Sensor-based Strength Training Tracking System

Strength training still largely relies on manual logging, limiting quantitative feedback and data-driven coaching. Beginners often struggle to learn correct exercise techniques, while experienced users and trainers face challenges in systematically analyzing and managing workout data. This project proposes an integrated strength training tracking system that connects sensor-based measurement devices with a mobile application to provide real-time monitoring, in-exercise feedback, and post-exercise analysis and visualization.

Project cover image

Questions

Q1. How can workout data be accurately measured across different machine structures?

  • Pin-loaded machines (linear motion) vs. plate-loaded machines (rotational load)
  • Multi-dimensional data: weight, repetitions, velocity, range of motion
  • Sensor stability under vibration and impact during exercise

Q2. How can real-time feedback be effectively provided during workouts?

  • Immediate feedback on speed, rhythm, and movement quality
  • Personalized guidance based on user goals (e.g., hypertrophy, rehabilitation, weight loss)
  • Enabling self-guided training without a trainer

Q3. How can interaction between machine, user, and mobile be seamless?

  • Instant connection without additional setup
  • Minimal disruption to workout flow
  • Continuous pipeline: data collection → analysis → feedback

Solutions

S1. Machine-specific sensor-based measurement system

  • Different sensing strategies were designed based on machine structure
  • Pin-loaded machines: IR sensor (repetitions/velocity), ToF/LiDAR (weight)
  • Plate-loaded machines: Load cell (weight), Gyroscope (motion)
  • → Ensured accurate measurement across heterogeneous equipment

S2. Real-time data processing and feedback loop

  • Data pipeline: Sensor → MCU (ESP32) → Bluetooth → Mobile App
  • Real-time data streaming and processing during exercise
  • Feedback on movement speed and repetition performance
  • → Implemented an immediate measurement–analysis–feedback loop

S3. NFC-based frictionless interaction design

  • NFC tag enables instant connection between device and smartphone
  • One-tap interaction without manual setup
  • Seamless onboarding between hardware and application
  • → Minimized user effort and preserved workout flow

S4. Integrated user–trainer UX system

  • User: Real-time coaching and performance feedback
  • User: Automatic logging and visualization of workout data
  • Trainer: Monitoring multiple users simultaneously
  • Trainer: Providing data-driven personalized feedback
  • → Established a connected ecosystem between personal training and expert coaching
Measurement device attached to a pin-loaded machine

Fig.1. Measurement device attached to a pin-loaded machine

Measurement device attached to a plate-loaded machine

Fig.2. Measurement device attached to a plate-loaded machine

System components: pin-loaded device, plate-loaded device, NFC-enabled smartphone dock, and mobile application

Fig.3. System components: pin-loaded device, plate-loaded device, NFC-enabled smartphone dock, and mobile application

Internal design of the pin-loaded and plate-loaded devices with NFC-enabled dock

Fig.4. Internal design of the pin-loaded and plate-loaded devices with NFC-enabled dock


Results

R1. Sensor-based tracking system for strength training environments

  • Implemented measurement strategies for both pin-loaded and plate-loaded machines
  • Expanded tracking capability beyond cardio-focused systems

R2. End-to-end hardware–software prototype development

  • Integrated sensor module, NFC docking system, and mobile application
  • Achieved full pipeline: sensing → processing → communication → visualization
  • Validated feasibility in real gym environments

R3. Enhanced user experience through real-time feedback

  • Provided immediate feedback during exercise execution
  • Improved movement consistency and performance quality
  • Enabled independent workouts for beginners without trainer assistance

R4. Data-driven training and coaching workflow

  • Automated workout logging and visualization
  • Enabled user–trainer interaction through shared performance data
  • Supported personalized coaching based on quantitative insights
Circuit design and hardware development process

Fig.5. Circuit design and hardware development process

Final prototype

Fig.6. Final prototype

Fig.7. Motion measurement process for the pin-loaded machine

Fig.8. Motion measurement process for the plate-loaded machine