Salman Faris / worker safety wearable - Ported for xG24 Public

This lists all test data. You can manage this data through Data acquisition.

Test data

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
testing.42hnssb1	testing	10s		2 Correct posture - squat	Show classification Show in data acquisition Show in feature explorer
Correct posture - squat.3fuata9p	Correct posture - squat	30s	86%	6 Correct posture - squat, 1 InCorrect posture - Bent Down	Show classification Show in data acquisition Show in feature explorer
InCorrect posture - Bent Down.3fubg05a	InCorrect posture - Bent Down	30s	86%	6 InCorrect posture - Bent Down, 1 Improper Sitting posture	Show classification Show in data acquisition Show in feature explorer
Walking.3fublcdc	Walking	30s	100%	7 Walking	Show classification Show in data acquisition Show in feature explorer
Good Sitting posture.3fuc2mba	Correct Sitting posture	20s	100%	5 Correct Sitting posture	Show classification Show in data acquisition Show in feature explorer
Improper Sitting posture.3fuc49m8	Improper Sitting posture	20s	80%	4 Improper Sitting posture, 1 InCorrect posture - Bent Down	Show classification Show in data acquisition Show in feature explorer

Model testing output

Results

Accuracy

90.32%

Confusion matrix

Feature explorer

Every learning block has a threshold. This can be the minimum confidence that a neural network needs to have, or the maximum anomaly score before a sample is tagged as an anomaly. You can configure these thresholds to tweak the sensitivity of these learning blocks. This affects both live classification and model testing.

NN Classifier

Minimum confidence rating

Should be numeric

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	Name
	Salman Faris

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Test data

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Model testing output

Results

Accuracy

Confusion matrix

Feature explorer

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