BME100 s2015:Group1 12pmL3

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BME 100 Spring 2015 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: Jake Packer
Name: Jake Packer
Name: Andre Nguyen
Name: Andre Nguyen
Name: Jorge Hernandez
Name: Jorge Hernandez
Name: Kaylena Conklin
Name: Kaylena Conklin
Name: Your name
Name: Your name
Name: Your name
Name: Your name


Descriptive Statistics

Temperature Statistics:


Heart Rate Statistics:






After the T-test was performed, it was shown that the two devices had no correlation. However, the standard deviation was much lower for the Spree when compared to the Gold Standard. The most likely reason for this is that the range of temperature that the Spree gauges is four different temperatures, 98-101 °F, at one degree intervals. The Gold Standard's standard deviation was much larger due to the potentially infinite amounts of possible temperatures that could be read to the tenth of a degree. After running a Pearson's correlation test, the value calculated was nearly 0 signifying no correlation between the two data sets. This was further supported after running a t-test, which ended up being 1.7x1019, meaning that there was nearly 100% certainty that the two data sets are statistically different. While the averages were very close to each other for the heart rate, after a t-test was preformed a value of 2.9844E-215. Therefore, there was a significant difference between the two values. The standard deviation was very similar as well, while the standard error was relatively different. This is most likely because the error was so different that p-value ultimately reflected that difference.


This discussion is based upon the experience and observations of group 1 only. Observations may vary from group to group. There were many flaws found in the Spree headband. From initial setup to ending the experiment, the Spree headband proved inconsistent. The device required a blue tooth connection. Upon attempts to connect the spree headband to the handheld display (a cell phone), it was found that connection was faulty, inconsistent, and difficult to begin. The spree bluetooth signal was in no way identified with the spree headband. In other words, when the spree was connected to the network, the spree ID displays as "spree" and then a sequence of random numbers. Since the experiment was done among other spree users, there was no way to identify the specific spree headband with its corresponding bluetooth wireless signal. To send information, the signal required constant motion from the spree headband. To operate at rest (while sitting for example), the user had to bob or wag his head back and forth to continue the wireless connection. After 20 minutes of wear, the user noticed discomfort at the point of contact with the spree headband. After 30 minutes, the discomfort was described as mild to significant. The user also noted added pressure around the temples. Battery life was sapped out of the cell phone at a high rate. During the 80 minute exercise, the battery life of an iPhone 6+ was drained from 87% to 47%. As mentioned earlier, the connection from the spree headband sensor to the display was inconsistent. During the course of the experiment, the device disconnected from the network 2 times. Upon reconnecting, the device began counting down time, whereas before it had been counting up. It was also noted that upon reconnecting, the heart rate monitor display changed from actual (or current) heart rate to target heart rate. This change was so subtle that it was not noticed immediately, causing 2 sets of data to be inaccurate. When the final cool down was performed, the heart rate monitor gauge of the device showed 0 readings.

Given our experience with the spree product, many improvements could be made. The bluetooth signal would be much easier to use if it was designated an ID found with the product. To operate at rest, the sensor should be improved to not just sense movement. Comfort was an issue as the user experienced discomfort within the first 20 minutes of a walking route. It could be argued that more strenuous activities would provide more and more irritation to the forehead as the device is not completely adhered to the head. The finding that discomfort increased with time could also give us concern for the device's performance over long periods of exertion (marathons, triathlons, etc). Battery life could be improved by employing Samsung-like technology of "power saving"; dimming the cell phone screen between views for example. The overall connection to bluetooth should be improved.


Target Population and Need

It has been shown that target populations should be large in nature (therefore to have a greater affect, reach out to more customers, make a greater difference). It is no different with our product. According to the Centers for Disease Control and prevention website, obesity plagues over 1/3 of the adult US population, over 78.6 million people. Money allocated to obesity-related illnesses by the US healthcare system totaled $147 billion dollars in 2008. This huge (no pun intended) problem is not only affecting people's self esteem and fitness, but is also linked to several sometimes fatal health complications, such as heart disease, stroke, type 2 diabetes, and cancer. The needs of these people include knowing caloric intake, or how much they eat, what types of food they eat, how much exercise is required to burn off excess fat and calories, and knowing when to stop consuming food. These combined needs are essential to eradicating obesity. Many people recognize they are overweight, but do not take the time to count calories. Many overweight people also do not know that there are "good" calories and "bad" calories, or in other words, that "not all calories are created equal". Certain calories affect your body differently than others. Finally, like many serious addictions, obese individuals struggle to stop their excessive eating. If a device could be programmed to encourage the individual to stop eating, then great improvements can occur in the individual's eating habits.


Device Design


Inferential Statistics








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