array composed of these four electrodes based on the Principle Component Analysis (PCA) technique. As a result, the main component of river samples, which is easy or difficult to be degraded, can be evaluated by the PCA technique. This evaluation is very helpful for the accuracy of COD detection. The resulting sensor-based method demonstrates great potential not only for estimating the precise value of COD, but for predicting the difficulty behavior in its degradation, in a simple, fast, and clean methodology, which is completely suited to the present demands of green techniques.

  • Open access
  • 38 Reads
Comparing Landsat-8 OLI, Sentinel-2 MSI, and PlanetScope Imagery for Coastline Change Detection: A Case Study of El-Alamein Coast, Egypt

The coastline extraction and change detection analysis is an important task that has application in different fields such as coastal development and planning, hazard mapping, erosion-accretion studies, predictive modeling of coastal morphodynamics. Coastline delineation is difficult, time consuming, and sometimes impossible for entire coastal system when using traditional ground survey techniques. Satellites provide data at spatial-temporal scales that can be used for coastal change detection. PlanetScope nano-satellites have spatial (3 m) and temporal (daily) resolutions that may help improve coastal monitoring compared to
coarser-resolution satellites. This work compared different Sensors of Landsat-8 OLI (15m resampled spatial resolution), Sentinel-2 MSI (10m resampled spatial resolution), and PlanetScope (3m) to detect coastline change overtime. Recent advances in remote sensing and geographical information system (GIS) techniques are overcoming the difficulties in extraction of shoreline position and detection of coastline changes.

In the paper, the area of El-Alamein area along the Egyptian Mediterranean coast, which facing recently a dramatically changes due to the urbanization and human impacts, has been chosen and coastline extracted from Landsat-8 (OLI), Sentinel-2 MSI, and PlanetScope satellite images (2015, 2018 and 2021). The Normalized Difference Water Index (NDWI) was applied to water/land separation using ERDAS Imagine 2015 Package, and then shoreline detection using ENVI 5.3 Software. The delineated coastlines have been analyzed using Digital Shoreline Analysis System (DSAS.v5), a GIS Software tool for estimation of shoreline change rates calculated through two statistical techniques such as, End Point Rate (EPR) and Linear Regression Rate (LRR). The results refers to mapping Coastline change and rates overtime-using different sensors, and evaluation the spatial accuracy.

  • Open access
  • 164 Reads
Optimization of Focused Ion Beam patterning parameters for direct integration of plasmonic nanostructures on Silicon photodiode

In the last twenty years, many theoretical studies have shown that plasmonic structures have astonishing, unique, and interesting optical characteristics. As a direct consequence, many scientific and industrial applications tried to take advantages by plasmonic, leading also to substantial innovation in nanofabrication methods. As an example, the combination of plasmonic nanostructures with complementary metal-oxide-semiconductor (CMOS) optical sensors, capable of converting photons into electrical signals, raised a great interest, due to potentiality of extend the spectral responsivity of Silicon in a wider spectral region, from the ultra-violet (UV) up to the near infra-red (NIR). Unlike the fabrication of plasmonic nanostructures on an inert substrate, the production of plasmonic nanostructures on active sensors requires consideration of surface topography as well as the sensors' active behaviors. Therefore, the choice of the production technique is a delicate step and required further investigation. Ion Beam Lithography (IBL), which does not require a mask or photoresist since the focused ions are deposited directly on the material of interest, is one of the process methods for fabricating nanostructures that is compatible with CMOS technology. Direct patterning by IBL gives the nanostructures total flexibility in terms of shape and aspect ratio. On the other hand, direct patterning can cause ions implantation in the substrate, causing flaws and modifying the electrical behavior of the sensors. Thus, to fabricate of plasmonic nanostructures directly on top of a CMOS sensors is pivotal to tune the IBL process parameters, such as beam energy and current, dose and ions species. In this paper, we demonstrate the optimization of Focused Ion Beam parameters by ion-solids interaction simulations and the preliminary results of direct patterning metallic nanostructures on a Si-based photodiode without damaging the active area and therefore, with an unmodified characteristic IV curve.

  • Open access
  • 88 Reads
A new three-phase Smart Meter for Cloud connection: network architecture and performances

Efficient energy consumption is essential for the development of a smart grid in the power system. As reliable monitoring and management of energy usage is a main priority for the smart grid1. The existing energy meter system has a host of concerns, one of which is the lack of full-duplex transmission2. In this paper, we present a novel architecture of cloud-connected Smart Meter. The proposed three-phase meter is capable of real-time measurement of the energy network status and data transfer to a cloud architecture.
The main features of this solution are:
• Accurate measurement enabling up to Class 0.2-meter accuracy.
• Support for several sensors (CT/Shunt/Rogo coil).
• Ensures a smart grid easily scalable.
• Possibility of reading data from multiple platforms.
The measuring task is entrusted to the STPM3x chips, produced by ST Microelectronics. The STPM3x ASSP series is developed for high accuracy power and energy measurement in power line systems; it evaluates instantaneous voltage and current waveforms and calculates RMS voltage and current values, as well as active, reactive, and apparent power and energy. The processing of the acquired data is guaranteed by a 32-bit ARM Cortex ™micro-controller from ST Microelectronics.
The communication block is based on multiple-choice hardware to guarantee the connection to the network infrastructure, also including an NB-IoT module, equipped with an ESIM. The protocol used between the nodes in the network is MQTT.
For the experimental validation, a stress test of the network and, in this case, the Virtual Private Server was performed. Results will be detailed reported in the full paper. What is more, a tiny smart grid was established in the city of Lipari (Italy) to test the concept. The installed smart grid is made up of three distinct types of smart meters, to validate on a test field the entire solution.

