update DOI for JOSS

paper/paper.md

@@ -55,7 +55,7 @@ These modules are pivotal because they enable researchers and clinicians to extr
 With the growing availability of digital health data, open-source implementations of relevant algorithms are increasingly becoming available. From the Mobilise-D consortium, the recommended algorithms for assessing real-world gait were released, but these algorithms were developed in MATLAB, that is not free to use [@mobilised:2019; @mobilised:2023]. Likewise, an algorithm for the estimation of gait quality was released, but it is also only available in MATLAB [@gaitqualitycomposite:2016; @MATLAB:2022]. Alternatively, open-source, Python packages are available, for example to detect gait and extract gait features from a low back-worn inertial measurement unit (IMU) [@czech:2019], or from two feet-worn IMUs [@kuederle:2024]. These advancements facilitate broader accessibility and usability across research and clinical applications. Additionally, innovative approaches like Mobile GaitLab focus on video input for predicting key gait parameters such as walking speed, cadence, knee flexion angle at maximum extension, and the Gait Deviation Index, leveraging open-source principles and designed to be accessible to non-computer science specialists [@kidzinski:2020; @mobile-gaitlab:2020]. Moreover, tools such as Sit2Stand and Sports2D contribute to this landscape by offering user-friendly platforms for assessing physical function through automated analysis of movements like sit-to-stand transitions and joint angles from smartphone videos (Sports2D) [@Boswell:2023; @Pagnon:2023]. KielMAT builds forth on these toolboxes by providing a module software package that goes beyond the analysis of merely gait, and extends these analyses by additionally allowing for the physical activity monitoring [@van:2013] and other daily life-relevant movements, such as sit-to-stand and stand-to-sit transitions [@pham:2017] as well as turns [@pham:2018].
 
 # Provided Functionality
-KielMAT offers a comprehensive suite of algorithms for motion data processing in neuroscience and biomechanics. Currently, the toolbox includes implementations for gait sequence detection (GSD) and initial contact detection (ICD), whereas algorithms for postural transition analysis [@pham:2017] and turns [@pham:2018] are under current development. KielMAT is built on principles from the Brain Imaging Data Structure (BIDS) [@gorgolewski:2016] and for the motion analysis data are organized similar to the Motion-BIDS specifications [@jeung:2023].
+KielMAT offers a comprehensive suite of algorithms for motion data processing in neuroscience and biomechanics. Currently, the toolbox includes implementations for gait sequence detection (GSD) and initial contact detection (ICD), whereas algorithms for postural transition analysis [@pham:2017] and turns [@pham:2018] are under current development. KielMAT is built on principles from the Brain Imaging Data Structure (BIDS) [@gorgolewski:2016] and for the motion analysis data are organized similar to the Motion-BIDS specifications [@jeung:2024].
 
 ## Dataclass
 Supporting the data curation as specified in BIDS, data are organized in recordings, where recordings can be simultaneously collected with different tracking systems (e.g., an camera-based optical motion capture system and a set of IMUs). A tracking system is defined as a group of motion channels that share hardware properties (the recording device) and software properties (the recording duration and number of samples). Loading of a recording returns a `KielMATRecording` object, that holds both `data` and `channels`. Here, `data` are the actual time series data, where `channels` provide information (meta-data) on the time series type, component, the sampling frequency, and the units in which the time series (channel) are recorded.

paper/references.bib

@@ -86,11 +86,19 @@ @article{hansen:2018
 	doi = {10.3233/JPD-181498}
 }
 
-@article{jeung:2023,
-  title={Motion-BIDS: extending the Brain Imaging Data Structure specification to organize motion data for reproducible research},
-  author={Jeung, Sein and Cockx, Helena and Appelhoff, Stefan and Berg, Timotheus and Gramann, Klaus and Grothkopp, S{\"o}ren and Warmerdam, Elke and Hansen, Clint and Oostenveld, Robert and Welzel, Julius and others},
-  year={2023},
-  publisher={PsyArXiv}
+@article{jeung:2024,
+  title = {Motion-{{BIDS}}: An Extension to the Brain Imaging Data Structure to Organize Motion Data for Reproducible Research},
+  shorttitle = {Motion-{{BIDS}}},
+  author = {Jeung, Sein and Cockx, Helena and Appelhoff, Stefan and Berg, Timotheus and Gramann, Klaus and Grothkopp, S{\"o}ren and Warmerdam, Elke and Hansen, Clint and Oostenveld, Robert and Welzel, Julius},
+  year = {2024},
+  month = jul,
+  journal = {Scientific Data},
+  volume = {11},
+  number = {1},
+  pages = {716},
+  publisher = {Nature Publishing Group},
+  issn = {2052-4463},
+  doi = {10.1038/s41597-024-03559-8},
 }
 
 @article{kidzinski:2020,
@@ -135,7 +143,8 @@ @article{mahlknecht:2013
   number={7},
   pages={e69627},
   year={2013},
-  publisher={Public Library of Science San Francisco, USA}
+  publisher={Public Library of Science San Francisco, USA},
+  doi = {10.1371/journal.pone.0069627}
 }
 
 @article{mazza:2021,
@@ -146,7 +155,8 @@ @article{mazza:2021
   number={12},
   pages={e050785},
   year={2021},
-  publisher={British Medical Journal Publishing Group}
+  publisher={British Medical Journal Publishing Group},
+  doi = {10.1136/bmjopen-2021-050785}
 }
 
 @article{micoamigo:2023,
@@ -168,7 +178,8 @@ @article{paraschiv:2019
   number={1},
   pages={1--11},
   year={2019},
-  publisher={BioMed Central}
+  publisher={BioMed Central},
+  doi = {10.1186/s12984-019-0494-z}
 }
 
 @inproceedings{paraschiv:2020,
@@ -177,7 +188,8 @@ @inproceedings{paraschiv:2020
   booktitle={2020 42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
   pages={4596--4599},
   year={2020},
-  organization={IEEE}
+  organization={IEEE},
+  doi={10.1109/EMBC44109.2020.9176281}
 }
 
 @article{pham:2017,