Search results for: healthcare monitoring

Authors: Komal K., Cleary F., Wells J S.G., Bennett L

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Smart fabric garments enable various monitoring applications across sectors such as healthcare, sports and fitness, and the military. Healthcare smart garments monitoring EEG, EMG, and ECG rely on the use of electrodes (dry or wet). However, such electrodes, when used for long-term monitoring, can cause discomfort and skin irritation for the wearer because of their inflexible structure and weight. Ongoing research has been investigating textile-based electrodes (textrodes) in order to provide more comfortable and usable fabric-based electrodes capable of providing intuitive biopotential monitoring. Progress has been made in this space, but they still face a critical design challenge in maintaining consistent skin contact, which directly impacts signal quality. Furthermore, there is a lack of an ISO-based testing framework to validate the electrode design and assess its ability to achieve enhanced performance, strength, usability, and durability. This study proposes the development and evaluation of an ISO-compliant testing framework for standard 2D and advanced 3D embroidered textrodes designs that have a unique structure in order to establish enhanced skin contact for the wearer. This testing framework leverages ISO standards: ISO 13934-1:2013 for tensile and zone-wise strength tests; ISO 13937-2 for tear tests; and ISO 6330 for washing, validating the textrode's performance, a necessity for wearables health parameter monitoring applications. Five textrodes (C1-C5) were designed using EPC win digitization software. Varying patterns such as running stitches, lock stitches, back-to-back stitches, and moss stitches were used to create various embroidered tetrodes samples using Madeira HC12 conductive thread with a resistivity of 100 ohm/m. The textrode designs were then fabricated using a ZSK technical embroidery machine. A comparative analysis was conducted based on a series of laboratory tests adhering to ISO compliance requirements. Tests focusing on the application of strain were applied to the textrodes, and these included: (1) analysis of the electrode's overall surface area strength; (2) assessment of the robustness of the textrodes boundaries; and (3) the assignment of fault test zones to each textrode, where vertical and horizontal slits of 3mm were applied to evaluate the performance of textrodes and its durability. Specific ISO-compliant tests linked to washing were conducted multiple times on each textrode sample to assess both mechanical and chemical damage. Additionally, abrasion and pilling tests were performed to evaluate mechanical damage on the surface of the textrodes and to compare it with the washing test. Finally, the textrodes were assessed based on morphological and surface resistance changes. Results demonstrate that textrode C4, featuring a 3-D layered structure consisting of foam, fabric, and conductive thread layers, significantly enhances skin-electrode contact for biopotential recording. The inclusion of a 3D foam layer was particularly effective in maintaining the shape of the electrode during strain tests, making it the top-performing textrode sample. Therefore, the layered 3D design structure of textrode C4 ranks highest when tested for durability, reusability, and washability. The ISO testing framework established in this study will support future research, validating the durability and reliability of textrodes for a wide range of applications.

Keywords: smart fabric, textrodes, testing framework, ISO compliant

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Authors: Olusegun Omoluwa, Kolawole Israel Anthony

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Pupils with learning disabilities are found in every classroom, but because learning disabilities cannot be seen, the condition is often too neglected. Unless these pupils are recognised and treated, they are likely to become educational discards. This study consequently attempted to determine effects of self-monitoring strategy on homework completion among pupils with learning disabilities. Ninety (90) participants were engaged in the study. Pre-test, post-test, control group quasi experimental design was adopted. Purposive sampling technique was used to select pupils with evidence of learning disabilities from three primary schools in Ondo State. Findings showed that self-monitoring strategy was significant in enhancing homework completion among pupils with learning disabilities. However, gender and self-esteem did not significantly contribute to homework completion. The study therefore recommended that measures such that would uncover unsettling academic, psychological and emotional deficiencies of these pupils through appropriate diagnosis should be undertaken by the parents and teachers, in order for them to have a sense of belonging in the society.

