1. 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. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI250380
  2. 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. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI250363
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI240021
  16. 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
  17. Kapsecker M, Charushnikov N, Nissen L, Jonas SM. PeakSwift: Mobile Detection of R-peaks in Single Lead Electrocardiograms. SoftwareX. 2024; 25: 101608.
  18. 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
  19. 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
  20. 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
  21. 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
  22. 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
  23. 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. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI220344
  24. 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.
  25. 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
  26. 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
  27. 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
  28. 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.
  29. 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.
  30. Hayn D, Schreier G, Baumgartner M. Navigating Healthcare Through Challenging Times: Proceedings of DHealth 2021 – Health Informatics Meets Digital Health. IOS Press; 2021.
  31. 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. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI210095
  32. 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. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI210092
  33. 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
  34. ElHady NE, Jonas SM, Provost J, Senner V. Sensor Failure Detection in Ambient Assisted Living Using Association Rule Mining. Sensors. 2020; 20: 6760.
  35. 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).
  36. 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.
  37. 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
  38. 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.
  39. 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.
  40. 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
  41. 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. Available from: http://link.springer.com/10.1007/978-3-319-64301-4_11
  42. 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.
  43. 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
  44. 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
  45. 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
  46. 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.
  47. 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
  48. 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
  49. 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
  50. 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
  51. 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
  52. 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
  53. Jovanović M, Seiffarth J, Kutafina E, Jonas SM. Automated Error Detection in Physiotherapy Training.. Studies in health technology and informatics. 2018; 248: 164-171.
  54. 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
  55. 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
  56. 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
  57. 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.
  58. 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
  59. 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
  60. 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.
  61. Kutafina E, Titgemeyer Y, Ramos R, Jonas SM. mEEG in medical applications. In: byteMAL. byteMAL. Maastricht, The Netherlands:; 2017.
  62. 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
  63. 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
  64. 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
  65. 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
  66. 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
  67. 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.
  68. 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
  69. 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
  70. 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
  71. 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
  72. 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.
  73. 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
  74. Kashif M, Deserno TM, Haak D, Jonas S. Feature description with SIFT, SURF, BRIEF, BRISK, or FREAK? A general question answered for bone age assessment. Computers in Biology and Medicine. 2016; 68: 67-75. doi: 10.1016/j.compbiomed.2015.11.006
  75. Jonas SM, Deserno TM, Buhimschi CS, Makin J, Choma MA, Buhimschi IA. Smartphone-based diagnostic for preeclampsia: an mHealth solution for administering the Congo Red Dot (CRD) test in settings with limited resources. Journal of the American Medical Informatics Association. 2016; ocv015. doi: 10.1093/jamia/ocv015
  76. Deniz E, Jonas SM, Griffin J, Hooper MC, Choma MA, Khokha MK. OCT imaging of craniofacial anatomy in xenopus embryos. In: Proc. SPIE 9716, Optical Methods in Developmental Biology IV. SPIE Photonics West BioS. San Francisco, CA, USA: SPIE; 2016. p. 97160F.
  77. 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
  78. 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
  79. 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
  80. 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.
  81. 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.
  82. 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
  83. 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
  84. Jonas SM, Sirazitdinova E, Lensen J, Kochanov D, Mayzek H, de Heus T, Houben R, Slijp H, Deserno TM. IMAGO: Image-guided navigation for visually impaired people. Journal of Ambient Intelligence and Smart Environments. 2015; 7(5): 679-692. doi: 10.3233/AIS-150334
  85. Jonas SM, Deserno TM. Mobile imaging and analytics for biomedical data. In: Reddy CK, Aggarwal CC, editors. Healthcare data analytics. CRC Press; 2015. Available from: https://books.google.de/books?hl=en&lr=&id=Iun5CQAAQBAJ&oi=fnd&pg=PP1&dq=Mobile+imaging+and+analytics+for+biomedical+data+jonas+deserno&ots=lGL3kX5HxK&sig=Xc6vsGTAHCRfnR4yC2vtfQxBufc
  86. Huang BK, Gamm UA, Jonas S, Khokha MK, Choma MA. Quantitative optical coherence tomography imaging of intermediate flow defect phenotypes in ciliary physiology and pathophysiology. Journal of Biomedical Optics. 2015; 20(3): 030502-030502. doi: 10.1117/1.JBO.20.3.030502
  87. Bitsch Link JÁ, Ramos R, Severijns C, Wehrle K. Towards bringing EEG research and diagnostics out of the lab. In: pHealth 2015: 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health. pHealth 2015: 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health. Amsterdam, The Netherlands: IOS Press BV; 2015. p. 185-191.
  88. Bitsch JÁ, Ramos R, Ix T, Ferrer-Cheng PG, Wehrle K. Psychologist in a Pocket: Towards depression screening in mobile phones. In: pHealth 2015: 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health. pHealth 2015: 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health. Amsterdam, The Netherlands: IOS Press BV; 2015. p. 153-160.
  89. 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
  90. 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
  91. 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
  92. Jonas S, Hannig A, Spreckelsen C, Deserno TM. Wearable technology as a booster of clinical care. In: SPIE Medical Imaging. Orlando, FL, USA: International Society for Optics and Photonics; 2014. p. 90390F-90390F. Available from: http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1851999
  93. Haak D, Samsel C, Gehlen J, Jonas S, Deserno TM. Simplifying Electronic Data Capture in Clinical Trials: Workflow Embedded Image and Biosignal File Integration and Analysis via Web Services. Journal of Digital Imaging. 2014; 27(5): 571-580. doi: 10.1007/s10278-014-9694-z
  94. Jonas S, Zhou E, Deniz E, Huang B, Chandrasekera K, Bhattacharya D, Wu Y, Fan R, Deserno TM, Khokha MK, Choma MA. A novel approach to quantifying ciliary physiology: microfluidic mixing driven by a ciliated biological surface. Lab on a Chip. 2013; 13(21): 4160-4163. doi: 10.1039/C3LC50571E
  95. Hannig A, Kuth N, Özman M, Jonas S, Spreckelsen C. eMedOffice: A web-based collaborative serious game for teaching optimal design of a medical practice. BMC Medical Education. 2012; 12(1): 104. doi: 10.1186/1472-6920-12-104
  96. Deniz E, Jonas S, Khokha M, Choma MA. Endogenous contrast blood flow imaging in embryonic hearts using hemoglobin contrast subtraction angiography. Optics Letters. 2012; 37(14): 2979. doi: 10.1364/OL.37.002979
  97. Jonas S, Bhattacharya D, Khokha MK, Choma MA. Microfluidic characterization of cilia-driven fluid flow using optical coherence tomography-based particle tracking velocimetry. Biomedical Optics Express. 2011; 2(7): 2022. doi: 10.1364/BOE.2.002022
  98. .
  99. 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. Available from: https://ebooks.iospress.nl/doi/10.3233/SHTI230472
  100. Buhimschi I, Buhimschi CS, Choma M, Tagare H, Jonas SM. METHODS AND COMPOSITIONS FOR DETECTING MISFOLDED PROTEINS. Available from: http://www.freepatentsonline.com/y2015/0293115.html

Letzte Aktualisierung: 2025-09-28 14:02