1. Bertram D, Ophey A, Röttgen S, Kufer K, Merten N, Fink GR, Kalbe E, Hansen C, Maetzler W, Kapsecker M, Reimer LM, Jonas S, Damgaard AT, Bertelsen NB, Skjaerbaek C, Borghammer P, Groenewald K, Ratti PL, Hu MT, Moreau N, Sommerauer M, Bozek K. ActiTect: a generalizable machine learning pipeline for REM sleep behavior disorder screening through standardized actigraphy. npj Digital Medicine. 2026; 9(1): 647. doi: 10.1038/s41746-026-02738-8
  2. Nissen L, Hanke A, Schweizer F, Liu Y, Kahl F, Rosendahl C, Rolke K, Tillmann J, Schaper P, Weckbecker K, Thyrian JR, Jonas S, Wagner M, Reimer LM. Tablet-based SDMT: Digital metric validation and within-task learning in MCI and dementia. DIGITAL HEALTH. 2026; 12: 20552076261484407. doi: 10.1177/20552076261484407
  3. Starnecker F, Krefting J, Nissen L, Schwab M, Jovanovic M, Najem SA, Von Scheidt M, Jonas S, Schunkert H, Reimer LM. Reciprocal Relationship Between Cardiovascular Risk and Attainment of Blood Pressure and Cholesterol Targets in Users of a Mobile Health App. High Blood Pressure & Cardiovascular Prevention. 2026. doi: 10.1007/s40292-026-00806-4
  4. Nissen L, Jonas S, Reimer LM. FaceTrackingKit: Simplifying background face tracking for iOS research apps. SoftwareX. 2026; 35: 102760. doi: 10.1016/j.softx.2026.102760
  5. Reimer LM, Nissen L, Starnecker F, Stepanova O, Dufour F, Ney R, Al Najem S, Schunkert H, Jonas SM. Fully Anonymized Digital Health Data Acquisition in a Research Partnership Using a Blinded Deidentification Proxy in the HerzFit App: Implementation Study. JMIR Formative Research. 2026; 10: e77983. doi: 10.2196/77983
  6. Kahl F, Schalkamp A, Gunter KM, Ophey A, Röttgen S, Razzaque J, Kufer K, Sandor C, Fink GR, Kalbe E, Maetzler W, Hansen C, Jonas SM, Hu MT, Reimer LM, Sommerauer M. Wearable Movement‐Tracking for Prodromal Parkinson's Disease Detection: A Cross‐Country Validation Study. Movement Disorders. 2026; mds.70329. doi: 10.1002/mds.70329
  7. Schweizer F, Yu J, Mille E, Reimer LM, Kapsecker M, Klinker J, Jonas S. Smartphone Sensor Battery Consumption: A Standardized and Reproducible Test Protocol. Sensors. 2026; 26(10): 2923. doi: 10.3390/s26102923
  8. Reimer LM, Pries L, Schweizer F, Nissen L, Jonas SM. On-Device Transformer Architectures for Speech Evaluation in Neurodegenerative Disease Detection. Computers. 2026; 15(5): 287. doi: 10.3390/computers15050287
  9. Kahl F, Wegner P, Kapsecker M, Nissen L, Faber J, Jonas SM, Reimer LM. Comparative Assessment of Accuracy in Video-based Monocular Human Pose Estimation Frameworks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2026; 1-16. doi: 10.1109/TPAMI.2026.3672463
  10. Céline Madeleine Aldenhoven, Leon Nissen, Marie Heinemann, Cem Doğdu, Alexander Hanke, Stephan Jonas, Lara Marie Reimer. Real-Time Emotion Recognition Performance of Mobile Devices: A Detailed Analysis of Camera and TrueDepth Sensors Using Apple’s ARKit. Sensors. 2026; 26(3): 1060. doi: 10.3390/s26031060
  11. Wegner P, Grobe-Einsler M, Reimer L, Kahl F, Koyak B, Elter T, Lange A, Kimmich O, Soub D, Hufschmidt F, Bernsen S, Ferreira M, Klockgether T, Faber J. Leveraging machine learning for digital gait analysis in ataxia using sensor-free motion capture. Communications Medicine. 2026. doi: 10.1038/s43856-025-01258-y
