BME100 f2013:W900 Group10 L3: Difference between revisions
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'''Recommendations as How to Improve the Device''' | '''Recommendations as How to Improve the Device''' | ||
Recommend a different wireless system be used other than bluetooth. Our team experience difficulties syncing the RAIING Wireless Thermometer to the iPhone app used to record the body temperature data | Recommend a different wireless system be used other than bluetooth. Our team experience difficulties syncing the RAIING Wireless Thermometer to the iPhone app used to record the body temperature data | ||
Revision as of 00:13, 2 October 2013
BME 100 Fall 2013 | Home People Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3 Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6 Course Logistics For Instructors Photos Wiki Editing Help | ||||||
OUR TEAMLAB 3A WRITE-UPDescriptive and Inferential StatisticsFor the experiment, two medical devices were utilized in the data collection of body temperature. The first device used was the RAIING Medical Company Wireless Thermometer (Model: WTM-BT30-T). The other medical device used was a normal oral thermometer to test the validity of results from the RAIING Wireless Thermometer. The table below shows the average, standard deviation, end point #'s and standard errors of body temperature for each medical device labeled Oral and Sensor (RAIING Wireless Thermometer).
Results
Analysis
Summary/DiscussionT-Test: Analysis of the data with a t-test shows that there is a significant correlation between data. The p-value is well below 0.05 which is the maximum value to show significance. Pearson's r: Pearson's r coefficient shows that the data has little linear correlation. This implies that that, when compared with the readings from the accepted measurement device (oral thermometer), the sensor reports widely varying and inconsistent temperature readings showing how imprecise it was in reality. Trend Line: If the sensor were to report precise data, we would expect the slope of the trend line to be close to one. The slope of our trend line was closer to 0, indicating that the sensor does not report precise data. Standard Deviation: Because we took both control readings (stationary in consistent environment) and non-control readings (outside, moving, exercise, etc.) we would expect the data of each group to have some standard deviation. Furthermore, if both devices were to precisely report data, we would expect the standard deviation of both groups to be almost the same. This is not the case with our data, indicating that one device (in this case the sensor) reports data with more variation. Summary From all of our collected data from both the thermometer and RAIING we concluded that the sensor was not a reliable source for determining temperature. Recommendations as How to Improve the Device Recommend a different wireless system be used other than bluetooth. Our team experience difficulties syncing the RAIING Wireless Thermometer to the iPhone app used to record the body temperature data
LAB 3B WRITE-UPTarget Population and Need
Device Design
Inferential Statistics
Graph
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