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Publications

2017

Bleser, G., Christmann, C.A., Taetz, B., Hoffmann, A., Steffen, D. and Miezal, M. (2017), Identification of Medically Relevant Application Scenarios for A Wearable Motion Analysis System, In Informatik, Workshop: Partizipatives Entwerfen soziotechnischer Systeme (accepted).
Abstract: This abstract presents the iterative and multi-perspective context of use analysis approach of the interdisciplinary junior research group wearHEALTH for identifying medically relevant application scenarios and required features for a motion analysis system based on inertial motion capture technology. Different iterations of one underlying process are described and discussed. The focus is on how all participating research disciplines as well as potential users in terms of healthcare providers can be involved into this process on equal footing.
BibTeX:
@inproceedings{Bleser2017a,
  author = {Bleser, Gabriele and Christmann, Corinna Anna and Taetz, Bertram and Hoffmann, Alexandra and Steffen, Daniel and Miezal, Markus},
  title = {Identification of Medically Relevant Application Scenarios for A Wearable Motion Analysis System},
  booktitle = {Informatik, Workshop: Partizipatives Entwerfen soziotechnischer Systeme (accepted)},
  year = {2017}
}
Bleser, G., Taetz, B., Miezal, M., Christmann, C.A., Steffen, D. and Regenspurger, K. (2017), Development of an Inertial Motion Capture System for Clinical Application - Potentials and challenges from the technology and application perspectives, Journal of Interactive Media.
Abstract: The ability to capture human motion based on wearable sensors has a wide range of applications, e.g., in healthcare, sports, well-being, and workflow analysis. This article focuses on the development of an online-capable system for accurately capturing joint kinematics based on inertial measurement units (IMUs) and its clinical application, with a focus on locomotion analysis for rehabilitation. The article approaches the topic from the technology and application perspectives and fuses both points of view. It presents, in a self-contained way, previous results from three studies as well as new results concerning the technological development of the system. It also correlates these with new results from qualitative expert interviews with medical practitioners and movement scientists. The interviews were conducted for the purpose of identifying relevant application scenarios and requirements for the technology used. As a result, the potentials of the system for the different identified application scenarios are discussed and necessary next steps are deduced from this analysis.
BibTeX:
@article{Bleser2017b,
  author = {Bleser, Gabriele and Taetz, Bertram and Miezal, Markus and Christmann, Corinna Anna and Steffen, Daniel and Regenspurger, Katja},
  title = {Development of an Inertial Motion Capture System for Clinical Application - Potentials and challenges from the technology and application perspectives},
  journal = {Journal of Interactive Media},
  year = {2017},
  volume = {16},
  number = {2}
}
Christmann, C.A., Hoffmann, A. and Bleser, G. (2017), Stress management apps with regard to emotion-focused coping and behavior change techniques: a content analysis, JMIR Mhealth and Uhealth.
Abstract: BACKGROUND: Chronic stress has been shown to be associated with disease. This link is not only direct but also indirect through harmful health behavior such as smoking or changing eating habits. The recent mHealth trend offers a new and promising approach to support the adoption and maintenance of appropriate stress management techniques. However, only few studies have dealt with the inclusion of evidence-based content within stress management apps for mobile phones.

OBJECTIVE:
The aim of this study was to evaluate stress management apps on the basis of a new taxonomy of effective emotion-focused stress management techniques and an established taxonomy of behavior change techniques.

METHODS:
Two trained and independent raters evaluated 62 free apps found in Google Play with regard to 26 behavior change and 15 emotion-focused stress management techniques in October 2015.

RESULTS:
The apps included an average of 4.3 behavior change techniques (SD 4.2) and 2.8 emotion-focused stress management techniques (SD 2.6). The behavior change technique score and stress management technique score were highly correlated (r=.82, P=.01).

CONCLUSIONS:
The broad variation of different stress management strategies found in this sample of apps goes in line with those found in conventional stress management interventions and self-help literature. Moreover, this study provided a first step toward more detailed and standardized taxonomies, which can be used to investigate evidence-based content in stress management interventions and enable greater comparability between different intervention types.