Keywords: self monitoring, home work completion, learning dissabilities, learning

Procedia PDF Downloads 316

Authors: Mera Ababneh, Sayer Al-Azzam, Karem Alzoubi, Abeer Rababa'h

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Background: Medication errors are among the most common medical errors. Their occurrences result in patient’s mortality, morbidity, and additional healthcare costs. Continuous monitoring and detection is required. Objectives: The aim of this study was to compare medication errors in outpatient’s prescriptions in two different hospitals (paper system vs. electronic system). Methods: This was a cross sectional observational study conducted in two major hospitals; King Abdullah University Hospital (KAUH) and Princess Bassma Teaching Hospital (PBTH) over three months period. Data collection was conducted by two trained pharmacists at each site. During the study period, medication prescriptions and dispensing procedures were screened for medication errors in both participating centers by two trained pharmacist. Results: In the electronic prescription hospital, 2500 prescriptions were screened in which 631 medication errors were detected. Prescription errors were 231 (36.6%), and dispensing errors were 400 (63.4%) of all errors. On the other side, analysis of 2500 prescriptions in paper-based hospital revealed 3714 medication errors, of which 288 (7.8%) were prescription errors, and 3426 (92.2%) were dispensing errors. A significant number of 2496 (67.2%) were inadequately and/or inappropriately labeled. Conclusion: This study provides insight for healthcare policy makers, professionals, and administrators to invest in advanced technology systems, education, and epidemiological surveillance programs to minimize medication errors.

Keywords: medication errors, prescription errors, dispensing errors, electronic prescription, handwritten prescription

Procedia PDF Downloads 249

Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: all-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk

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Authors: Marketa Kotova, Jana Kolarova, Ludek Zalud, Petr Dobsak

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A game for training of breath (TRABR) for continuous monitoring of pulmonary ventilation during the patients’ therapy focuses especially on monitoring of their ventilation processes. It is necessary to detect, monitor and differentiate abdominal and thoracic breathing during the therapy. It is a fun form of rehabilitation where the patient plays and also practicing isolated breathing. Finally the game to practice breath was designed to evaluate whether the patient uses two types of breathing or not.

Keywords: pulmonary ventilation, thoracic breathing, abdominal breathing, breath monitoring using pressure sensors, game TRABR TRAining of BReath)

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: Josephine Aikpitanyi, Friday Okonofua, Lorrettantoimo, Sandy Tubeuf

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Every day, 800 women die from conditions related to pregnancy and childbirth, resulting in an estimated 300,000 maternal deaths worldwide per year. Over 99 percent of all maternal deaths occur in developing countries, with more than half of them occurring in sub-Saharan Africa. Nigeria being the most populous nation in sub-Saharan Africa bears a significant burden of worsening maternal and child health outcomes with a maternal mortality rate of 917 per 100,000 live births and child mortality rate of 117 per 1,000 live births. While several studies have documented that financial barriers disproportionately discourage poor women from seeking needed maternal and child healthcare, other studies have indicated otherwise. Evidence shows that there are instances where health facilities with skilled healthcare providers exist, and yet maternal, and child health outcomes remain abysmally low, indicating the presence of non-cognitive and behavioural factors that may affect the utilization of healthcare services. This study investigated the influence of locus of control and self-esteem on utilization of maternal and child healthcare services in Nigeria. Specifically, it explored the differences in utilization of antenatal care, skilled birth care, postnatal care, and child vaccination by women having an internal and external locus of control and women having high and low self-esteem. We collected information on non-cognitive traits of 1411 randomly selected women, along with information on utilization of the various indicators of maternal and child healthcare. Estimating logistic regression models for various components of healthcare services utilization, we found that women’s internal locus of control was a significant predictor of utilization of antenatal care, skilled birth care, and completion of child vaccination. We also found that having high self-esteem was a significant predictor of utilization of antenatal care, postnatal care, and completion of child vaccination after adjusting for other control variables. By improving our understanding of non-cognitive traits as possible barriers to maternal and child healthcare utilization, our findings offer important insights for enhancing participant engagement in intervention programs that are initiated to improve maternal and child health outcomes in low-and-middle-income countries.

