Computer Vision for Alternative Input Systems
In the fast-paced environment of a hospital intensive care unit (ICU), good doctor-patient communication is essential. However, medical conditions and devices often inhibit a patient’s ability to speak, write or type. Current assistive communication devices are either prohibitively expensive or cumbersome and time-consuming, creating a gap in communication during a patient’s first days in the ICU. This project applies computer vision to develop a low-cost software solution that bridges this gap by enabling patients to generate words with eye movements. In the system, a webcam acquires an image of the patient, and an image processing algorithm classifies patient’s gaze as pointing in one of eight directions. Each direction corresponds to an option on a graphical menu presented to the patient on the computer’s display. The patient can use the menu to select a preformed phrase from a list of common phrases. Patients desiring to express more complex ideas can type custom words using the menu as an ambiguous keyboard (similar to a phone keypad). In either case, the patient-generated text will be displayed on screen and read aloud through the computer’s audio system. The only hardware requirements are an existing computer and a $6 webcam. The program can process and respond to an image in 148ms. A new user can be trained in approximately 10 minutes, and after training can type a simple phrase such as “hello world” in 40 seconds. While further testing and improvement is required before the system will be ready for implementation, the project shows promise as a low-cost solution to ICU communication.
Development of an ECG-System using AndroidTM and Modified Bluebeatc Hardware
Electrocardiograms are important medical devices used to monitor the cardiac activity of patients over a period of time. Designed to provide convenient monitoring of patients, although most useful, ECG’s however are expensive and usually not portable, limiting its availability and therefore usefulness. Taking advantage of current technological developments, the researchers developed an ECG System with Androidâ„¢ smartphone based monitor, and Bluebeat© ECG Front circuit based electrodes. The system is divided into two, software and hardware interface. The developed software interface code used an Android based Java language which displays the converted ADC values in the LCD. Saving and user friendly features were also included in the smartphone. The hardware interface is composed of the ECG front and the Data Acquisition Module. The ECG front contains the filters and amplifiers that will receive the human cardiac signal. The DAT Module will then receive it with its Gizduino (Arduinoâ„¢ clone) microcontroller which converts the analog signals into ADC values, and finally sends it to the smartphone using Bluetooth© wireless communication. The first phase of data gathering used signal generator and indicates the system’s accuracy and speed. The second phase testing of the study meanwhile utilizes the ECG front to get actual cardiac signals from human. This phase has already been done, though it still needs more polishing and further trials. For the final testing, nine patients of varying ages and cardiac health status will be taken with ECG readings, three replicates from the developed ECG system, and one from an actual ECG device. Using cardiologists’ and patients’ feedback, the user friendliness and accuracy of the ECG-system will be confirmed, and further modifications shall be made. Lastly, the overall cost of producing the ECG system shall be compared to the price of an ECG device, to see if the developed system is indeed cheaper. However, it is ensured that the system is far more portable than its bulkier ancestors. Once the project is fully finished, the accuracy, replicability and usefulness of the system shall be confirmed using F-test.
A Study For Heavy Metals Detection Using The Solubility change of Different Kinds Solute
A research on how a solution mixed with two or more solutes affect the solubility of each solute was done. If different solutes are put in a solution with a specific concentration, the solubility of the single state solute increases, stays the same, or decreases. The difference in solubility caused by several solutes will give solutions on selectively collecting heavy metals from bodies of water polluted by these heavy metals even more effectively. To test the changes in the solubility of the solution with several solutes, sedimentation has been used; however, colorimetric analysis was also done to observe the changes in color of solutes that show color in the solution. Nitrate compounds of Sodium, Magnesium, Strontium and Potassium were used for the typical metals, and for the transition metals, nitrate compounds of Silver, Cadmium and Lead were used. Test results show that Sodium decreased the solubility of Lead, and as the concentration of Sodium increased, the solubility of Lead increased too. On the other hand, K increased the solubility of Pb, and as the concentration of K increased, the solubility of Pb decreased. We can use the radius of ions and the enthalpy of hydration to explain the changes in solubility. In the case of Cd, as the concentration of K, Mg and Sr increase, the solubility of Cd increased with it. This is because the difference between the ionic radii of Cd and the other ions (K, Mg, Sr) has a tendency to increase in solubility in the enthalpy of hydration. Also, as the concentration of Ca increased, there was a tendency in which the solubility of Cd decreased. This is because the ionic radii of Cd and Ca are similar to each other and there was a tendency that the solubility decreased in the enthalpy of hydration. Through this experiment, the study shows the tendency of the change in solubility of several solutes by comparing ionic radius and the enthalpy of hydration, and if this result is used, the processing of certain heavy metals in the bodies of water can be even more effectively used than the previous method.