The Development and Validation of a One Tier Diagnostic Assessment to Test Premedical Students\u27 Misconceptions about Traumatic Brain Injury

Since brain injury is common in the United States, it is important for health professionals and the public to have accurate knowledge about traumatic brain injury (TBI). Understanding misconceptions is important for health educators, nurses, and physicians, who work with TBI patients. While previous studies on misconceptions about TBI have been undertaken, these have not focused on pre-medical students, nor utilized validated assessments. The purpose of this study was to develop and validate a one tier diagnostic test with a confidence index to determine premedical students\u27 misconceptions about TBI. Using the theoretical framework suggested by Treagust (1986, 1988, and 1995), we developed and validated the Traumatic Brain Injury Knowledge Test (TBIKT) in two phases. The pilot trial, which was an open-ended assessment, had a total of 20 items and 37 participants. This open-ended assessment, along with the literature review, helped in constructing the final multiple choice assessment. The TBIKT (Appendix A) had 43 items with an additional item about students\u27 source of knowledge about TBI. Applying Classical Test Theory and an internal consistency definition for reliability to data from 38 participants, we found that the TBIKT can provide reliable and valid measures of students\u27 knowledge and misconceptions about TBI. Students showed misconceptions in identifying physical, cognitive, and emotional symptoms of TBI. This study also identified several misconceptions about TBI such as it is likely a TBI patient may wake up from the coma without any lasting effects , a TBI patient needs to take rest all of the time, even a little physical exercise may be harmful , and the patient can be completely cured if enough neurons are recruited to take over the loss of the damaged ones . Validity evidence and limitations of the TBIKT are discussed and suggestions for future studies are included

The Development and Validation of a One Tier Diagnostic Assessment to Test Premedical Students\u27 Misconceptions about Traumatic Brain Injury

Since brain injury is common in the United States, it is important for health professionals and the public to have accurate knowledge about traumatic brain injury (TBI). Understanding misconceptions is important for health educators, nurses, and physicians, who work with TBI patients. While previous studies on misconceptions about TBI have been undertaken, these have not focused on pre-medical students, nor utilized validated assessments. The purpose of this study was to develop and validate a one tier diagnostic test with a confidence index to determine premedical students\u27 misconceptions about TBI. Using the theoretical framework suggested by Treagust (1986, 1988, and 1995), we developed and validated the Traumatic Brain Injury Knowledge Test (TBIKT) in two phases. The pilot trial, which was an open-ended assessment, had a total of 20 items and 37 participants. This open-ended assessment, along with the literature review, helped in constructing the final multiple choice assessment. The TBIKT (Appendix A) had 43 items with an additional item about students\u27 source of knowledge about TBI. Applying Classical Test Theory and an internal consistency definition for reliability to data from 38 participants, we found that the TBIKT can provide reliable and valid measures of students\u27 knowledge and misconceptions about TBI. Students showed misconceptions in identifying physical, cognitive, and emotional symptoms of TBI. This study also identified several misconceptions about TBI such as it is likely a TBI patient may wake up from the coma without any lasting effects , a TBI patient needs to take rest all of the time, even a little physical exercise may be harmful , and the patient can be completely cured if enough neurons are recruited to take over the loss of the damaged ones . Validity evidence and limitations of the TBIKT are discussed and suggestions for future studies are included

Smartphone-based Calorie Estimation From Food Image Using Distance Information

Personal assistive systems for diet control can play a vital role to combat obesity. As smartphones have become inseparable companions for a large number of people around the world, designing smartphone-based system is perhaps the best choice at the moment. Using this system people can take an image of their food right before eating, know the calorie content based on the food items on the plate. In this paper, we propose a simple method that ensures both user flexibility and high accuracy at the same time. The proposed system employs capturing food images with a fixed posture and estimating the volume of the food using simple geometry. The real world experiments on different food items chosen arbitrarily show that the proposed system can work well for both regular and liquid food items