Keywords: behavioural economics, health-seeking behaviour, locus of control and self-esteem, maternal and child healthcare, non-cognitive traits, and healthcare utilization

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Authors: Andrew Hall, Paul Clarkson

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Climate change is predicted to increase the number of extreme weather events intensifying the strain on Railway Earthworks. This paper describes the use of Distributed Rayleigh Sensing to monitor low frequency activity on a vulnerable earthworks sectionprone to landslides alongside a railway line in Northern Spain. The vulnerable slope is instrumented with conventional slope stability sensors allowing an assessment to be conducted of the application of Distributed Rayleigh Sensing as an earthwork condition monitoring tool to enhance the resilience of railway networks.

Keywords: condition monitoring, railway earthworks, distributed rayleigh sensing, climate change

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Authors: Andrey V. Timofeev, Dmitry Egorov

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This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: C-OTDR monitoring system, bimodal processing, LPboost, SVM

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Authors: Jessica Hemberg, Mikaela Miller

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Unreasonable workload and work-related stress can reduce nurse leaders’ job satisfaction and productivity and can increase absence and burnout. Nurse leaders’ workload in public healthcare settings is relatively unresearched. The aim of this study was to investigate nurse leaders’ perceptions of workload and task distribution with relation to leading work tasks in public healthcare. A qualitative explorative design was used. The data material consisted of texts from interviews with nurse leaders in public healthcare (N=8). The method was inspired by content analysis. The COREQ checklist was used. Informed consent was sought from the participants regarding study participation and the storage and handling of data for research purposes. Six main themes were found: Increased and unreasonable workload, Length of work experience as nurse leader affects perception of workload, Number of staff and staff characteristics affect perception of workload, Versatile and flexible task distribution, Working overtime as a way of managing high workload, and Insufficient time for leadership mission. The workload for nurse leaders in a public healthcare setting was perceived to be unreasonable. Common measures for managing high workload included working overtime, delegating work tasks and organizing more staff resources in the form of additional staff. How nurse leaders perceive their workload was linked to both the number of staff and staff characteristics. These should both be considered equally important when determining staff levels and measuring nurse leaders’ workload. Future research should focus on investigating workload and task distribution from nurses’ perspectives.

Keywords: nurse leaders, workload, task distribution, public healthcare, qualitative

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Authors: Brock Liden, Eric Janowitz

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Introduction: Diabetic peripheral neuropathy (DPN) affects 70% of individuals with diabetes1. DPN causes a loss of protective sensation, which can lead to tissue damage and diabetic foot ulcer (DFU) formation2. These ulcers can result in infections and lower-extremity amputations of toes, the entire foot, and the lower leg. Even after a DFU is healed, recurrence is common, with 49% of DFU patients developing another ulcer within a year and 68% within 5 years3. This case series examines the use of sensory insoles and newly available plantar data (pressure, temperature, step count, adherence) and remote patient monitoring in patients at risk of DFU. Methods: Participants were provided with custom-made sensory insoles to monitor plantar pressure, temperature, step count, and daily use and were provided with real-time cues for pressure offloading as they went about their daily activities. The sensory insoles were used to track subject compliance, ulceration, and response to feedback from real-time alerts. Patients were remotely monitored by a qualified healthcare professional and were contacted when areas of concern were seen and provided coaching on reducing risk factors and overall support to improve foot health. Results: Of the 40 participants provided with the sensory insole system, 4 presented with a DFU. Based on flags generated from the available plantar data, patients were contacted by the remote monitor to address potential concerns. A standard clinical escalation protocol detailed when and how concerns should be escalated to the provider by the remote monitor. Upon escalation to the provider, patients were brought into the clinic as needed, allowing for any issues to be addressed before more serious complications might arise. Conclusion: This case series explores the use of innovative sensory technology to collect plantar data (pressure, temperature, step count, and adherence) for DFU detection and early intervention. The results from this case series suggest the importance of sensory technology and remote patient monitoring in providing proactive, preventative care for patients at risk of DFU. This robust plantar data, with the addition of remote patient monitoring, allow for patients to be seen in the clinic when concerns arise, giving providers the opportunity to intervene early and prevent more serious complications, such as wounds, from occurring.

