Project

# Title Team Members TA Documents Sponsor
11 The Smart Fitness Coach
 Lishan Shi
Xingyu Li
Yuxuan Lin
 design_document1.pdf
final_paper1.pdf
final_paper2.pdf
final_paper3.pdf
other1.pptx
presentation1.pptx
presentation2.pptx
proposal1.pdf
 Bruce Xinbo Yu
# PROBLEM

With the national fitness campaign, people's fitness habits are being established, and the demand for personalized fitness plans is increasing. Many individuals now exercise at home due to its convenience. However, unfamiliarity with professional knowledge can lead to injuries. This is the issue the Smart Fitness Coach aims to solve. Our goal is to provide an accessible and customized fitness experience, enhancing workout safety and efficiency.

# SOLUTION OVERVIEW

Our app, The Smart Fitness Coach helps home exercisers by offering a system that recognizes exercise forms, provides real-time feedback on posture, and suggests improvements for better safety and effectiveness based on the captured movements.

# SOLUTION COMPONENTS

## FRONTEND (MOBILE APPLICATION)
User Interface: A user-friendly interface that provides visual feedback on exercise form, indicating correct and incorrect posture.
Real-Time Feedback: Visual cues and alerts to guide users, such as highlighting misaligned body parts and offering feedback on exercise correctness.
Exercise Suggestions: Personalized workout recommendations based on user performance.

## BACKEND (PROCESSING UNIT)
Data Processing: Real-time processing of the video feed, ensuring minimal delay in feedback to the mobile app during workouts.
Pose Estimation: Techniques like OpenPose or MediaPipe are used to estimate the user’s body pose and evaluate alignment during exercises.
Action Recognition: Machine learning models, for example, Yolo, identify exercises such as squats or push-ups by analyzing movement patterns.

## CLOUD DATABASE (OPTIONAL)
Stores user profiles, exercise logs, and performance metrics. The cloud also hosts models, enabling periodic updates to improve accuracy.

# CRITERION OF SUCCESS

The project will be successful if the system can accurately identify user movements, provide reliable feedback, and suggest improvements to reduce injuries and enhance fitness. User satisfaction and fitness improvement are key indicators of success.

Electronic Automatic Transmission for Bicycle

Featured Project

Tianqi Liu(tliu51)

Ruijie Qi(rqi2)

Xingkai Zhou(xzhou40)

Sometimes bikers might not which gear is the optimal one to select. Bicycle changes gears by pulling or releasing a steel cable mechanically. We could potentially automate gear changing by hooking up a servo motor to the gear cable. We could calculate the optimal gear under current condition by using several sensors: two hall effect sensors, one sensing cadence from the paddle and the other one sensing the overall speed from the wheel, we could also use pressure sensors on the paddle to determine how hard the biker is paddling. With these sensors, it would be sufficient enough for use detect different terrains since the biker tend to go slower and pedal slower for uphill or go faster and pedal faster for downhill. With all these information from the sensors, we could definitely find out the optimal gear electronically. We plan to take care of the shifting of rear derailleur, if we have more time we may consider modifying the front as well.

Besides shifting automatically, we plan to add a manual mode to our project as well. With manual mode activated, the rider could override the automatic system and select the gear on its own.

We found out another group did electronic bicycle shifting in Spring 2016, but they didn't have a automatic function and didn't have the sensor set-up like ours. Commercially, both SRAM and SHIMANO have electronic shifting products, but these products integrate the servo motor inside the derailleurs, and they have a price tag over $1000. Only professionals or rich enthusiasts can have a hand on them. As our system could potentially serve as an add-on device to all bicycles with gears, it would be much cheaper.