BME100 f2013:W1200 Group15 L3

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|- |style="background-color: #EEE"|Owwnotebook icon.png BME 100 Fall 2013 |style="background-color: #F2F2F2" | Home
Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6
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Name: Patrick McFarland
Name: Taylor Olvey
Name: Zac Roy
Name: Tameem Jamal
Name: student
Name: student


Descriptive Statistics

The oral sensor: The data from the oral thermometer averaged at 97.57 degrees Fahrenheit, and most of the data didn't deviate from the average more than a couple degrees. There are a few outlying points in the data that suddenly changed by 4 and 5 degrees. And any changes that occurred changed gradually, usually by 0.1 to 0.3 degrees at each time the temperature was taken.

The App Sensor: The data from the App Sensor averaged at 96.14 degrees Fahrenheit, and most of the data deviated from the average by several degrees. There are many outlying points in the data that suddenly changed by 4 and 5 degrees. And any changes that occurred usually changed suddenly by 1 to 4 degrees at each time the temperature was taken.


(Well-labeled graph with error bars and significance)


It can be observed from the data that there is a major difference from the different readings. The oral readings were always a lot higher and much more accurate than the sensor readings. The oral readings actually gave a temperature reading that is normal for a healthy human body. Such conclusions could result from flaws in the sensor design( sensor location, sensor insulation). Also the readings of the oral thermometer had a lower within group variation too.

The Pearson's r value was very interesting for this experiment because it was nearly 0, at 0.021580717, meaning a very weak positive correlation between the oral temperature and sensor temperature. The Student's t test gave a p value of 9.59E-17, which is essentially 0. This means that there is almost certainly a difference between the oral temperature and the sensors given temperature that is not due to sampling error.

(Perform inferential statistics described in assignment.)

After testing the device, the data collected through the use of the device was relatively close to the oral test, however design flaws were prevalent in both measurement and the physical product. In regards to the measurement component of the device, the temperature would vary greatly depending on the orientation of the arm which would often inaccurately analyze the data. In order to alleviate this problem, the devices sensors on the external parts of the hardware should be less sensitive in order to only asses body temperature. The physical flaws of the device include its size, which given the location of the device is not very comfortable when being used. Finally, the adhesive used to hold the device is not very suitable for the human skin as it causes irritation when removed, in order to asses this, a strap should be designed, or at least a new adhesive.

(Please discuss the results and statistical analysis. State your conclusion as well as design flaws and recommendations.)


Target Population and Need

The target population are parents who want to monitor their child's body temperature, such as when the child has a fever.

Device Design

The device design will consist of flexable metal strands inside a plastic figure to insure durability and to keep a defined placement on the wrist. Sensors on the inside of the wristband will measure the body tempature of the individual. Blue tooth and Wifi will be included so the data from the wristband can be accessed through the internet or any celluar device. Finally, a screen will be on top of the wristband to monitor constant body tempature and powered by a button cell.


Inferential Statistics

Pearson R = .885
Student's t test = .016