  12. Schaper P, Hanke A, Jonas S, Nissen L, Reimer LM, Schweizer F, Wagner M, Rolke K, Rosendahl C, Tillmann J, Weckbecker K, Thyrian JR. Usability of a Tablet-Based Cognitive Assessment Administered by Medical Assistants in General Practice: Implementation Study. JMIR Formative Research. 2025; 9: e76010. doi: 10.2196/76010
  13. Nissen L, Rother JF, Heinemann M, Reimer LM, Jonas S, Raupach T. A randomised cross-over trial assessing the impact of AI-generated individual feedback on written online assignments for medical students. Medical Teacher. 2025; 47(9): 1544-1550. doi: 10.1080/0142159X.2025.2451870
  14. Küppers L, Pfannenstiel R, Bozorgmehr A, Jonas S, Weltermann B, Reimer LM. Short physical performance battery: Pilot study of a human motion capture app (MobiSPPB). DIGITAL HEALTH. 2025; 11: 20552076251346575. doi: 10.1177/20552076251346575
  15. Rolke K, Rosendahl C, Weckbecker K, Hanke A, Wagner M, Nissen L, Reimer LM, Jonas S, Schaper P, Thyrian JR, Schweizer F, Tillmann J. How do patients, medical assistants and physicians accept and experience tablet-based cognitive testing by medical assistants in general practice? - A qualitative study. BMC Primary Care. 2025; 26(1): 174. doi: 10.1186/s12875-025-02823-z
  16. Rosendahl C, Rolke K, Tillmann J, Hanke A, Wagner M, Nissen L, Reimer L, Schweizer F, Schaper P, Thyrian JR, Weckbecker K. Hürden im Versorgungspfad der Demenzdiagnostik: Framework-Analyse des Projektes „iCreate“. Zeitschrift für Gerontologie und Geriatrie. 2025. doi: 10.1007/s00391-025-02507-4
  17. Kahl F, Kahl I, Jonas SM. XGBOrdinal: An XGBoost Extension for Ordinal Data. In: Andrikopoulou E, Gallos P, Arvanitis TN, Austin R, Benis A, Cornet R, Chatzistergos P, Dejaco A, Dusseljee-Peute L, Mohasseb A, Natsiavas P, Nakkas H, Scott P, editors. Studies in Health Technology and Informatics. IOS Press; 2025. doi: 10.3233/SHTI250380
  18. Spreckelsen C, Schneider T, Festag S, Uschmann S, Maatouk H, Jonas S, Weber A, Bock S, Klan F. TrustNShare – Data Trust Model Balancing Privacy Risk, Reputation, and Incentives. In: Andrikopoulou E, Gallos P, Arvanitis TN, Austin R, Benis A, Cornet R, Chatzistergos P, Dejaco A, Dusseljee-Peute L, Mohasseb A, Natsiavas P, Nakkas H, Scott P, editors. Studies in Health Technology and Informatics. IOS Press; 2025. doi: 10.3233/SHTI250363
  19. Baldinger M, Reimer LM, Senner V. Influence of the Camera Viewing Angle on OpenPose Validity in Motion Analysis. Sensors. 2025; 25(3): 799. doi: 10.3390/s25030799
  20. Kapsecker M, Möller MC, Jonas SM. Disentangled representational learning for anomaly detection in single-lead electrocardiogram signals using variational autoencoder. Computers in Biology and Medicine. 2025; 184: 109422. doi: 10.1016/j.compbiomed.2024.109422
  21. Kapsecker M, Mille E, Schweizer F, Klinker J, Yu J, Leube A, Jonas SM. Facial Landmark Analysis for Detecting Visual Impairment in Mobile LogMAR Test. IEEE Journal of Biomedical and Health Informatics. 2025; 1-13. doi: 10.1109/JBHI.2025.3529288
  22. Wegner P, Grobe-Einsler M, Reimer L, Kahl F, Koyak B, Elter T, Lange A, Kimmich O, Soub D, Hufschmidt F, Bernsen S, Ferreira M, Klockgether T, Faber J. Sensor-free motion registration and automated movement evaluation: Leveraging machine learning for clinical gait analysis in ataxia disorders. 2024. doi: 10.1101/2024.05.29.24308057
