1000 resultados para PERSONNEL MONITORING


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Physicians who frequently perform fluoroscopic examinations are exposed to high intensity radiation fields. The exposure monitoring is performed with a regular personal dosimeter under the apron in order to estimate the effective dose. However, large parts of the body are not protected by the apron (e.g. arms, head). Therefore, it is recommended to wear a supplemental dosimeter over the apron to obtain a better representative estimate of the effective dose. The over-apron dosimeter can also be used to estimate the eye lens dose. The goal of this study was to investigate the relevance of double dosimetry in interventional radiology. First the calibration procedure of the dosimeters placed over the apron was tested. Then, results of double dosimetry during the last five years were analyzed. We found that the personal dose equivalent measured over a lead apron was underestimated by ∼20% to ∼40% for X-ray beam qualities used in radiology. Measurements made over five-year period confirm that the use of a single under-apron dosimeter is inadequate for personnel monitoring. Relatively high skin dose (>10 mSv/month) would have remained undetected without a second dosimeter placed on the apron.

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Nepal has a long history of medical radiology since1923 but unfortunately, we still do not have any Radiation Protection Infrastructure to control the use of ionizing radiations in the various fields. The objective of this study was an assessment of the radiation protection in medical uses of ionizing radiation. Twenty-eight hospitals with diagnostic radiology facility were chosen for this study according to patient loads, equipment and working staffs. Radiation surveys were also done at five different radiotherapy centers. Questionnaire for radiation workers were used; radiation dose levels were measured and an inventory of availability of radiation equipment made. A corollary objective of the study was to create awareness in among workers on possible radiation health hazard and risk. It was also deemed important to know the level of understanding of the radiation workers in order to initiate steps towards the establishment of Nepalese laws, regulation and code of radiological practice in this field. Altogether, 203 Radiation workers entertained the questionnaire, out of which 41 are from the Radiotherapy and 162 are from diagnostic radiology. The radiation workers who have participated in the questionnaire represent more than 50% of the radiation workers working in this field in Nepal. Almost all X-ray, CT and Mammogram installations were built according to protection criteria and hence found safe. Radiation dose level at the reference points for all the five Radiotherapy centers are within safe limit. Around 65% of the radiation workers have never been monitored for radiation. There is no quality control program in any of the surveyed hospitals except radiotherapy facilities.

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A thorough literature review about the current situation on the implementation of eye lens monitoring has been performed in order to provide recommendations regarding dosemeter types, calibration procedures and practical aspects of eye lens monitoring for interventional radiology personnel. Most relevant data and recommendations from about 100 papers have been analysed and classified in the following topics: challenges of today in eye lens monitoring; conversion coefficients, phantoms and calibration procedures for eye lens dose evaluation; correction factors and dosemeters for eye lens dose measurements; dosemeter position and influence of protective devices. The major findings of the review can be summarised as follows: the recommended operational quantity for the eye lens monitoring is H p (3). At present, several dosemeters are available for eye lens monitoring and calibration procedures are being developed. However, in practice, very often, alternative methods are used to assess the dose to the eye lens. A summary of correction factors found in the literature for the assessment of the eye lens dose is provided. These factors can give an estimation of the eye lens dose when alternative methods, such as the use of a whole body dosemeter, are used. A wide range of values is found, thus indicating the large uncertainty associated with these simplified methods. Reduction factors from most common protective devices obtained experimentally and using Monte Carlo calculations are presented. The paper concludes that the use of a dosemeter placed at collar level outside the lead apron can provide a useful first estimate of the eye lens exposure. However, for workplaces with estimated annual equivalent dose to the eye lens close to the dose limit, specific eye lens monitoring should be performed. Finally, training of the involved medical staff on the risks of ionising radiation for the eye lens and on the correct use of protective systems is strongly recommended.

