@inproceedings{fischer_auditory_2016, address = {Segovia, Spain}, series = {Biosystems \& {Biorobotics}}, title = {An {Auditory} {Feedback} {System} in {Use} with {People} {Aged} +50 {Years}: {Compliance} and {Modifications} in {Gait} {Pattern}}, copyright = {©2017 Springer International Publishing AG}, isbn = {978-3-319-46668-2 978-3-319-46669-9}, shorttitle = {An {Auditory} {Feedback} {System} in {Use} with {People} {Aged} +50 {Years}}, url = {http://link.springer.com/chapter/10.1007/978-3-319-46669-9_143}, doi = {10/gnt2tg}, abstract = {Aging leads to gait impairments, which increases the risk for falls. In this study the impact of the auditory feedback system SONIGait on gait parameters in elderly persons was investigated. Twenty-one participants walked at self-selected speed with four variations of real-time auditory feedback of their plantar pressure. Repeated measures ANOVA was utilized to determine changes in time-distance parameters between walking without feedback and four feedback variations. After walking, they completed a questionnaire about their appraisal of the SONIGait system and the four different feedback modalities. There was a significant reduction in gait velocity (0.142 ± 0.04 m/s; p {\textless} 0.001) and prolongation of step time (0.02 ± 0.005 s; p {\textless} 0.001) during walking with SONIGait. No significant preference for any of the feedback variations was observed. Most participants evaluated the system SONIGait positively. Thus, real-time auditory feedback may be used in gait rehabilitation and may support an older person’s gait stability.}, language = {en}, urldate = {2016-10-19}, booktitle = {Converging {Clinical} and {Engineering} {Research} on {Neurorehabilitation} {II}}, publisher = {Springer International Publishing}, author = {Fischer, Theresa and Kiselka, Anita and Dlapka, Ronald and Doppler, Jakob and Iber, Michael and Gradl, Christian and Gorgas, Anna-Maria and Siragy, Tarique and Horsak, Brian}, editor = {Ibáñez, Jaime and González-Vargas, José and Azorín, José María and Akay, Metin and Pons, José Luis}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Departement Soziales, Department Gesundheit, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, SP IGW Health Promotion \& Healthy Ageing, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait}, pages = {881--885}, } @article{wagner_kavagait_2018, title = {{KAVAGait}: {Knowledge}-{Assisted} {Visual} {Analytics} for {Clinical} {Gait} {Analysis}}, volume = {25}, url = {https://doi.org/10.1109/TVCG.2017.2785271}, doi = {10/ghppzn}, abstract = {In 2014, more than 10 million people in the US were affected by an ambulatory disability. Thus, gait rehabilitation is a crucial part of health care systems. The quantification of human locomotion enables clinicians to describe and analyze a patient’s gait performance in detail and allows them to base clinical decisions on objective data. These assessments generate a vast amount of complex data which need to be interpreted in a short time period. We conducted a design study in cooperation with gait analysis experts to develop a novel Knowledge-Assisted Visual Analytics solution for clinical Gait analysis (KAVAGait). KAVAGait allows the clinician to store and inspect complex data derived during clinical gait analysis. The system incorporates innovative and interactive visual interface concepts, which were developed based on the needs of clinicians. Additionally, an explicit knowledge store (EKS) allows externalization and storage of implicit knowledge from clinicians. It makes this information available for others, supporting the process of data inspection and clinical decision making. We validated our system by conducting expert reviews, a user study, and a case study. Results suggest that KAVAGait is able to support a clinician during clinical practice by visualizing complex gait data and providing knowledge of other clinicians.