# BME100 f2015:Group13 1030amL3

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# OUR TEAM

 Name: Drew Worman Name: Tanner Ivey Name: Bramuel Simiyu Name: Kaylee Antill Name: Jonah Brosemann Name: Christopher Chen

# LAB 3A WRITE-UP

## Descriptive Statistics

 Heart Rate (beats per minute) Gold Standard (Pulse Ox) Spree Mean 88.92493188 88.30790191 Standard Deviation 23.2322048 22.99431 Standard Error 1.212711219 1.200293
 Temperature (temperature in Fahrenheit) Gold Standard (Oral Thermometer) Spree Mean 97.25641711 99.26738 Standard Deviation 1.170267263 1.347485 Standard Error 0.06051308 1.200293

Heart Rate

Temperature

## Analysis

We decided to use a T-test because there were only two groups being compared in each situation: the spree headband and pulse ox for heart rate, and the spree headband and thermometer for body temperature. As the devices were all used on the same person during our data gathering, we used a paired T-test comparing the spree app results of heart rate and the pulse ox. Then we compared the spree app temperature results to the thermometer. We made two separate graphs, one for pulse and the other for body temperature.

Our p values were 0.390 for our heart rate data and 4.696 E-77 for our temperature data.

We also calculated Pearson's R values for the measurements, obtaining the following numbers: 0.823329451 for heart rate and 0.167425906 for body temperature.

The purpose of the Pearson's R values are to show the correlation between the actual (pulse ox and thermometer) and theoretical (spree headband). In terms of heart rate, the measurements the spree headband and pulse ox made correlated fairly well (since R values close to 1 indicate high correlation). This is consistent with the fact that we obtained a p value above 0.05 (0.39), indicating that there is very likely no statistically significant difference between the measurements made by the two devices. Since the measurements made by the headband are so similar to those made the pulse ox, our gold standard device, they are likely accurate and reliable measurements. The Pearson's R value for body temperature showed that the measurements made by the spree headband and thermometer did not correlate much at all (since R values close to 0 indicate little to no correlation). This is consistent with the fact that we obtained a p value far below 0.05 (4.696 E-77), indicating that we are more than 95% confident that the differences in the measurements made by the two devices are statistically significant.

## Summary/Discussion

There were several design flaws with the product (the spree headband). For starters, the apparatus is not aesthetically pleasing, being a heavy metal headband that must be placed around the forehead. This also made it uncomfortable to wear for long periods of time. Making a device for a different part of the body, such as the wrist, would improve user comfort. Another flaw is the fact that the device did not measure temperature well at all. Instead of showing an actual numerical value for temperature, it would represent the temperature using a three color-based temperature meter. To make the measurements more accurate, the device would need to measure the temperature with an actual number. Also, the device didn’t measure the distance traveled or speed at a certain instant accurately at all. Both these could be helped by putting better sensors within the device. The low Bluetooth range was another problem because the user would go out of range very easily, decreasing the convenience and usability of the device. Lengthening the Bluetooth range would allow the user to set the device down and do their workout without losing the signal.

# LAB 3B WRITE-UP

## Target Population and Need

Our target population for our device is male and female adults, 20-50 years old, who are concerned about their health or want to be able to better track factors that can influence their health, such as their diet or exercise levels. In the United States alone, our specified age range would easily encompass more than 100 million people. Narrowing this down to people who care strongly about their health and have the economic means to purchase our device, our target population could still number several million people. We are basing this design off the needs of a consumer who wants more information about their health but either doesn't have the means to obtain such information or finds the process of getting such information too difficult. Our target population might want to find out things such as their current heart rate, temperature, how many calories they've burned during an exercise session, or how many steps they've taken over the course of a normal day. Metrics such as these could help our target population better adjust their lifestyles to remain healthy. In providing consumers with a convenient device that can measure such things and provide data directly to the consumers in an easy to understand format, our device could improve the general quality of life of its consumers. Perhaps knowing more about their health could even lead to them having to go to the doctor less, and allow them treat small problems with their body by themselves at home.