BibTeX:
@article{Christmann2017a,
  author = {Christmann, Corinna Anna and Hoffmann, Alexandra and Bleser, Gabriele},
  title = {Stress management apps with regard to emotion-focused coping and behavior change techniques: a content analysis},
  journal = {JMIR Mhealth and Uhealth},
  year = {2017},
  volume = {5},
  number = {2},
  pages = {e22},
  url = {http://mhealth.jmir.org/2017/2/e22/}
}
Christmann, C.A., Zolynski, G., Hoffmann, A. and Bleser, G. (2017), Effective visualization of long term health data to support behavior change, In HCI International (in press).
Abstract: The reflective stage, which is crucial for behavior change, can be facilitated with suitable visualizations that allow users to answer specific questions with regard to their health data. To date, effective visualizations which combine time series data and the appraisal of this data in one chart are, however, rare. To close this gap in research, twenty participants compared two alternative long-term visualizations of health behavior: an accumulated bar chart and a point chart which both include appraisals of the underlying health data based on current recommendations of leading health organizations, such as the World Health Organization or the European Food Information Council. Participants answered three types of question (progress over time, correlations between different health behaviors, and health consciousness). The sequence of visualization for the underlying data sets was cross balanced over participants. The accumulated bar chart resulted in more trials in which participants were unable to answer. In some cases, this type of visualization also resulted in biased interpretations with regard to progress over time and health consciousness. Summarizing, we recommend the point chart, in which the background is colored according to the recommendation of the respective health behavior. Both types of visualization are, however, not optimal for the identification of correlations.
BibTeX:
@inproceedings{Christmann2017b,
  author = {Christmann, Corinna Anna and Zolynski, Gregor and Hoffmann, Alexandra and Bleser, Gabriele},
  title = {Effective visualization of long term health data to support behavior change},
  booktitle = {HCI International (in press)},
  year = {2017}
}
Hermanny, K., Christmann, C., Bleser, G., Martens, A. and Dogangün, A. (2017), Bewertung ausgewählter Studiendesigns zur Untersuchung persuasiver Selbstmonitoringsysteme, In 63. Kongress der Gesellschaft für Arbeitswissenschaft: Soziotechnische Gestaltung des digitalen Wandels – kreativ, innovativ, sinnhaft.
Abstract: Im Rahmen der Digitalisierung von Gesundheitsprozessen wird eine personalisierte Analyse des Gesundheitszustandes, des subjektiven Wohlbefindens und der Kontextparameter zunehmend durch mobile Tagebücher, Smartphone-gestützte Sensorik und am Körper getragene Computer (Wearables) ermöglicht. Für den erfolgreichen persuasiven Einsatz des persönlichen Monitorings ist jedoch eine arbeitswissenschaftliche Betrachtung nötig, die neue methodische Herangehensweisen, sowie Anpassungen bei gängigen Evaluationsmethoden erfordert. Dieser Beitrag wird daher auf Basis der Forschung dreier interdisziplinärer Projektteams eine Auswahl von gängigen (vergleichende Marktanalyse, Fokusgruppe, Mixed-Methods Design) und bisher weniger gebräuchlichen Studiendesigns (Felduntersuchung ohne Probandenkontakt) für arbeitswissenschaftliche Untersuchungen von persuasiven Selbst-Monitoring-Systemen vorstellen und diskutieren um damit eine Hilfestellung und Entscheidungsgrundlage für die Methodenauswahl zu liefern.
BibTeX:
@inproceedings{Hermanny2017,
  author = {Hermanny, Katja and Christmann, Corinna and Bleser, Gabriele and Martens, Alexander and Dogangün, Aysegül},
  title = {Bewertung ausgewählter Studiendesigns zur Untersuchung persuasiver Selbstmonitoringsysteme},
  booktitle = {63. Kongress der Gesellschaft für Arbeitswissenschaft: Soziotechnische Gestaltung des digitalen Wandels – kreativ, innovativ, sinnhaft},
  year = {2017}
}
Hoffmann, A., Christmann, C.A. and Bleser, G. (2017), Gamification in Stress Management Apps: A Critical App Review, JMIR Serious Games.
Abstract: Background: In today’s society, stress is more and more often a cause of disease. This makes stress management an important target of behavior change programs. Gamification has been suggested as one way to support health behavior change. However, it remains unclear to which extend available gamification techniques are integrated in stress management apps, and if their occurrence is linked to the use of elements from behavior change theory.
Objective: The aim of this study was to investigate the use of gamification techniques in stress management apps and the co-occurrence of these techniques with evidence-based stress management methods and behavior change techniques.
