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A multi-sensor wearable system for the assessment of diseased gait in real-world conditions.
Salis, Francesca; Bertuletti, Stefano; Bonci, Tecla; Caruso, Marco; Scott, Kirsty; Alcock, Lisa; Buckley, Ellen; Gazit, Eran; Hansen, Clint; Schwickert, Lars; Aminian, Kamiar; Becker, Clemens; Brown, Philip; Carsin, Anne-Elie; Caulfield, Brian; Chiari, Lorenzo; D'Ascanio, Ilaria; Del Din, Silvia; Eskofier, Bjoern M; Garcia-Aymerich, Judith; Hausdorff, Jeffrey M; Hume, Emily C; Kirk, Cameron; Kluge, Felix; Koch, Sarah; Kuederle, Arne; Maetzler, Walter; Micó-Amigo, Encarna M; Mueller, Arne; Neatrour, Isabel; Paraschiv-Ionescu, Anisoara; Palmerini, Luca; Yarnall, Alison J; Rochester, Lynn; Sharrack, Basil; Singleton, David; Vereijken, Beatrix; Vogiatzis, Ioannis; Della Croce, Ugo; Mazzà, Claudia; Cereatti, Andrea.
Afiliação
  • Salis F; Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
  • Bertuletti S; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System (IuC BoHNes), Sassari, Italy.
  • Bonci T; Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
  • Caruso M; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System (IuC BoHNes), Sassari, Italy.
  • Scott K; Department of Mechanical Engineering, Insigneo Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom.
  • Alcock L; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System (IuC BoHNes), Sassari, Italy.
  • Buckley E; Department of Electronics and Telecommunications, Politecnico Di Torino, Torino, Italy.
  • Gazit E; Department of Mechanical Engineering, Insigneo Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom.
  • Hansen C; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom.
  • Schwickert L; National Institute for Health and Care Research (NIHR) Newcastle Biomedical Research Centre (BRC), Newcastle University, Newcastle Upon Tyne, United Kingdom.
  • Aminian K; Department of Mechanical Engineering, Insigneo Institute for In Silico Medicine, The University of Sheffield, Sheffield, United Kingdom.
  • Becker C; Centre for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Centre, Tel Aviv, Israel.
  • Brown P; Department of Neurology, University Medical Centre Schleswig-Holstein Campus Kiel and Kiel University, Kiel, Germany.
  • Carsin AE; Department for Geriatric Rehabilitation, Robert-Bosch-Hospital, Stuttgart, Germany.
  • Caulfield B; Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
  • Chiari L; Department for Geriatric Rehabilitation, Robert-Bosch-Hospital, Stuttgart, Germany.
  • D'Ascanio I; Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, United Kingdom.
  • Del Din S; Instituto de Salud Global Barcelona, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
  • Eskofier BM; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
  • Garcia-Aymerich J; CIBER Epidemiología y Salud Pública, Madrid, Spain.
  • Hausdorff JM; Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.
  • Hume EC; Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy.
  • Kirk C; Health Sciences and Technologies-Interdepartmental Centre for Industrial Research (CIRI-SDV), University of Bologna, Bologna, Italy.
  • Kluge F; Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy.
  • Koch S; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom.
  • Kuederle A; National Institute for Health and Care Research (NIHR) Newcastle Biomedical Research Centre (BRC), Newcastle University, Newcastle Upon Tyne, United Kingdom.
  • Maetzler W; Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Micó-Amigo EM; Instituto de Salud Global Barcelona, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
  • Mueller A; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
  • Neatrour I; CIBER Epidemiología y Salud Pública, Madrid, Spain.
  • Paraschiv-Ionescu A; Centre for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Centre, Tel Aviv, Israel.
  • Palmerini L; Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Northumbia, United Kingdom.
  • Yarnall AJ; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom.
  • Rochester L; Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Sharrack B; Novartis Institutes of Biomedical Research, Novartis Pharma AG, Basel, Switzerland.
  • Singleton D; Instituto de Salud Global Barcelona, Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.
  • Vereijken B; Faculty of Health and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
  • Vogiatzis I; CIBER Epidemiología y Salud Pública, Madrid, Spain.
  • Della Croce U; Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Mazzà C; Department of Neurology, University Medical Centre Schleswig-Holstein Campus Kiel and Kiel University, Kiel, Germany.
  • Cereatti A; Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom.
  • For The Mobilise-D Consortium; Novartis Institutes of Biomedical Research, Novartis Pharma AG, Basel, Switzerland.
Front Bioeng Biotechnol ; 11: 1143248, 2023.
Article em En | MEDLINE | ID: mdl-37214281
ABSTRACT

Introduction:

Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors).

Methods:

The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and

discussion:

Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article