Introduction: Squats Counter Using TensorFlow Lite and Tiny Motion Trainer
This ‘Arduino Nano 33 BLE Sense’ based Squats counter can count the number of Squats performed by an individual using the Accelerometer readings and TinyML based Machine learning model.
- Arduino Nano 33 BLE Sense
- USB to Micro USB Type B Cable
- Arduino IDE
- Tensorflow Lite
Step 1: Demonstration
The Squats counter can detect squats by measuring the accelerometer readings and prints them on the Serial monitor.
The device is to be attached to the individual’s thigh and can be powered using a power bank or a battery.
Step 2: Things Used in This Project:
I am using this complementary Google IO kit from Sparkfun which includes the Arduino Nano 33 BLE Sense which is capable of running TinyML projects with ease.
Step 3: Getting Things Ready
Step 4: Select the Appropriate Settings for Training the Model
Step 5: Capture the Data Required to Train Your Model
Step 6: Train Your Model
Step 7: Test Your Model
Step 8: Download the Arduino Code and Upload It to the Arduino BLE Sense Board
Step 9: Test the Model by Using the Serial Monitor
Step 10: Final Touch
Update the code as per your requirements or use mine: BLE_Sense_Arduino_Code
Place the device on your thigh using a Hook and Loop fastener (Velcro tape)
Step 11: Done!
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