요약정보
Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases.
- Resource Type
- Academic Journal
- Authors
- Romijnders R; Digital Signal Processing and System Theory, Electrical and Information Engineering, Faculty of Engineering, Kiel University, Kiel, Germany.; Arbeitsgruppe Neurogeriatrie, Department of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, Germany.; Salis F; Department of Biomedical Sciences, University of Sassari, Sassari, Italy.; Hansen C; Arbeitsgruppe Neurogeriatrie, Department of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, Germany.; Küderle A; Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.; Paraschiv-Ionescu A; Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.; Cereatti A; Department of Electronics and Telecommunications, Polytechnic of Turin, Turin, Italy.; Alcock L; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.; Aminian K; Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.; Becker C; Gesellschaft für Medizinische Forschung, Robert-Bosch Foundation GmbH, Stuttgart, Germany.; Bertuletti S; Department of Biomedical Sciences, University of Sassari, Sassari, Italy.; Bonci T; INSIGNEO Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom.; Department of Mechanical Engineering, The University of Sheffield, Sheffield, United Kingdom.; Brown P; Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom.; Buckley E; INSIGNEO Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom.; Department of Mechanical Engineering, The University of Sheffield, Sheffield, United Kingdom.; Cantu A; School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.; Carsin AE; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.; CIBER Epidemiología y Salud Pública, Madrid, Spain.; Caruso M; Department of Electronics and Telecommunications, Polytechnic of Turin, Turin, Italy.; Caulfield B; Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.; School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.; Chiari L; Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Bologna, Italy.; Health Sciences and Technologies-Interdepartmental Center for Industrial Research (CIRISDV), University of Bologna, Bologna, Italy.; D'Ascanio I; Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Bologna, Italy.; Del Din S; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.; Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.; Eskofier B; Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.; Fernstad SJ; School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.; Fröhlich MS; Grünenthal GmbH, Aachen, Germany.; Garcia Aymerich J; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.; CIBER Epidemiología y Salud Pública, Madrid, Spain.; Gazit E; Center for the Study of Movement, Cognition and Mobility, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.; Hausdorff JM; Center for the Study of Movement, Cognition and Mobility, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.; Department of Physical Therapy, Sackler Faculty of Medicine & Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.; Hiden H; School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.; Hume E; Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne, United Kingdom.; Keogh A; Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.; School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.; Kirk C; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.; Kluge F; Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.; Novartis Institute of Biomedical Research, Novartis Pharma AG, Basel, Switzerland.; Koch S; Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.; CIBER Epidemiología y Salud Pública, Madrid, Spain.; Mazzà C; INSIGNEO Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom.; Department of Mechanical Engineering, The University of Sheffield, Sheffield, United Kingdom.; Megaritis D; Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne, United Kingdom.; Micó-Amigo E; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.; Müller A; Novartis Institute of Biomedical Research, Novartis Pharma AG, Basel, Switzerland.; Palmerini L; Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Bologna, Italy.; Health Sciences and Technologies-Interdepartmental Center for Industrial Research (CIRISDV), University of Bologna, Bologna, Italy.; Rochester L; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.; Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom.; Schwickert L; Gesellschaft für Medizinische Forschung, Robert-Bosch Foundation GmbH, Stuttgart, Germany.; Scott K; INSIGNEO Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom.; Department of Mechanical Engineering, The University of Sheffield, Sheffield, United Kingdom.; Sharrack B; Department of Neuroscience and Sheffield NIHR Translational Neuroscience BRC, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom.; Singleton D; Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.; School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.; Soltani A; Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.; Digital Health Department, CSEM SA, Neuchâtel, Switzerland.; Ullrich M; Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.; Vereijken B; Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway.; Vogiatzis I; Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne, United Kingdom.; Yarnall A; Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.; Department of Mechanical Engineering, The University of Sheffield, Sheffield, United Kingdom.; Schmidt G; Digital Signal Processing and System Theory, Electrical and Information Engineering, Faculty of Engineering, Kiel University, Kiel, Germany.; Maetzler W; Arbeitsgruppe Neurogeriatrie, Department of Neurology, Universitätsklinikum Schleswig-Holstein, Kiel, Germany.
- Source
- Publisher:
Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101546899 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2295 (Print) Linking ISSN:16642295 NLM ISO Abbreviation: Front Neurol Subsets: PubMed not MEDLINE - Subject
- Language
- English
- ISSN
- 1664-2295