Keywords: diabetic foot ulcer, DFU prevention, digital therapeutics, remote patient monitoring

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Authors: K. Shiba, T. Kobayashi, T. Kaburagi, Y. Kurihara

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Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Keywords: turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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Authors: Raed Alsufyani, Hissam Tawfik, Victor Chang, Muthu Ramachandran

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This study investigates the factors that influence the decision by players in the healthcare sector to embrace Cloud Business Intelligence Technology with a focus on healthcare organizations in Saudi Arabia. To bring this matter into perspective, this study primarily considers the Technology-Organization-Environment (TOE) framework and the Human Organization-Technology (HOT) fit model. A survey was hypothetically designed based on literature review and was carried out online. Quantitative data obtained was processed from descriptive and one-way frequency statistics to inferential and regression analysis. Data were analysed to establish factors that influence the decision to adopt Cloud Business intelligence technology in the healthcare sector. The implication of the identified factors was measured, and all assumptions were tested. 66.70% of participants in healthcare organization backed the intention to adopt cloud business intelligence system. 99.4% of these participants considered security concerns and privacy risk have been the most significant factors in the adoption of cloud Business Intelligence (CBI) system. Through regression analysis hypothesis testing point that usefulness, service quality, relative advantage, IT infrastructure preparedness, organization structure; vendor support, perceived technical competence, government support, and top management support positively and significantly influence the adoption of (CBI) system. The paper presents quantitative phase that is a part of an on-going project. The project will be based on the consequences learned from this study.

Keywords: cloud computing, business intelligence, HOT-fit model, TOE, healthcare and innovation adoption

Procedia PDF Downloads 139

Authors: Teo Hao Jing, Shane Ho Ken Wae, Lee Jin Yu, Burra Venkata Durga Kumar

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Current distributed healthcare systems face the challenge of interoperability of health data. Storing electronic health records (EHR) in local databases causes them to be fragmented. This problem is aggravated as patients visit multiple healthcare providers in their lifetime. Existing solutions are unable to solve this issue and have caused burdens to healthcare specialists and patients alike. Blockchain technology was found to be able to increase the interoperability of health data by implementing digital access rules, enabling uniformed patient identity, and providing data aggregation. Consortium blockchain was found to have high read throughputs, is more trustworthy, more secure against external disruptions and accommodates transactions without fees. Therefore, this paper proposes a blockchain-based model for data management applications. In this model, a consortium blockchain is implemented by using a delegated proof of stake (DPoS) as its consensus mechanism. This blockchain allows collaboration between users from different organizations such as hospitals and medical bureaus. Patients serve as the owner of their information, where users from other parties require authorization from the patient to view their information. Hospitals upload the hash value of patients’ generated data to the blockchain, whereas the encrypted information is stored in a distributed cloud storage.

Keywords: blockchain technology, data management applications, healthcare, interoperability, delegated proof of stake

Procedia PDF Downloads 113

Authors: Keiko Sakai

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In Japan, all stages of public education aim to foster a zest for life. ‘Zest’ implies solving problems by oneself, using acquired knowledge and skills. It is related to the self-regulation of metacognition. To enhance this, establishing good learning habits is important. Tardiness in undergraduate students should be examined based on self-regulation. Accordingly, we focussed on self-monitoring and self-planning strategies among self-regulated learning factors to examine the causes of tardiness. This study examines the impact of self-monitoring and self-planning learning skills on the degree and reason for tardiness in undergraduate students. A questionnaire survey was conducted, targeted to undergraduate students in University X in the autumn semester of 2018. Participants were 247 (average age 19.7, SD 1.9; 144 males, 101 females, 2 no answers). The survey contained the following items and measures: school year, the number of classes in the semester, degree of tardiness in the semester (subjective degree and objective times), active participation in and action toward schoolwork, self-planning and self-monitoring learning skills, and reason for tardiness (open-ended question). First, the relation between strategies and tardiness was examined by multiple regressions. A statistically significant relationship between a self-monitoring learning strategy and the degree of subjective and objective tardiness was revealed, after statistically controlling the school year and the number of classes. There was no significant relationship between a self-planning learning strategy and the degree of tardiness. These results suggest that self-monitoring skills reduce tardiness. Secondly, the relation between a self-monitoring learning strategy and the reason of tardiness was analysed, after classifying the reason for tardiness into one of seven categories: ‘overslept’, ‘illness’, ‘poor time management’, ‘traffic delays’, ‘carelessness’, ‘low motivation’, and ‘stuff to do’. Chi-square tests and Fisher’s exact tests showed a statistically significant relationship between a self-monitoring learning strategy and the frequency of ‘traffic delays’. This result implies that self-monitoring skills prevent tardiness because of traffic delays. Furthermore, there was a weak relationship between a self-monitoring learning strategy score and the reason-for-tardiness categories. When self-monitoring skill is higher, a decrease in ‘overslept’ and ‘illness’, and an increase in ‘poor time management’, ‘carelessness’, and ‘low motivation’ are indicated. It is suggested that a self-monitoring learning strategy is related to an internal causal attribution of failure and self-management for how to prevent tardiness. From these findings, the effectiveness of a self-monitoring learning skill strategy for reducing tardiness in undergraduate students is indicated.

