tag:joss.theoj.org,2005:/papers/reviewed_by/@lucask07Journal of Open Source Software2024-01-11T22:46:25ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/47432024-01-11T22:46:25Z2024-01-12T00:05:23ZPhysioLabXR: A Python Platform for Real-Time, Multi-modal, Brain–Computer Interfaces and Extended Reality Experimentsacceptedv1.0.02023-09-09 02:37:52 UTC932024-01-11 22:46:25 UTC920245854Ziheng'Leo'LiColumbia University, New York, New York, United States of America0000-0001-5187-200XHaowen'John'WeiColumbia University, New York, New York, United States of America0000-0003-1856-5627ZiwenXieColumbia University, New York, New York, United States of America0009-0006-2304-7591YunxiangPengColumbia University, New York, New York, United States of America0009-0000-1824-970XJunePyoSuhColumbia University, New York, New York, United States of America0009-0005-1211-6101StevenFeinerColumbia University, New York, New York, United States of America0000-0001-9978-7090PaulSajdaColumbia University, New York, New York, United States of America0000-0002-9738-134210.21105/joss.05854https://doi.org/10.5281/zenodo.10471500Python, C++, Cythonhttps://joss.theoj.org/papers/10.21105/joss.05854.pdfneuroscience, human–computer interaction, brain-computer interface, multi-modality, virtual augmented realitytag:joss.theoj.org,2005:Paper/39502023-03-09T21:41:24Z2023-03-10T00:04:45ZOpenMSIStream: A Python package for facilitating integration of streaming data in diverse laboratory environmentsacceptedv1.0.02022-10-07 21:45:41 UTC832023-03-09 21:41:24 UTC820234896MargaretEminizerInstitute for Data Intensive Engineering and Science (IDIES), The Johns Hopkins University, USA0000-0003-4591-2225SamTabriskyDepartment of Biology, Dartmouth College, USA, Department of Computer Science, Dartmouth College, USA, Hopkins Extreme Materials Institute (HEMI), The Johns Hopkins University, USAAmirSharifzadehInstitute for Data Intensive Engineering and Science (IDIES), The Johns Hopkins University, USA0000-0002-4100-4898ChristopherDiMarcoHopkins Extreme Materials Institute (HEMI), The Johns Hopkins University, USA0000-0002-2267-938XJacobM.DiamondHopkins Extreme Materials Institute (HEMI), The Johns Hopkins University, USA, Department of Mechanical Engineering, The Johns Hopkins University, USA0000-0001-7905-4260K.t.RameshHopkins Extreme Materials Institute (HEMI), The Johns Hopkins University, USA0000-0003-2659-4698ToddC.HufnagelHopkins Extreme Materials Institute (HEMI), The Johns Hopkins University, USA, Department of Materials Science and Engineering, The Johns Hopkins University, USA, Department of Mechanical Engineering, The Johns Hopkins University, USA0000-0002-6373-9377TyrelM.McQueenHopkins Extreme Materials Institute (HEMI), The Johns Hopkins University, USA, Department of Materials Science and Engineering, The Johns Hopkins University, USA, Department of Chemistry, The Johns Hopkins University, USA, Institute for Quantum Matter (IQM), William H. Miller III Department of Physics and Astronomy, The Johns Hopkins University, USA0000-0002-8493-4630DavidElbertInstitute for Data Intensive Engineering and Science (IDIES), The Johns Hopkins University, USA, Hopkins Extreme Materials Institute (HEMI), The Johns Hopkins University, USA0000-0002-2292-180X10.21105/joss.04896https://doi.org/10.5281/zenodo.7713196Pythonhttps://joss.theoj.org/papers/10.21105/joss.04896.pdfdata streaming, science data, Apache Kafka, materials sciencetag:joss.theoj.org,2005:Paper/18352020-10-09T16:20:21Z2022-01-18T11:43:19Zpirecorder: Controlled and automated image and video recording with the raspberry piacceptedv3.1.02020-07-07 11:01:06 UTC542020-10-09 16:20:21 UTC520202584JolleW.JollesDepartment of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz, Germany, Zukunftskolleg, Institute of Advanced Study, University of Konstanz, Germany10.21105/joss.02584https://doi.org/10.5281/zenodo.4058628Jupyter Notebook, Pythonhttps://joss.theoj.org/papers/10.21105/joss.02584.pdfraspberry pi, camera, recording, video, automationtag:joss.theoj.org,2005:Paper/9542019-06-18T11:20:00Z2021-02-15T11:32:19Zlabjack-controller: Robust and Easy Data Collection with Labjack T-Series DAQs in Pythonaccepted0.32019-04-10 14:08:51 UTC382019-06-18 11:20:00 UTC420191448BenjaminA.MontgomeryUniversity of Southern Maine0000-0002-1240-5385PaulA.NakroshisUniversity of Southern Maine0000-0003-1887-354X10.21105/joss.01448https://doi.org/10.5281/zenodo.3247140Pythonhttps://joss.theoj.org/papers/10.21105/joss.01448.pdfexperimental, daq, labjack, paralleltag:joss.theoj.org,2005:Paper/8092019-02-16T22:07:57Z2021-02-15T11:32:40ZAxoPy: A Python Library for Implementing Human-Computer Interface Experimentsacceptedv0.2.12019-01-12 04:34:58 UTC342019-02-16 22:07:57 UTC420191191KennethR.LyonsUniversity of California, Davis0000-0002-9143-8459BenjaminW. l.MargolisUniversity of California, Davis0000-0001-5602-188810.21105/joss.01191https://doi.org/10.5281/zenodo.2562630Pythonhttps://joss.theoj.org/papers/10.21105/joss.01191.pdfelectrophysiology, electromyography, human-computer interface, prosthetics