ABSTRACT
Due to improvements in information and communication technology and growth of sensor technologies, Internet of Things is now widely used in medical field for optimal resource management and ubiquitous sensing. In hospitals, many IoT devices are linked together via gateways. Importance of gateways in modernization of hospitals cannot be overstated, but their centralized nature exposes them to a variety of security threats, including integrity, certification, and availability. Block chain technology for level monitoring in oxygen cylinders is a scattered record containing the data related to oxygen levels in the cylinder, patient's name, patient's ID number, patient's medical history, and all connected information carried out and distributed among the hospitals (nodes) present in the locality (network). Designing an oxygen level monitoring technique in an oxygen cylinder used as the support system for COVID-19-affected patients is a challenging task. Monitoring the level of oxygen in the cylinders is very important because they are used for saving the lives of the patients suffering from COVID-19. Not only the COVID-19 patients are dependent on this system, but this system will also be helpful for other patients who require oxygen support. The present scenario many COVID-19 hospitalized patients rely upon oxygen supply through oxygen cylinders and manual monitoring of oxygen levels in these cylinders has become a challenging task for the healthcare professionals due to overcrowding. If this level monitoring of oxygen cylinders are automated and developed as a mobile App, it would be of great use to the medical field, saving the lives of the patients who are left unmonitored during this pandemic. This proposal is entitled to develop a system to measure oxygen level using a smartphone App which will send instantaneous values about the level of the oxygen inside the cylinder. Pressure sensors and load cell are fitted to the oxygen cylinders, which will measure the oxygen content inside the cylinder in terms of the pressure and weight. The pressure sensors and load cells are connected to the Arduino board and are programmed to display the actual level of oxygen inside the cylinder in terms of numerical values. A beep sound is generated as an indicator to caution the nurses and attendants of the patients regarding the level of the oxygen inside the cylinder when it is only 15% of the total oxygen level in the cylinder in correlation to the pressure and weight. The signal with respect to the level corresponding to the measured pressure and weight of the cylinder is further transmitted to the monitoring station through Global System for Mobile communication (GSM). Graphical display is used at monitoring end to indicate the level of oxygen inside all oxygen cylinders to facilitate actions like 100% full, 80% full, 60% full, 40% full, 20% full which states that either the oxygen cylinder is in good condition, or requires a replacement of empty cylinders with filled ones in correlation to the pressure and weight being sensed by the sensors. The levels of the oxygen monitored inside the cylinder and other related data can also be stored on a cloud storage which will facilitate the retrieval of the status at any point of time, as when required by the physicians and nurses. These results reported, are valued in monitoring the level of the oxygen cylinder remotely connected to the patients, affected by COVID-19, using a smartphone App. This mobile phone App is an effective tool for investigating the oxygen cylinder level used as a life-support system for COVID-19-affected patients. A virtual model of the partial system is developed using TINKER CAD simulation package. In real time, the sensor data analysis with cloud computing will be deployed to detect and track the level of the oxygen cylinders. © 2023 Elsevier Inc. All rights reserved.
ABSTRACT
To meet the growing demand for sustainable development and ecofriendliness, hydrogels based on biopolymers have attracted widespread attention for developing flexible pressure sensors. Natural globular proteins exhibit great potential for developing biobased pressure sensors owing to their advantages of high water solubility, easy gelation, biocompatibility, and low production cost. However, realizing globular protein hydrogel-based sensors with interfacial and bulk toughness for pressure sensing and use in wearable devices remains a challenge. This study focuses on developing a high-performance flexible pressure sensor based on a biobased protein hydrogel. Consequently, a flexible protein/polyacrylamide (PAM) hydrogel with a featured double-network (DN) structure linked covalently with hydrogen bonds was first synthesized via a one-pot method based on natural ovalbumin (OVA). The unique DN structure of the as-synthesized OVA/PAM hydrogel affords excellent mechanical performance, flexibility, and adhesion properties. The mechanical properties of the DN hydrogel were enhanced after further cross-linking with Fe3+ and treatment with glycerol. Subsequently, the flexible pressure sensor was constructed by sandwiching a microstructured OVA/PAM dielectric layer between two flexible silver nanowire electrodes. The obtained sensor exhibits a high sensitivity of 2.9 kPa-1 and a short response time of 18 ms, ensuring the ability to monitor physiological signals. Based on its excellent performance, the fabricated sensor was used for monitoring the signals obtained using practical applications such as wrist bending, finger knocking, stretching, international Morse code, and pressure distribution. Particularly, we implemented a contactless delivery system using the fabricated OVA-based pressure sensors linked to unmanned vehicles and global positioning systems, providing a solution for low-risk commodity distribution during Coronavirus disease 2019 (COVID-19).