Pain Level Detection From Facial Image Captured by Smartphone

Accurate symptom of cancer patient in regular basis is highly concern to the medical service provider for clinical decision making such as adjustment of medication. Since patients have limitations to provide self-reported symptoms, we have investigated how mobile phone application can play the vital role to help the patients in this case. We have used facial images captured by smart phone to detect pain level accurately. In this pain detection process, existing algorithms and infrastructure are used for cancer patients to make cost low and user-friendly. The pain management solution is the first mobile-based study as far as we found today. The proposed algorithm has been used to classify faces, which is represented as a weighted combination of Eigenfaces. Here, angular distance, and support vector machines (SVMs) are used for the classification system. In this study, longitudinal data was collected for six months in Bangladesh. Again, cross-sectional pain images were collected from three different countries: Bangladesh, Nepal and the United States. In this study, we found that personalized model for pain assessment performs better for automatic pain assessment. We also got that the training set should contain varying levels of pain in each group: low, medium and high

A Novel Real-Time Non-invasive Hemoglobin Level Detection Using Video Images from Smartphone Camera

Hemoglobin level detection is necessary for evaluating health condition in the human. In the laboratory setting, it is detected by shining light through a small volume of blood and using a colorimetric electronic particle counting algorithm. This invasive process requires time, blood specimens, laboratory equipment, and facilities. There are also many studies on non-invasive hemoglobin level detection. Existing solutions are expensive and require buying additional devices. In this paper, we present a smartphone-based non-invasive hemoglobin detection method. It uses the video images collected from the fingertip of a person. We hypothesized that there is a significant relation between the fingertip mini-video images and the hemoglobin level by laboratory gold standard. We also discussed other non-invasive methods and compared with our model. Finally, we described our findings and discussed future works

128-QAM Based mm-Wave Communication (5G) Architecture

Demand for bandwidth can never be fulfilled with any definite amount. Population is growing at a high speed which also causes an increase in the demand for bandwidth. Currently available bands ranging up-to 10 GHz is at the edge of saturation. So a newer and unutilized bandwidth is mandatory for the fulfillment of the increasing bandwidth demand. The millimeter wave band which is fully used. This band offers a wide range of bandwidth (30 GHz ~ 300 GHz). A slight part of this band, the E-band, has been used in the design of the 5G network proposed in this paper. Single-carrier frequency-division multiple access (SC-FDMA) and orthogonal frequency-division multiple access (OFDMA) have been proposed for the uplink and downlink multiple access respectively. A Rayleigh fading channel is used as the propagation environment along with considering different losses at sea level (T = 0 ˚C, P = 760 mm Hg, H2O = 1 gm/m3). 128-quadrature amplitude modulation (QAM) has been used as the principle modulation technique. Also, the use of adaptive beam-forming antennas ensure an increased coverage of about 2 km

SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network

Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-invasively. We recorded 10 second-300 frame fingertip videos using a smartphone in 75 adults. Red, green, and blue pixel intensities were estimated for each of 100 area blocks in each frame and the patterns across the 300 frames were described. ANN was then used to develop a model using the extracted video features to predict hemoglobin levels. In our study sample, with patients 20-56 years of age, and gold standard hemoglobin levels of 7.6 to 13.5 g/dL., we observed a 0.93 rank order of correlation between model and gold standard hemoglobin levels. Moreover, we identified specific regions of interest in the video images which reduced the required feature space

Dynamic Modeling and Analysis of a Remote Hybrid Power System with Pumped Hydro Storage

In this research, dynamic modeling of a remote hybrid power system and feasibility of a pumped hydro storage system is presented. Current hybrid system in Ramea, Newfoundland has an electrolyzer, storage and hydrogen generator system. This research proposes a pumped hydro storage as a replacement to the hydrogen system. Detailed MATLAB-Simulink modeling has been done for every component of the Ramea hybrid power system. Incorporation of a pumped hydro system and some lead acid batteries will eliminate the low turn around efficiency of the electrolyzer and hydrogen generator system. The system dynamic model presented here is fast, accurate and includes dynamic and supervisory controllers. The proposed real time supervisory controller algorithm observes the available surplus/missing power in the system and regulates pump/turbine and charging/discharging of the battery bank to maintain a stable system frequency. This paper presents dynamic model, supervisory controller design and algorithm, six case studies and detailed simulation results