Browsing Bergen Open Research Archive by Author "Riegler, Michael"

Now showing items 1-13 of 13

    • Affect Recognition in Muscular Response Signals 

      Boeker, Matthias; Jakobsen, Petter; Riegler, Michael; Stabell, Lena Antonsen; Fasmer, Ole Bernt; Halvorsen, Pål; Hammer, Hugo Lewi (Journal article; Peer reviewed, 2023)
      This study investigated the potential of recognising arousal in motor activity collected by wrist-worn accelerometers. We hypothesise that emotional arousal emerges from the generalised central nervous system which embeds ...

    • Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls 

      Jakobsen, Petter; Garcia-Ceja, Enrique; Riegler, Michael; Stabell, Lena Antonsen; Nordgreen, Tine; Tørresen, Jim; Fasmer, Ole Bernt; Ødegaard, Ketil Joachim (Journal article; Peer reviewed, 2020)
      Current practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner ...

    • Comparing approaches to interactive lifelog search at the lifelog search challenge (LSC2018) 

      Gurrin, Cathal; Schoeffmann, Klaus; Joho, Hideo; Leibetseder, Andreas; Zhou, Liting; Duane, Aaron; Dang Nguyen, Duc Tien; Riegler, Michael; Piras, Luca; Tran, Minh-Triet; Lokoc, Jakub; Hurst, Wolfgang (Peer reviewed; Journal article, 2019)
      The Lifelog Search Challenge (LSC) is an international content retrieval competition that evaluates search for personal lifelog data. At the LSC, content-based search is performed over a multi-modal dataset, continuously ...

    • Complexity and variability analyses of motor activity distinguish mood states in Bipolar Disorder 

      Jakobsen, Petter; Stautland, Andrea; Riegler, Michael; Côté-Allard, Ulysse Teller Masao; Sepasdar, Zahra; Nordgreen, Tine; Tørresen, Jim; Fasmer, Ole Bernt; Ødegaard, Ketil Joachim (Journal article; Peer reviewed, 2022)
      Changes in motor activity are core symptoms of mood episodes in bipolar disorder. The manic state is characterized by increased variance, augmented complexity and irregular circadian rhythmicity when compared to healthy ...

    • Diagnosing Schizophrenia from Activity Records using Hidden Markov Model Parameters 

      Boeker, Matthias; Riegler, Michael; Hammer, Hugo Lewi; Halvorsen, Pål; Fasmer, Ole Bernt; Jakobsen, Petter (Chapter, 2021)
      The diagnosis of Schizophrenia is mainly based on qualitative characteristics. With the usage of portable devices which measure activity of humans, the diagnosis of Schizophrenia can be enriched through quantitative features. ...

    • HYPERAKTIV: An Activity Dataset from Patients with Attention-Deficit/Hyperactivity Disorder (ADHD) 

      Hicks, Steven; Stautland, Andrea; Fasmer, Ole Bernt; Førland, Wenche; Hammer, Hugo Lewi; Halvorsen, Pål; Mjeldheim, Kristin; Ødegaard, Ketil Joachim; Osnes, Berge; Syrstad, Vigdis Elin Giæver; Riegler, Michael; Jakobsen, Petter (Chapter, 2021)
      Machine learning research within healthcare frequently lacks the public data needed to be fully reproducible and comparable. Datasets are often restricted due to privacy concerns and legal requirements that come with ...

    • HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy 

      Borgli, Hanna; Thambawita, Vajira; Smedsrud, Pia H; Hicks, Steven; Jha, Debesh; Eskeland, Sigrun Losada; Randel, Kristin Ranheim; Pogorelov, Konstantin; Lux, Mathias; Dang Nguyen, Duc Tien; Johansen, Dag; Griwodz, Carsten; Stensland, Håkon Kvale; Garcia-Ceja, Enrique; Schmidt, Peter T; Hammer, Hugo Lewi; Riegler, Michael; Halvorsen, Pål; de Lange, Thomas (Journal article; Peer reviewed, 2020)
      Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of medical personnel for the cumbersome and tedious process to ...

