"A wireless wearable battery-operated pulse oximeter has been developed in our laboratory for field triage applications. The wearable pulse oximeter, which uses a forehead-mounted sensor to provide arterial oxygen saturation (SpO2) and heart rate (HR) information, would enable field medics to monitor vital physiological information following critical injuries, thereby helping to prioritize life saving medical interventions. This study was undertaken to investigate if accelerometry (ACC)-based adaptive noise cancellation (ANC) is effective in minimizing SpO2 and HR errors induced during jogging to simulate certain motion artifacts expected to occur in the field. Preliminary tests confirmed that processing the motion corrupted photoplethysmographic (PPG) signals by simple Least-Mean-Square (LMS) and Recursive Least-Squares (RLS) ANC algorithms can help to improve the signal-to-noise ratio of motion-corrupted PPG signals, thereby reducing SpO2 and HR errors during jogging. The study showed also that the degree of improvement depends on filter order. In addition, we found that it would be more feasible to implement an LMS adaptive filter within an embedded microcontroller environment since the LMS algorithm requires significantly less operations."

This mixed-method study investigated the effects of self-directed physiological monitoring on therapists anxiety. Ten therapists participated in a10-week physiological monitoring training sessions while monitoring respiratory sinus arrhythmia (RSA) and heart rate variability (HRV). The participants completed the state-trait anxiety inventory questionnaire after having a first, sixth, or tenth therapy session with a client. This was designed to monitor their state anxiety while working with clients. A series of paired sampled t-tests was conducted to assess changes in HRV, RSA, trait anxiety, and state anxiety. One significant result was found: the RSA of the therapist increased significantly. Correlations existed between the HRV of the therapist increasing and the trait anxiety of the therapist decreasing through RSA training sessions although they were not significant at the .05 level.

Abstract The rationale for automatically monitoring anesthetic drug effects on the central nervous system (CNS) is to improve possibilities to gain objective information on a patient's state and to adjust the medication individually. Although monitors have shown their usefulness in practice, there are still a number of unclear issues, especially with respect to the scientific foundations and validity of CNS monitoring techniques, and in monitoring the light hypnotic levels. Current monitors are, for example, often based on heuristics and ad hoc solutions. However, a quantitative index for anesthetic drug effect should have a sound relationship with observations and with the selected control variable. The research objectives are: (1) to explore propofol anesthetic related neurophysiological phenomena that can be applied in the automatic assessment of CNS suppression; (2) to develop a valid control variable for this purpose; (3) by means of digital signal processing and mathematical modeling, to design and to evaluate the performance of an index that correlates with the control variable. This dissertation introduces potentially useful neurophysiological phenomena, such as changes in phase synchronization between different EEG channels due to anesthesia, and painful stimulus evoked responses during the burst suppression. Furthermore, it refines the progression of the time-frequency patterns during the induction of anesthesia and shows their relation to the instant of unresponsiveness. The presented spontaneous and evoked EEG phenomena provide complementary information about the CNS functional suppression. Most significantly, the dissertation proposes a continuous and observation based control variable (r scale) and the means to predict its values by using EEG data. The definition of the scale provides a basis for anticipating the instant of the loss of consciousness. Additionally, the phase synchronization index as an indicator of drug effect is introduced. The approximate entropy descriptor performance is evaluated and optimised with a non-stationary signal recorded during the induction of anesthesia. The results open up opportunities to improve the preciseness, scientific validity and the interpretation of information on the anesthetic effects on CNS, and therefore, to increase the reliability of the anesthesia monitoring. Further work is needed to extend and verify the results in deep anesthesia.

No description available.