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Background: Oncological treatments are traditionally administered via intravenous injection by qualified personnel. Oral formulas which are developing rapidly are preferred by patients and facilitate administration however they may increase non-adherence. In this study 4 common oral chemotherapeutics are given to 50 patients, who are still in the process of inclusion, divided into 4 groups. The aim is to evaluate adherence and offer these patients interdisciplinary support with the joint help of doctors and pharmacists. We present here the results for capecitabine. Materials and Methods: The final goal is to evaluate adhesion in 50 patients split into 4 groups according to oral treatments (letrozole/exemestane, imatinib/sunitinib, capecitabine and temozolomide) using persistence and quality of execution as parameters. These parameters are evaluated using a medication event monitoring system (MEMS®) in addition to routine oncological visits and semi-structured interviews. Patients were monitored for the entire duration of treatment up to a maximum of 1 year. Patient satisfaction was assessed at the end of the monitoring period using a standardized questionary. Results: Capecitabine group included 2 women and 8 men with a median age of 55 years (range: 36−77 years) monitored for an average duration of 100 days (range: 5-210 days). Persistence was 98% and quality of execution 95%. 5 patients underwent cyclic treatment (2 out of 3 weeks) and 5 patients continuous treatment. Toxicities higher than grade 1 were grade 2−3 hand-foot syndrome in 1 patient and grade 3 acute coronary syndrome in 1 patient both without impact on adherence. Patients were satisfied with the interviews undergone during the study (57% useful, 28% very useful, 15% useless) and successfully integrated the MEMS® in their daily lives (57% very easily, 43% easily) according to the results obtained by questionary at the end of the monitoring period. Conclusion: Persistence and quality of execution observed in our Capecitabine group of patients were excellent and better than expected compared to previously published studies. The interdisciplinary approach allowed us to better identify and help patients with toxicities to maintain adherence. Overall patients were satisfied with the global interdisciplinary follow-up. With longer follow up better evaluation of our method and its impact will be possible. Interpretation of the results of patients in the other groups of this ongoing trial will provide us information for a more detailed analysis.

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A questionnaire was developed by the members of WG12 of EURADOS in order to establish an overview of the current status of eye lens radiation dose monitoring in hospitals. The questionnaire was sent to medical physicists and radiation protection officers in hospitals across Europe. Specific topics were addressed in the questionnaire such as: knowledge of the proposed eye lens dose limit; monitoring and dosimetry issues; training and radiation protection measures. The results of the survey highlighted that the new eye lens dose limit can be exceeded in interventional radiology procedures and that eye lens protection is crucial. Personnel should be properly trained in how to use protective equipment in order to keep eye lens doses as low as reasonably achievable. Finally, the results also highlighted the need to improve the design of eye dosemeters in order to ensure satisfactory use by workers.

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Following a high wind event on January 24, 2006, at least five people claimed to have seen or felt the superstructure of the Saylorville Reservoir Bridge in central Iowa moving both vertically and laterally. Since that time, the Iowa Department of Transportation (DOT) contracted with the Bridge Engineering Center at Iowa State University to design and install a monitoring system capable of providing notification of the occurrence of subsequent high wind events. In subsequent years, a similar system was installed on the Red Rock Reservoir Bridge to provide the same wind monitoring capabilities and notifications to the Iowa DOT. The objectives of the system development and implementation are to notify personnel when the wind speed reaches a predetermined threshold such that the bridge can be closed for the safety of the public, correlate structural response with wind-induced response, and gather historical wind data at these structures for future assessments. This report describes the two monitoring systems, their components, upgrades, functionality, and limitations, and results from one year of wind data collection at both bridges.

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"Metric Training For The Highway Industry", HR-376 was designed to produce training materials for the various divisions of the Iowa DOT, local government and the highway construction industry. The project materials were to be used to introduce the highway industry in Iowa to metric measurements in their daily activities. Five modules were developed and used in training over 1,000 DOT, county, city, consultant and contractor staff in the use of metric measurements. The training modules developed deal with the planning through operation areas of highway transportation. The materials and selection of modules were developed with the aid of an advisory personnel from the highway industry. Each module is design as a four hour block of instruction and a stand along module for specific types of personnel. Each module is subdivided into four chapters with chapter one and four covering general topics common to all subjects. Chapters two and three are aimed at hands on experience for a specific group and subject. This module includes: Module 4 - Transportation Planning and Traffic Monitoring. Hands on examples of applications of metric measurements in the development of planning reports and traffic data collection are included in this module.

