Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 5 | Directional Impact Sensing Helmet (DISH) |
Patrick Sear Ryan Josephson Saathvik Narra |
Ugur Akcal | design_document2.pdf final_paper1.pdf photo1.png photo2.png presentation1.pptx proposal1.pdf video |
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| ## Team Members: - Patrick Sear (sear2) - Saathvik Narra (snarra2) - Ryan Josephson (ryanj2) ## Problem In the NFL, many athletes suffer from concussions or other conditions as a result of repetitive, severe head trauma. These events can lead to long-term effects on the athlete’s health and significantly contribute to the reduced lifespan of professional football players. The average professional football player dies younger than age 60 (Source). This problem can be helped by making accurate collision data immediately available to medical personnel for making game-time decisions and helmet manufacturers so that they can make informed design choices based on real, in-game data. ## Solution The Directional Impact Sensing Helmet (DISH) is a helmet that can determine where on an athlete’s head a hard collision occurs, as well as how hard the hit is. This is useful information for both medical personnel, as well as those working on helmet renovations. For the DISH to work correctly, we believe we can group our project into four modules: data input and digestion, data transmission, data reception and visualization, and power. ## Subsystem 1 - Data Input and Digestion This subsystem is responsible for measuring the data. It has an array of force sensors and the IMU. By using an array of force sensors rather than a single sensor, we can pinpoint where a blunt force collision occurs. We plan to use 9 force sensing resistors, specifically the FlexiForce A401 Sensor (https://www.tekscan.com/products-solutions/force-sensors/a401). In addition to these sensors, we will need an OpAmp for each sensor. We can use the OPA1637DGKT (https://www.digikey.com/short/p048q0fq), but any OpAmp should suffice. The IMU will be acting as a trigger, as well as collecting acceleration data. This functionality allows us to only send data to the receiver when it is needed. For now, we plan to use the LSM6DSV16BXTR IMU from Mouser (https://mou.sr/3HrM8e2). The microcontroller would then take the sensor inputs and do some calculations to recognize an impact. ## Subsystem 2 - Data Transmission This subsystem is responsible for sending the data to the sidelines. For this, we plan to use a Zigbee communication regime. The amount of information we need to transmit is low volume and Zigbee’s power consumption is also low, making it perfect for the small batteries that we plan to use. We’d need to buy 2 XBee S2 Modules (XB24CAWIT-001, https://www.digikey.com/short/n3wf0pwd), one for sending data and one for receiving. ## Subsystem 3 - Data Reception and Visualization We will need software to receive the Zigbee communication and digest it into meaningful data. Zigbee will be sending a confirmation signal to the receiver every 15 seconds to confirm the connection is stable. We want to ensure those using the data are able to understand the data in an easy way. There will be a UI display to help disgust the information. We are targeting a 3D model showing a ‘thermal map’ of the collision on the player’s head/helmet, where the point of impact is highlighted in red on the model. The scope of the DISH project primarily includes the helmet, as a Zigbee receiver along with our software should be sufficient for digesting the data. For this reason, we will use one of the two XBee S2 modules along with an Arduino hooked up to a Arduino UNO REV3 for our receiver. ## Subsystem 4 - Power For the battery, we plan on using standard 3V coin batteries. We would use two in series to exceed the 5V recommendation to power the microchip, where we would then step it down to 5V for the rest of our system to use using a 7805 fixed voltage regulator (https://www.ti.com/lit/ds/symlink/lm340.pdf). Additionally, we could use a separate 3V coin battery for any instances where 3V is needed. Or, we could use a different fixed voltage regulator to step down to 3V. ## Microprocessor Additionally, the microcontroller that we would like to use is the ATmega328P. This is because some of us have experience using Zigbee with an Arduino, and, with a USB loader on our board, we should be able to program this chip using the Arduino IDE. ## Criterion For Success The key criteria for success are as follows. -The helmet must accurately track the location and severity of each collision. -The data must be transmitted quickly and reliably across the distance of a football field. -The data must be properly visualized on the receiving end such that it can be read, understood, and responded to. -The design does not negatively impact the user’s performance or comfort. If all conditions are met, then our product can be considered successful. ## Alternatives There are some existing alternatives to our design, however, each lacks some key features that our design implements. One such product is the Gridiron Tech Shockbox. It offers a modular solution that can be velcro-strapped into the helmet which records the estimated hit direction and force and transmits it via bluetooth to a smartphone. The key difference here is that using a clustered set of sensors greatly limits its ability to get an accurate determination of the position of the hit on the helmet. Additionally, the company appears to no longer exist, as all of its social media accounts are either deleted or have not been updated in nearly 5 years, so it is not a true “competitor.” The NFL also currently uses a mouthguard in order to collect impact data for their players. This tracker can deliver similar information regarding how the hit impacts the player, but lacks precision regarding the precise location of the contact. The key advantage of our design is that it can determine exactly where on the helmet collision occurred. This data is critical for improvements in future helmet design based on the most common collisions. |
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