{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T03:14:45Z","timestamp":1770520485042,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The streaming and recording of smartphone sensor signals is desirable for mHealth, telemedicine, environmental monitoring and other applications. Time series data gathered in these fields typically benefit from the time-synchronized integration of different sensor signals. However, solutions required for this synchronization are mostly available for stationary setups. We hope to contribute to the important emerging field of portable data acquisition by presenting open-source Android applications both for the synchronized streaming (Send-a) and recording (Record-a) of multiple sensor data streams. We validate the applications in terms of functionality, flexibility and precision in fully mobile setups and in hybrid setups combining mobile and desktop hardware. Our results show that the fully mobile solution is equivalent to well-established desktop versions. With the streaming application Send-a and the recording application Record-a, purely smartphone-based setups for mobile research and personal health settings can be realized on off-the-shelf Android devices.<\/jats:p>","DOI":"10.3390\/s21238135","type":"journal-article","created":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T03:10:38Z","timestamp":1638760238000},"page":"8135","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer"],"prefix":"10.3390","volume":"21","author":[{"given":"Sarah","family":"Blum","sequence":"first","affiliation":[{"name":"Neuropsychology Lab, Department of Psychology, University of Oldenburg, 26111 Oldenburg, Germany"},{"name":"Cluster of Excellence Hearing4all, 26111 Oldenburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6056-7872","authenticated-orcid":false,"given":"Daniel","family":"H\u00f6lle","sequence":"additional","affiliation":[{"name":"Neurophysiology of Everyday Life Group, Department of Psychology, University of Oldenburg, 26111 Oldenburg, Germany"}]},{"given":"Martin Georg","family":"Bleichner","sequence":"additional","affiliation":[{"name":"Neurophysiology of Everyday Life Group, Department of Psychology, University of Oldenburg, 26111 Oldenburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4265-5542","authenticated-orcid":false,"given":"Stefan","family":"Debener","sequence":"additional","affiliation":[{"name":"Neuropsychology Lab, Department of Psychology, University of Oldenburg, 26111 Oldenburg, Germany"},{"name":"Cluster of Excellence Hearing4all, 26111 Oldenburg, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5496196","DOI":"10.1155\/2017\/5496196","article-title":"Categorisation of Mobile EEG: A Researcher\u2019s Perspective","volume":"2017","author":"Bateson","year":"2017","journal-title":"BioMed Res. 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