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OBJECTIVE: This study aimed to survey current practices in European epilepsy monitoring units (EMUs) with emphasis on safety issues. METHODS: A 37-item questionnaire investigating characteristics and organization of EMUs, including measures for prevention and management of seizure-related serious adverse events (SAEs), was distributed to all identified European EMUs plus one located in Israel (N=150). RESULTS: Forty-eight (32%) EMUs, located in 18 countries, completed the questionnaire. Epilepsy monitoring unit beds are 1-2 in 43%, 3-4 in 34%, and 5-6 in 19% of EMUs; staff physicians are 1-2 in 32%, 3-4 in 34%, and 5-6 in 19% of EMUs. Personnel operating in EMUs include epileptologists (in 69% of EMUs), clinical neurophysiologists trained in epilepsy (in 46% of EMUs), child neurologists (in 35% of EMUs), neurology and clinical neurophysiology residents (in 46% and in 8% of EMUs, respectively), and neurologists not trained in epilepsy (in 27% of EMUs). In 20% of EMUs, patients' observation is only intermittent or during the daytime and primarily carried out by neurophysiology technicians and/or nurses (in 71% of EMUs) or by patients' relatives (in 40% of EMUs). Automatic detection systems for seizures are used in 15%, for body movements in 8%, for oxygen desaturation in 33%, and for ECG abnormalities in 17% of EMUs. Protocols for management of acute seizures are lacking in 27%, of status epilepticus in 21%, and of postictal psychoses in 87% of EMUs. Injury prevention consists of bed protections in 96% of EMUs, whereas antisuffocation pillows are employed in 21%, and environmental protections in monitoring rooms and in bathrooms are implemented in 38% and in 25% of EMUs, respectively. The most common SAEs were status epilepticus reported by 79%, injuries by 73%, and postictal psychoses by 67% of EMUs. CONCLUSIONS: All EMUs have faced different types of SAEs. Wide variation in practice patterns and lack of protocols and of precautions to ensure patients' safety might promote the occurrence and severity of SAEs. Our findings highlight the need for standardized and shared protocols for an effective and safe management of patients in EMUs.

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Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

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SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

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Especially in pharmacotherapeutic research, a variety of methods to monitor behavioural and psychological symptoms of dementia (BPSD) are currently being discussed. To date, the most frequently used of these are clinical scales, which, however, are subjective and highly dependent on personnel resources. In our study, we tested the usefulness of actigraphy as a more direct and objective way to measure day-night rhythm disturbances and agitated behaviour.After a baseline assessment, 24 patients with probable dementia of the Alzheimer type (NINCDS-ADRDA) and agitated behaviour received either 3 mg melatonin (n=7), 2.5 mg dronabinol (n=7), or placebo (n=10) for two weeks. In addition, 10 young and 10 elderly healthy subjects were examined as a control group. Motor activity levels were assessed using an actigraph worn continuously on the wrist of the non-dominant hand. At the beginning and the end of the study, patients' Neuropsychiatric Inventory (NPI) scores were also assessed.In the verum group, actigraphic nocturnal activity (P=0.001), NPI total score (P=0.043), and NPI agitation subscale score (P=0.032) showed significant reductions compared to baseline. The treatment-baseline ratio of nocturnal activity (P=0.021) and treatment-baseline difference of the nocturnal portion of 24 h activity (P=0.012) were reduced. Patients' baseline activity levels were similar to those seen in healthy elderly subjects. Younger healthy subjects exhibited higher motor activity even at night. There was no correlation between actigraphy and NPI.Both actigraphic measures and the gold standard clinical scale were able to distinguish between the verum and placebo groups. However, because they did not correlate with each other, they clearly represent different aspects of BPSD, each of which reacts differently to therapy. As a result, actigraphy may well come to play an important role in monitoring treatment success in BPSD.