Keywords: higher-education, self-monitoring, self-regulation, tardiness

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Authors: Wannakorn Sangthongngam, Melissa Huerta, Jaewoo Kim, Doyeon Kim

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Continuous glucose monitoring systems are essential for diabetics to avoid health complications but come at a costly price, especially when insurance does not fully cover the diabetic testing kits needed. This paper proposes a noninvasive continuous glucose monitoring system to provide an accessible, low-cost, and painless alternative method of accurate glucose measurements to help improve quality of life. Using a light source with a wavelength of 850nm illuminates the fingertip for the photodetector to detect the transmitted light. Utilizing SeeDevice’s photon-assisted tunneling photodetector (PAT-PD)-based QMOS™ sensor, fluctuations of voltage based on photon absorption in blood cells are comparable to traditional glucose measurements. The performance of the proposed method was validated using 4 test participants’ transmitted voltage readings compared with measurements obtained from the Accu-Chek glucometer. The proposed method was able to successfully measure concentrations from linear regression calculations.

Keywords: continuous glucose monitoring, non-invasive continuous glucose monitoring, NIR, photon-assisted tunneling photodetector, QMOS™, wearable device

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Authors: Yihua Wang, Yunru Lai

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Statistical process control has been successfully applied in a variety of industries. In some applications, the quality of a process or product is better characterized and summarized by a functional relationship between a response variable and one or more explanatory variables. A collection of this type of data is called a profile. Profile monitoring is used to understand and check the stability of this relationship or curve over time. The independent assumption for the error term is commonly used in the existing profile monitoring studies. However, in many applications, the profile data show correlations over time. Therefore, we focus on a general linear regression model with a first-order autocorrelation between profiles in this study. We propose an exponentially weighted moving average charting scheme to monitor this type of profile. The simulation study shows that our proposed methods outperform the existing schemes based on the average run length criterion.

Keywords: autocorrelation, EWMA control chart, general linear regression model, profile monitoring

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Authors: Farid Eltom A. E., Mustafa Abdul-Halim, Abdalla Markaz, Sami Atta, Mohamed Azhari, Ahmed Rashed

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Smart environment sensors integrated with ‘Internet of Things’ (IoT) technology can provide a new concept in tracking, sensing, and monitoring objects in the environment. The aim of the study is to evaluate the farm environmental monitoring system based on (IoT) and to realize the automated management of agriculture and the implementation of precision production. Until now, irrigation monitoring operations in Sudan have been carried out using traditional methods, which is a very costly and unreliable mechanism. However, by utilizing soil moisture sensors, irrigation can be conducted only when needed without fear of plant water stress. The result showed that software application allows farmers to display current and historical data on soil moisture and nutrients in the form of line charts. Design measurements of the soil factors: moisture, electrical, humidity, conductivity, temperature, pH, phosphorus, and potassium; these factors, together with a timestamp, are sent to the data server using the Lora WAN interface. It is considered scientifically agreed upon in the modern era that artificial intelligence works to arrange the necessary procedures to take care of the terrain, predict the quality and quantity of production through deep analysis of the various operations in agricultural fields, and also support monitoring of weather conditions.

