An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis
| Autor: | Ch. Truong, Stéphane Buffat, Aliénor Vienne, Th. Moreau, C. de Waele, Pierre-Paul Vidal, Nicolas Vayatis, Ch. Labourdette, Alain Yelnik, Alfredo Aram Pulini, Sébastien Laporte, Damien Ricard, Th. Gregory, Laurent Oudre, R. Barrois |
|---|---|
| Přispěvatelé: | Cognition and Action Group (COGNAC-G - UMR 8257), École normale supérieure - Cachan (ENS Cachan)-Université Paris Descartes - Paris 5 (UPD5)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Cachan, antenne de Bretagne (ENS Cachan Bretagne), École normale supérieure - Cachan (ENS Cachan), Centre de Mathématiques et de Leurs Applications (CMLA), École normale supérieure - Cachan (ENS Cachan)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche Biomédicale des Armées (IRBA), Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP), Institut de Biomecanique Humaine Georges Charpak, Université Paris 13 (UP13)-Arts et Métiers ParisTech, Hôpital d'instruction des Armées Percy, Service de Santé des Armées, Université René Descartes, Institut Galilée, Laboratoire de Génie Electrique de Grenoble (G2ELab), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Service de chirurgie orthopédique et traumatologique, hôpital d'Instruction des Armées Percy, 92140 Clamart, France, parent |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Male
Inertia Physiology Limp Velocity lcsh:Medicine Walking 02 engineering and technology Accelerometer Clinical Biomechanics Severity of Illness Index Mathematical and Statistical Techniques 0302 clinical medicine Gait (human) Medicine and Health Sciences Medicine Biomechanics lcsh:Science Gait Musculoskeletal System Aged 80 and over Multidisciplinary medicine.diagnostic_test Physics Classical Mechanics [SPI.MECA.BIOM]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph] Signal Processing Computer-Assisted Middle Aged Biomechanical Phenomena 3. Good health Physical Sciences Legs Female [SDV.IB]Life Sciences [q-bio]/Bioengineering Step detection Anatomy medicine.symptom Gait Analysis Statistics (Mathematics) Research Article Adult medicine.medical_specialty Acceleration 0206 medical engineering Physical examination Research and Analysis Methods Motion 03 medical and health sciences Physical medicine and rehabilitation Rheumatology Inertial measurement unit Osteoarthritis Humans Statistical Methods Mécanique: Biomécanique [Sciences de l'ingénieur] Aged Monitoring Physiologic Leg Analysis of Variance Biological Locomotion business.industry Arthritis Limbs (Anatomy) lcsh:R ingénierie bio-médicale [Sciences du vivant] Biology and Life Sciences 020601 biomedical engineering Preferred walking speed Gait analysis Physical therapy lcsh:Q Feet (Anatomy) business Mathematics 030217 neurology & neurosurgery |
| Zdroj: | PLoS ONE PLoS ONE, Public Library of Science, 2016, 11 (10), pp.1-15 PLoS ONE, Public Library of Science, 2016, 11 (10), pp.1-15. ⟨10.1371/journal.pone.0164975⟩ PLoS ONE, Vol 11, Iss 10, p e0164975 (2016) |
| ISSN: | 1932-6203 |
| DOI: | 10.1371/journal.pone.0164975⟩ |
| Popis: | International audience; For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor’s office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient’s home. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|