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Utilizing advanced information technology, Intensive Care Unit (ICU) remote monitoring allows highly trained specialists to oversee a large number of patients at multiple sites on a continuous basis. In the current research, we conducted a time-motion study of registered nurses’ work in an ICU remote monitoring facility. Data were collected on seven nurses through 40 hours of observation. The results showed that nurses’ essential tasks were centered on three themes: monitoring patients, maintaining patients’ health records, and managing technology use. In monitoring patients, nurses spent 52% of the time assimilating information embedded in a clinical information system and 15% on monitoring live vitals. System-generated alerts frequently interrupted nurses in their task performance and redirected them to manage suddenly appearing events. These findings provide insight into nurses’ workflow in a new, technology-driven critical care setting and have important implications for system design, work engineering, and personnel selection and training.

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This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 0.2% live births, 1.1% for preterm neonates, and 1.3% for infants weighing less than 2500 g at birth. Neonatal seizures can be classified into four main categories: clonic, tonic, myoclonic, and subtle. Seizures in newborns have to be promptly and accurately recognized in order to establish timely treatments that could avoid an increase of the underlying brain damage. Respiratory diseases related to the occurrence of apnoea episodes may be caused by cerebrovascular events. Among the wide range of causes of apnoea, besides seizures, a relevant one is Congenital Central Hypoventilation Syndrome (CCHS) \cite{Healy}. With a reported prevalence of 1 in 200,000 live births, CCHS, formerly known as Ondine's curse, is a rare life-threatening disorder characterized by a failure of the automatic control of breathing, caused by mutations in a gene classified as PHOX2B. CCHS manifests itself, in the neonatal period, with episodes of cyanosis or apnoea, especially during quiet sleep. The reported mortality rates range from 8% to 38% of newborn with genetically confirmed CCHS. Nowadays, CCHS is considered a disorder of autonomic regulation, with related risk of sudden infant death syndrome (SIDS). Currently, the standard method of diagnosis, for both diseases, is based on polysomnography, a set of sensors such as ElectroEncephaloGram (EEG) sensors, ElectroMyoGraphy (EMG) sensors, ElectroCardioGraphy (ECG) sensors, elastic belt sensors, pulse-oximeter and nasal flow-meters. This monitoring system is very expensive, time-consuming, moderately invasive and requires particularly skilled medical personnel, not always available in a Neonatal Intensive Care Unit (NICU). Therefore, automatic, real-time and non-invasive monitoring equipments able to reliably recognize these diseases would be of significant value in the NICU. A very appealing monitoring tool to automatically detect neonatal seizures or breathing disorders may be based on acquiring, through a network of sensors, e.g., a set of video cameras, the movements of the newborn's body (e.g., limbs, chest) and properly processing the relevant signals. An automatic multi-sensor system could be used to permanently monitor every patient in the NICU or specific patients at home. Furthermore, a wire-free technique may be more user-friendly and highly desirable when used with infants, in particular with newborns. This work has focused on a reliable method to estimate the periodicity in pathological movements based on the use of the Maximum Likelihood (ML) criterion. In particular, average differential luminance signals from multiple Red, Green and Blue (RGB) cameras or depth-sensor devices are extracted and the presence or absence of a significant periodicity is analysed in order to detect possible pathological conditions. The efficacy of this monitoring system has been measured on the basis of video recordings provided by the Department of Neurosciences of the University of Parma. Concerning clonic seizures, a kinematic analysis was performed to establish a relationship between neonatal seizures and human inborn pattern of quadrupedal locomotion. Moreover, we have decided to realize simulators able to replicate the symptomatic movements characteristic of the diseases under consideration. The reasons is, essentially, the opportunity to have, at any time, a 'subject' on which to test the continuously evolving detection algorithms. Finally, we have developed a smartphone App, called 'Smartphone based contactless epilepsy detector' (SmartCED), able to detect neonatal clonic seizures and warn the user about the occurrence in real-time.