Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 38 | Perfect Posture |
Apoorva Josyula Julianna Gecsey Rohan Kanianchalil |
Daniel Vargas | design_document1.pdf design_document2.docx final_paper1.pdf photo1.pdf presentation1.pptx proposal1.pdf |
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| Group Members: Julianna Gecsey (jgecsey2) Rohan Kanianchalil (rohansk2) Apoorva Josyula (josyula3) #Perfect Posture ## Problem In today’s world, millions of people, whether they are at work or at home, are sitting in front of a desk. Most people who are sitting or walking don’t practice good posture, leading to severe upper back pain and spinal deformities. We have the issue of "hunch back" and "text neck" becoming more and more of a problem. This problem was already prevalent, however, with the pandemic, over the past year, this issue has gotten worse as more people have been stuck at home. Many products currently on the market focus on usually just one aspect of a person's posture and often are just physical braces but rarely do we see devices approach this issue holistically, where we can naturally train a person's entire spinal posture. ## Solution Overview Our approach is to focus on holistically training and correcting a person's upper back posture. We propose a wearable device for users to wear throughout their workday. The device will relay data on a person's upper spine position, calculate whether their posture is not upright, and send a message back to the user to inform them their posture is off. The user will be able to see the data of their posture through a phone app that will be connected to the device, along with receiving a vibration from the device which will alert the user when their posture is worsening and then again but stronger if their posture has hit inadequate measurements. ## Solution Components **Posture Sensors** - We will use a combination of an accelerometer and gyroscope to calculate the angular positions of a person's entire spine. We will include these sensors in two places, the upper back and at the base of the neck. Our goal with these sensors is not just to calculate a person's position deviances at these particular spots, but to also use them to ensure that a person's entire spinal curve is appropriate. From the placement of these two sensors and the angles we will get from the reading, we can use an algorithm from our phone app module to calculate what approximately that person's upper spinal form is. **Control Unit** - Our control unit will consist of a microcontroller that will collect sensor information, where we will include a BlueTooth module to send receiving data to our phone app. The microcontroller will be in charge to convert the readings to something that our software algorithm can read for calculation. The microcontroller will be the one to set off initial readings once the user starts using the device. Our phone app will send a message back to our controller when it deems that a person's spine is off track of their initial calibration. From there it will be in charge of figuring out when to alert our feedback systems. We will want to include an internal timer as we don't want to alert the user every time their posture is off, only when they participate in a bad posture for a certain amount of time. **App interface** - For users to see their analytics on how much their posture is changing we will include an app interface that will show a person how often they are in bad posture, creating goals on improving their posture from the last time they used the device. It will also be in charge of the calibration process, where it will record initially what that person's upright position is, giving us a threshold on when we can say a person's entire upper spinal curve is off. The calibration process will include an algorithm of reading the angular data received from the sensors and calculating the normal curvature of that person's spine. **Feedback System** - For users to be made aware when they are in a bad posture for an extended period of time we will include a vibrational motor to physically alert the user of their bad posture. **Power System** - Ideally we would like to include a small lithium battery to power our device, we want it to be relatively small in size for the sake of the device being wearable. ## Criterion for Success - Sensors are giving quick and accurate feedback on angular readings. - Our control unit is able to process information received from sensors and relay it back accurately to our phone app. - Phone app will accurately analyze a person's spinal information and detect irregularities. - Control Unit will be able to send signals to our feedback systems after a given amount of time when an irregularity alert is received. - Vibrational motors are quickly and effectively able to alert the user. - The placements of the device sensors will be readily wearable and relatively small in size, to not add weight to a person's back. - Being able to successfully train users in improving their posture by creating a habit, essentially through classical conditioning and a reward system of checking their posture. |
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