ABSTRACT
Ventilators we are available with have several drawbacks such as difficult to port, expensive and meant to be operated by professionals which create hardness in fighting with medical care. Thus, it creates suffering for people in the pandemic like COVID19. So, it is required to develop a ventilator that can be affordable, easy to port and install. We aimed to design a IoT based ventilator system using various electronic devices such as microcontroller and sensors that could monitor patient's body status. People suffering from COVID19 or any lung disease find difficulty in breathing so in such condition of emergency this smart ventilator system can be used. Ambu bag is used to provide certain volume of air that is pressed by using motor mechanism. A portable low-cost ventilator with computerized controlling and feedback system is installed. Ventilator designed can be connected to an interface for smart functioning. This paper provides us with different methods to monitor the patient's health condition by measurement of pressure, level of breathing to know whether the condition is healthy or unhealthy. The designing and developing of low-cost portable ventilator deliver breaths to patients when Ambu bag is compressed by using a piston connected to servo motor whose speed can be varied. Input of the designed system is patient's heart beat and breathing rate and the volume of oxygen provided to patient's lung with required beathing rate is the output of the system. PID (proportional Integral Derivative) and Full state feedback H2 controllers are used for the performance analysis of the system. Result of this review paper is found that a low-cost ventilator is developed removing all the possible shortcomings of existing conventional ventilator. Ventilator designed is portable and smart by using Arduino, servo motor and ambu bag preferred for emergency uses and available for clinical application. © 2023 IEEE.
ABSTRACT
To meet the growing demand for sustainable development and ecofriendliness, hydrogels based on biopolymers have attracted widespread attention for developing flexible pressure sensors. Natural globular proteins exhibit great potential for developing biobased pressure sensors owing to their advantages of high water solubility, easy gelation, biocompatibility, and low production cost. However, realizing globular protein hydrogel-based sensors with interfacial and bulk toughness for pressure sensing and use in wearable devices remains a challenge. This study focuses on developing a high-performance flexible pressure sensor based on a biobased protein hydrogel. Consequently, a flexible protein/polyacrylamide (PAM) hydrogel with a featured double-network (DN) structure linked covalently with hydrogen bonds was first synthesized via a one-pot method based on natural ovalbumin (OVA). The unique DN structure of the as-synthesized OVA/PAM hydrogel affords excellent mechanical performance, flexibility, and adhesion properties. The mechanical properties of the DN hydrogel were enhanced after further cross-linking with Fe3+ and treatment with glycerol. Subsequently, the flexible pressure sensor was constructed by sandwiching a microstructured OVA/PAM dielectric layer between two flexible silver nanowire electrodes. The obtained sensor exhibits a high sensitivity of 2.9 kPa-1 and a short response time of 18 ms, ensuring the ability to monitor physiological signals. Based on its excellent performance, the fabricated sensor was used for monitoring the signals obtained using practical applications such as wrist bending, finger knocking, stretching, international Morse code, and pressure distribution. Particularly, we implemented a contactless delivery system using the fabricated OVA-based pressure sensors linked to unmanned vehicles and global positioning systems, providing a solution for low-risk commodity distribution during Coronavirus disease 2019 (COVID-19). © 2023 American Chemical Society.
ABSTRACT
In this study, a tunable terahertz (THz) metamaterial using the micro-electro-mechanical system (MEMS) technique is proposed to demonstrate pressure sensing application. This MEMS-based tunable metamaterial (MTM) structure is composed of gold (Au) split-ring resonators (SRRs) on patterned silicon (Si) substrate with through Si via (TSV). SRR is designed as a cantilever on the TSV structure. When the airflow passes through the TSV from bottom to up and then bends the SRR cantilever, the SRR cantilever will bend upward. The electromagnetic responses of MTM show the tunability and polarization-dependent characteristics by bending the SRR cantilever. The resonances can both be blue-shifted from 0.721 THz to 0.796 THz with a tuning range of 0.075 THz in transverse magnetic (TM) mode and from 0.805 THz to 0.945 THz with a tuning range of 0.140 THz in transverse electric (TE) mode by changing the angle of SRR cantilever from 10° to 45°. These results provide the potential applications and possibilities of MTM design for use in pressure and flow rate sensors.
