Embedded Control: Bio-Motor Activation

By Nolan Knight
Biofeedback C Embedded_Systems Microcontrollers Signal_Processing

This project involved designing and developing a bioinstrument that triggers motor movement in response to a person’s heartbeat. The system processes ECG signals and converts them into motor actuation, creating a visual representation of cardiac activity through moving elements in a fish tank.

School: Purdue University - Indianapolis
Location: Indianapolis, IN
Duration: March 2023 - May 2023

Github Link: https://github.com/ncknight-un/BioSense-Motor-Activation

Biosense Fishtank:

Fish Tank Setup

Fish Setup

Hardware Achitecture

Circuits

Artificial Heart Device

Heart Sim

Activation Oscilloscope

Activation

System Architecture

The device integrates multiple hardware components:

  • Microcontroller: MSP430-FR2355
  • Sensor: ECG module
  • Motor Driver: TB6612FNG

These components work together to process biological signals and control motor behavior.

Signal Processing & Control

  • The MSP430 acts as the central processor, converting analog ECG signals into digital outputs
  • A heartbeat is detected based on the QRS complex of the ECG signal
  • An LED flashes to visually confirm heartbeat detection

Motor Control

  • The motor driver receives signals from the microcontroller
  • PWM signals control motor speed
  • Standby input enables or disables motor operation
  • AI1 and AI2 pins control direction using an H-bridge mechanism

Testing & Demonstration

  • An artificial heart signal (Fluke PS410) was used to streamline testing
  • The ECG signal is processed in real time
  • A square wave signal at the QRS peak triggers motor activation

Skills Improved

  • Embedded systems design and integration
  • ADC for biosignal (ECG) processing
  • Biomedical sensor interfacing
  • Motor control (TB6612FNG, H-bridge, PWM)
  • C programming for embedded systems

Key Takeaway

This project provided hands-on experience integrating biological signals with embedded systems by converting ECG data into real-time motor control. It reinforced the role of microcontrollers in sensing, signal processing, and actuation.

Working on this system strengthened my understanding of motor control (PWM speed regulation and H-bridge direction control) and highlighted the challenges of hardware–software co-design in timing-sensitive applications. It also improved my ability to write low-level C code, debug embedded systems, and interpret hardware datasheets for system integration.