}, number = {3}, journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)}, author = {Wagner, Markus and Slijepcevic, Djordje and Horsak, Brian and Rind, Alexander and Zeppelzauer, Matthias and Aigner, Wolfgang}, year = {2018}, note = {Projekt: KAVA-Time Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Design Study, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Healthcare, Human Gait Analysis, Human-Computer Interaction, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Visual analytics, Wiss. Beitrag, best, best-bhorsak, best-lbaigner, best-lbwagnerm, best-mzeppelzauer, information visualization, knowledge generation, peer-reviewed}, pages = {1528--1542}, } @article{slijepcevic_automatic_2018, title = {Automatic {Classification} of {Functional} {Gait} {Disorders}}, volume = {5}, issn = {2168-2194}, url = {https://arxiv.org/abs/1712.06405}, doi = {10/ghz24w}, number = {22}, urldate = {2017-12-21}, journal = {IEEE Journal of Biomedical and Health Informatics}, author = {Slijepcevic, Djordje and Zeppelzauer, Matthias and Raberger, Anna-Maria and Schwab, Caterine and Schuller, Michael and Baca, Arnold and Breiteneder, Christian and Horsak, Brian}, year = {2018}, note = {Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, best-mzeppelzauer, peer-reviewed}, pages = {1653 -- 1661}, } @inproceedings{schwab_intelligait_2018, address = {Hamburg, Deutschland}, title = {{IntelliGait}: {Automatische} {Gangmusteranalyse} für die robuste {Erkennung} von {Gangstörungen}}, booktitle = {Tagungsband des 2ten {GAMMA} {Kongress} ({Gesellschaft} für die {Analyse} {Menschlicher} {Motorik} in ihrer klinischen {Anwendung})}, author = {Schwab, Caterine and Slijepcevic, Djordje and Zeppelzauer, Matthias and Raberger, Anna-Maria and Dumphart, Bernhard and Baca, Arnold and Breitender, Christian and Horsak, Brian}, year = {2018}, note = {Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, Creative Industries, DHLab, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, Pattern recognition, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, ⛔ No DOI found}, } @inproceedings{slijepcevic_towards_2018, address = {Prague, Czech Republic}, title = {Towards an optimal combination of input signals and derived representations for gait classification based on ground reaction force measurements.}, volume = {65}, doi = {10/gh38wn}, booktitle = {Gait \& {Posture} {Supplement}}, author = {Slijepcevic, Djordje and Zeppelzauer, Matthias and Schwab, Caterine and Raberger, Anna-Maria and Dumphart, B and Baca, Arnold and Breiteneder, Christian and Horsak, Brian}, year = {2018}, note = {Projekt: IntelliGait Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Artificial Intelligence, Center for Digital Health and Social Innovation, Classification, DHLab, FH SP Data Analytics \& Visual Computing, Feature Representations, Forschungsgruppe Media Computing, Gait Analysis, Gait Classification, Gait Recognition, Human Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Machine Learning, Media Computing Group, PCA, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, SVM, Wiss. Beitrag, best, best-bhorsak, pattern recognition, peer-reviewed}, } @misc{fischer_auditory_2016-1, address = {Segovia, Spain}, title = {An {Auditory} {Feedback} {System} in {Use} with {People} {Aged} +50 {Years}: {Compliance} and {Modifications} in {Gait} {Pattern}}, abstract = {Aging leads to gait impairments, which increases the risk for falls. In this study the impact of the auditory feedback system SONIGait on gait parameters in elderly persons was investigated. Twenty-one participants walked at self-selected speed with four variations of real-time auditory feedback of their plantar pressure. Repeated measures ANOVA was utilized to determine changes in time-distance parameters between walking without feedback and four feedback variations. After walking, they completed a questionnaire about their appraisal of the SONIGait system and the four different feedback modalities. There was a significant reduction in gait velocity (0.142 ± 0.04 m/s; p {\textless} 0.001) and prolongation of step time (0.02 ± 0.005 s; p {\textless} 0.001) during walking with SONIGait. No significant preference for any of the feedback variations was observed. Most participants evaluated the system SONIGait positively. Thus, real-time auditory feedback may be used in gait rehabilitation and may support an older person’s gait stability.