TY - JOUR A1 - Owoyele, Babajide A1 - Trujillo, James A1 - de Melo, Gerard A1 - Pouw, Wim T1 - Masked-Piper: masking personal identities in visual recordings while preserving multimodal information JF - SoftwareX N2 - In this increasingly data-rich world, visual recordings of human behavior are often unable to be shared due to concerns about privacy. Consequently, data sharing in fields such as behavioral science, multimodal communication, and human movement research is often limited. In addition, in legal and other non-scientific contexts, privacy-related concerns may preclude the sharing of video recordings and thus remove the rich multimodal context that humans recruit to communicate. Minimizing the risk of identity exposure while preserving critical behavioral information would maximize utility of public resources (e.g., research grants) and time invested in audio-visual research. Here we present an open-source computer vision tool that masks the identities of humans while maintaining rich information about communicative body movements. Furthermore, this masking tool can be easily applied to many videos, leveraging computational tools to augment the reproducibility and accessibility of behavioral research. The tool is designed for researchers and practitioners engaged in kinematic and affective research. Application areas include teaching/education, communication and human movement research, CCTV, and legal contexts. KW - multimodal communication KW - kinematic research KW - data privacy KW - open science KW - masking KW - research reproducibility Y1 - 2022 U6 - https://doi.org/10.1016/j.softx.2022.101236 SN - 2352-7110 VL - 20 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Konigorski, Stefan A1 - Wernicke, Sarah A1 - Slosarek, Tamara A1 - Zenner, Alexander M. A1 - Strelow, Nils A1 - Ruether, Darius F. A1 - Henschel, Florian A1 - Manaswini, Manisha A1 - Pottbäcker, Fabian A1 - Edelman, Jonathan A. A1 - Owoyele, Babajide A1 - Danieletto, Matteo A1 - Golden, Eddye A1 - Zweig, Micol A1 - Nadkarni, Girish N. A1 - Böttinger, Erwin T1 - StudyU: a platform for designing and conducting innovative digital N-of-1 trials JF - Journal of medical internet research N2 - N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available. Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app. With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials. The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health. Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner. We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice. KW - digital interventions KW - N-of-1 trial KW - SCED KW - single-case experimental design KW - web application KW - mobile application KW - app KW - digital health Y1 - 2022 U6 - https://doi.org/10.2196/35884 SN - 1439-4456 SN - 1438-8871 VL - 24 IS - 7 PB - Healthcare World CY - Richmond, Va. ER - TY - GEN A1 - Konigorski, Stefan A1 - Wernicke, Sarah A1 - Slosarek, Tamara A1 - Zenner, Alexander Maximilian A1 - Strelow, Nils A1 - Ruether, Darius Ferenc A1 - Henschel, Florian A1 - Manaswini, Manisha A1 - Pottbäcker, Fabian A1 - Edelman, Jonathan Antonio A1 - Owoyele, Babajide A1 - Danieletto, Matteo A1 - Golden, Eddye A1 - Zweig, Micol A1 - Nadkarni, Girish N. A1 - Böttinger, Erwin T1 - StudyU: A Platform for Designing and Conducting Innovative Digital N-of-1 Trials T2 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät N2 - N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available. Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app. With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials. The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health. Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner. We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice. T3 - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 12 KW - digital interventions KW - N-of-1 trial KW - SCED KW - single-case experimental design KW - web application KW - mobile application KW - app KW - digital health Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-580370 IS - 12 ER - TY - JOUR A1 - Adnan, Hassan Sami A1 - Matthews, Sam A1 - Hackl, M. A1 - Das, P. P. A1 - Manaswini, Manisha A1 - Gadamsetti, S. A1 - Filali, Maroua A1 - Owoyele, Babajide A1 - Santuber, Joaquín A1 - Edelman, Jonathan T1 - Human centered AI design for clinical monitoring and data management JF - European journal of public health : official journal of the European Health Association N2 - In clinical settings, significant resources are spent on data collection and monitoring patients' health parameters to improve decision-making and provide better care. With increased digitization, the healthcare sector is shifting towards implementing digital technologies for data management and in administration. New technologies offer better treatment opportunities and streamline clinical workflow, but the complexity can cause ineffectiveness, frustration, and errors. To address this, we believe digital solutions alone are not sufficient. Therefore, we take a human-centred design approach for AI development, and apply systems engineering methods to identify system leverage points. We demonstrate how automation enables monitoring clinical parameters, using existing non-intrusive sensor technology, resulting in more resources toward patient care. Furthermore, we provide a framework on digitization of clinical data for integration with data management. Y1 - 2020 U6 - https://doi.org/10.1093/eurpub/ckaa165.225 SN - 1101-1262 SN - 1464-360X VL - 30 IS - 5 SP - V86 EP - V86 PB - Oxford Univ. Press CY - Oxford ER -