@article{ChromikKirstenHerdicketal.2022,
  author    = {Chromik, Jonas and Kirsten, Kristina and Herdick, Arne and Kappattanavar, Arpita Mallikarjuna and Arnrich, Bert},
  title     = {SensorHub},
  series = {Sensors},
  volume    = {22},
  journal   = {Sensors},
  number    = {1},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s22010408},
  pages     = {18},
  year      = {2022},
  abstract  = {Observational studies are an important tool for determining whether the findings from controlled experiments can be transferred into scenarios that are closer to subjects' real-life circumstances. A rigorous approach to observational studies involves collecting data from different sensors to comprehensively capture the situation of the subject. However, this leads to technical difficulties especially if the sensors are from different manufacturers, as multiple data collection tools have to run simultaneously. We present SensorHub, a system that can collect data from various wearable devices from different manufacturers, such as inertial measurement units, portable electrocardiographs, portable electroencephalographs, portable photoplethysmographs, and sensors for electrodermal activity. Additionally, our tool offers the possibility to include ecological momentary assessments (EMAs) in studies. Hence, SensorHub enables multimodal sensor data collection under real-world conditions and allows direct user feedback to be collected through questionnaires, enabling studies at home. In a first study with 11 participants, we successfully used SensorHub to record multiple signals with different devices and collected additional information with the help of EMAs. In addition, we evaluated SensorHub's technical capabilities in several trials with up to 21 participants recording simultaneously using multiple sensors with sampling frequencies as high as 1000 Hz. We could show that although there is a theoretical limitation to the transmissible data rate, in practice this limitation is not an issue and data loss is rare. We conclude that with modern communication protocols and with the increasingly powerful smartphones and wearables, a system like our SensorHub establishes an interoperability framework to adequately combine consumer-grade sensing hardware which enables observational studies in real life.},
  language  = {en}
}
@misc{KonigorskiWernickeSlosareketal.2022,
  author    = {Konigorski, Stefan and Wernicke, Sarah and Slosarek, Tamara and Zenner, Alexander M. and Strelow, Nils and Ruether, Darius F. and Henschel, Florian and Manaswini, Manisha and Pottb{\"a}cker, Fabian and Edelman, Jonathan A. and Owoyele, Babajide and Danieletto, Matteo and Golden, Eddye and Zweig, Micol and Nadkarni, Girish N. and B{\"o}ttinger, Erwin},
  title     = {StudyU: a platform for designing and conducting innovative digital N-of-1 trials},
  series = {Journal of medical internet research},
  volume    = {24},
  journal   = {Journal of medical internet research},
  number    = {7},
  publisher = {Healthcare World},
  address   = {Richmond, Va.},
  issn      = {1439-4456},
  doi       = {10.2196/35884},
  pages     = {12},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@article{LewkowiczWohlbrandtBoettinger2022,
  author    = {Lewkowicz, Daniel and Wohlbrandt, Attila M. and B{\"o}ttinger, Erwin},
  title     = {Digital therapeutic care apps with decision-support interventions for people with low back pain in Germany},
  series = {JMIR mhealth and uhealth},
  volume    = {10},
  journal   = {JMIR mhealth and uhealth},
  number    = {2},
  publisher = {JMIR Publications},
  address   = {Toronto},
  issn      = {2291-5222},
  doi       = {10.2196/35042},
  pages     = {17},
  year      = {2022},
  abstract  = {Background: Digital therapeutic care apps provide a new effective and scalable approach for people with nonspecific low back pain (LBP). Digital therapeutic care apps are also driven by personalized decision-support interventions that support the user in self-managing LBP, and may induce prolonged behavior change to reduce the frequency and intensity of pain episodes. However, these therapeutic apps are associated with high attrition rates, and the initial prescription cost is higher than that of face-to-face physiotherapy. In Germany, digital therapeutic care apps are now being reimbursed by statutory health insurance; however, price targets and cost-driving factors for the formation of the reimbursement rate remain unexplored. Objective: The aim of this study was to evaluate the cost-effectiveness of a digital therapeutic care app compared to treatment as usual (TAU) in Germany. We further aimed to explore under which circumstances the reimbursement rate could be modified to consider value-based pricing. Methods: We developed a state-transition Markov model based on a best-practice analysis of prior LBP-related decision-analytic models, and evaluated the cost utility of a digital therapeutic care app compared to TAU in