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Human breath monitoring with embedded condensation sensor for 2 different designs (module size: 30x7.5x8 mm 3 ), copy of oxygen supply canula with upward openings: (a) modified canula with stirrups and (b) downward openings.
Source publication
A portable, non-invasive and easy to operate wireless system has been developed for monitoring the breathing activity of patient. The system is composed of a capacitive microsensor (airflow-humidity sensor) integrated on a silicon chip and of a Negative Temperature Coefficient thermistor; both are connected to a wireless network to allow efficient...
Contexts in source publication
Context 1
... change is thus directly linked to the microsensor response to fluctuations of evaporation / condensation caused by the breathing of the patient. For the board hosting the microsensor and the electronic interface, a comfortable, robust and sterilizable module is designed by rapid prototyping with two small windows in front of each nostril (Fig. 7). To avoid water inside the support tubes and to decrease the response time, epoxy glue insulates the sensing chip from the rest of the module. Rotary junctions between the module and the support tubes allow an adapted fitting for any patient morphology. All the mini modules can be easily disconnected from the transceiver located to the ...
Context 2
... SoC chip is mounted in a DIL 16 package and the signal voltage of the oscillating output is amplified to an acceptable level for the CC2430 on an external PCB. The signal is then transmitted by radio signal. The module described in Fig. 7, as dedicated for the SiP, is not suited for this case. 4 chips were mounted in DIL 16 and consecutively tested under ambient atmosphere and exhaled air. According to ring oscillators supply voltages, oscillation frequency f 0 and power consumption increase. In best case, i.e. for 0.6 V supply, sub-microwatt consumption -0.1 µW -is ...
Context 3
... breath is detected, independently if oral or nasal respiratory tracts are used. Talking during monitoring will cause perturbations by adding unwanted signals, requiring longer counting periods and was not recommended to the patient during measurements. For the mini module, a quick positioning is reached for design b, without parts inside nostrils (Fig. 7). Oriented towards the superior lip, saturation can easily occur, enabling respiratory rate monitoring. A microsensor with thin aluminum oxide, providing higher C wet /C 0 ratios in comparison with anodized microsensor, allows detection for weak breaths, as in the case of old patient revalidation. Other design parameters should be ...
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Citations
... To improve the patients comfort, the electrodes may be integrated into a belt that is attached at the chest [26] or at the abdomen [27], or integrated into a vest [28]. A different capacitive approach is presented in [29]. The sensor is placed below the nose and measures the breath water vapor of the respiration. ...
Contact-free detection of human vital signs like heart rate and respiration rate will improve the patients' comfort and enables long-term monitoring of newborns or bedridden patients. For that, reliable and safe measurement techniques are indispensable. The aim of this work is the development and comparison of novel ultrasonic and capacitive measurement setups, sharing a common hardware platform. Both measurement techniques that are implemented and compared are based on the detection of minor chest wall vibrations in millimeter ranges, due to geometrical thorax changes during respiration and heartbeat activities. After examining the physical measurement conditions and simulating the capacitive sensor, a problem-specific measurement setup is proposed. The system is characterized to be capable of detecting distance changes below 2 {\mu}m via the ultrasonic sensor and below 800 {\mu}m via the capacitive sensor. First subject measurements show that the detection of heart activities is possible under ideal conditions and exclusively with the proposed ultrasonic approach. However, the capacitive sensor works reliably for respiration monitoring, even when the subject is fully-clothed and covered with a blanket. The chosen ultrasonic approach is sensitive regarding minor changes of the reflecting surface and therefore has high uncertainty. In contrast, capacitive respiration detection is very reliable. It is conceivable that improvements in the capacitive sensor circuitry will also enable the detection of heart activities. The proposed ultrasonic approach presents current problems of this technique. In contrast to that, the unusual approach of capacitive sensing demonstrates a high potential regarding vital signs acquisition.
... To improve the patients comfort, the electrodes may be integrated into a belt that is attached at the chest [26] or at the abdomen [27], or integrated into a vest [28]. A different capacitive approach is presented in [29]. The sensor is placed below the nose and measures the breath water vapor of the respiration. ...
