Tuesday, May 12, 2015
Thursday, April 30, 2015
Wednesday, April 29, 2015
PCB Failed, Demo of Bluetooth System.
Sadly, the PCB that we made has failed. Below we have the video of the circuit board version of the circuit. This version worked fairly well.
We then transferred this circuit to a pcb. The pcb, did not work at all as shown in the video below.
In better news we were able to put together an android app to control our circuit. In order to this we attached a Bluetooth module that converted Bluetooth to serial that our mbed could handle. The way it works is that when you start chewing the vibration motor on your body will start vibrating and will not stop until you open our app and log your meal. When you click the button to decide what meal you ate, we will send a post to ThingSpeak to log the time and what meal you are eating. We then open myfitness pal so that you can log exactly what you ate.
Since we had everything working after the 519 demos earlier today, we even had Deeksha and Sid try it out. I was able to get a video of Sid trying out our system.
Bluetooth Works
Today we got bluetooth integration with our android app. Building the android app was a pain but eventually we got our mbed and my android phone to communicate. When the user is chewing for too long, they will not be able to stop the vibration until they log their meal, and they then have the option to fill out their meal on myfitnesspal.
Sunday, April 26, 2015
First Demo
On our first demo day, we had a couple bugs for our presentation. We made our own EMG circuit, but sadly we were not able to demo it because we were missing some of the ICs that we ordered for it. Furthermore, our vibration motor died early on in our demos due to a loose connection somewhere in our perfboard. We now have the basics of our design completed. We have started to work on an android app for the next demo day. We are working on interfacing our circuit with an android phone.
Tuesday, April 21, 2015
Goals
Baseline Goal(4/24/2015):
As stated in our project proposal, our baseline goal is to detect when a person chewing and to give them feedback to inform them that they should watch what they are eating, and to do this by using an mbed and our own emg sensor. To meet this goal we must work on packaging our product into our fanny pack and integrating our emg own emg sensor which we will receive on Wednesday.
Reach Goal(5/1/2015):
We will integrate an android app that will allow the user to tag their eating habits. This means that they will not only get the feedback from the sensors on their body, but they will now be able to create timestamps of when they were eating in order to see how strictly one is adhering to their diet.
As stated in our project proposal, our baseline goal is to detect when a person chewing and to give them feedback to inform them that they should watch what they are eating, and to do this by using an mbed and our own emg sensor. To meet this goal we must work on packaging our product into our fanny pack and integrating our emg own emg sensor which we will receive on Wednesday.
Reach Goal(5/1/2015):
We will integrate an android app that will allow the user to tag their eating habits. This means that they will not only get the feedback from the sensors on their body, but they will now be able to create timestamps of when they were eating in order to see how strictly one is adhering to their diet.
Sunday, April 19, 2015
More difficutly in detecting swallowing
On Friday, we mainly looked at the materials that were sent to us on using a microphone and found that it was infeasible due to the ideal environment and expensive equipment required for the study that we looked at.
We then moved on and tried to detect swallowing using our EMG sensors. We tried two locations, below the chin as we had seen in another study and on the side of the face where we currently have our chewing EMG. For both locations we captured 1 minute of training data for both talking and swallowing. I drank about a little more than a gallon of water in the 2 minutes of capture for swallowing.
When we started looking at the chin electrode data things looked promising, because our training data was able to predict talking or swallowing with 85% accuracy. We soon learned that this was a fluke because our decision tree had been fit precisely to our training data and our testing data sets had an accuracy between 11% and 50%.
Detection of drinking on the side of the face was even worse our training set was only about 50% accurate.
After seeing these results we decided to search on line to see if anyone was able to detect swallowing using an EMG. It turned out again that this required an ideal situation. In this study, "oscilloscope traces were started at the examiner's order to swallow."
Basically what we have found is that the only way to detect swallowing is in an ideal environment where the user is only swallowing. The reasoning is that the muscles that one uses to swallow are used consistently when talking and doing other normal activities.
After 3 days of trying to get swallowing to work, we have decided to move on to packaging our product and making sure that the chewing mechanism works properly and that the user will get valuable feedback.
We then moved on and tried to detect swallowing using our EMG sensors. We tried two locations, below the chin as we had seen in another study and on the side of the face where we currently have our chewing EMG. For both locations we captured 1 minute of training data for both talking and swallowing. I drank about a little more than a gallon of water in the 2 minutes of capture for swallowing.
When we started looking at the chin electrode data things looked promising, because our training data was able to predict talking or swallowing with 85% accuracy. We soon learned that this was a fluke because our decision tree had been fit precisely to our training data and our testing data sets had an accuracy between 11% and 50%.
Detection of drinking on the side of the face was even worse our training set was only about 50% accurate.
After seeing these results we decided to search on line to see if anyone was able to detect swallowing using an EMG. It turned out again that this required an ideal situation. In this study, "oscilloscope traces were started at the examiner's order to swallow."
Basically what we have found is that the only way to detect swallowing is in an ideal environment where the user is only swallowing. The reasoning is that the muscles that one uses to swallow are used consistently when talking and doing other normal activities.
After 3 days of trying to get swallowing to work, we have decided to move on to packaging our product and making sure that the chewing mechanism works properly and that the user will get valuable feedback.
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