Keywords: smart environment, monitoring systems, IoT, LoRa Gateway, center pivot

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Authors: Ofoegbu Ositadinma Edward

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This research paper discusses a web based monitoring system that enables effective monitoring of fuel pump output and sales volume from distributed fuel stations under the domain of a single company/organization. The traditional method of operation by these organizations in Nigeria is non-automated and accounting for dispensed product is usually approximated and manual as there is little or no technology implemented to presently provide information relating to the state of affairs in the station both to on-ground staff and to supervisory staff that are not physically present in the station. This results in unaccountable losses in product and revenue as well as slow decision making. Remote monitoring technology as a vast research field with numerous application areas incorporating various data collation techniques and sensor networks can be applied to provide information relating to fuel pump status in distributed fuel stations reliably. Thus, the proposed system relies upon a microcontroller, keypad and pump to demonstrate the traditional fuel dispenser. A web-enabled PC with an accompanying graphic user interface (GUI) was designed using virtual basic which is connected to the microcontroller via the serial port which is to provide the web implementation.

Keywords: fuel pump, microcontroller, GUI, web

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Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

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The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

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Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

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Authors: Tianyi Wang, Hieyong Jeong, An Guo, Yuko Ohno

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Healthcare robot for assisting sit-to-stand (STS) performance had aroused numerous research interests. To author’s best knowledge, knowledge about how evaluating healthcare robot is still unknown. Robot should be labeled as fault if users feel demanding during STS when they are assisted by robot. In this research, we aim to propose a method to evaluate sit-to-stand assist robot through center of pressure (CoP), then classify different STS performance. Experiments were executed five times with ten healthy subjects under four conditions: two self-performed STSs with chair heights of 62 cm and 43 cm, and two robot-assisted STSs with chair heights of 43 cm and robot end-effect speed of 2 s and 5 s. CoP was measured using a Wii Balance Board (WBB). Bayesian classification was utilized to classify STS performance. The results showed that faults occurred when decreased the chair height and slowed robot assist speed. Proposed method for fault classification showed high probability of classifying fault classes form others. It was concluded that faults for STS assist robot could be detected by inspecting center of pressure and be classified through proposed classification algorithm.

Keywords: center of pressure, fault classification, healthcare robot, sit-to-stand movement

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Authors: Yun-Tsuen Chen, Shih-Ting Huang, Pi-Fen Cheng, Yu-Ting Su, Joffrey Hsu, Hui-Zhu Chen

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Acute intestinal obstruction is one of the differentials of acute abdomen and requires timely alleviation of intestinal distention and abdominal pain to avoid perforation, intra-abdominal infection, and peritonitis. Investigation to identify the cause of obstruction will direct treatment planning and allow for more effective management. In this study, we present a 71-year-old female presenting with symptoms of acute intestinal obstruction for five days. After extensive history taking, physical exam, medical imaging, and pathology, the patient was diagnosed with colon cancer with lung metastasis and acute intestinal obstruction. The patient was placed on nil per os status with intravenous fluid support, intravenous antibiotics, and a decompression nasogastric tube was placed. The patient received decompression with colostomy creation surgery. After assessing the patient’s clinical condition and tumor staging, a multidisciplinary healthcare team created an individualized treatment plan, which included plans to prepare the patient for home self-care and maintain good mental health with regular monitoring in the clinic setting. This case demonstrates the importance of early diagnosis, effective treatment, and a multidisciplinary approach to the management of acute intestinal obstruction secondary to colon cancer.

Keywords: acute intestinal obstruction, colostomy surgery, metastatic colon cancer, multidisciplinary healthcare team

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Authors: Qing Wu, Xuchun Ye, Kirsten Corazzini