Germany. Based on a 3-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALYs) for people with nonacute LBP from the societal perspective. In the deterministic sensitivity and scenario analyses, we focused on diverging attrition rates and app cost to assess our model's robustness and conditions for changing the reimbursement rate. All costs are reported in Euro (euro1=US \$1.12). Results: Our base case results indicated that the digital therapeutic care strategy led to an incremental cost of euro121.59, but also generated 0.0221 additional QALYs compared to the TAU strategy, with an estimated incremental cost-effectiveness ratio (ICER) of euro5486 per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of digital therapeutic care to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remained unaffected and thus supported the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influenced the economic outcome. Reducing the cost of the app to euro99 per 3 months or decreasing the app's attrition rate resulted in digital therapeutic care being significantly less costly with more generated QALYs, and is thus considered to be the dominant strategy over TAU. Conclusions: The current reimbursement rate for a digital therapeutic care app in the statutory health insurance can be considered a cost-effective measure compared to TAU. The app's attrition rate and effect on the patient's prolonged behavior change essentially influence the settlement of an appropriate reimbursement rate. Future value-based pricing targets should focus on additional outcome parameters besides pain intensity and functional disability by including attrition rates and the app's long-term effect on quality of life.},
  language  = {en}
}
@article{SchachnerGrossHasletal.2021,
  author    = {Schachner, Theresa and Gross, Christoph and Hasl, Andrea and Wangenheim, Florian von and Kowatsch, Tobias},
  title     = {Deliberative and paternalistic interaction styles for conversational agents in digital health},
  series = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR},
  volume    = {23},
  journal   = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR},
  number    = {1},
  publisher = {Healthcare World},
  address   = {Richmond, Va.},
  issn      = {1438-8871},
  doi       = {10.2196/22919},
  pages     = {13},
  year      = {2021},
  abstract  = {Background: Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users. Objective: The objective of this study was to develop an approach to reproducibly induce 2 specific interaction styles into CA-patient dialogs and subsequently test and validate them in a chronic health care context. Methods: On the basis of the Roter Interaction Analysis System and iterative evaluations by scientific experts and medical health care professionals, we identified 10 communication components that characterize the 2 developed interaction styles: deliberative and paternalistic interaction styles. These communication components were used to develop 2 CA variations, each representing one of the 2 interaction styles. We assessed them in a web-based between-subject experiment. The participants were asked to put themselves in the position of a patient with chronic obstructive pulmonary disease. These participants were randomly assigned to interact with one of the 2 CAs and subsequently asked to identify the respective interaction style. Chi-square test was used to assess the correct identification of the CA-patient interaction style. Results: A total of 88 individuals (42/88, 48\% female; mean age 31.5 years, SD 10.1 years) fulfilled the inclusion criteria and participated in the web-based experiment. The participants in both the paternalistic and deliberative conditions correctly identified the underlying interaction styles of the CAs in more than 80\% of the assessments (X-1(,8)8(2)=38.2; P<.001; phi coefficient r(phi)=0.68). The validation of the procedure was hence successful. Conclusions: We developed an approach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.},
  language  = {en}
}
@misc{KonigorskiWernickeSlosareketal.2021,
  author    = {Konigorski, Stefan and Wernicke, Sarah and Slosarek, Tamara and Zenner, Alexander Maximilian and Strelow, Nils and Ruether, Darius Ferenc and Henschel, Florian and Manaswini, Manisha and Pottb{\"a}cker, Fabian and Edelman, Jonathan Antonio and Owoyele, Babajide and Danieletto, Matteo and Golden, Eddye and Zweig, Micol and Nadkarni, Girish N. and Bottinger, Erwin},
  title     = {StudyU: A Platform for Designing and Conducting Innovative Digital N-of-1 Trials},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  number    = {12},
  doi       = {10.25932/publishup-58037},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-580370},
  pages     = {12},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@article{KonigorskiWernickeSlosareketal.2021,