}, author = {Fischer, Theresa and Kiselka, Anita}, collaborator = {Dlapka, Ronald and Doppler, Jakob and Iber, Michael and Gradl, Christian and Gorgas, Anna-Maria and Siragy, Tarique and Horsak, Brian}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, } @inproceedings{gorgas_short-term_2016, address = {Segovia, Spain}, series = {Biosystems \& {Biorobotics}}, title = {Short-{Term} {Effects} of {Real}-{Time} {Auditory} {Display} ({Sonification}) on {Gait} {Parameters} in {People} with {Parkinsons}’ {Disease}—{A} {Pilot} {Study}}, copyright = {©2017 Springer International Publishing AG}, isbn = {978-3-319-46668-2 978-3-319-46669-9}, url = {http://link.springer.com/chapter/10.1007/978-3-319-46669-9_139}, doi = {10/gnt2th}, abstract = {Parkinson’s disease PD patients frequently experience gait impairments. Auditory input has been shown to be an effective measure to benefit critical gait aspects related to the timing and initiation of movement. An instrumented shoe insole device for real-time sonification of gait has been developed for rehabilitation purposes (SONIGait). The objective of the present pilot study was to gain insight about possible effects of SONIGait on gait parameters in PD patients. Five PD patients participated in this pilot study and completed three series of trials with and without sonification. Spatio-temporal gait parameters were recorded during these trials. The outcomes revealed an increase in walking velocity and cadence along with other gait parameters between pre- and posttest. These data indicate that sonification affects gait parameters and fosters (short-term) learning effects in PD patients. Thus, SONIGait may be a suitable measure to promote gait rehabilitation in PD in the future.}, language = {en}, urldate = {2016-10-19}, booktitle = {Converging {Clinical} and {Engineering} {Research} on {Neurorehabilitation} {II}}, publisher = {Springer International Publishing}, author = {Gorgas, Anna-Maria and Schön, Lena and Dlapka, Ronald and Doppler, Jakob and Iber, Michael and Gradl, Christian and Kiselka, Anita and Siragy, Tarique and Horsak, Brian}, editor = {Ibáñez, Jaime and González-Vargas, José and Azorín, José María and Akay, Metin and Pons, José Luis}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait}, pages = {855--859}, } @article{horsak_sonigait_2016, title = {{SONIGait}: a wireless instrumented insole device for real-time sonification of gait}, volume = {10}, issn = {1783-7677, 1783-8738}, shorttitle = {{SONIGait}}, url = {http://link.springer.com/10.1007/s12193-016-0216-9}, doi = {10/gh38bg}, language = {en}, number = {3}, urldate = {2016-04-26}, journal = {Journal on Multimodal User Interfaces}, author = {Horsak, Brian and Dlapka, Ronald and Iber, Michael and Gorgas, Anna-Maria and Kiselka, Anita and Gradl, Christian and Siragy, Tarique and Doppler, Jakob}, year = {2016}, note = {Projekt: CARMA Projekt: SoniGait Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed}, pages = {195--206}, } @inproceedings{siragy_framework_2016, address = {Wien, Österreich}, title = {Framework for {Real}-time {Auditory} {Display} of {Plantar} {Pressure} during {Walking}}, booktitle = {Tagungsband des 10. {Forschungsforum} der Österreichischen {Fachhochschulen}}, author = {Siragy, Tarique and Doppler, Jakob and Gorgas, Anna-Maria and Dlapka, Ronald and Iber, Michael and Kiselka, Anita and Gradl, Christian and Horsak, Brian}, year = {2016}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biofeedback, Biomechanics, Center for Digital Health Innovation, Center for Digital Health and Social Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP CDHSI Motor Rehabilitation, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait, ⛔ No DOI found}, } @inproceedings{iber_pilotstudie_2015, address = {FH St. Pölten}, title = {Pilotstudie zur sonifikationsgestützten {Ganganalyse}}, isbn = {987-3-86488-090-2}, abstract = {Verletzungs- oder krankheitsbedingte