Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 38 | Athletic Tracking Sensor |
Ethan Pizarro J.D. Armedilla Ryan Horstman |
Jiankun Yang | proposal1.pdf |
|
| # Title Team Members: - Ryan Horstman (ryanjh4) - Ethan Pizarro (epizar4) - J.D. Armedilla (johndel2) # Problem Currently the main metric of progress in weightlifting is varying weight and reps, but there is also value in (and workouts designed around) moving weight either quicker or slower, known as Velocity Based Training. However, this type of training is inaccessible as current sensors are very expensive and infeasible for the everyday weightlifter. Additionally, incorrect form in workouts can lead to gradual and immediate injury to users, especially to those new to working out. Current sensors offer some solutions, but lack in some key features. Some assist with form tracking but not velocity. Most current sensors offer "real-time" feedback that consists of the lifter doing their exercise and then checking their results on their phones. This results in the user finishing a set, then getting feedback, then going back to another set. For exercises that are not just "move the weight as fast as you can" this is unideal. Additionally, with respect to form, this type of feedback does not inform until bad form is already used and the damage is done. # Solution We propose a compact wearable device that takes and transmits workout data to a phone via Bluetooth. It will utilize a 9-axis sensor (acceleration, gyroscope, and magnetometer). However, in addition to sending data to a phone, it will internally process data taken during the workout and provide immediate feedback to the user through haptic signaling and/or LED feedback. Before starting the workout, the user can indicate on his phone which workout he is doing and any desired constraints. Based on that workout the device will track the user's form and acceleration, alerting him/her if a desired constraint is not being met so that it can be immediately corrected mid-set. It would be small enough that you could strap to your wrist or neck, around a weight set, or attach to a desired object. If time allows, we could add a plug-in module that would connect a force sensor (likely piezoelectric) for quantification of exercises that are force based (another feature not currently available with other current acceleration sensors). # Solution Components ## Microcontroller Our microcontroller would an ESP32, and it would take data from the sensor and process it based on constraints transmitted to it from the app. For example, determine if velocity exceeds or is under a certain level or if form is incorrect to the point of risk. The ESP32 includes Bluetooth capability that will be used to communicate with the app. ## Sensors Our 9-axis sensor would be a ICM-20948, which includes acceleration sensor, magnetometer, and gyroscope. This would be utilized to collect acceleration data, as well as motion tracking data for form analysis. The data would be sent to our microcontroller. Additionally, our add-on force sensor would be one such as a 7BB-20-6 Piezo Disc. ## Feedback The immediate feedback to the user would be through vibration with a FIT0774. It would be actuated by the microcontroller. Additionally, we could integrate LED feedback via single-color LEDs. ## App The app would communicate to the device via Bluetooth and send constraints to the microcontroller based on what workout is being done (for example, maximum acceleration in a given direction or gyroscope orientation that indicates correct form). There would be a library of workouts, or the user could implement his own workout. Throughout the workout, the microcontroller will send data to the app. Once finished with the workout, the app will display the data that been collected as well as key statistics, such as the maximum and minimum acceleration/force. ## ... # Criterion For Success For our device to be effective, we will have to be able to enter constraints into the app, do a workout, and be alerted whenever in that workout we are not meeting our goals, or if our form is posing risk. We will first aim to utilize with squats (which necessitates good straight-back form) and bench press. Our app will have to also accurately display workout data. |
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