  23. McRae HL, Kahl F, Kapsecker M, Rühl H, Jonas SM, Pötzsch B. Evaluation of an Explainable Tree-based AI Model for Optimizing Outpatient Thrombophilia Diagnosis and Thrombosis Risk Stratification. In: GTH Congress 2024 – 68th Annual Meeting of the Society of Thrombosis and Haemostasis Research – Building Bridges in Coagulation. Vienna, Austria:; 2024. p. s-0044-1779240. doi: 10.1055/s-0044-1779240
  24. Klinker J, Jonas S. The rationality behind irrationality: A game theoretical challenge to traditional navigation. Transportation Research Interdisciplinary Perspectives. 2024; 25: 101099. doi: 10.1016/j.trip.2024.101099
  25. Willinger L, Böhm B, Schweizer F, Reimer LM, Jonas S, Scheller DA, Oberhoffer-Fritz R, Müller J. KIJANI App to Promote Physical Activity in Children and Adolescents: Protocol for a Mixed Method Evaluation. JMIR Research Protocols. 2024; 13: e55156. doi: 10.2196/55156
  26. Willinger L, Schweizer F, Böhm B, Scheller DA, Jonas S, Oberhoffer-Fritz R, Müller J, Reimer LM. Evaluation of the gamified application KIJANI to promote physical activity in children and adolescents: A multimethod study. DIGITAL HEALTH. 2024; 10: 20552076241271861. doi: 10.1177/20552076241271861
  27. Kristof F, Kapsecker M, Nissen L, Brimicombe J, Cowie MR, Ding Z, Dymond A, Jonas SM, Lindén HC, Lip GYH, Williams K, Mant J, Charlton PH, on behalf of the SAFER Investigators. QRS detection in single-lead, telehealth electrocardiogram signals: Benchmarking open-source algorithms. PLOS Digital Health. 2024; 3(8): e0000538. doi: 10.1371/journal.pdig.0000538
  28. Kahl F, Kapsecker M, Nissen L, Bresser L, Heinemann M, Reimer LM, Jonas SM. Digital Technologies in Hereditary Coagulation Disorders: A Systematic Review. Hämostaseologie. 2024; 44(06): 446-458. doi: 10.1055/a-2415-8646
  29. Farhadi Ghalati P, E. Samadi M, Verket M, Balfanz P, Müller-Wieland D, Jonas S, Napp A, Wanner C, Ketteler M, Vassiliadou A, Heidenreich S, Deserno T, Hetzel G, Fliser D, Kelm M, Floege J, Marx N, Schuppert A. Monitoring individualized glucose levels predicts risk for bradycardia in type 2 diabetes patients with chronic kidney disease: a pilot study. Scientific Reports. 2024; 14(1): 30290. doi: 10.1038/s41598-024-81983-x
  30. Reimer LM, Nissen L, Von Scheidt M, Perl B, Wiehler J, Najem SA, Limbourg FP, Tacke T, Müller A, Jonas S, Schunkert H, Starnecker F. User-centered development of an mHealth app for cardiovascular prevention. DIGITAL HEALTH. 2024; 10: 20552076241249269. doi: 10.1177/20552076241249269
  31. Schweizer F, Willinger L, Oberhoffer-Fritz R, Müller J, Jonas S, Reimer LM. KIJANI: Designing a Physical Activity Promoting Collaborative Augmented Reality Game. In: Hayn D, Pfeifer B, Schreier G, Baumgartner M, editors. Studies in Health Technology and Informatics. IOS Press; 2024. doi: 10.3233/SHTI240021
  32. Tacke T, Nohl-Deryk P, Lingwal N, Reimer LM, Starnecker F, Güthlin C, Gerlach FM, Schunkert H, Jonas S, Müller A. The German version of the mHealth App Usability Questionnaire (GER-MAUQ): Translation and validation study in patients with cardiovascular disease. DIGITAL HEALTH. 2024; 10: 20552076231225168. doi: 10.1177/20552076231225168
  33. Kapsecker M, Charushnikov N, Nissen L, Jonas SM. PeakSwift: Mobile Detection of R-peaks in Single Lead Electrocardiograms. SoftwareX. 2024; 25: 101608.