Methods: A total of 62 stress management apps from the Google Play Store were reviewed on their inclusion of 17 gamification techniques, 15 stress management methods, and 26 behavior change techniques. For this purpose, an extended taxonomy of gamification techniques was constructed and applied by 2 trained, independent raters.
Results: Interrater-reliability was high, with agreement coefficient (AC)=.97. Results show an average of 0.5 gamification techniques for the tested apps and reveal no correlations between the use of gamification techniques and behavior change techniques (r=.17, P=.20), or stress management methods (r=.14, P=.26).
Conclusions: This leads to the conclusion that designers of stress management apps do not use gamification techniques to influence the user’s behaviors and reactions. Moreover, app designers do not exploit the potential of combining gamification techniques with behavior change theory.
BibTeX:
@article{Hoffmann2017a,
  author = {Hoffmann, Alexandra and Christmann, Corinna Anna and Bleser, Gabriele},
  title = {Gamification in Stress Management Apps: A Critical App Review},
  journal = {JMIR Serious Games},
  year = {2017},
  volume = {5},
  number = {2},
  pages = {e13},
  url = {http://games.jmir.org/2017/2/e13/}
}
Hoffmann, A., Christmann, C.A., Bleser, G. and Lachmann, T. (2017), Evaluating the Reliability and Validity of the Wearable EEG-System Muse, In Tagung experimentell arbeitender Psychologen (TeaP).
Abstract: Wearable EEG systems are small wireless devices which can e.g., be used in a wide range of field studies and brain-computer-interfaces outside the laboratory. They are increasingly used in research because they are easy to transport, can be applied in a broad variety of settings and they are much cheaper than conventional wired EEG systems. However, there is still a lack of knowledge about the validity and reliability of wearable EEG systems.
Muse, for instance, is a wearable EEG system often used by researchers to measure and classify alpha activity even though there exists no published independent proof of the device’s validity and reliability.
Therefore, the recent study aimed to test both these criteria. A total of 20 participants took part in two recording sessions, with a 30 minutes break between sessions. The EEG signal was recorded simultaneously by the wearable device and by the Brain Products gel-based Anti-Champ system. Each session consisted of four conditions, which were performed in randomized order. Conditions included an eyes open and an eyes closed scenario to induce changes in the relative extent of alpha and beta activity due to the alpha blockage. Moreover, participants performed a breath-counting relaxation exercise aimed at eliciting enhanced alpha activity and a brain storming exercise aimed at eliciting enhanced beta activity.
BibTeX:
@conference{Hoffmann2017b,
  author = {Hoffmann, Alexandra and Christmann, Corinna Anna and Bleser, Gabriele and Lachmann, Thomas},
  title = {Evaluating the Reliability and Validity of the Wearable EEG-System Muse},
  booktitle = {Tagung experimentell arbeitender Psychologen (TeaP)},
  year = {2017}
}
Miezal, M., Taetz, B. and Bleser, G. (2017), Real-time inertial lower body kinematics and ground contact estimation at anatomical foot points for agile human locomotion, In International Conference on Robotics and Automation.
Abstract: The ability to accurately capture locomotion is relevant in various use cases, in particular in the sports and health area. With the major goal of providing a measurement system that can deliver different types of relevant information (3D body segment kinematics, spatiotemporal locomotion parameters, and locomotion patterns) in-field and in real-time, we propose a novel probabilistic (single-plane) ground contact estimation method, using four contact points defined through a biomechanical foot model, and integrate this into an existing inertial motion capturing method. The resulting method is quantitatively evaluated on simulated and real IMU data in comparison to an optical motion capture system on walking, running, and jumping sequences. The results show its ability to maintain a good average 3D kinematics estimation error on low- and high-acceleration locomotion, whereas many previous accuracy studies restrict themselves to movements with low to moderate global accelerations, such as upper body activities or slow locomotion. Moreover, a qualitative evaluation of the estimated ground contact probabilities demonstrates the method's ability to also provide consistent information also for deriving spatiotemporal locomotion parameters as well as locomotion patterns (e.g. over-pronation/-supination) simultaneously with the 3D kinematics.
BibTeX:
@inproceedings{Miezal2017a,
  author = {Miezal, Markus and Taetz, Bertram and Bleser, Gabriele},
  title = {Real-time inertial lower body kinematics and ground contact estimation at anatomical foot points for agile human locomotion},
