title: Whole body center of mass estimation with portable sensors: using the statically equivalent serial chain and a Kinect.
abstract: The trajectory of the whole body center of mass (CoM) is useful as a reliable metric of postural stability. If the evaluation of a subject-specific CoM were available outside of the laboratory environment, it would improve the assessment of the effects of physical rehabilitation. This paper develops a method that enables tracking CoM position using low-cost sensors that can be moved around by a therapist or easily installed inside a patient's home. Here, we compare the accuracy of a personalized CoM estimation using the statically equivalent serial chain (SESC) method and measurements obtained with the Kinect to the case of a SESC obtained with high-end equipment (Vicon). We also compare these estimates to literature-based ones for both sensors. The method was validated with seven able-bodied volunteers for whom the SESC was identified using 40 static postures. The literature-based estimation with Vicon measurements had a average error 24.9 ± 3.7 mm; this error was reduced to 12.8 ± 9.1 mm with the SESC identification. When using Kinect measurements, the literature-based estimate had an error of 118.4 ± 50.0 mm, while the SESC error was 26.6 ± 6.0 mm. The subject-specific SESC estimate using low-cost sensors has an equivalent performance as the literature-based one with high-end sensors. The SESC method can improve CoM estimation of elderly and neurologically impaired subjects by considering variations in their mass distribution.
authors.affiliation: INRIA (Institut National de Recherche en Informatique et en Automatique), DEMAR Team, Montpellier 34095, France. gonzalezde@lirmm.fr.
authors.forename: Alejandro
authors.initials: A
authors.lastname: González
authors.affiliation: INRIA (Institut National de Recherche en Informatique et en Automatique), DEMAR Team, Montpellier 34095, France. hayashibe@lirmm.fr.
authors.forename: Mitsuhiro
authors.initials: M
authors.lastname: Hayashibe
authors.affiliation: Movement to Health (M2H) Laboratory, EuroMov, University of Montpellier 1, Montpellier 34090, France. bonnet.vincent@gmail.com.
authors.forename: Vincent
authors.initials: V
authors.lastname: Bonnet
authors.affiliation: INRIA (Institut National de Recherche en Informatique et en Automatique), DEMAR Team, Montpellier 34095, France. fraisse@lirmm.fr.
authors.forename: Philippe
authors.initials: P
authors.lastname: Fraisse
mesh_terms: D015992:Body Mass Index; D001834:Body Water / Q000502:physiology*; D003198:Computer Simulation; D034201:Computers, Handheld; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D008954:Models, Biological; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014159:Transducers