The structure of education has changed dramatically in the last few decades. Despite major changes in how students are learning, there has not been as dramatic of a shift in how student learning is assessed. Standard letter grades are still the paradigm for evaluating a student's mastery of course content and the grade point average is still one of the largest determining factors in judging a graduate's academic aptitude. This research presents a modern approach to modeling knowledge and evaluating students. Based upon the model of a closed-loop feedback controller it considers education as a system with an instructor determining the set of knowledge he or she wishes to impart to students, the instruction method as a transfer function, and evaluation methods serving as sensors to provide feedback determining the subset of the information students have learned. This method uses comprehensive concept maps to depict all of the concepts and relationships an educator intends to cover and student maps to depict the subset of knowledge that students have mastered. Concept inventories are used as an assessment tool to determine, at the conceptual level, what students have learned. Each question in the concept inventory is coupled with one or more components of a comprehensive concept map and based upon the answers students give to concept inventory questions those components may or may not appear in a student's knowledge map. The level of knowledge a student demonstrates of each concept and relationship is presented in his or her student map using a color scheme tied to the levels of learning in Bloom's taxonomy. Topological principles are used to establish metrics to quantify the distance between two students' knowledge maps and the distance between a student's knowledge map and the corresponding comprehensive concept map. A method is also developed for forming aggregate maps representative of the knowledge of a group of students. Aggregate maps can be formed for entire classes of students or based upon various demographics including race and gender. XML schemas have been used throughout this research to encapsulate the information in both comprehensive maps and student maps and to store correlations between concept inventory questions and corresponding comprehensive map components. Three software packages have been developed to store concept inventories into an XML Schema, to process student responses to concept inventory questions and generate student maps as a result, and to generate aggregate maps. The methods presented herein have been applied to two learning units that are part of two freshman engineering courses at Virginia Tech. Example student maps and aggregate maps are included for these course units. / Ph. D.

Although steady progress has been made towards the development of a wearable pulse oximeter to aid in remote physiological status monitoring (RPSM) and triage operations, the ability to extract accurate physiological data from a forehead pulse oximeter during extended periods of activity and in the presence of pressure disturbances acting on the sensor remains a significant challenge. This research was undertaken to assess whether the attachment method used to secure a pulse oximeter sensor affects arterial oxygen saturation (SpO2) and heart rate (HR) accuracy during motion. Additionally, two sensor housings were prototyped to assess whether isolating the sensor from external pressure disturbances could improve SpO2 and HR accuracy. The research revealed that measurement accuracy during walking is significantly affected by the choice of an attachment method. Specifically, the research indicated that an elastic band providing a contact pressure of 60 mmHg can result in decreased measurement error and improved reliability. Furthermore, the research validated that the two isolating housings we have investigated improve SpO2 and HR errors significantly at pressures as high as 1200 mmHg (160 kPa) compared to current commercial housings. This information may be helpful in the design of a more robust pulse oximeter sensor for use in RPSM.

The desire to send humans to Mars will require a change in the way that extravehicular activity (EVA) is performed; in-space crews (including those within a vehicle or habitat monitoring others conducting EVA) will need to be more autonomous and that will require them to monitor large amounts of information in order to ensure crew safety and mission success. The amount of information to perceive and process will overwhelm unassisted intra-vehicular (IV) crewmembers, meaning that automation will need to be developed to support these crews on Mars while EVA is performed (Mishkin, Lee, Korth, & LeBlanc, 2007). This dissertation seeks to identify the information requirements for the performance of scientific EVA and determine which information streams will need to be allocated to in-space crew and which are the most effective streams to automate. The first study uses Mars rover operations as a homology—as defined by von Bertalanffy (1968)—to human scientific exploration. Mars rover operations personnel were interviewed using a novel method to identify the information requirements to perform successful science on Mars, how that information is used, and the timescales on which those information streams operate. The identified information streams were then related to potential information streams relevant to human exploration in order to identify potential function allocation or automated system development areas. The second study focused on one identified mission-critical information stream for human space exploration: monitoring astronaut status physiologically. Heart rate, respiration rate, and heart rate variability measurements were recorded from participants as they performed field science tasks (potentially tasks that are similar to those that will be performed by astronauts on Mars). A statistical method was developed to analyze this data in order to determine whether or not physiological responses to different tasks were statistically different, and whether any of those differences followed consistent patterns. A potential method to automate the monitoring of physiological data was also described. The results of this work provide a more detailed outline of the information requirements for EVA on Mars and can be used as a starting point for others in the exploration community to further develop automation or function allocation to support astronauts as they explore Mars.

No description available.

