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README.md

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@@ -11,13 +11,15 @@ Welcome to the NeuroGeriatricMotionToolbox (NGMT). We are a Python based toolbox
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> The toolbox is currently under development and is not yet ready for use.
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The toolbox is aimed at a wide variety of motion researchers who want to use open souce software to process their data.
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We have implemented a wide variety of functions to process motion data, such as:
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The toolbox is aimed at motion researchers who want to use python based open source software to process their data.
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We have implemented validated algorithms in modules to process motion data, such as:
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- Gait sequence detection (GSD)
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- Inital contact detection (ICD)
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- Physical activity monitoring (PAM)
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- Postrual transition detection (STSD)
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- More to follow ...
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The idea is that various motion data can be loaded into our dedicated dataclasses which rely on principles from the [Motion-BIDS](https://bids-specification.readthedocs.io/en/latest/modality-specific-files/motion.html) standard.
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The idea is that various motion data can be loaded into our dedicated dataclass which rely on principles from the [Motion-BIDS](https://bids-specification.readthedocs.io/en/latest/modality-specific-files/motion.html) standard.
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## Data classes
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### Data classes: conceptual framework
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In NGMT, data from a single tracking system is therefore loaded into a single `pandas.DataFrame`. The column headers of this `pandas.DataFrame` refer to the channels, and the corresponding [channels information](https://bids-specification.readthedocs.io/en/stable/modality-specific-files/motion.html#channels-description-_channelstsv) is likewise available as a `pandas.DataFrame`.
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Similarly, if any [events](https://bids-specification.readthedocs.io/en/stable/modality-specific-files/task-events.html) are available for the given recording, these are loaded into a single `pandas.DataFrame` for each tracking system as well.
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Similarly, if any [events](https://bids-specification.readthedocs.io/en/stable/modality-specific-files/task-events.html) are available for the given recording, these are loaded into a single `pandas.DataFrame` for each tracking system as well. The events derived from the toolbox can be exported to a BIDS like '*_events.tsv' file.
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### Data classes: in practice
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These concepts are translated into a NGMT dataclass for each recording: `NGMTRecording`:

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