  34. Maatouk,Hamza, Uschmann, Sebastian, Festag, Sven, Schneider, Tim, Weber, Anna, Khoi, Ngo, Bock, Sven, Jonas, Stephan, Spreckelsen, Cord, Klan, Friederike. TrustNShare: Development of a Blockchain-Based Data Trust Model for Secure and Controlled Health Data Sharing Grounded on Empirical Research. In: 2023. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI230472
  35. McRae HL, Kahl F, Kapsecker M, Rühl H, Jonas SM, Pötzsch B. Evaluation of an Explainable Tree-Based AI Model for Thrombophilia Diagnosis and Thrombosis Risk Stratification. Blood. 2023; 142: 2300. doi: 10.1182/blood-2023-190920
  36. Kristof F, Kapsecker M, Nissen L, Brimicombe J, Cowie MR, Ding Z, Dymond A, Jonas SM, Clair Lindén H, Lip GY. QRS detection in single-lead, telehealth electrocardiogram signals: benchmarking open-source algorithms. medRxiv. 2023; 2023-11. Available from: https://www.medrxiv.org/content/10.1101/2023.11.07.23298202.abstract
  37. Madhi K, Reimer LM, Jonas S. Attribution-based Personas in Virtual Software Engineering Education. In: 2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET). 2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET). Melbourne, Australia: IEEE; 2023. p. 235-246. doi: 10.1109/ICSE-SEET58685.2023.00028
  38. Starnecker F, Reimer LM, Nissen L, Jovanović M, Kapsecker M, Rospleszcz S, Von Scheidt M, Krefting J, Krüger N, Perl B, Wiehler J, Sun R, Jonas S, Schunkert H. Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study. JMIR Cardio. 2023; 7: e50813. doi: 10.2196/50813
  39. Kapsecker M, Nugraha D, Weinhuber C, Lane ND, Jonas SM. Federated Learning with Swift: An Extension of Flower and Performance Evaluation. SoftwareX. 2023; 24: 101533. doi: 10.1016/j.softx.2023.101533
  40. Aldenhoven CM, Reimer LM, Jonas S. mBalance: Detect Postural Imbalance with Mobile Devices. In: Schreier G, Pfeifer B, Baumgartner M, Hayn D, editors. Studies in Health Technology and Informatics. IOS Press; 2022. doi: 10.3233/SHTI220344
  41. Annika Wiebe, Kyra Kannen, Benjamin Selaskowski, Aylin Mehren, Ann-Kathrin Thöne, Lisa Pramme, Nike Blumenthal, Mengtong Li, Laura Asché, Stephan Jonas, Katharina Bey, Marcel Schulze, Maria Steffens, Max Christian Pensel, Matthias Guth, Felicia Rohlfsen, Mogda Ekhlas, Helena Lügering, Helena Fileccia, Julian Pakos, Silke Lux, Alexandra Philipsen, Niclas Braun. Virtual reality in the diagnostic and therapy for mental disorders: A systematic review. Clinical Psychology Review. 2022; 98: 102213.
  42. Kapsecker M, Strobel B, Jonas S. SAFMA: Secure Aggregation Framework for mHealth Applications. In: German Medical Science GMS Publishing House; 2022. p. DocAbstr. 95. doi: 10.3205/22gmds010
  43. Kapsecker M, Osterlehner S, Jonas SM. Analysis of Mobile Typing Characteristics in the Light of Cognition. In: 2022 IEEE International Conference on Digital Health (ICDH). 2022 IEEE International Conference on Digital Health (ICDH). 2022. p. 87-95. doi: 10.1109/ICDH55609.2022.00022
  44. Reimer LM, Kapsecker M, Fukushima T, Jonas SM. Evaluating 3D Human Motion Capture on Mobile Devices. Appl. Sci. 2022; 12(10): 4806. doi: 10.3390/app12104806
  45. Tobias Piotrowski, Oliver Rippel, Andreas Elanzew, Bastian Nießing, Sebastian Stucken, Sven Jung, Niels König, Simone Haupt, Laura Stappert, Oliver Brüstle, Robert Schmitt, Stephan Jonas. Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status. Computers in Biology and Medicine. 2021; 129: 104172.
  46. Klinker J, Selmi MH, Avezum M, Jonas S. Introducing a Navigation Algorithm for Reducing the Spread of Diseases in Public Transport Networks. In: Navigating Healthcare Through Challenging Times. IOS Press; 2021. p. 113-121.
  47. Hayn D, Schreier G, Baumgartner M. Navigating Healthcare Through Challenging Times: Proceedings of DHealth 2021 – Health Informatics Meets Digital Health. IOS Press; 2021.
