Effects of Contact Pressure in Reflectance Photoplethysmography in an In Vitro Tissue-Vessel Phantom

With the continued development and rapid growth of wearable technologies, PPG has become increasingly common in everyday consumer devices such as smartphones and watches. There is, however, minimal knowledge on the effect of the contact pressure exerted by the sensor device on the PPG signal and how it might affect its morphology and the parameters being calculated. This study explores a controlled in vitro study to investigate the effect of continually applied contact pressure on PPG signals (signal-to-noise ratio (SNR) and 17 morphological PPG features) from an artificial tissue-vessel phantom across a range of simulated blood pressure values. This experiment confirmed that for reflectance PPG signal measurements for a given anatomical model, there exists an optimum sensor contact pressure (between 35.1 mmHg and 48.1 mmHg). Statistical analysis shows that temporal morphological features are less affected by contact pressure, lending credit to the hypothesis that for some physiological parameters, such as heart rate and respiration rate, the contact pressure of the sensor is of little significance, whereas the amplitude and geometric features can show significant change, and care must be taken when using morphological analysis for parameters such as SpO2 and assessing autonomic responses.

Pengembangan Sensor Kimia Deteksi Albumin dalam Urin untuk Penyakit Gagal Ginjal Berbasis Cobalt (Co)

Penyakit PGK (Penyakit Gagal Ginjal), protein yang hilang melalui urin dapat menyebabkan penurunan kadar albumin atau hipoalbuminemia. Keluarnya albumin melalui urin disebabkan karena adanya penurunan protein yang keluar kedalam filtrat glomerulus. Pengembangan teknologi sensor untuk mendeteksi gagal ginjal. Pada penelitian ini telah dilakukan pembuatan sensor kimia dengan menggunakan reagen cobalt dan amoniak. Pembuatan sensor kimia menggunakan teknik imobilisasi. Teknik imobilisasi merupakan suatu proses pengikatan molekul reagen cobalt pada bahan pendukung yaitu amoniak sehingga molekul reagen dapat tersebar didalam fase pendukung tersebut secara merata dan homogen. Tahap awal pada pembuatan sensor kimia adalah menentukan kondisi reagen yang optimum. Sensor memiliki hasil optimasi dengan pH optimum pH 7. Memiliki linearitas yang baik pada rentang konsentrasi 150-650 ppm dengan nilai koefisien korelasi r = 0,9677. Waktu pakai strip test lebih dari 3 bulan pada suhu ruang. Hasil penelitian validasi metode ini memenuhi persyaratan standar. Pengembangan sensor kimia berbasis cobalt (Co) dapat digunakan untuk mendeteksi PGK (Penyakit Gagal Ginjal) karena telah memenuhi kriteria validasi metode selektivitas, linearitas, akurasi, presisi, LOD dan LOQ sehingga dapat digunakan dalam deteksi albumin dalam urin.

Investigation on the Printed CNT-Film-Based Electrochemical Sensor for Detection of Liquid Chemicals

We studied electrochemical sensors using printed carbon nanotubes (CNT) film on a polyethylene telephtalate (PET) substrate. The mechanical stability of the printed CNT film (PCF) was confirmed by using bending and Scotch tape tests. In order to determine the optimum sensor structure, a resistance-type PCF sensor (R-type PCF sensor) and a comb-type PCF sensor (C-type PCF sensor) were fabricated and compared using a diluted NH3 droplet with various concentrations. The magnitude of response, response time, sensitivity, linearity, and limit of detection (LOD) were compared, and it was concluded that C-type PCF sensor has superior performance. In addition, the feasibility of PCF electrochemical sensor was investigated using 12 kinds of hazardous and noxious substances (HNS). The detection mechanism and selectivity of the PCF sensor are discussed.

Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

The inverse problem of structural system identification is prone to ill-conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part.

