Edwin / Thingy: Movement 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.3tj0fciq	testing	1s		uncertain	Show classification Show in data acquisition Show in feature explorer
up-down.3tiv52q6	up-down	1s	100%	up-down	Show classification Show in data acquisition Show in feature explorer
up-down.3tiv4t2g	up-down	1s	100%	up-down	Show classification Show in data acquisition Show in feature explorer
up-down.3tiv3cqi	up-down	1s	100%	up-down	Show classification Show in data acquisition Show in feature explorer
up-down.3tiv298g	up-down	1s	100%	up-down	Show classification Show in data acquisition Show in feature explorer
up-down.3tiv1mk8	up-down	1s	100%	up-down	Show classification Show in data acquisition Show in feature explorer
left-right	left-right	1s	0%	uncertain	Show classification Show in data acquisition Show in feature explorer
other-move.3tiutdq8	other-move	1s		uncertain	Show classification Show in data acquisition Show in feature explorer
testing.3tiuovfr	testing	1s		uncertain	Show classification Show in data acquisition Show in feature explorer
other-move.3tiu1rh1	other-move	1s		left-right	Show classification Show in data acquisition Show in feature explorer
other-move.3tit3dnb	other-move	1s		up-down	Show classification Show in data acquisition Show in feature explorer
front-back.3tisu3k2	front-back	1s		up-down	Show classification Show in data acquisition Show in feature explorer
front-back.3tist4if	front-back	1s		up-down	Show classification Show in data acquisition Show in feature explorer
left-right.3tisip0e	left-right	1s	100%	left-right	Show classification Show in data acquisition Show in feature explorer
left-right.3tisifq6	left-right	1s	0%	uncertain	Show classification Show in data acquisition Show in feature explorer
left-right.3tisi3nh	left-right	1s	100%	left-right	Show classification Show in data acquisition Show in feature explorer
left-right.3tijqj1u	left-right	1s	100%	left-right	Show classification Show in data acquisition Show in feature explorer

Model testing output

Results

Accuracy

80.00%

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.

Classifier

Minimum confidence rating

Should be numeric

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	E Edwin

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Target device

Define your target device requirements to inform model optimizations and performance calculations. No device yet? Use the default settings which you can change at any time.

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Specify the available RAM and ROM for the model's operation, along with the maximum allowed latency for your specific application. Not sure yet? Start with the defaults and modify them later on.

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Test data

Model variants

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Sample length (ms)

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Model testing output

Results

Accuracy

Confusion matrix

Feature explorer

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