Contact-free detection of human vital signs like heart rate and respiration rate will improve the patients’ comfort and enables long-term monitoring of newborns or bedridden patients. For that, reliable and safe measurement techniques are indispensable. The aim of this work is the development and comparison of novel ultrasonic and capacitive measurement setups, sharing a common hardware platform. Both measurement techniques that are implemented and compared are based on the detection of minor chest wall vibrations in millimeter ranges, due to geometrical thorax changes during respiration and heartbeat activities. After examining the physical measurement conditions and simulating the capacitive sensor, a problem-specific measurement setup is proposed. The system is characterized to be capable of detecting distance changes below 2μm via the ultrasonic sensor and below 800μm via the capacitive sensor. First subject measurements show that the detection of heart activities is possible under ideal conditions and exclusively with the proposed ultrasonic approach. However, the capacitive sensor works reliably for respiration monitoring, even when the subject is fully-clothed and covered with a blanket. The chosen ultrasonic approach is sensitive regarding minor changes of the reflecting surface and therefore has high uncertainty. In contrast, capacitive respiration detection is very reliable. It is conceivable that improvements in the capacitive sensor circuitry will also enable the detection of heart activities. The proposed ultrasonic approach presents current problems of this technique. In contrast to that, the unusual approach of capacitive sensing demonstrates a high potential regarding vital signs acquisition.
... The figure illustrates a substantially improved current consumption for the proposed WPMS with sleep/wake algorithm compared with conventional WPMS. The life comparison relative to many related studies is shown in Figure 11 [3,6,7,19,20,23,32,34,50]. ...
Power consumption is an essential challenge in medical application devices using WSN, where the patient who carries a battery power system. Thus, an energy-efficient monitoring system that can independently measure the vital signs of the patient is necessary. This study presents an energy-efficient wearable patient monitoring system (WPMS) to monitor the temperature, heart rate, and oxygen level in the blood (SpO2). A low power consumption ZigBee wireless protocol was interfaced with Arduino Pro Mini microcontroller based on Atmega 328P to alert caregivers in real-time during emergency cases when risks are observed in the patient's biomedical signs. A sleep/wake algorithm has been proposed and implemented inside the microcontroller to improve the power consumption of this wearable device. Results show that the power saving of 92.39% was achieved based on sleep/wake algorithm relative to the traditional wearable device (i.e., without sleep/wake algorithm). In addition, the battery life was extended to approximately 15 days relative to the traditional one-day operation. Comparison results disclosed that the WPMS outperform the power consumption of other studies in medical applications. Where the average current consumption of 6.13 mA is obtained based on the sleep/wake scheme. We can be concluded that the proposed system is energy-efficient, real-time monitoring, cost-effective, none-complex, comfortable due to it is dispense of wire connection, and easily implemented.
... Moreover, a versatile system was introduced to detect heart rate, respiration waveform, and skin temperature via a wearable device [61]. In other studies, continuous respiration monitoring was proposed where the respiration rate was extracted from chest movements or airflow humidity changes in patient's nasal prongs or breathing masks [237,11,96]. ...
The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources.
There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements.
For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed.
This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months.
... The accumulation of water drops on the top of the printed IDC alter the effective permittivity and thus, capacitance changes by up to 105% for 11 drops of water as shown in Fig. 5b. The impedance change is also due to the change in the fingers conductance attributed to the ionic conduction, however in our application, we are interested in the capacitance change solely 25 . This screen-printed sensor was integrated with off-the-shelf components such as resistors, capacitors, a 555-timer, and a counter to form a complete circuitry for humidity sensing. ...
The healthcare system is undergoing a noticeable transformation from a reactive, post-disease treatment to a preventive, predictive continuous healthcare. The key enabler for such a system is a pervasive wearable platform. Several technologies have been suggested and implemented as a wearable platform, but these technologies either lack reliability, manufacturing practicability or pervasiveness. We propose a screen-printed circuit board on bio-degradable hydrocolloid dressings, which are medically used and approved, as a platform for wearable biomedical sensors to overcome the aforementioned problems. We experimentally characterize and prepare the surface of the hydrocolloid and demonstrate high-quality screen-printed passive elements and interconnects on its surface using conductive silver paste. We also propose appropriate models of the thick-film screen-printed passives, validated through measurements and FEM simulations. We further elucidate on the usage of the hydrocolloid dressing by prototyping a Wireless Power Transfer (WPT) sensor and a humidity sensor using printed spiral inductors and interdigital capacitors, respectively.