 Customizable (cheaper base model) Soft Material Lightweight/Compact Reliable sensors Simple buttons/ Touch screen Low Cost Comfortable Unobtrusive Accurate Easy to Use

In order to create a low cost device for the consumer, our product, the UwATCH, would be available in multiple models. The base model would have functions such as measuring heart rate, temperature, steps taken, and basic diet monitoring and would retail for around \$120. Additional features could be added for extra fees. Fees could be charged for cosmetic customization as well. To ensure that the device is comfortable to wear and unobstrusive, soft material would be used for the watch band, and the technological component of the device would be made as lightweight and compact as possible. In order for the device to actually be useful, it would have to accurately measure the things it claims to. In order to ensure measurements as accurate as possible, we would of course use sensors that provide reliable and precise readings. Finally, the device would have to be easy to use for it to be a convenient, practical device for the consumer. Taking this into consideration, we decided that our product would feature a UI that could be navigated using buttons alone. This would avoid the need to obscure the screen to use the device and reduce problems posed by things such as sweaty hands during exercise (which can greatly reduce the functionality of things such as touch screens). In maintaining the philosophy of customizability, however, we would allow the consumer to add features such as a touchscreen if they wanted one.

## Inferential Statistics

In order to validate the design of our product we needed to test it on many subjects. We tested our device on 50 subjects, picking randomly from both genders and people of different physical size and stature. While our sample was largely random, we specifically narrowed the possible subjects to people between the ages of 20 and 50 before selection, as this age range comprises our target population. In order to test the accuracy of our device, we had subjects perform physical activity, light or heavy, over the course of an hour and recorded the number of calories burned in 3 min intervals and found the total calories burned. The subjects simultaneously tested both our UwATCH and a brand from our competitors, the Nike Fuel Band, to see how accurate our device’s measurements are compared to devices already on the market. The next day we tested the subjects again, using the same procedures except for measuring body temperatures. We compared our UwATCH to a standard oral thermometer. On a third day we utilized the same procedure as previous tests and measured for heart rate, comparing our UwATCH to a pulse oximeter.

As for the data we ran a paired t-test to evaluate the statistical significance between the two sets of data in calories burned, body temperature, and heart rate(which were for the UwATCH and the Nike Fuel Band, the UwATCH and oral thermometer, and the UwATCH and pulse oximeter, respectively). The test was paired because only one group was tested using the two devices (subjects measured their calories burned/temperature/heart rate using both devices at the same time). The resulting p-value for measurements of calories burned was 0.503552128. Because this value is over .05, there proves to be no statistically significant difference between the measurements made by the UwATCH and the Nike Fuel Band. The p-value for the temperature data was 0.4736 and the p-value for the heart rate data was 0.4816, meaning that the was no statistically significant difference between measurements obtained by the UwATCH and oral thermometer or the UwATCH and the pulse oximeter.

The Pearson’s r-value of 0.999360395 that was found for the calories burned data set shows a strong correlation between the UwATCH measurement and that of competitors. These two values mean that the measurement readings for calories burned that the UwATCH produces are accurate and can be trusted by consumers. The Pearson's r-value of 0.9827 for the temperature data set similarly shows a strong correlation between measurements obtained by the oral thermometer and UwATCH. The Pearson's r-value of 0.9912 demonstrates a strong correlation between measurements obtained by the pulse oximeter and uWATCH. The UwATCH therefore compares favorably to existing, reliable devices for body temperature and heart rate measurement as well.

## Graph

 Calories Burned Nike Fuel Band UwATCH Mean 153.6862745 154.0980392 Standard Deviation 119.3654037 120.1982121 Standard Error 16.88081728 16.99859417

 Temperature (°F) Oral Thermometer UwATCH Mean 98.514 98.486 Standard Deviation 1.490 1.438 Standard Error 0.211 0.203

 Heart Rate (bpm) Pulse Oximeter UwATCH Mean 98.820 98.520 Standard Deviation 21.595 20.523 Standard Error 3.054 2.902