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Technical validation of real-world monitoring of gait: a multicentric observational study.
Mazzà, Claudia; Alcock, Lisa; Aminian, Kamiar; Becker, Clemens; Bertuletti, Stefano; Bonci, Tecla; Brown, Philip; Brozgol, Marina; Buckley, Ellen; Carsin, Anne-Elie; Caruso, Marco; Caulfield, Brian; Cereatti, Andrea; Chiari, Lorenzo; Chynkiamis, Nikolaos; Ciravegna, Fabio; Del Din, Silvia; Eskofier, Björn; Evers, Jordi; Garcia Aymerich, Judith; Gazit, Eran; Hansen, Clint; Hausdorff, Jeffrey M; Helbostad, Jorunn L; Hiden, Hugo; Hume, Emily; Paraschiv-Ionescu, Anisoara; Ireson, Neil; Keogh, Alison; Kirk, Cameron; Kluge, Felix; Koch, Sarah; Küderle, Arne; Lanfranchi, Vitaveska; Maetzler, Walter; Micó-Amigo, M Encarna; Mueller, Arne; Neatrour, Isabel; Niessen, Martijn; Palmerini, Luca; Pluimgraaff, Lucas; Reggi, Luca; Salis, Francesca; Schwickert, Lars; Scott, Kirsty; Sharrack, Basil; Sillen, Henrik; Singleton, David; Soltani, Abolfazi; Taraldsen, Kristin.
Afiliación
  • Mazzà C; INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, UK c.mazza@sheffield.ac.uk.
  • Alcock L; Department of Mechanical Engineering, The University of Sheffield, Sheffield, UK.
  • Aminian K; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
  • Becker C; Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
  • Bertuletti S; Robert Bosch Gesellschaft für Medizinische Forschung, Stuttgart, Germany.
  • Bonci T; Department of Biomedical Sciences, University of Sassari, Sassari, Sardegna, Italy.
  • Brown P; INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, UK.
  • Brozgol M; Department of Mechanical Engineering, The University of Sheffield, Sheffield, UK.
  • Buckley E; The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK.
  • Carsin AE; Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
  • Caruso M; INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, UK.
  • Caulfield B; Department of Mechanical Engineering, The University of Sheffield, Sheffield, UK.
  • Cereatti A; ISGlobal, Barcelona, Spain.
  • Chiari L; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
  • Chynkiamis N; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
  • Ciravegna F; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
  • Del Din S; Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy.
  • Eskofier B; PolitoBIOMed Lab - Biomedical Engineering Lab, Politecnico di Torino, Torino, Italy.
  • Evers J; Insight Centre for Data Analytics, O'Brien Science Centre, University College Dublin, Dublin, Ireland.
  • Garcia Aymerich J; UCD School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.
  • Gazit E; Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy.
  • Hansen C; Department of Electrical, Electronic and Information Engineering «Guglielmo Marconi¼, University of Bologna, Bologna, Italy.
  • Hausdorff JM; Health Sciences and Technologies-Interdepartmental Center for Industrial Research (CIRI-SDV), University of Bologna, Bologna, Italy.
  • Helbostad JL; Department of Sport, Exercise and Rehabilitation, Northumbria University Newcastle, Newcastle upon Tyne, UK.
  • Hiden H; INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, UK.
  • Hume E; Department of Computer Science, The University of Sheffield, Sheffield, UK.
  • Paraschiv-Ionescu A; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
  • Ireson N; Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Keogh A; McRoberts BV, Den Haag, Zuid-Holland, Netherlands.
  • Kirk C; ISGlobal, Barcelona, Spain.
  • Kluge F; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
  • Koch S; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
  • Küderle A; Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
  • Lanfranchi V; Department of Neurology, University Medical Center Schleswig-Holstein Campus Kiel, Kiel, Germany.
  • Maetzler W; Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
  • Micó-Amigo ME; Department of Physical Therapy, Sackler Faculty of Medicine & Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
  • Mueller A; Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway.
  • Neatrour I; School of Computing, Newcastle University, Newcastle upon Tyne, UK.
  • Niessen M; Department of Sport, Exercise and Rehabilitation, Northumbria University Newcastle, Newcastle upon Tyne, UK.
  • Palmerini L; Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
  • Pluimgraaff L; INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, UK.
  • Reggi L; Department of Computer Science, The University of Sheffield, Sheffield, UK.
  • Salis F; Insight Centre for Data Analytics, O'Brien Science Centre, University College Dublin, Dublin, Ireland.
  • Schwickert L; UCD School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.
  • Scott K; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
  • Sharrack B; Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Sillen H; ISGlobal, Barcelona, Spain.
  • Singleton D; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
  • Soltani A; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
  • Taraldsen K; Machine Learning and Data Analytics Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
BMJ Open ; 11(12): e050785, 2021 12 02.
Article en En | MEDLINE | ID: mdl-34857567
INTRODUCTION: Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real-world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users' perspective on the device. METHODS AND ANALYSIS: This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs.After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson's disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users' perspective on the deployed technology and relevance of the mobility assessment. ETHICS AND DISSEMINATION: The study has been granted ethics approval by the centre's committees (London-Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available. TRIAL REGISTRATION NUMBER: ISRCTN (12246987).
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Dispositivos Electrónicos Vestibles / Esclerosis Múltiple Tipo de estudio: Clinical_trials / Guideline / Observational_studies / Qualitative_research Límite: Aged / Humans Idioma: En Revista: BMJ Open Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Parkinson / Dispositivos Electrónicos Vestibles / Esclerosis Múltiple Tipo de estudio: Clinical_trials / Guideline / Observational_studies / Qualitative_research Límite: Aged / Humans Idioma: En Revista: BMJ Open Año: 2021 Tipo del documento: Article