    • ImageCLEF 2019: Multimedia retrieval in lifelogging, medical, nature, and security applications 

      Ionescu, Bogdan; Müller, Henning; Peteri, Renaud; Dang Nguyen, Duc Tien; Piras, Luca; Riegler, Michael; Tran, Minh Triet; Lux, Mathias; Gurrin, Cathal; Cid, Yashin Dicente; Liauchuk, Vitali; Kovalev, Vassili; Ben Abacha, Asma; Hasan, Sadid A.; Datla, Vivek; Liu, Joey; Demner-Fushman, Dina; Pelka, Obioma; Friedrich, C.; Chamberlain, Jon; Clark, Adrian; de Herrera, Alba Garcia Seco; Garcia, Narciso; Kavallieratou, Ergina; del Blanco, Carlos Roberto; Rodriguez, Carlos Cuevas; Vasillopoulos, Nikos; Karampidis, Konstantinos (Lecture Notes in Computer Science, Chapter; Peer reviewed; Journal article, 2019)
      This paper presents an overview of the foreseen ImageCLEF 2019 lab that will be organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started ...

    • LIFER 2.0: Discovering Personal Lifelog Insights using an Interactive Lifelog Retrieval System 

      Van, Tu-ninh; Le, Tu-Khiem; Zhou, Liting; Piras, Luca; Riegler, Michael; Lux, Mathias; Tran, Minh-Triet; Gurrin, Cathal; Dang Nguyen, Duc Tien (Peer reviewed; Journal article, 2019)
      This paper describes the participation of the Organiser Team in the ImageCLEFlifelog 2019 Solve My Life Puzzle (Puzzle) and Lifelog Moment Retrieval (LMRT) tasks. We proposed to use LIFER 2.0, an enhanced version of LIFER, ...

    • Medico multimedia task at MediaEval 2018 

      Pogorelov, Konstantin; Riegler, Michael; Halvorsen, Pål; Hicks, Steven; Randel, Kristin Ranheim; Dang Nguyen, Duc Tien; Lux, Mathias; Ostroukhova, Olga; de Lange, Thomas (Peer reviewed; Journal article, 2018-12-22)
      The Medico: Multimedia for Medicine Task, running for the second time as part of MediaEval 2018, focuses on detecting abnormalities, diseases, anatomical landmarks and other findings in images captured by medical devices ...

    • Overview of ImageCLEFlifelog 2019: Solve My Life Puzzle and Lifelog Moment Retrieval 

      Dang Nguyen, Duc Tien; Piras, Luca; Riegler, Michael; Zhou, Liting; Lux, Mathias; Tran, Minh Triet; Le, Tu-Khiem; Ninh, Van-Tu; Gurrin, Cathal (Peer reviewed; Journal article, 2019)
      This paper describes ImageCLEFlifelog 2019, the third edition of the Lifelog task. In this edition, the task was composed of two subtasks (challenges): the Lifelog Moments Retrieval (LMRT) challenge that followed the same ...

    • Overview of the ImageCLEF 2020: Multimedia Retrieval in Medical, Lifelogging, Nature, and Internet Applications 

      Ionescu, Bogdan; Müller, Henning; Péteri, Renaud; Abacha, Asma Ben; Datla, Vivek; Hasan, Sadid A.; Demner-Fushman, Dina; Kozlovski, Serge; Liauchuk, Vitali; Cid, Yashin Dicente; Kovalev, Vassili; Pelka, Obioma; Friedrich, Christoph M.; García Seco de Herrera, Alba; Ninh, Van-Tu; Le, Tu-Khiem; Zhou, Liting; Piras, Luca; Riegler, Michael; Halvorsen, Pål; Tran, Minh-Triet; Lux, Mathias; Gurrin, Cathal; Dang Nguyen, Duc Tien; Chamberlain, Jon; Clark, Adrian; Campello, Antonio; Fichou, Dimitri; Berari, Raul; Brie, Paul; Dogariu, Mihai; Ştefan, Liviu Daniel; Constantin, Mihai Gabriel (Journal article; Peer reviewed, 2020)
      This paper presents an overview of the ImageCLEF 2020 lab that was organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2020. ImageCLEF is an ongoing evaluation initiative (first run in 2003) ...

    • Predicting an unstable tear film through artificial intelligence 

      Fineide, Fredrik; Storås, Andrea; Chen, Xiangjun; Magnø, Morten Schjerven; Yazidi, Anis; Riegler, Michael; Utheim, Tor Paaske (Journal article; Peer reviewed, 2022)
      Dry eye disease is one of the most common ophthalmological complaints and is defined by a loss of tear film homeostasis. Establishing a diagnosis can be time-consuming, resource demanding and unpleasant for the patient. ...