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perceiveModular('Report_Json_Session_Report_20200115T123657.json',25,'MedOff','yes', 'yes', 'perceive_localsettings_default.json') % combination of all above
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```
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# OUTPUT
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The script generates BIDS bids.neuroimaging.io/ inspired subject and session folders with the
## i.e. stitching 2 or more streams together due to interruption
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## How?
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The sampleinfo is used, which is a sample information based on the MSecTicks.
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The sampleinfotime is now the sample number of the FirstPackageTime of the absolute time, computed from midnight, with a length of the sample frequency x the trial length (no further correction).
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2 streams are concatenated by compute the sample difference between the last sample of the first part, and the first sample of the next part, (iteratively for multiple parts). This amount are the NaN values inserted when concatenating the streams.
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##GUI
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## note on time-specificity
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Because the FirstPacketDateTime is used, the resolution of that is 1 second, according to the Medtronic documentation.
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The TicksInMSec have a resolution of 50ms, however, it is according to the ongoing information exchange with Medtronic as of now not possible to use the TicksInMSec of 2 streams to use these for concatenation.
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According to the documenation TicksInMSec roll over at 2^16 Ticks unless it is an ongoing streaming. However, we were unable to find a satisfying solution for stream concatination based on our observations.
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For higher time resolution and external synchronization, we refer to our colleagues with the Toolbox DBSSync [DOI: 10.21203/rs.3.rs-8228751/v1](https://doi.org/10.21203/rs.3.rs-8228751/v1)
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## Manually increasing or decreasing the NaN interval
perceive_stitch_interruption_together('sub-006_ses-Fu18mMedOff02_task-Rest_acq-StimOff_mod_BrainSenseBip_run-1_part-', -145, true) %remove 145ms of NaNs from the the default NaN-insertion in between streams
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```
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# artefact rejection
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Currently, there is in this perceiveModular version no automatic artefact rejection (e.g. ECG cleaning); we refer to our colleagues [DOI: 10.21203/rs.3.rs-8228751/v1](https://doi.org/10.21203/rs.3.rs-8228751/v1)
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and the Stam et al. 2023 Clinical Neurophysiology [DOI: 10.1016/j.clinph.2022.11.011](https://doi.org/10.1016/j.clinph.2022.11.011)
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# package loss
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Currently, there is no correction implemented for package loss, as it did not produce stable results for us.
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Therefore, we refer to the documenation of Medtronic:
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