An Innovative Deployment Technique to Optimize Logging Conveyance and Improve Data Quality

Wireline logging in a complex well profile, such as extended reach drilling (ERD) wells, presents many challenges for conveyance and data quality. Traditional pipe conveyed logging (PCL) or coiled tubing (CT) are prohibitive in terms of rig time, operational complexity and cost. Alternatively, tractor conveyance is limited by the available force in long laterals. Tools and accessories create higher friction and might jeopardize tool position in the horizontal section. Consequently, both data quality and reaching total depth are compromised. This paper details an innovative deployment technique using oriented wheels to address these challenges.The new centralizing system, comprised of bespoke wheeled carriages, takes a holistic approach to tool conveyance, reducing drag while ensuring optimum sensor orientation. Tool position is achieved through management of tool center of gravity, relative to the wheel axes. The idea of "centralizing by decentralizing" uses the wheeled carriages instead of bow spring centralizers. An eccentered counterweight is included to ensure the proper orientation of the logging sensors.In addition to improving data quality with proper centralization, the wheels minimize friction and the required force to push the toolstring when combined with a tractor. This enables the toolstring to safely and efficiently reach the well bottom and avoid multiple attempts and associated downhole failures. In the planning phase, calibrated software simulation parameters for this technique help to predict free-fall depth and required tractoring force.The wheeled carriages were deployed in an ERD well for cement evaluation across a 9-5/8" casing and could reach a world record of 85° by gravity. The reduced friction and optimized tool position resulted in higher tractor force margins; and so a net gain in the overall tractoring distance. Also, the low drag and surface tension enabled a sufficient pull capacity with a minimum drive combination. For data acquisition, this deployment enabled a minimum eccentricity, resulting in better cement evaluation data quality and reduced uncertainty related to interpretation. In addition to these benefits, a tangible and direct savings of rig time has improved safety, operational efficiency and well delivery KPIs. Oriented wheels with tractors were deployed in other challenging environments and showed consistent and reliable results.This innovative technique can be deployed in both open-hole and cased-hole with fitted design depending on the borehole size, well profile and complexity of the toolstring configuration.

Optimal thermal sensors placement based on indoor thermal environment characterization by using CFD model

This paper discusses an analysis to obtain the optimal thermal sensor placement based on indoor thermal characteristics. The method relies on the Computational Fluid Dynamics (CFD) simulation by manipulating the outdoor climate and indoor air conditioning (AC) system. First, the alternative sensor's position is considered the optimum installation and the occupant's safety. Utilizing the Standardized Euclidean Distance (SED) analysis, these positions are then selected for the best position using the distribution of the thermal parameters' values data at the activity zones. Onsite measurement validated the CFD model results with the maximum root means square error, RMSE, between both data sets as 0.8°C for temperature, the relative humidity of 3.5%, and an air velocity of 0.08m/s, due to the significant effect of the building location. The Standardized Euclidean Distance (SED) analysis results are the optimum sensor positions that accurately, consistently, and have the optimum % coverage representing the thermal condition at 1,1m floor level. At the optimal positions, actual sensors are installed and proven to be valid results since sensors could detect thermal variables at the height of 1.1m with SED validation values of 2.5±0.3, 2.2±0.6, 2.0±1.1, for R15, R33, and R40, respectively.

Graphene/PSMA composite for gas sensing application

This paper presents the fabrication of conducting polymer sensor which comprise of graphene-poly styrene-co-maleic acid (PSMA) composite that responds to volatile organic compound (VOC) via a change in the electrical resistance of the sensors. Five sensors composed of different material ratio were fabricated to find out the most prominent weight percentage ratio (wt %) for optimum sensor response. Those materials were deposited onto silver electrode using drop-casting method. NI Card PCIE-6323 measures the voltage obtained from the sensor circuit and the resistance of the gas sensor monitored using LabVIEW instrument. It was observed from the experiments that combination of 60% graphene and 40% PSMA gives the highest sensor response.