  • Open access
  • 72 Reads
Design and Characterization of a Passive Wireless DNA Sensor

This research is aiming at developing an innovative DNA sensing platform that exploits a multidisciplinary area synthesizing the conventional DNA capacitive sensing mechanism and surface-based conformational characterization throughout DNA immobilization and hybridization. The resonant frequency shift caused by the change of capacitance throughout DNA immobilization and hybridization occurring on top of a capacitor is monitored by the means of impedance analyzer, with which it is possible to inspect the graph amplitude on the behavior of signal strength and compute the quality factor of the coupling element represented by bandwidth. Experiments for measuring the frequency shift due to interface charge transmission were carried out to study its DNA sensing mechanism and the possibility of DNA sensing enhancement. 32 samples were measured throughout the experiment and the average capacitance measurements represented a variety of surface charges resulting from DNA molecule behavior. It is found that the capacitance changed from 11.58pF to 114.5pF when specific ssDNA was attached to electrodes and then increased to 218.6pF once complementary strand DNA was involved and hybridized with existing DNA chains. In addition, using impedance analyzer measurements, the resonant frequency decreased from 2.01MHz to 1.97MHz in the presence of ssDNA and further down to 0.95MHz after the complementary strand DNA was deposited.

  • Open access
  • 109 Reads
Opensim Visualization of the classification of finger movements based on electromyography signal as the single input variable during predefined movements.

A classifier is commonly generated for multifunctional prostheses control or also as input devices in human-computer interfaces. The complementary use of the open access biomechanical simulation software, OpenSim, is demonstrated for the hand movement classification performance visualization. The classifier was created from a previously captured database, which has 15 finger movements that were acquired during synchronized hand movements repetitions with an 8-electrode sensor array placed on the forearm; a 92.89% recognition based on a complete movement was obtained. The OpenSim’s upper limb wrist model is employed, with movement in each of the joints of the hand-fingers. Several hand motion visualizations were then generated, for the Ideal hand movements, and for the best and the worst (53.03%)reproduction, in order to perceive the classification error in a specific task movement. This demonstrates the usefulness of this simulation tool before applying the classifier to a multifunctional prosthesis.

  • Open access
  • 62 Reads
Smart glasses and visually evoked potentials applications: characterisation of the optical output for different display technologies.
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Consumer-grade smart-glasses are available now and are being increasingly used in Visually Evoked Potential - Brain Computer Interfaces (VEP-BCI) applications. Among various paradigms, these application represents the one called reactive BCI, in which the user is exposed to a visual stimulus from a display (the smart glasses lenses in this case) and the evoked brain response is detected usually by means of an electroencelograph (EEG) [1]

For example, in steady state VEP-BCI, when two icons, blinking at different frequency (e.g. 10 Hz and 12 Hz), are shown to the user, the EEG measurement of the evoked brain potential allow to discriminate the user attention for one rather that the other icon, without ani active action required by the user. Such a VEP-BCI application requires high distinguishability of the elicited brain potentials to be reliable [2 § 3.2.2], and this aspect may strongly depend on the visual stimulus actually induced by the optical output of the smart glasses.

We characterised the optical output of three models of smart glasses with different display technology, i) Epson BT-200 (based on LCD technology), ii) Epson BT-350 (OLED) and iii) Microsoft Hololens (waveguides), by means of a photo-transducer based on a OPT-101 photodiode, in order to get insight on the exploit-ability of these smart glasses in VEP-BCI applications .

Results will be presented at the conference showing that the display technology used in different models of these consumer-grade smart glasses, and other characteristics, lead to rather different optical outputs for the same nominal programmed stimulus. Hence the choice of the visual technology may strongly depend on the particular target application.


[1] Arpaia P, Callegaro L, Cultrera A, Esposito A, Ortolano M. Metrological characterization of a low-cost electroencephalograph for wearable neural interfaces in industry 4.0 applications. In2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0 & IoT) 2021 Jun 7 (pp. 1-5). IEEE.

[2] Abiri R, Borhani S, Sellers EW, Jiang Y, Zhao X. A comprehensive review of EEG-based brain–computer interface paradigms. Journal of neural engineering. 2019 Jan 9; 16(1) : 011001.

  • Open access
  • 117 Reads
Electrochemical screening of tyrosine and tryptophan as potential biomarkers for prostate cancer
Published: 01 November 2021 by MDPI in 8th International Electronic Conference on Sensors and Applications session Posters

Detection of diseases at an early stage is important for an effective treatment, hence electrochemical biosensors for early detection of many diseases are on their way. Prostate cancer is one of the leading causes of cancer death. In this study, we developed an electrochemical method to measure tyrosine and tryptophan in urine and performed a pilot study to investigate their potential clinical use as biomarkers for prostate cancer. The biosensors were able to measure the tyrosine and tryptophan content in patient urine samples. This study is the first to present electrochemical quantitative data of these amino acids in biological fluids. We demonstrated an inverse correlation between the levels of tyrosine and tryptophan and the clinical stage of prostate cancer. Liquid Chromatography Tandem Mass spectrometry (LC/MS/MS) was used to validate the results obtained by the biosensors. The conventional method for detection of tyrosine and tryptophan is expensive and time-consuming; therefore, the use of the electrochemical biosensor for that purpose seems ideal, due to fast, simple and cheap detection.