  booktitle = {International Conference on Robotics and Automation},
  year = {2017}
}
Steffen, D., Christmann, C.A. and Bleser, G. (2017), jumpBALL - Ein mobiles Exergame für die Thromboseprophylaxe, In Mensch und Computer 2017 - Tagungsband.
Abstract: Über 37.000 Patienten wurden 2015 bundesweit in Krankenhäusern unter der Hauptdiagnose I80 (Thrombose, Phlebitis und Thrombophlebitis) behandelt. Bewegungsübungen, wie beispielsweise die Muskel-Venen-Pumpe, werden als allgemeine Basismaßnahmen zur Thromboseprophylaxe für alle Risikogruppen empfohlen. Allerdings können solche repetitiven Übungen schnell monoton und langweilig werden, wodurch die Motivation des Patienten sinkt und die Therapietreue gefährdet wird. Das mobile Exergame jumpBALL adressiert die zuvor beschriebene Problematik und unterstützt und motiviert bei der Durchführung der Muskel-Venen-Pumpe. jumpBALL verwendet zwei drahtlose, inertiale Messeinheiten zur Erfassung der Fußbewegungen und zur Interaktion mit dem Spiel, welches auf einem Tablet PC läuft. jumpBALL kann sowohl im stationären als auch im post-stationären Bereich zur Thromboseprophylaxe eingesetzt werden. Anhand einer experimentellen Benutzerstudie mit Studierenden und Angestellten (N = 40) konnte gezeigt werden, dass sich durch den Einsatz von jumpBALL die Wiederholungshäufigkeit der Muskel-Venen-Pumpe und die Übungsdauer im Vergleich zu einer Kontrollversion der App, bei der die Anzahl der Wiederholungen ohne spielerische Einbettung lediglich gezählt wird, signifikant steigern lässt.
BibTeX:
@inproceedings{Steffen2017,
  author = {Steffen, Daniel and Christmann, Corinna Anna and Bleser, Gabriele},
  editor = {Burghardt, Manuel AND Wimmer, Raphael AND Wolff, Christian AND Womser-Hacker, Christa},
  title = {jumpBALL - Ein mobiles Exergame für die Thromboseprophylaxe},
  booktitle = {Mensch und Computer 2017 - Tagungsband},
  publisher = {Gesellschaft für Informatik e.V.},
  year = {2017},
  pages = {27-36},
  url = {http://dx.doi.org/10.18420/muc2017-mci-0198},
  doi = {10.18420/muc2017-mci-0198}
}
Steffen, D., Christmann, C.A., Teufl, W. and Bleser, G. (2017), No Game, No Pain? Towards a Mobile Exergame for Rehabilitation, In CHI PLAY'17 Extended Abstracts.
Abstract: Exergames are considered useful to facilitate specific exercises in rehabilitation. This context, however, raises questions regarding pain management: How do we have to consider pain sensations in game design? Beside some rules to avoid overexertion, these important aspects have rather been neglected in prior research.
Within this contribution we address these questions and present an example of a mobile exergame for thrombosis prophylaxis. In a pilot study, 40 healthy young adults rated their subjective pain sensation on a numeric rating scale before and after having completed one of two versions of the exergame (counting of exercise repetitions only vs. controlling a beach ball through exercise repetitions). Beside possible effects of gender and level of fitness on pain reports, we focus on limitations that should be addressed in future research.
BibTeX:
@inproceedings{Steffen2017a,
  author = {Daniel Steffen and Corinna Anna Christmann and Wolfgang Teufl and Gabriele Bleser},
  title = {No Game, No Pain? Towards a Mobile Exergame for Rehabilitation},
  booktitle = {CHI PLAY'17 Extended Abstracts},
  year = {2017},
  doi = {10.1145/3130859.3131310}
}
Taetz, B., Miezal, M. and Bleser, G. (2017), Modell-basierte Algorithmen zur Rekonstruktion kinematischer Bewegungsparameter aus IMU-Netzwerken, In 23. Sportwissenschaftlicher Hochschultag der dvs. Arbeitskreis: Inertialsensorik zur Bewegungsanalyse in Sport, Rehabilitation und Gesundheit (accepted).
Abstract: Herausforderungen inertialer Bewegungserfassung:
Inertiale Messeinheiten (IMUs) erlauben die Schätzung kinematischer, räumlich-zeitlicher sowie kinetischer Bewegungsvariablen außerhalb des Labors. Im Gegensatz zu einem optischen System, mit dem die Positionen präzise am Körper platzierter Marker direkt vermessen und zur Bestimmung von Gelenkzentren und -winkeln verwendet werden können, basiert die inertiale Bewegungserfassung meist auf einem angenommenen biomechanischen Modell, dessen Bewegungsfreiheitsgrade aus den verrauschten IMU-Messungen durch einen stochastischen Sensorfusionsalgorithmus geschätzt werden. Neben einem personalisierten Modell ist für eine valide Rekonstruktion auch Wissen über die Lage der IMUs relativ zu den entsprechenden Segmenten (IMU-zu-Segment-Kalibrierungen) notwendig. Die Kalibrierungen werden üblicherweise durch funktionale Bewegungen oder statische Posen berechnet, was bei einer unpräzisen Ausführung zu Fehlern führt. Magnetische Störungen stellen eine weitere Fehlerquelle dar. Außerdem besteht eine große Herausforderung in einer langzeitstabilen globalen Translationsschätzung.