ABSTRACT
We are surrounded by oxygen in the air we We cannot even exist without the ability to breathe. The need for oxygen has increased during the COVID19 pandemic, and although there is enough oxygen in our country, the main issue is getting it to hospitals or those in need on time. This is simply due to a significant communication gap between suppliers and hospitals, so we plan to implement an idea that will close this gap using real-time tracking as we can track the movement of oxygen tankers by gathering the requirements. We are using an ESP32 Wi-Fi module, a MEMS pressure sensor that enables the combination of precise sensors, potential processing, and wireless communication, such as Wi-Fi, Bluetooth, IFTTT, and MQTT protocols, to implement it successfully. The pressure sensor publishes the value of oxygen remaining from the location to the MQTT broker. © 2022 IEEE.
ABSTRACT
Flexible wearable pressure sensors play a pivotal role in healthcare monitoring, disease prevention, and humanmachine interactions. However, their narrow sensing ranges, low detection sensitivities, slow responses, and complex preparation processes restrict their application in smart wearable devices. Herein, a capacitive pressure sensor with high sensitivity and flexibility that uses an ionic collagen fiber material as the dielectric layer is proposed. The sensor exhibits a high sensitivity (5.24 kPa-1), fast response time (40 ms), long-term stability, and excellent repeatability over 3000 cycles. Because the sensor is resizable, flexible, and has a simple preparation process, it can be flexibly attached to clothes and the human body for wearable monitoring. Furthermore, the practicality of the sensor is proven by attaching it to different measurement positions on the human body to monitor the activity signal.
ABSTRACT
The increasingly active cases of people with the COVID- 19 viruses have reached a very worrying level in most countries globally. The availability of ventilators in hospitals is one factor that increases the number of deaths in Indonesia. In this study, we present a control system on a mechanical ventilator using an inexpensive pressure sensor to control pressure, flow rate, and volume during the process of inspiration and expiration. The implemented method uses the venturi meter concept by comparing two air pressure sensors flowed by the Ambu bag. The control system on this ventilator uses a microcontroller and MPX5050DP sensor. The system tries to maintain the PEEP value of 5 cmH2O, and the feedback obtained ranges from 2.7-5.16 cmH2O. At the same time, the expected flowrate value of 55 L/min can be maintained at a value of 53.9 - 59.5 L/min. The tidal volume, which functions as a limiter for inspiration and expiration, is set at a value of 400 ml;the feedback given by the sensor varies between 416 ml - 436 ml. Nevertheless, on the other hand, this system needs to be developed further because there are problems with sensor precision. © 2021 IEEE.
ABSTRACT
A novel highly sensitive cone structured porous polydimethylsiloxane (PDMS) based pressure sensor capable of detecting very low-pressure ranges was developed for wearable respiration monitoring applications. The pressure sensor was fabricated using a master mold, a dielectric layer and fabric-based electrodes. The master mold with inverted cone structures was created using a rapid and precise three-dimensional (3D) printing technique. The dielectric layer with a porous and cone structures was prepared by annealing the mixture of PDMS, nitric acid (HNO3) and sodium bicarbonate (NaHCO3) in a master mold with inverted cone structures. The electrodes were developed by screen printing silver on fabric. A sensitivity of approximate to 530 %kPa(-1) was measured for the fabricated pressure sensor at ultra-low-pressure ranges from 0 Pa to 10 Pa. The porous-cone structures provided an excellent deformation and thus resulted in high sensitivity for detecting very low pressure ranges below 100 Pa (135 %kPa(-1)). As application demonstration, the pressure sensor was sewed inside a surgical mask and it's capability to detect different respiration rates (normal, fast, and deep breathes) was investigated. An airflow controller system and custom-built software was also developed for performing the continuous sensor data acquisition and capacitance conversions while changing the airflow rate.
