For our final project, we will be making a glove that changes color depending on its position and the angle of the fingers. For this, we will be using an accelerometer to track the relative motion in space and flex sensors attached to the fingers to track their range of motion. We will also use WiFi to send and collect the data from the glove. We will map the data across a 1-10 range. Ranges in the middle will represent limited motion, while values at the extremes of the range represent maximal motion. By the April 3rd deadline, we are planning to have most of the general circuit for the motion tracking done. By the April 17th deadline, we are planning to have the WiFi connectivity established.

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The goal of our project was to create a glove that tracks motion over various directions, including side to side, front to back, and additionally, the bend of the fingers. The practical application of this project would be for physical therapy for individuals with joint issues in their wrist and hand. In theory, those individuals would be able to use the glove to track the range of motion of their wrist movements, as well as their fingers. The main components of our project were flex sensors attached to the fingers of the glove and an accelerometer, which was placed on the back of the hand. The flex sensors, which are variable resistors, measure the bend angle of the fingers and the accelerometer tracks the wrist and hand motion. For the first demo day, we had the flex sensors working and attached to the fingers of the glove where we were able to print out the bend angle. However, the angles were not perfectly zeroed when laid flat and by the time the project was completed the angles were much closer, if not exactly, zero when laying flat. Because the flex sensor is a resistor, it outputs resistance. Our goal was to convert that resistance into a meaningful output (i.e. the bend angle). To do so we first set the straight resistance to 26000 Ohms and the bend resistance to 90000 Ohms (resistance at 90 degrees). We took the analog value from the flex sensor and converted it to a new value and mapped it on a range of zero to 90 degrees. For the accelerometer, we found the minimum and maximum for each of the X, Y, and Z analog outputs and used a map function to convert those values to a 1-10 scale. Values toward the ends of the scale represented maximal motion, while values near the middle represented a minimal range of motion. This data from the accelerometer was sent via Wi-Fi to Thingspeak where the data was compiled over time. The proect could have been improved in a number of ways. First, we were unable to send data from all the flex sensors through Wi-Fi. Additionally, we could have improved tracking from the Z-direction of the accelerometer, however, the movements did not seem to be sensitive enough to register changes in values for data collection. Furthermore, we could have shortened the wires, which proved to be relatively cumbersome to the overall functionality of the device. We could have also used a better glove as or base as the one we used proved to be rather difficult to attach the flex sensors to. Also, we could have found a better way to attach the boards onto the glove, as it was uncomfortable, clunky, and difficult to put on and take off. If we made these improvements, the device could in theory stand a better chance of becoming a real product. Also, we could have converted the accelerometer data into a more meaningful value than a simple range of 1-10. This project challenged us, however, we feel as though we learned a lot and gained valuable experience.

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