Lösungsansätze:
In (Taetz, Bleser & Miezal, 2016) sind Vorarbeiten für ein selbstkalibrierendes System beschrieben, welches IMU-zu-Segment Kalibrierparameter und Segmentorientierungen gleichzeitig schätzt. Das Verfahren wird aktuell auf den gesamten unteren Körper zur Schätzung der Kalibrierparameter und kinematischen Bewegungsvariablen auf Basis beliebiger Bewegungen (z.B. weniger Schritte) erweitert. Weitere Forschungsarbeiten beziehen sich auf eine magnetometerfreie Gelenkswinkelschätzung auf Basis von (Miezal, Taetz & Bleser, 2016) sowie eine globale Translationsschätzung durch Nutzung ermittelter Bodenkontakte (Miezal, Taetz & Bleser, 2017). Letztere erlauben auch Rückschlüsse auf räumlich-zeitliche Bewegungsparameter sowie Abrollmuster. Aktuelle Arbeiten beziehen sich außerdem auf die Extraktion personalisierter anthropometrischer Daten aus Kameradaten mit Tiefeninformationen, auf die automatische IMU-zu-Segment-Zuordnung durch Verfahren des maschinellen Lernens sowie auf die Rekonstruktion von Bodenreaktionskräften und Muskelaktivierungen auf Basis der geschätzten Kinematik und eines komplexeren Muskel-Skelett-Modells.