ABSTRACT
With the research and the development of graphene-based materials, new sensors based on graphene compound materials are of great significance to scientific research and the consumer market. However, in the past ten years, due to the requirements of sensor accuracy, reliability, and durability, the development of new graphene sensors still faces many challenges in the future. Due to the special structure of graphene, the obtained characteristics can meet the requirements of high-performance sensors. Therefore, graphene materials have been applied in many innovative sensor materials in recent years. This paper introduces the important role and specific examples of sensors based on graphene and its base materials in biomedicine, photoelectrochemistry, flexible pressure, and other fields in recent years, and it puts forward the difficulties encountered in the application of graphene materials in sensors. Finally, the development direction of graphene sensors has been prospected. For the past two years of the COVID-19 epidemic, the detection of the virus sensor has been investigated. These new graphene sensors can complete signal detection based on accuracy and reliability, which provides a reference for researchers to select and manufacture sensor materials.
ABSTRACT
Because of the COVID-19 pandemic, the number of bicycle users has increased, raising concerns regarding bicycle safety. Although various small electronic devices have been used to ensure bicycle safety, such devices require an external battery, which introduces certain limitations such as recharging requirements. Several researchers have investigated methods to sustainably harvest energy from bicycles. Triboelectric-generator-based solutions, which can utilize the mechanical motion of a rolling tire can serve as the auxiliary power source of small electronics or self-powered sensors. However, research on practical and reliable bicycle-related triboelectric nanogenerators is limited. In this study, a triboelectric bicycle tire (TBT) was developed, considering the actual material/structure of commercial bicycle tires, and the novel electricity-generation mechanism was clarified. As the TBT system had a fully inserted (packaged) structure, it could generate extremely stable electrical output for 120,000 cycles. The electrical performance was quantitatively analyzed depending on the design parameters and riding situation. The findings demonstrated that the TBT system can be effectively used to enhance bicycle safety;according to the peak magnitude and waveform data, the TBT system can function as a self-powered bicycle pressure sensor. Second, the freestanding-mode TBT system can be utilized as a self-powered bicycle safety light in real time, demonstrated by its ability to power LEDs. © 2021
ABSTRACT
Wearable technologies are known to improve our quality of life. Among the various wearable devices, shoes are non-intrusive, lightweight, and can be used for outdoor activities. In this study, we estimated the energy consumption and heart rate in an environment (i.e., running on a treadmill) using smart shoes equipped with triaxial acceleration, triaxial gyroscope, and four-point pressure sensors. The proposed model uses the latest deep learning architecture which does not require any separate preprocessing. Moreover, it is possible to select the optimal sensor using a channel-wise attention mechanism to weigh the sensors depending on their contributions to the estimation of energy expenditure (EE) and heart rate (HR). The performance of the proposed model was evaluated using the root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). Moreover, the RMSE was 1.05 ± 0.15, MAE 0.83 ± 0.12 and R2 0.922 ± 0.005 in EE estimation. On the other hand, and RMSE was 7.87 ± 1.12, MAE 6.21 ± 0.86, and R2 0.897 ± 0.017 in HR estimation. In both estimations, the most effective sensor was the z axis of the accelerometer and gyroscope sensors. Through these results, it is demonstrated that the proposed model could contribute to the improvement of the performance of both EE and HR estimations by effectively selecting the optimal sensors during the active movements of participants.
Subject(s)
Deep Learning , Shoes , Energy Metabolism , Heart Rate , Humans , Quality of LifeABSTRACT
Heart failure (HF) is a major public health problem and a leading cause of hospitalization in western countries. Over the past decades, the goal has been to find the best method for monitoring congestive symptoms to prevent hospitalizations. Addressing this task through regular physician visits, blood tests, and imaging has proven insufficient for optimal control and has not decreased enough HF-related hospitalization rates. In recent years, new devices have been developed for this reason and CardioMEMS is one of the therapeutic monitoring options. CardioMEMS has shown to be effective in preventing and reducing HF hospitalizations in patients both with HF with reduced ejection fraction and HF with preserved ejection fraction. CardioMEMS' versatility has made it a great option for pulmonary artery pressure monitoring, both during the coronavirus disease-19 (COVID-19) pandemic and when the clinic visits have (partially) resumed. CardioMEMS is the remote haemodynamic monitoring system with the most evidence-driven efficacy, and COVID-19 has put it in the spot as a centre-stage technology for HF monitoring. In a few months of the COVID-19 epidemic, CardioMEMS has grown to maturity, making it the new normal for high-quality, high-value remote HF care.