Accurate assessment of a child’s health is critical for appropriate allocation of medical resources and timely delivery of healthcare in both primary care (GP consultations) and secondary care (ED consultations). Serious illnesses such as meningitis and pneumonia account for 20% of deaths in childhood and require early recognition and treatment in order to maximize the chances of survival of affected children. Due to time constraints, poorly defined normal ranges, difficulty in achieving accurate readings and the difficulties faced by clinicians in interpreting combinations of vital signs, vital signs are rarely measured in primary care and their utility is limited in emergency departments. This thesis aims to develop a monitoring and data fusion system, to be used in both primary care and emergency department settings during the initial assessment of children suspected of having a serious infection. The proposed system relies on the photoplethysmogram (PPG) which is routinely recorded in different clinical settings with a pulse oximeter using a small finger probe. The most difficult vital sign to measure accurately is respiratory rate which has been found to be predictive of serious infection. An automated method is developed to estimate the respiratory rate from the PPG waveform using both the amplitude modulation caused by changes in thoracic pressure during the respiratory cycle and the phenomenon of respiratory sinus arrhythmia, the heart rate variability associated with respiration. The performance of such automated methods deteriorates when monitoring children as a result of frequent motion artefact. A method is developed that automatically identifies high-quality PPG segments mitigating the effects of motion on the estimation of respiratory rate. In the final part of the thesis, the four vital signs (heart rate, temperature, oxygen saturation and respiratory rate) are combined using a probabilistic framework to provide a novelty score for ranking various diagnostic groups, and predicting the severity of infection in two independent data sets from two different clinical settings.

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-07-14T12:32:09Z No. of bitstreams: 1 George Almeida De Oliveira_.pdf: 1203626 bytes, checksum: 54258ab2dd96b3f2309b53d61fd0ce0f (MD5) / Made available in DSpace on 2016-07-14T12:32:09Z (GMT). No. of bitstreams: 1 George Almeida De Oliveira_.pdf: 1203626 bytes, checksum: 54258ab2dd96b3f2309b53d61fd0ce0f (MD5) Previous issue date: 2016-03-21 / Nenhuma / Com a popularização no mercado de consumo de wearables, ou dispositivos vestíveis, a computação móvel e ubíqua vem se tornando presente em diversas áreas como educação, comércio e entretenimento. Na área da saúde estes dispositivos têm um importante papel, pois contam com sensores para captura de sinais fisiológicos, como por exemplo, medir a temperatura corporal e batimentos cardíacos do usuário. Em muitos casos não há qualquer padronização ou comunicação entre os diferentes sistemas de cuidados ubíquos que administram os dados fisiológicos do usuário. Esse trabalho apresenta uma proposta para gerenciamento de históricos de contextos fisiológicos através de um modelo denominado GECONFI. O modelo suporta a coleta de dados através de aplicações que utilizam dispositivos e sensores de monitoramento, também define uma ontologia para o domínio de contextos fisiológicos. Esse trabalho apresenta o uso de três aplicações integradas ao GECONFI que permitiram avaliar e testar os serviços disponibilizados pelo modelo. A primeira aplicação chamada SiCuide foi aplicada com treze pacientes e um enfermeiro, que apresentaram pareceres positivos em relação a sua utilidade para o monitoramento fisiológico dos usuários. Os outros dois sistemas denominados FitBurn e Heart-Control foram aplicados em um cenário baseado em sensibilidade a contexto permitindo o acesso compartilhado de uma mesma trilha. Os resultados obtidos mostraram a viabilidade para que outros sistemas realizem a administração de históricos contextuais de maneira genérica através do modelo proposto. / With the popularization in wearables market, or wearable devices, the mobile and ubiquitous computing is becoming present in areas such as education, commerce and entertainment. In healthcare these devices have an important role, as have sensors for capturing physiological signals, such as measuring the body temperature and heart rate of the user. In many cases there´s no standardization or communication between different Ubiquitous care systems that manage the physiological user data. This work presents a proposal for historical contexts of physiological management through a model called GECONFI. The model supports data collection through applications that use devices and monitoring sensors, defines an ontology for the domain of physiological contexts. This work presents the use of three integrated applications to GECONFI, that allowed evaluate and test the services provided by the model. The first application called SiCuide was applied with thirteen patients and a nurse, who showed positive opinions regarding its usefulness for physiological monitoring of users. The other two systems called FitBurn and Heart-Control were applied in a scenario based on sensitivity to context allowing shared access to the same track. The results showed the feasibility for other systems to perform the administration of contextual historical generically through the proposed model.