title: Comparative assessment of different methods for the estimation of gait temporal parameters using a single inertial sensor: application to elderly, post-stroke, Parkinson's disease and Huntington's disease subjects.
abstract: The estimation of gait temporal parameters with inertial measurement units (IMU) is a research topic of interest in clinical gait analysis. Several methods, based on the use of a single IMU mounted at waist level, have been proposed for the estimate of these parameters showing satisfactory performance when applied to the gait of healthy subjects. However, the above mentioned methods were developed and validated on healthy subjects and their applicability in pathological gait conditions was not systematically explored. We tested the three best performing methods found in a previous comparative study on data acquired from 10 older adults, 10 hemiparetic, 10 Parkinson's disease and 10 Huntington's disease subjects. An instrumented gait mat was used as gold standard. When pathological populations were analyzed, missed or extra events were found for all methods and a global decrease of their performance was observed to different extents depending on the specific group analyzed. The results revealed that none of the tested methods outperformed the others in terms of accuracy of the gait parameters determination for all the populations except the Parkinson's disease subjects group for which one of the methods performed better than others. The hemiparetic subjects group was the most critical group to analyze (stride duration errors between 4-5 % and step duration errors between 8-13 % of the actual values across methods). Only one method provides estimates of the stance and swing durations which however should be interpreted with caution in pathological populations (stance duration errors between 6-14 %, swing duration errors between 10-32 % of the actual values across populations).
authors.affiliation: Information Engineering Unit, POLCOMING Department, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy. Electronic address: dtrojaniello@uniss.it.
authors.forename: Diana
authors.initials: D
authors.lastname: Trojaniello
authors.affiliation: Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Ravaschio
authors.affiliation: Center for the study of Movement, Cognition and Mobility, Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv 64239, Israel; Department of Physical Therapy, Sackler School of Medicine and Sagol School of Neuroscience, Tel Aviv University, Israel.
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Hausdorff
authors.affiliation: Information Engineering Unit, POLCOMING Department, University of Sassari, Sassari, Italy; Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Sassari, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Cereatti
mesh_terms: D061725:Accelerometry / Q000295:instrumentation / Q000379:methods*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D006816:Huntington Disease / Q000150:complications / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000150:complications / Q000503:physiopathology*; D020521:Stroke / Q000150:complications / Q000503:physiopathology*; D013997:Time Factors
keywords: Accelerometry; Gait events; Inertial sensor; Temporal parameters; Trunk