Project

# Title Team Members TA Documents Sponsor
40 Precision Dumbbell Assistant
 Cole Trautman
Ellie Beck
Ronit Kumar
 Douglas Yu design_document1.pdf
final_paper1.pdf
presentation1.pptx
proposal1.pdf
proposal2.pdf
video
# Team Members
- Cole Trautman (colept2)
- Ronit Kumar (ronitk2)
- Ellie Beck (elliana2)

# Problem

Many gym goers struggle to maintain proper form during their workouts with dumbbells, which is why they rely heavily on exercise machines. However, if you are trying to construct an at-home gym, it is not feasible to order too many machines. Hence, there should be a way to help people maintain proper form even when they just use dumbbells. To start simple, we will first make our design compatible with bicep curls. We will add more exercises depending on time constraints.

# Solution

Our design will use 3 6-axis (accelerometer and gyroscope) IMU sensors on each arm to calculate the position of each arm and ensure that the user is performing the exercise correctly. There will be two small sensor boards located on the lower arm and shoulder, and a larger main board with another sensor on the upper arm. There will also be a battery that will be attached to the user, most likely on the upper arm or back. There will be a total of 5 subsystems in this design: sensing, processing, wireless communication, feedback, and power

# Solution Components

## Sensing

The sensing subsystem consists of 6 total LSM6DSMTR 6-axis IMUs, 3 for each arm. Each IMU will be on its own board, and connected to the processor via SPI. As mentioned before, the sensors will be located on the lower and upper arm, as well as the shoulder, which should allow us to accurately track the entire arm and dumbbell. The two small sensor boards will be connected to the main board with some kind of wire harness for power and SPI.

## Processing

The processing subsystem contains the two ESP32 processors. These were chosen because of their wireless capabilities, which we will get to later. Each processor will initialize its three sensors and then read in the sensor data and make sure that they are within the threshold necessary to perform the exercise correctly.

## Wireless Communication

This subsystem will handle the communication between the two ESP32 processors, as well as to the user’s phone so that they can see feedback via the feedback subsystem. We plan to use BLE (Bluetooth Low Energy), but if we run into problems with that ESP32 also should support WiFi.

## Feedback

This subsystem will handle the audible and visual feedback needed to let the user know whether they are doing the exercise correctly or not. We plan to have a buzzer on each main board to provide audible feedback, and a phone app to provide visual feedback. We want to at least list data regarding the number of curls, speed of workout, and angle of movements. Based on the data, it will compile a report that describes the accuracy of the user's form. If we can make some sort of graphic that displays where the movement was incorrect that would be incredibly helpful, although implementing this feature seems like it would be very time consuming.

## Power

Power will come from two 3.7V Li-ion battery packs, one on each arm. We plan to have these near the main board that attaches to the upper arm, but if it is too heavy it could be located elsewhere. This subsystem will also contain the circuitry needed to convert the voltage down to the voltage needed by the processor and sensors if needed.

# Criterion For Success

Our device needs to be accurate in motion and form analysis. To test this goal, we should be able to move our arms at the same distance and angle that we determine from our research of an online fitness expert and the feedback should be positive. We will also need to test each of our sensors individually to ensure that the accelerometer and gyroscope are providing accurate data based on our movements.

We also need to provide real time feedback to the user for improper form. To test this goal, we will purposely use improper form and the buzzer should sound to alert the user.

Our device should also allow the user to do proper movements. When we connect the sensors and ESP32 microcontroller, we will have to make sure that we don’t have overly rigid connections that prevent the user from moving their body parts naturally.

Smart Frisbee

Ryan Moser, Blake Yerkes, James Younce

Smart Frisbee

Featured Project

The idea of this project would be to improve upon the 395 project ‘Smart Frisbee’ done by a group that included James Younce. The improvements would be to create a wristband with low power / short range RF capabilities that would be able to transmit a user ID to the frisbee, allowing the frisbee to know what player is holding it. Furthermore, the PCB from the 395 course would be used as a point of reference, but significantly redesigned in order to introduce the transceiver, a high accuracy GPS module, and any other parts that could be modified to decrease power consumption. The frisbee’s current sensors are a GPS module, and an MPU 6050, which houses an accelerometer and gyroscope.

The software of the system on the frisbee would be redesigned and optimized to record various statistics as well as improve gameplay tracking features for teams and individual players. These statistics could be player specific events such as the number of throws, number of catches, longest throw, fastest throw, most goals, etc.

The new hardware would improve the frisbee’s ability to properly moderate gameplay and improve “housekeeping”, such as ensuring that an interception by the other team in the end zone would not be counted as a score. Further improvements would be seen on the software side, as the frisbee in it’s current iteration will score as long as the frisbee was thrown over the endzone, and the only way to eliminate false goals is to press a button within a 10 second window after the goal.