  48. Reimer LM, Starnecker F, Schunkert H, Jonas S. Developing an App for Cardiovascular Prevention and Scientific Data Collection. In: Hayn D, Schreier G, Baumgartner M, editors. Studies in Health Technology and Informatics. IOS Press; 2021. doi: 10.3233/SHTI210095
  49. Reimer LM, Weigel S, Ehrenstorfer F, Adikari M, Birkle W, Jonas S. Mobile Motion Tracking for Disease Prevention and Rehabilitation Using Apple ARKit. In: Hayn D, Schreier G, Baumgartner M, editors. Studies in Health Technology and Informatics. IOS Press; 2021. doi: 10.3233/SHTI210092
  50. Schmiedmayer P, Reimer LM, Jovanović M, Henze D, Jonas S. Transitioning to a Large-Scale Distributed Programming Course. In: 2020 IEEE 32nd Conference on Software Engineering Education and Training (CSEE T). 2020 IEEE 32nd Conference on Software Engineering Education and Training (CSEE T). 2020. p. 1-6. doi: 10.1109/CSEET49119.2020.9206239
  51. ElHady NE, Jonas SM, Provost J, Senner V. Sensor Failure Detection in Ambient Assisted Living Using Association Rule Mining. Sensors. 2020; 20: 6760.
  52. Hagel S, Gantner J, Spreckelsen C, Fischer C, Ammon D, Saleh K, Phan-Vogtmann LA, Heidel A, Müller S, Helhorn A, Kruse H, Thomas E, Rißner F, Haferkamp S, Vorwerk J, Deffge S, Juzek-Küpper MF, Lippmann N, Lübbert C, Trawinski H, Wendt S, Wendt T, Andreas Dürschmid, Konik M, Moritz S, Tiller D, Röhrig R, Schulte-Coerne J, Fortmann J, Jonas S, Witzke O, Rath PM, Pletz MW, Scherag A. Hospital-wide ELectronic medical record evaluated computerised decision support system to improve outcomes of Patients with staphylococcal bloodstream infection (HELP): study protocol for a multicentre stepped-wedge cluster randomised trial. BMJ open. 2020; 10(2).
  53. Kutafina E, Brenner A, Titgemeyer Y, Surges R, Jonas SM. Comparison of mobile and clinical EEG sensors through resting state simultaneous data collection. PeerJ. 2020; 8: e8969.
  54. Titgemeyer Y, Surges R, Altenmüller DM, Fauser S, Kunze A, Lanz M, Malter MP, Nass RD, von Podewils F, Remi J, von Spiczak S, Strzelczyk A, Ramos RM, Kutafina E, Jonas SM. Can commercially available wearable EEG devices be used for diagnostic purposes? An explorative pilot study. Epilepsy & Behavior. 2020; 106507. doi: 10.1016/j.yebeh.2019.106507
  55. Waldmüller H, Spreckelsen C, Rudat H, Krumm N, Rolke R, Jonas SM. 360-degree Delphi: addressing sociotechnical challenges of healthcare IT. BMC Medical Informatics and Decision Making. 2020; 20(1): 1-13.
  56. Haßler M, Burgdorf A, Pomp A, Kohlschein C, Büsing C, Jonas S. A Holistic System for Pre-clinical Diagnosis of Sleep Disorders in the Home Environment. In: IEEE HealthCom. IEEE HealthCom. 2019.
  57. Ramos RM, Cheng PGF, Jonas SM. Validation of an mHealth App for Depression Screening and Monitoring (Psychologist in a Pocket): Correlational Study and Concurrence Analysis. JMIR mHealth and uHealth. 2019; 7(9): e12051. doi: 10.2196/12051
  58. Kutafina E, Jovanović M, Kabino K, Jonas SM. Learning Manual Skills with Smart Wearables. In: Buchem I, Klamma R, Wild F, editors. Perspectives on Wearable Enhanced Learning (WELL). Cham: Springer International Publishing; 2019. p. 229-250. doi: 10.1007/978-3-319-64301-4_11
  59. Deniz E, Jonas S, Khokha M, Choma M. Quantitative phenotyping of Xenopus embryonic heart pathophysiology using hemoglobin contrast subtraction angiography to screen human cardiomyopathies. Frontiers in Physiology. 2019; 10: 1197.