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Objective: It is increasingly recognized that patients’ rational and meaningful engagement in healthcare could make important contributions to their health care and safety management. However, recent evidence indicated that patients' actual roles in healthcare didn’t match their desired roles, and many patients reported a less active role than desired, which suggested that patient engagement in healthcare may be influenced by various factors. This study aimed to analyze influencing factors on patient engagement and explore the influence mechanism, which will be expected to contribute to the strategy development of patient engagement in healthcare. Methods: On the basis of analyzing the literature and theory study, the research framework was developed. According to the research framework, a cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale, Facilitation of Patient Involvement Scale and Wake Forest Physician Trust Scale, and other influencing factor related scales. A convenience sample of 580 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province, and Zhejiang Province. Results: The results of the cross-sectional survey indicated that the mean score for the patient engagement behavior was (4.146 ± 0.496), and the mean score for the willingness was (4.387 ± 0.459). The level of patient engagement behavior was inferior to their willingness to be involved in healthcare (t = 14.928, P ＜ 0.01). The influencing mechanism model of patient engagement in healthcare was constructed by the path analysis. The path analysis revealed that patient attitude toward engagement, patients’ perception of facilitation of patient engagement and health literacy played direct prediction on the patients’ willingness of engagement, and standard estimated values of path coefficient were 0.341, 0.199, 0.291, respectively. Patients’ trust in physician and the willingness of engagement played direct prediction on the patient engagement, and standard estimated values of path coefficient were 0.211, 0.641, respectively. Patient attitude toward engagement, patients’ perception of facilitation and health literacy played indirect prediction on patient engagement, and standard estimated values of path coefficient were 0.219, 0.128, 0.187, respectively. Conclusions: Patients engagement behavior did not match their willingness to be involved in healthcare. The influencing mechanism model of patient engagement in healthcare was constructed. Patient attitude toward engagement, patients’ perception of facilitation of engagement and health literacy posed indirect positive influence on patient engagement through the patients’ willingness of engagement. Patients’ trust in physician and the willingness of engagement had direct positive influence on the patient engagement. Patient attitude toward engagement, patients’ perception of physician facilitation of engagement and health literacy were the factors influencing the patients’ willingness of engagement. The results of this study provided valuable evidence on guiding the development of strategies for promoting patient rational and meaningful engagement in healthcare.

Keywords: healthcare, patient engagement, influencing factor, the mechanism

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Authors: Mamoon Masud, Suleman Mazhar

Abstract:

Indus river basin’s irrigation system in Pakistan is extremely complex, spanning over 50,000 km. Maintenance and monitoring of this demands enormous resources. This paper describes the development of a streamlined and low-cost autonomous underwater vehicle (AUV) for the monitoring of irrigation canals including water quality monitoring and water theft detection. The vehicle is a hovering-type AUV, designed mainly for monitoring irrigation canals, with fully documented design and open source code. It has a length of 17 inches, and a radius of 3.5 inches with a depth rating of 5m. Multiple sensors are present onboard the AUV for monitoring water quality parameters including pH, turbidity, total dissolved solids (TDS) and dissolved oxygen. A 9-DOF Inertial Measurement Unit (IMU), GY-85, is used, which incorporates an Accelerometer (ADXL345), a Gyroscope (ITG-3200) and a Magnetometer (HMC5883L). The readings from these sensors are fused together using directional cosine matrix (DCM) algorithm, providing the AUV with the heading angle, while a pressure sensor gives the depth of the AUV. 2 sonar-based range sensors are used for obstacle detection, enabling the vehicle to align itself with the irrigation canals edges. 4 thrusters control the vehicle’s surge, heading and heave, providing 3 DOF. The thrusters are controlled using a proportional-integral-derivative (PID) feedback control system, with heading angle and depth being the controller’s input and the thruster motor speed as the output. A flow sensor has been incorporated to monitor canal water level to detect water-theft event in the irrigation system. In addition to water theft detection, the vehicle also provides information on water quality, providing us with the ability to identify the source(s) of water contamination. Detection of such events can provide useful policy inputs for improving irrigation efficiency and reducing water contamination. The AUV being low cost, small sized and suitable for autonomous maneuvering, water level and quality monitoring in the irrigation canals, can be used for irrigation network monitoring at a large scale.