... Some studies [38][39][40][41][42] have proposed a power-saving algorithm for VSMS based on a variable rate sampling strategy. This proposed algorithm focused on controlling the hardware component sampling frequency, allowing a reduction in the proposed devices' power consumption. ...
... The power consumption of the proposed HVSMS using a DE algorithm was compared with the current drain of other systems outlined in existing studies [16][17][18][19][20][21]24,[37][38][39][40][41][42] on patient vital signs monitoring systems ( Figure 10) to confirm the proposed HVSMS. The performance of the current work in terms of current drain was accomplished by relying on the designed system in Section 3 and was confirmed by the implementation prototype (Section 3) and proposed DE algorithm in Section 4, and current consumption modeling (Section 5) and current measurements (Section 6.1). ...
Elderly fall detection systems based on wireless body area sensor networks (WBSNs) have increased significantly in medical contexts. The power consumption of such systems is a critical issue influencing the overall practicality of the WBSN. Reducing the power consumption of these networks while maintaining acceptable performance poses a challenge. Several power reduction techniques can be employed to tackle this issue. A human vital signs monitoring system (HVSMS) has been proposed here to measure vital parameters of the elderly, including heart rate and fall detection based on heartbeat and accelerometer sensors, respectively. In addition, the location of elderly people can be determined based on Global Positioning System (GPS) and transmitted with their vital parameters to emergency medical centers (EMCs) via the Global System for Mobile Communications (GSM) network. In this paper, the power consumption of the proposed HVSMS was minimized by merging a data-event (DE) algorithm and an energy-harvesting-technique-based wireless power transfer (WPT). The DE algorithm improved HVSMS power consumption, utilizing the duty cycle of the sleep/wake mode. The WPT successfully charged the HVSMS battery. The results demonstrated that the proposed DE algorithm reduced the current consumption of the HVSMS to 9.35 mA compared to traditional operation at 85.85 mA. Thus, an 89% power saving was achieved based on the DE algorithm and the battery life was extended to 30 days instead of 3 days (traditional operation). In addition, the WPT was able to charge the HVSMS batteries once every 30 days for 10 h, thus eliminating existing restrictions involving the use of wire charging methods. The results indicate that the HVSMS current consumption outperformed existing solutions from previous studies.
... Complex, Costly. Nicolas Andre et al. [12] proposed the concept of using capacitive micro sensors and negative temperature coefficient thermistor integrated on a silicon chip to monitor breathing with the help of wireless sensor system. ...
This research presents the usage of modern 5G C-Band sensing for health care monitoring. The focus of this research is to monitor the respiratory symptoms for COPD (Chronic Obstructive Pulmonary Disease). The C-Band sensing is used to detect the respiratory conditions, including normal, abnormal breathing and coughing of a COPD patient by utilizing the simple wireless devices, including a desktop system, network interface card, and the specified tool for the extraction of wireless channel information with Omni directional antenna operating at 4.8 GHz frequency. The 5G sensing technique enhances the sensing performance for the health care sector by monitoring the amplitude information for different respiratory activities of a patient using the above-mentioned devices. This method examines the rhythmic breathing patterns obtained from C-Band sensing and digital respiratory sensor and compared the result.
... Complex, Costly. Nicolas Andre et al. [12] proposed the concept of using capacitive micro sensors and negative temperature coefficient thermistor integrated on a silicon chip to monitor breathing with the help of wireless sensor system. ...
This research presents the usage of modern 5G C-Band sensing for health care monitoring. The focus of this research is to monitor the respiratory symptoms for COPD (Chronic Obstructive Pulmonary Disease). The C-Band sensing is used to detect the respiratory conditions, including normal, abnormal breathing and coughing of a COPD patient by utilizing the simple wireless devices, including a desktop system, network interface card, and the specified tool for the extraction of wireless channel information with Omni-directional antenna operating at 4.8 GHz frequency. The 5G sensing technique enhances the sensing performance for the health care sector by monitoring the amplitude information for different respiratory activities of a patient using the above-mentioned
devices. This method examines the rhythmic breathing patterns obtained from C-Band sensing and digital respiratory sensor and compared the result.
