Middle school students propose solution for concussion in hockey by AI

Qiushi Han – The developer of Shotguard & Junior hockey player, OJHL

The escalating issue of concussions in ice hockey seems to have found a potential solution. An innovative mobile application and sensing device named Shotguard recently made its debut at the MIT App Inventor SUMMER APPATHON. It not only alerts but, more importantly, has the potential to prevent concussions in ice hockey.

Shotguard device & APP

Concussions are a prevalent and potentially dangerous injury in contact sports, particularly hockey. Each year, between 1.7 and 3 million concussions occur due to sports, with over 50% of NHL players experiencing a concussion at some point in their careers. 

According to 2017 statistics, the percentage of men’s hockey players 16 years and younger diagnosed with concussions during games and practices was 10.4% and 7.9%, and 8.6% and 6.9% for women’s players. According to Canada/USA Hockey data, the 2019-2020 season reached 1.15 million players under the age of 16 in Canada 2019-2020 and 560,000 in the United States. Hockey is one of the sports that cause the highest probability of concussions in children. 

The emergence of Shotguard may offer hope for addressing this issue. The Shotguard device consists of a low cost off-shelf ESP32 M5 sensor and an app. The app is developed by using MIT App Inventor. The sensor unit comes with WiFi, Bluetooth, a rechargable battery, and an IMU sensor. The retail cost for the sensor is under US$25 and could be developed with a standard Arduino development environment. 

Shotguard was developed by two Canadian middle school students, Qiushi Han and Qianhao Han, who are siblings. Qiushi Han, a junior hockey player from the Ontario Junior Hockey League (OJHL), stated that Shotguard’s core goal is to provide a safe playing environment for players like himself, promptly identifying potential concussion risks and taking preventive measures. 

Shotguard records data on brain activity and provides updates on the player’s health to their coach and parents. As the game or practice progresses, the data is analyzed by the AI to determine the risk of a concussion. The accompanying app also displays a color-coded system (green for safe, yellow for at risk, and red for likely concussed) to inform coaches and parents of the player’s safety status. 

If a player is at risk of a concussion, the app will notify the relevant parties so that they can communicate and take the necessary precautions. This information can also be shared with doctors to provide additional support for the player’s recovery. 

Shotguard addresses the issue of concussion prevention through the use of machine learning. It can accurately predict the risk of a concussion by analyzing patterns and considering factors such as age, weight, and height. Coaches and parents can proactively take steps to prevent concussions, rather than simply reacting after the fact. Through data analysis and machine learning, Shotguard provided a warning to the coaches and parents in real time. 

Cloud data transmission of Shotguard

Shotguard sensor and app were field tested with the support of former NHL hocket player Adam Henrich and the North York Rangers Jr Hockey team. Sensor data were collected throughout the game. The shock value is between 0-3 during normal playing time, while collisions result in over 12. Shotguard effectively collected and analyzed the data and provided warnings to the coach and parents in real time. 

“Our analysis indicates that six factors are likely related to whether a hockey player suffers a concussion after an impact. These are age, height, weight, gender, instantaneous impact force, and cumulative impact force during a period.” Qiushi Han said, “Our DNN model takes the six features as input layer nodes. The model then processes the information through three hidden layers to produce three nodes in the output layer. These output nodes represent the probability that a player will be at low, medium, and high risk of sustaining a concussion after a new impact. “

Then, the app displays the probability value corresponding to the output node with the highest probability. This enables coaches, players, and medical staff to quickly assess the player’s risk level and take appropriate measures to prevent or manage a concussion. 

Adam Henrich praised the product, stating that “Shotguard could become a game-changer in preventing concussions.”

Shotguard participated in the 2023 MIT App Inventor SUMMER APPATHON Youth Challenge and secured the third place. The MIT App Inventor Summer Appathon is an event organized by MIT App Inventor to encourage team collaboration and the development of applications that address complex and challenging issues. Participants are required to create and submit an App Inventor application that assists those in need or brings change to the community. The competition’s judging panel consists of members from MIT, the App Inventor Foundation, Kanagawa Institute of Technology in Japan, the Hong Kong Jockey Club Charities Trust, and others. A total of 212 entries from around the world reached the final round.

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