Beeinträchtigungen des Ganges stellen die physiotherapeutische Behandlung vor große Herausforderungen. Aktuelle Technologien erlauben heute die Entwicklung preiswerter tragbarer Ganganalysesysteme, die den gewohnten Bewegungsablauf nicht einschränken und auch außerhalb eines Labors verwendet werden können. Über eine diagnostische Anwendung hinaus können sie auch den motorischen Lernprozess in der physiotherapeutischen Behandlung unterstützen. Eine akustische Darstellung des Abrollverhaltens erlaubt PatientInnen mögliche Abweichungen wahrzunehmen und ermöglicht folglich Eigenkontrolle und Eigenständigkeit beim Üben. Auf Grundlage dieser Rahmenbedingungen wurde ein Hardware-Prototyp bestehend aus einem Paar mit Sensoren ausgestatteter Schuhsohlen und einem Mikroprozessor mit BluetoothLE entwickelt, der Bewegungsdaten in Echtzeit an ein handelsübliches mobiles Endgerät schickt. Auf diesem werden die parametrisierten Daten in Echtzeit sonifiziert, d.h. als Klänge synthetisiert, und über Kopfhörer der PatientIn zugespielt. Dadurch erhält die PatientIn eine zusätzliche Rückmeldung zu seinem Gangmuster. In einer Pilotstudie wurden Sonifikationsvarianten entwickelt und nach einer Vorauswahl durch PhysiotherapeutInnen durch eine Gruppe gesunder ProbandInnen evaluiert. Darüber hinaus wurde der objektive Einfluss der Sonifikationen auf das Gangmuster anhand von Bewegungsdaten, die mit Druckmessplatten erhobenen wurden, verglichen.}, booktitle = {Forum {Medientechnik} - {Next} {Generation}, {New} {Ideas}}, publisher = {Verlag Werner Hülsbusch, Fachverlag für Medientechnik und -wirtschaft}, author = {Iber, Michael and Horsak, Brian and Bauer, Karin and Kiselka, Anita and Gorgas, Anna-Maria and Dlapka, Ronald and Doppler, Jakob}, year = {2015}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {2015, Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, peer-reviewed, project\_carma, project\_sonigait}, pages = {51--68}, } @inproceedings{horsak_wireless_2015, address = {Graz, Austria}, title = {A wireless instrumented insole device for real-time sonification of gait}, isbn = {978-3-902949-01-1}, booktitle = {Proceedings of the 21st {International} {Conference} on {Auditory} {Display}}, author = {Horsak, Brian and Iber, Michael and Bauer, Karin and Kiselka, Anita and Gorgas, Anna-Maria and Dlapka, Ronald and Doppler, Jakob}, year = {2015}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait}, pages = {94--101}, } @inproceedings{kiselka_demands_2015, address = {Hagenberg, Österreich}, title = {Demands on a mobile auditory feedback system for gait rehabilitation}, booktitle = {Tagungsband des 9. {Forschungsforum} der Österreichischen {Fachhochschulen}}, author = {Kiselka, Anita and Gorgas, A.-M. and Bauer, Karin and Dlapka, Ronald and Gusenbauer, Markus and Doppler, Jakob and Horsak, Brian}, year = {2015}, note = {Projekt: CARMA Projekt: DHLab}, keywords = {Biomechanics, Center for Digital Health Innovation, DHLab, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, best, best-bhorsak, interdisziplinär, peer-reviewed, project\_carma, project\_sonigait, ⛔ No DOI found}, } @incollection{bauer_towards_2014, address = {St. Poelten}, series = {Forum {Medientechnik}}, title = {Towards an insole sensor platform for auditory feedback applications in gait rehabilitation}, booktitle = {Forum {Medientechnik} - {Next} {Generation}, {New} {Ideas}: {Beiträge} der {Tagung} 2014 an der {Fachhochschule} {St}. {Pölten}}, publisher = {Huelsbusch, W}, author = {Bauer, Karin and Kiselka, Anita and Dlapka, Ronald and Gorgas, Anna-Maria and Gusenbauer, M and Horsak, Brian and Doppler, Jakob}, editor = {Seidl, Markus and Schmiedl, Grischa}, year = {2014}, note = {Projekt: CARMA}, keywords = {Biomechanics, Department Gesundheit und Soziales, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, project\_carma, project\_sonigait}, } @inproceedings{dlapka_gaitcam_2012, title = {{GAITCam} – {Entwicklung} einer automatisierten {Kamera}- {Bewegungssteuerung} zur bildbasierten {Ganganalyse}}, booktitle = {Proceedings of 5. {Forum} {Medientechnik}}, publisher = {vwh Verlag}, author = {Dlapka, Ronald and Doppler, Jakob and Horsak, Brian}, year = {2012}, note = {Projekt: CARMA Projekt: GAIT SCORE}, keywords = {Department Gesundheit und Soziales, Department Technologie, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, peer-reviewed, ⛔ No DOI found}, } @inproceedings{horsak_akustischer_2010, address = {Berlin, Deutschland}, title = {Ein akustischer {Ansatz} zur {Bestimmung} der {Durchführungsqualität} von {Bogenschüssen}}, booktitle = {Fortschritte der {Akustik}}, author = {Horsak, Brian and Heller, Mario and Reuter, Christoph}, year = {2010}, note = {Projekt: CARMA}, keywords = {Department Gesundheit und Soziales, Forschungsgruppe Digital Technologies, Gait Analysis, Institut für Gesundheitswissenschaften, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, Publikationstyp Vortrag, SP IGW Clinical \& Healthcare Research, Studiengang Physiotherapie, Wiss. Beitrag, peer-reviewed, ⛔ No DOI found}, pages = {487--488}, } @article{bernard_vial_2018, title = {{VIAL} – {A} {Unified} {Process} for {Visual}-{Interactive} {Labeling}}, volume = {34}, copyright = {Springer, Berlin, Heidelberg}, issn = {1432-2315}, url = {https://bit.ly/2My1Yrt}, doi = {10/gd5hr3}, abstract = {The assignment of labels to data instances is a fundamental prerequisite for many machine learning tasks. Moreover, labeling is a frequently applied process in visual-interactive analysis approaches and visual analytics. However, the strategies for creating labels usually differ between these two fields. This raises the question whether synergies between the different approaches can be attained. In this paper, we study the process of labeling data instances with the user in the loop, from both the machine learning and visual-interactive perspective. Based on a review of differences and commonalities, we propose the ’Visual-Interactive Labeling‘ (VIAL) process that unifies both approaches. We describe the six major steps of the process and discuss their specific challenges. Additionally, we present two heterogeneous usage scenarios from the novel VIAL perspective, one on metric distance learning and one on object detection in videos. Finally, we discuss general challenges to VIAL and point out necessary work for the realization of future VIAL approaches.}, number = {1189}, journal = {The Visual Computer}, author = {Bernard, Jürgen and Zeppelzauer, Matthias and Sedlmair, Michael and Aigner, Wolfgang}, year = {2018}, note = {Projekt: KAVA-Time Projekt: IntelliGait Projekt: CARMA}, keywords = {Active Learning, Candidate Selection, Center for Artificial Intelligence, Creative Industries, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Interactive Labeling, Labeling Strategies, Machine Learning, Media Computing Group, Visual Interactive Labeling, best, best-mzeppelzauer, information visualization}, pages = {16}, } @inproceedings{heller_digital_2018, address = {Dublin, Irland}, title = {A digital home-based physical training programme to improve balance and mobility performance among older adults}, language = {English}, author = {Heller, Mario and Stübler, Andreas and Sandner, Emanuel and Kropf, Johannes and Kumpf, Andreas and Oppenauer-Meerskraut, Claudia and Stamm, Tanja and Lampel, Kerstin}, year = {2018}, note = {Projekt: Train\&Win Projekt: CARMA}, keywords = {Center for Digital Health Innovation, Digital Healthcare, Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP IGW Health Promotion \& Healthy Ageing, Studiengang Digital Healthcare, Studiengang Physiotherapie, Vortrag, Wiss. Beitrag, best-lbheller, peer-reviewed, ⛔ No DOI found}, } @inproceedings{heller_fitdaheim_2018, address = {München}, series = {Schriften der {Deutschen} {Vereinigung} für {Sportwissenschaft}}, title = {„{FitDaheim}“ - ein {IKT}-gestütztes, physio- und ergotherapiebasiertes {Trainingsprogramm} zur {Förderung} von {Bewegung} im {Alter}.