  60. Date P, Ackermann P, Furey C, Fink IB, Jonas S, Khokha MK, Kahle KT, Deniz E. Visualizing flow in an intact CSF network using optical coherence tomography: implications for human congenital hydrocephalus. Scientific Reports. 2019; 9(1): 1-15. doi: 10.1038/s41598-019-42549-4
  61. Weismann CG, Blice-Baum A, Tong T, Li J, Huang BK, Jonas SM, Cammarato A, Choma MA. Multi-modal and multiscale imaging approaches reveal novel cardiovascular pathophysiology in Drosophila melanogaster. Biology Open. 2019; 8(8): bio044339. doi: 10.1242/bio.044339
  62. Klischies D, Kohlschein C, Werner CJ, Jonas SM. Evaluation of Deep Clustering for Diarization of Aphasic Speech.. Studies in health technology and informatics. 2019; 260: 81-88. Available from: http://europepmc.org/abstract/med/31118322
  63. Ballast T, Jonas S, Spreckelsen C, Jovanović M. Digitale Unterstützung für informell Pflegende - der interaktive TK-Pflege-Coach. In: Elmer A, Matusiewicz D, editors. Die digitale Transformation der Pflege: Wandel. Innovation. Smart Services.. Berlin: Medizinisch Wissenschaftliche Verlagsgesellschaft; 2019.
  64. von Stein N, Schulte-Coerne J, Jonas SM, Kutafina E. Robust Comparison of Simultaneous EEG Recordings Using Kalman Filters and Gaussian Mixture Models. Studies in Health Technology and Informatics. 2019; 113-120. doi: 10.3233/978-1-61499-971-3-113
  65. Jonas S, Siewert S, Spreckelsen C. Privacy-Preserving Record Grouping and Consent Management Based on a Public-Private Key Signature Scheme: Theoretical Analysis and Feasibility Study. Journal of Medical Internet Research. 2019; 21(4): e12300. doi: 10.2196/12300
  66. Kutafina E, Bechtold I, Kabino K, Jonas SM. Recursive neural networks in hospital bed occupancy forecasting. BMC Medical Informatics and Decision Making. 2019; 19(1): 39. doi: 10.1186/s12911-019-0776-1
  67. Stang A, Jonas S, Poole C. Case study in major quotation errors: a critical commentary on the Newcastle–Ottawa scale. European Journal of Epidemiology. 2018; 33(11): 1025-1031. doi: 10.1007/s10654-018-0443-3
  68. Burgdorf A, Güthe I, Jovanovic M, Kutafina E, Kohlschein C, Bitsch JÁ, Jonas SM. The mobile sleep lab app: An open-source framework for mobile sleep assessment based on consumer-grade wearable devices. Computers in Biology and Medicine. 2018; 103: 8-16. doi: 10.1016/j.compbiomed.2018.09.025
  69. Brenner A, Kutafina E, Jonas SM. Automatic Recognition of Epileptiform EEG Abnormalities. Studies in Health Technology and Informatics. 2018; 171-175. doi: 10.3233/978-1-61499-852-5-171
  70. Jovanović M, Seiffarth J, Kutafina E, Jonas SM. Automated Error Detection in Physiotherapy Training.. Studies in health technology and informatics. 2018; 248: 164-171.
  71. Burgdorf A, Bitsch JÁ, Jonas SM. SleepyLab: An Extendable Mobile Sleeplab Based On Wearable Sensors. In: Informatics for Health. Informatics for Health. Manchester, UK:; 2017. Available from: http://informaticsforhealth.org/wp-content/uploads/2017/04/IFH2017-Digital-Programme.pdf
  72. Burgdorf A, Bitsch JÁ, Jonas SM. SleepyLab: An Extendable Mobile Sleeplab Based On Wearable Sensors. In: Helmholtz Symposium. Helmholtz Symposium. Aachen, Germany:; 2017. Available from: http://www.hia.rwth-aachen.de/fileadmin/hia_001/images/Helmholtz_Symposium/2017/HIA_Symposium_Final_Program.pdf
  73. Dohmen D, Förster J, Jonas SM, Jovanovic M, Lemos M, Ohnesorge-Radtke U, Renardy C, Schemmann U. MediWeCo Physio - Mediengestütztes Lehren & Lernen motorischer Fertigkeiten. In: Helmholtz Symposium. Helmholtz Symposium. Aachen, Germany:; 2017. Available from: http://www.hia.rwth-aachen.de/fileadmin/hia_001/images/Helmholtz_Symposium/2017/HIA_Symposium_Final_Program.pdf
  74. Fink IB, Hankammer B, Stopinski T, Titgemeyer Y, Ramos R, Kutafina E, Bitsch Link JÁ, Jonas SM. BrainLab - Ein Framework für mobile neurologische Untersuchungen. In: GMDS annual meeting. GMDS annual meeting. Oldenburg, DE:; 2017.