BibTeX:
@conference{Taetz2017a,
  author = {Taetz, Betram and Miezal, Markus and Bleser, Gabriele},
  title = {Modell-basierte Algorithmen zur Rekonstruktion kinematischer Bewegungsparameter aus IMU-Netzwerken},
  booktitle = {23. Sportwissenschaftlicher Hochschultag der dvs. Arbeitskreis: Inertialsensorik zur Bewegungsanalyse in Sport, Rehabilitation und Gesundheit (accepted)},
  year = {2017}
}

2016

Miezal, M., Taetz, B. and Bleser, G. (2016), On inertial body tracking in the presence of model calibration errors, MDPI Sensors.
Abstract: In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods, based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments - the IMU-to-segment calibrations, subsequently called I2S calibrations - to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and segment length errors in the tested ranges. Errors in the I2S orientations were, however, linearly propagated into the estimated segment orientations. In the absence of magnetic disturbances, severe model calibration errors and fast motion changes, the newly developed IMU centered EKF-based method yielded comparable results with lower computational complexity.
BibTeX:
@article{Miezal2016,
  author = {Miezal, Markus and Taetz, Bertram and Bleser, Gabriele},
  title = {On inertial body tracking in the presence of model calibration errors},
  journal = {MDPI Sensors},
  year = {2016},
  volume = {16},
  number = {7},
  pages = {1132},
  url = {http://www.mdpi.com/1424-8220/16/7/1132}
}
Taetz, B., Bleser, G. and Miezal, M. (2016), Towards self-calibrating inertial body motion capture, In International Conference on Information Fusion.
Abstract: This paper presents a novel online capable method for simultaneous estimation of human motion in terms of segment orientations and positions along with sensor-to-segment calibration parameters from inertial sensors attached to the body. In order to solve this ill-posed estimation problem, state-of-the-art motion, measurement and biomechanical models are combined with new stochastic equations and priors. These are based on the kinematics of multi-body systems, anatomical and body shape information, as well as, parameter properties for regularisation. This leads to a constrained weighted least squares problem that is solved in a sliding window fashion. Magnetometer information is currently only used for initialisation, while the estimation itself works without magnetometers. The method was tested on simulated, as well as, on real data, captured from a lower body configuration.
BibTeX:
@inproceedings{Taetz2016,
  author = {Taetz, Bertram and Bleser, Gabriele and Miezal, Markus},
  title = {Towards self-calibrating inertial body motion capture},
  booktitle = {International Conference on Information Fusion},
  year = {2016},
  pages = {1751-1759}
}

2015

Taetz, B., Miezal, M. and Bleser, G. (2015), From traditional to interdisciplinary approaches for inertial body motion capture, In International Conference on Biomechanics in Sports, Applied Session: Physical Activity Monitoring.
Abstract: Inertial motion capture (mocap) is a widespread technology for capturing human motion outside the lab, e.g., for applications in sports, ergonomics, rehabilitation and personal fitness. Even though mature systems are commercially available, inertial mocap is still a subject of research due to a number of limitations: besides measurement errors and sparsity, also simplified body models and calibration routines, soft tissue artefacts and varying body shapes lead to limited precision and robustness compared to optical gold standard systems. The goal of the research group wearHEALTH at the TU Kaiserslautern is to tackle these challenges by bringing together ideas and approaches from different disciplines including biomechanics, sensor fusion, computer vision and (optimal control) simulation. In this talk, we will present an overview of our approaches and applications, starting from the more traditional ones.
BibTeX:
@inproceedings{Taetz2015,
  author = {Bertram Taetz and Markus Miezal and Gabriele Bleser},
  title = {From traditional to interdisciplinary approaches for inertial body motion capture},
  booktitle = {International Conference on Biomechanics in Sports, Applied Session: Physical Activity Monitoring},
  year = {2015}
}