  author    = {Konigorski, Stefan and Wernicke, Sarah and Slosarek, Tamara and Zenner, Alexander Maximilian and Strelow, Nils and Ruether, Darius Ferenc Ruether and Henschel, Florian and Manaswini, Manisha and Pottb{\"a}cker, Fabian and Edelman, Jonathan Antonio and Owoyele, Babajide and Danieletto, Matteo and Golden, Eddye and Zweig, Micol and Nadkarni, Girish N. and Bottinger, Erwin},
  title     = {StudyU: A Platform for Designing and Conducting Innovative Digital N-of-1 Trials},
  series = {Journal of Medical Internet Research},
  volume    = {24},
  journal   = {Journal of Medical Internet Research},
  edition   = {7},
  publisher = {JMIR Publications},
  address   = {Richmond, Virginia, USA},
  issn      = {1438-8871},
  doi       = {10.2196/35884},
  pages     = {12},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@misc{AlbertOwolabiGebeletal.2020,
  author    = {Albert, Justin Amadeus and Owolabi, Victor and Gebel, Arnd and Brahms, Clemens Markus and Granacher, Urs and Arnrich, Bert},
  title     = {Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard},
  series = {Postprints der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  journal   = {Postprints der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  number    = {3},
  doi       = {10.25932/publishup-48413},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-484130},
  pages     = {24},
  year      = {2020},
  abstract  = {Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.},
  language  = {en}
}
@article{AlbertOwolabiGebeletal.2020,
  author    = {Albert, Justin Amadeus and Owolabi, Victor and Gebel, Arnd and Brahms, Clemens Markus and Granacher, Urs and Arnrich, Bert},
  title     = {Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard},
  series = {Sensors},
  volume    = {20},
  journal   = {Sensors},
  number    = {18},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {1424-8220},
  doi       = {10.3390/s20185104},
  pages     = {22},
  year      = {2020},
  abstract  = {Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With this calibration, the spatial agreement of joint positions between the two Kinect cameras and the reference system was evaluated. In addition, we compared the accuracy of certain spatio-temporal gait parameters, i.e., step length, step time, step width, and stride time calculated from the Kinect data, with the gold standard system. Our results showed that the improved hardware and the motion tracking algorithm of the Azure Kinect camera led to a significantly higher accuracy of the spatial gait parameters than the predecessor Kinect v2, while no significant differences were found between the temporal parameters. Furthermore, we explain in detail how this experimental setup could be used to continuously monitor the progress during gait rehabilitation in older people.},
  language  = {en}
}
@article{SalzwedelRabeZahnetal.2018,
  author    = {Salzwedel, Annett and Rabe, Sophie and Zahn, Thomas and Neuwirth, Julia and Eichler, Sarah and Haubold, Kathrin and Wachholz, Anne and Reibis, Rona Katharina and V{\"o}ller, Heinz},
  title     = {Nutzerinteresse an mobilen digitalen Assistenzsystemen zur F{\"o}rderung k{\"o}rperlicher Aktivit{\"a}t bei Studierenden und Mitarbeitern einer Universit{\"a}t},
  series = {Gesundheitswesen},
  volume    = {80},
  journal   = {Gesundheitswesen},
  number    = {11},
  publisher = {Thieme},
  address   = {Stuttgart},
  issn      = {0941-3790},
  doi       = {10.1055/s-0043-103951},
  pages     = {1023 -- 1025},
  year      = {2018},
  abstract  = {Hintergrund Einem Großteil der Bev{\"o}lkerung gelingt es trotz ausreichenden Wissens um die protektiven Effekte nicht, ausreichende k{\"o}rperliche Aktivit{\"a}t in den Alltag zu integrieren. Digitale Assistenzsysteme k{\"o}nnten hierbei unterst{\"u}tzend eingesetzt werden. Dies setzt jedoch das Interesse potentieller Nutzer voraus. Methode In einer Online-Befragung wurden im Juni/Juli 2015 Mitarbeiter und Studierende der Universit{\"a}t Potsdam zum individuellen Ausmaß der sportlichen Aktivit{\"a}t, dem Interesse an elektronischer Trainingsunterst{\"u}tzung und weiteren Parametern befragt. Ergebnis 1217 Studierende und 485 Mitarbeiter (67,3 bzw. 67,5\% Frauen, 26±4,9 bzw. 42,7±11,7 Jahre) nahmen an der Studie teil. Die empfohlene sportliche Aktivit{\"a}t (≥3 Tage bzw. 150 min/Woche) wurde von 70,1\% der Mitarbeiter und 52,7\% der Studierenden nicht erreicht. Innerhalb dieser Gruppen zeigten 53,2\% (Studierende) bzw. 44,2\% (Mitarbeiter), unabh{\"a}ngig von Alter, Geschlecht, BMI bzw. Bildungsniveau, Interesse an einer elektronischen Trainingsunterst{\"u}tzung. Schlussfolgerung Auch in j{\"u}ngeren Bev{\"o}lkerungsgruppen mit hohem Bildungsniveau ist die Mehrzahl der Personen unzureichend k{\"o}rperlich aktiv. Ein Interesse an Trainingsunterst{\"u}tzung besteht in etwa der H{\"a}lfte dieser sportlich inaktiven Gruppe. Dies legt den Schluss nahe, dass der personalisierte Einsatz mobiler Assistenzsysteme f{\"u}r die positive Beeinflussung des Lebensstils zunehmend an Bedeutung gewinnen k{\"o}nnte.},
  language  = {de}
}