  75. Fink IB, Hankammer B, Stopinski T, Ramos R, Kutafina E, Bitsch JÁ, Jonas SM. BrainLab - Towards Mobile Brain Research. In: Informatics for Health. Informatics for Health. Manchester, UK:; 2017. Available from: http://informaticsforhealth.org/wp-content/uploads/2017/04/IFH2017-Digital-Programme.pdf
  76. Jovanovic M, Dohmen D, Renardy C, Schemmann U, Förster J, Ohnesorge-Radtke U, Jonas SM. The MediWeCo Project: A Wearable Sensor-Assisted Blended Learning Approach for Physiotherapy Education. In: Informatics for Health. Informatics for Health. Manchester, UK:; 2017. Available from: http://informaticsforhealth.org/wp-content/uploads/2017/04/IFH2017-Digital-Programme.pdf
  77. Kutafina E, Jonas SM. Atlasis - Optimierung komplexer Medikationsprozesse durch automatische Fehlerdetektion und Dokumentation mit tragbaren Smart Devices. In: Tag der Medizinischen Forschung, Uniklinik RWTH Aachen. Tag der Medizinischen Forschung, Uniklinik RWTH Aachen. Aachen, Germany:; 2017.
  78. Kutafina E, Titgemeyer Y, Ramos R, Jonas SM. mEEG in medical applications. In: byteMAL. byteMAL. Maastricht, The Netherlands:; 2017.
  79. Titgemeyer Y, Kutafina E, Ramos R, Jonas SM. Mobile EEG for Personal Well-Being. In: Helmholtz Symposium. Helmholtz Symposium. Aachen, Germany:; 2017. Available from: http://www.hia.rwth-aachen.de/fileadmin/hia_001/images/Helmholtz_Symposium/2017/HIA_Symposium_Final_Program.pdf
  80. Deniz E, Jonas SM, Hooper MC, Griffin J, Choma MA, Khokha MK. Analysis of Craniocardiac Malformations in Xenopus using Optical Coherence Tomography. Scientific Reports. 2017; 7: 42506. Available from: http://www.nature.com/articles/srep42506
  81. Baqapuri HI, Wajdan A, Kutafina E, Misgeld B, Jonas SM. Low-cost wearable for fatigue and back- stress measurement in nursing. In: Nursing Informatics. Nursing Informatics. Geneva, Switzerland:; 2016. p. 372-376. Available from: http://ebooks.iospress.nl/volumearticle/43070
  82. Bukowski M, Kühn M, Zhao X, Bettermann R, Jonas S. Gamification of Clinical Routine: The Dr. Fill Approach. In: Nursing Informatics. Nursing Informatics. Geneva, Switzerland:; 2016. p. 262-266. Available from: http://ebooks.iospress.nl/volumearticle/43048
  83. Klein F, Severijns C, Albiez D, Seljutin E, Jovanović M, Hesar M. The Hygiene Games. In: Nursing Informatics. Nursing Informatics. Geneva, Switzerland:; 2016. p. 262-266. Available from: http://ebooks.iospress.nl/publication/43142
  84. Ramos R, Ferrer-Cheng PG, Bitsch JÁ, Jonas SM. "How do I say sad?" Building a depression-lexicion for Psychologist in a Pocket. In: InPACT International Psychological Applications Conference and Trends. InPACT International Psychological Applications Conference and Trends. Lisbon, Portugal:; 2016.
  85. Kashif M, Jonas S, Deserno T. Deterioration of R-wave Detection in Pathology and Noise: A Comprehensive Analysis Using Simultaneous Truth and Performance Level Estimation. IEEE Transactions on Biomedical Engineering. 2016; PP(99): 1-1. doi: 10.1109/TBME.2016.2633277
  86. Sirazitdinova E, Jonas SM, Lensen J, Kochanov D, Houben R, Slijp H, Deserno TM. Towards efficient mobile image-guided navigation through removal of outliers. EURASIP Journal on Image and Video Processing. 2016; 2016(1). doi: 10.1186/s13640-016-0146-1
  87. Cheng PGF, Ramos RM, Bitsch JÁ, Jonas SM, Ix T, See PLQ, Wehrle K. Psychologist in a Pocket: Lexicon Development and Content Validation of a Mobile-Based App for Depression Screening. JMIR mHealth and uHealth. 2016; 4(3): e88. doi: 10.2196/mhealth.5284
  88. Pop-Fele L, Curaj A, Jovanovic M, Jonas SM, Moellmann J, Ghertescu D, Novac OC, Rusu M, Liehn EA. Advanced modular automated calculation of the morpho-histological parameters in myocardial infarction. Discoveries. 2016; 4: e66. doi: 10.15190/d.2016.13
  89. Ramos R, Ferrer-Cheng PG, Bitsch JÁ, Jonas SM. Feeling Meh: Psychologist in a Pocket application for depression screening. In: InPACT International Psychological Applications Conference and Trends. InPACT International Psychological Applications Conference and Trends. Lisbon, Portugal:; 2016.
