Henry Vu / Fall Detection w Arduino Nano 33 BLE Public
Target: Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz) Clone this project

Test data

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Model variants
Test 'Unoptimized (float32)' model Test 'Quantized (int8)' model
Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.

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Sample name Expected outcome Length Accuracy Result
FALL.53eib2et FALL 5s 100% 1 FALL
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FALL.53ei7kma FALL 5s 100% 1 FALL
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IDLE.53ei0lif IDLE 5s 100% 1 IDLE
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IDLE.53eh81sg IDLE 5s 100% 1 IDLE
Show classification Show in data acquisition Show in feature explorer
IDLE.53dv9tm5 IDLE 5s 100% 1 IDLE
Show classification Show in data acquisition Show in feature explorer
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Model testing output

Results

Model version:
Accuracy
100.00%

Metrics for Classifier

Metric Value
Area under ROC Curve 1.00
Weighted average Precision 1.00
Weighted average Recall 1.00
Weighted average F1 score 1.00

Confusion matrix

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Feature explorer

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