}, volume = {274}, abstract = {Der Einsatz von Informations- und Kommunikationstechnologien (IKT) in gesundheitsbezo-genen Produkten, Dienstleistungen und Prozessen hat nicht zuletzt aufgrund neuer techno-logischer Entwicklungen wie dem mobilen Internet oder dem Internet der Dinge zu einer Vielzahl von Anwendungen für das gesamte Gesundheitswesen geführt. Neben klassischen Informationssystemen zur Speicherung und zum Austausch von Daten in stationären Ge-sundheitseinrichtungen wie z.B. Krankenhäusern oder Pflegeeinrichtungen findet insbeson-dere auf dem zweiten Gesundheitsmarkt eine dynamische Entwicklung von Digital-Health-Anwendungen statt, bei der Produkte und Dienstleistungen auf individuelle Bedürfnisse zu-geschnitten werden und somit ein souveräneres und aktiveres Gestalten des eigenen Ge-sundheitshandelns ermöglichen (Knöppler, Neiseke und Nölke, 2016). Das Ziel dieses Beitrages ist es, den Aufbau und die Funktionsweise eines IKT-gestützten Trainingsprogramms zur Förderung von Bewegung im Alter vorzustellen, welches Übungen aus der Physio- und Ergotherapie enthält und zu Hause vor dem eigenen Fernsehbildschirm durchgeführt werden kann. Rückmeldungen über die Qualität der Bewegungsausführungen ermöglichen dabei ein quasi-angeleitetes kontrolliertes Bewegungstraining.}, language = {Deutsch}, booktitle = {Sportinformatik {XII}}, publisher = {Feldhaus}, author = {Heller, Mario and Stübler, Andreas and Sandner, Emanuel and Kropf, Johannes and Kumpf, Andreas and Oppenauer-Meerskraut, Claudia and Stamm, Tanja and Lampel, Kerstin}, editor = {Link, Daniel and Hermann, Aljoscha and Lames, Martin and Senner, Veit}, year = {2018}, note = {Projekt: Train\&Win Projekt: CARMA}, keywords = {Center for Digital Health Innovation, Digital Healthcare, Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Institut für Gesundheitswissenschaften, SP IGW Health Promotion \& Healthy Ageing, Vortrag, Wiss. Beitrag, best-lbheller, peer-reviewed, ⛔ No DOI found}, pages = {49--50}, } @misc{aigner_media-assisted_2018, address = {Vienna}, type = {Keynote}, title = {Media-{Assisted} {Healthcare} {\textbackslash}\& {Living}: {Daten} besser nutzbar machen mit {Interaktiven} {Technologien}}, shorttitle = {{ADV} e-{Health}}, author = {Aigner, Wolfgang}, month = jun, year = {2018}, note = {Projekt: VisOnfire Projekt: KAVA-Time Projekt: CARMA Projekt: BRELOMATE Projekt: BRELOMATE2 Projekt: Umbrello Projekt: SoniGait Projekt: VisuExplore Projekt: IntelliGait Projekt: LifeStream}, keywords = {Artificial Intelligence, Center for Digital Health Innovation, Data Science, Digital Health, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Machine Learning, Visual Computing}, } @misc{aigner_visual_2018, address = {Johannes-Kepler University Linz (Austria)}, type = {Inivited talk}, title = {Visual {Analytics} as a {Design} {Science} {Discipline}}, shorttitle = {{CG} {Lab} {Talk}}, author = {Aigner, Wolfgang}, month = may, year = {2018}, note = {Projekt: CARMA Projekt: Sonigait Projekt: KAVA-Time Projekt: VALiD Projekt: VAST}, keywords = {Center for Digital Health Innovation, Data Science, Digital Health, FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Malware Analysis, Visual Computing}, } @misc{aigner_visual_2018-1, address = {City University London (UK)}, type = {Inivited talk}, title = {Visual {Analytics} as a {Design} {Science} {Discipline}}, shorttitle = {{giCentre}}, author = {Aigner, Wolfgang}, month = may, year = {2018}, note = {Projekt: Sonigait Projekt: KAVA-Time Projekt: CARMA Projekt: VALiD Pojekt: VAST}, keywords = {Center for Digital Health Innovation, Data Science, Digital Health, FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Malware Analysis, Visual Computing}, } @misc{aigner_visual_2018-2, address = {TU Graz (Austria)}, type = {Invited talk}, title = {Visual {Analytics} as a {Design} {Science} {Discipline}}, shorttitle = {{TU} {Graz}}, author = {Aigner, Wolfgang}, month = apr, year = {2018}, note = {Projekt: CARMA Projekt: Sonigait Projekt: KAVA-Time Projekt: VALiD Projekt: VAST}, keywords = {Center for Digital Health Innovation, Data Science, Digital Health, FH SP Cyber Security, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Human-Computer Interaction, Institut für Creative Media Technologies, Malware Analysis, Visual Computing}, }