  90. Kutafina E, Laukamp D, Bettermann R, Schroeder U, Jonas SM. Wearable Sensors for eLearning of Manual Tasks: Using Forearm EMG in Hand Hygiene Training. Sensors. 2016; 16(8): 1221. doi: 10.3390/s16081221
  91. Kashif M, Jonas S, Haak D, Deserno TM. Bone age assessment meets SIFT. In: Medical Imaging 2015: Computer-Aided Diagnosis. Medical Imaging 2015: Computer-Aided Diagnosis. International Society for Optics and Photonics; 2015. p. 941439. doi: 10.1117/12.2074572
  92. Jose A, Haak D, Jonas S, Brandenburg V, Deserno TM. Human wound photogrammetry with low-cost hardware based on automatic calibration of geometry and color. In: SPIE Medical Imaging. Orlando, Florida, United States:; 2015. p. 94143J. doi: 10.1117/12.2081809
  93. Jose A, Haak D, Jonas S, Brandenburg V, Deserno TM. Human wound photogrammetry with low-cost hardware based on automatic calibration of geometry and color. In: Medical Imaging 2015: Computer-Aided Diagnosis. Medical Imaging 2015: Computer-Aided Diagnosis. International Society for Optics and Photonics; 2015. p. 94143J. doi: 10.1117/12.2081809
  94. Jose A, Haak D, Jonas SM, Brandenburg V, Deserno TM. Towards Standardized Wound Imaging. In: Bildverarbeitung für die Medizin 2015. Springer Berlin Heidelberg; 2015. p. 269-274.
  95. Sirazitdinova E, Jonas SM, Kochanov D, Lensen J, Houben R, Slijp H, Deserno TM. Outliers in 3D Point Clouds Applied to Efficient Image-Guided Localization. In: Bildverarbeitung für die Medizin 2015. Springer Berlin Heidelberg; 2015. p. 197-202.
  96. Ramos R, Ferrer-Cheng PG, de Castro FR. Attitudes toward mHealth: A look at general attitudinal indices among selected Filipino undergraduates. In: Mohan B, editors. Construction of Social Psychology: Advances in Psychology and Psychological Trends Series. Lisbon, Portugal: InScience Press; 2015. p. 186-204. Available from: http://press.insciencepress.org/index.php/press/catalog/book/6
  97. Kutafina E, Laukamp D, Jonas SM. Wearable Sensors in Medical Education: Supporting Hand Hygiene Training with a Forearm EMG. In: pHealth. Västeras, Sweden:; 2015. Available from: http://ebooks.iospress.nl/publication/39272
  98. Haak D, Gehlen J, Jonas S, Deserno TM. OC ToGo: bed site image integration into OpenClinica with mobile devices. In: Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations. Medical Imaging 2014: PACS and Imaging Informatics: Next Generation and Innovations. International Society for Optics and Photonics; 2014. p. 903909. doi: 10.1117/12.2042847
  99. Deserno TM, Sárándi I, Jose A, Haak D, Jonas S, Specht P, Brandenburg V. Towards quantitative assessment of calciphylaxis. In: Medical Imaging 2014: Computer-Aided Diagnosis. Medical Imaging 2014: Computer-Aided Diagnosis. International Society for Optics and Photonics; 2014. p. 90353C. doi: 10.1117/12.2043820
  100. Voss B, Wilop S, Jonas S, El-Komy M, Schaller J, von Felbert V, Megahed M. Tumor Volume as a Prognostic Factor in Resectable Malignant Melanoma. Dermatology. 2014; 228(1): 66-70. doi: 10.1159/000356121

Letzte Aktualisierung: 2026-10-19 19:18