Keywords: the autonomous underwater vehicle, irrigation canal monitoring, water quality monitoring, underwater line tracking

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Authors: Hend Albassam, Nouf Alrumaih

Abstract:

Nowadays we are in the age of technologies and communication and there is no doubt that technologies such as the Internet can offer many advantages for many business fields, and the health field is no execution. In fact, using the Internet provide us with a new path to improve the quality of health care throughout the world. The e-healthcare offers many advantages such as: efficiency by reducing the cost and avoiding duplicate diagnostics, empowerment of patients by enabling them to access their medical records, enhancing the quality of healthcare and enabling information exchange and communication between healthcare organizations. There are many problems that result from using papers as a way of communication, for example, paper-based prescriptions. Usually, the doctor writes a prescription and gives it to the patient who in turn carries it to the pharmacy. After that, the pharmacist takes the prescription to fill it and give it to the patient. Sometimes the pharmacist might find difficulty in reading the doctor’s handwriting; the patient could change and counterfeit the prescription. These existing problems and many others heighten the need to improve the quality of the healthcare. This project is set out to develop a distributed e-healthcare system that offers some features of e-health and addresses some of the above-mentioned problems. The developed system provides an electronic health record (EHR) and enables communication between separate health care organizations such as the clinic, pharmacy and laboratory. To develop this system, the Service Oriented Architecture (SOA) is adopted as a design approach, which helps to design several independent modules that communicate by using web services. The layering design pattern is used in designing each module as it provides reusability that allows the business logic layer to be reused by different higher layers such as the web service or the website in our system. The experimental analysis has shown that the project has successfully achieved its aims toward solving the problems related to the paper-based healthcare systems and it enables different health organization to communicate effectively. It implements four independent modules including healthcare provider, pharmacy, laboratory and medication information provider. Each module provides different functionalities and is used by a different type of user. These modules interoperate with each other using a set of web services.

Keywords: e-health, services oriented architecture (SOA), web services, interoperability

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Authors: Jing Hu, Dong Yang

Abstract:

With the increasingly difficult development and operating environment of exploration, there are many new challenges and difficulties in developing and exploiting oil and gas resources. These include the ability to dynamically monitor wells and provide data and assurance for the completion and production of high-cost and complex wells. A key technology in providing these assurances and maximizing oilfield profitability is real-time permanent reservoir monitoring. The emergence of optical fiber sensing systems has gradually begun to replace traditional electronic systems. Traditional temperature sensors can only achieve single-point temperature monitoring, but fiber optic sensing systems based on the Bragg grating principle have a high level of reliability, accuracy, stability, and resolution, enabling cost-effective monitoring, which can be done in real-time, anytime, and without well intervention. Continuous data acquisition is performed along the entire wellbore. The integrated package with the downhole pressure gauge, packer, and surface system can also realize real-time dynamic monitoring of the pressure in some sections of the downhole, avoiding oil well intervention and eliminating the production delay and operational risks of conventional surveys. Real-time information obtained through permanent optical fibers can also provide critical reservoir monitoring data for production and recovery optimization.

Keywords: PDHM, optical fiber, coiled tubing, photoelectric composite cable, digital-oilfield

Procedia PDF Downloads 53

Authors: Abdessamad Dali-Ali, Houaria Beldjillali, Fouzia Agag, Asmaa Oukebdane, Ramzi Tidjani, Arslane Bettayeb, Khadidja Meddeber, Radia Dali-Yahia, Nori Midoun

Abstract:

Healthcare-associated infections are a real public health problem, especially in intensive care units. The aim of our study was to describe the epidemiological profile and to estimate the incidence of these infections at the intensive care unit of our teaching hospital. A prospective study was conducted, from June 2012 to December 2013. During this period, 305 patients having a duration of hospitalization equal or more than 48 hours were included in the study. In terms of the incidence of healthcare associated infections, nosocomial pneumonia occupied the first position with a cumulative incidence rate of 20.0%, followed by bacteremia (5.6%), central venous catheter infections (4%), and urinary tract infections (3%). In the case of isolated microorganisms, Gram-negative bacilli not enterobacteriaceae occupied the first place with 48.5%, followed by enterobacteria (32.1%). Acinetobacter baumannii was the most common germ (27.6%). Our study showed that the rate of health-care-associated infections was relatively high in the intensive care unit. A control program to reduce all infections is a priority for the Infection Control Associated Committee.

Keywords: epidemiological profile, healthcare associated infections, intensive care units, teaching hospital of Oran, Algeria

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Authors: Hyun-Woo Cho

Abstract:

Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

Procedia PDF Downloads 214