... Periodical clinical reassessment With Internet of Things-based solutions vital signs can be recorded using wireless devices connected to a gateway (Hart et al., 2010;Shi-Lin et al., 2015), body worn wireless sensors (Andre et al., 2010;Donnelly et al., 2012;Huang et al., 2013) or ambient sensors attached on walls or objects (Güder et al., 2016;Mamun et al., 2014;Xinming Huang et al., 2015;Zito et al., 2011). Wireless detection systems have the advantage of giving patients real-time dependable and continuous monitoring without causing any inconvenience to patients (Hu et al., 2010). ...
... Respiratory rate and pattern can be detected contactless from chest movements, using ultra-wideband technology (Xinming Huang et al., 2015;Zito et al., 2011). The sensor can also be connected into a patient's nasal prongs (Andre et al., 2010) or attached into a breathing mask (Güder et al., 2016) to detect respiration through airflow humidity changes. Humidity changes ionic conductivity which can be measured electrically and the data can be further transmitted to a smartphone or tablet computer for post-processing (Güder et al., 2016). ...
Background:
The novel technology of the Internet of Things (IoT) connects objects to the Internet and its most advanced applications refine obtained data for the user. We propose that Internet of Things technology can be used to promote basic nursing care in the hospital environment by improving the quality of care and patient safety.
Objectives:
To introduce the concept of Internet of Things to nursing audience by exploring the state of the art of Internet of Things based technology for basic nursing care in the hospital environment.
Data sources and review methods:
Scoping review methodology following Arksey & O'Malley's stages from one to five were used to explore the extent, range, and nature of current literature. We searched eight databases using predefined search terms. A total of 5030 retrievals were found which were screened for duplications and relevancy to the study topic. 265 papers were chosen for closer screening of the abstracts and 93 for full text evaluation. 62 papers were selected for the review. The constructs of the papers, the Internet of Things based innovations and the themes of basic nursing care in hospital environment were identified.
Results:
Most of the papers included in the review were peer-reviewed proceedings of technological conferences or articles published in technological journals. The Internet of Things based innovations were presented in methodology papers or tested in case studies and usability assessments. Innovations were identified in several topics in four basic nursing care activities: comprehensive assessment, periodical clinical reassessment, activities of daily living and care management.
Conclusions:
Internet of Things technology is providing innovations for the use of basic nursing care although the innovations are emerging and still in early stages. Internet of things is yet vaguely adopted in nursing. The possibilities of the Internet of Things are not yet exploited as well as they could. Nursing science might benefit from deeper involvement in engineering research in the area of health.
... As global demographic trend of aging will result in increasing healthcare workforce shortage 7,8 , electronic healthcare monitoring is gradually taking over the role of human-based observation on both diagnostic and therapeutic sides 9-14 . It is predicted that wirelessly networked sensors with not only high sensitivity, but also small size, low power and minimum cost (in fabrication, deployment and maintenance) will receive growing popularity in healthcare industry 13,15 . ...
Autonomous liquid-volume monitoring is crucial in ubiquitous healthcare. However, conventional approach is based on either human visual observation or expensive detectors, which are costly for future pervasive monitoring. Here we introduce a novel approach based on passive harmonic transponder antenna sensor and frequency hopping spread spectrum (FHSS) pattern analysis, to provide a very low cost wireless μL-resolution liquid-volume monitoring without battery or digital circuits. In our conceptual demonstration, the harmonic transponder comprises of a passive nonlinear frequency multiplier connected to a metamaterial-inspired 3-D antenna designed to be highly sensitive to the liquid-volume within a confined region. The transponder first receives some FHSS signal from an interrogator, then converts such signal to its harmonic band and re-radiates through the antenna sensor. The harmonic signal is picked up by a sniffer receiver and decoded through pattern analysis of the high dimensional FHSS signal strength data. A robust, zero power, absolute accuracy wireless liquid-volume monitoring is realized in the presence of strong direct coupling, background scatters, distance variance as well as near-field human-body interference. The concepts of passive harmonic transponder sensor, metamaterial-inspired antenna sensor, and FHSS pattern analysis based sensor decoding may help establishing cost-effective, energy-efficient and intelligent wireless pervasive healthcare monitoring platforms.
