On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator.
Gait analysis can provide valuable information on a person's condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts for calibration, operation and/or to place sensors on volunteers. Alternatively, mobility support devices like rollators can be equipped with onboard sensors to monitor gait parameters, while users perform their Activities of Daily Living. Gait analysis in rollators may use odometry and force sensors in the handlebars. However, force based estimation of gait parameters is less accurate than traditional methods, especially when rollators are not properly used. This paper presents an evaluation of force based gait analysis using a smart rollator on different groups of users to determine when this methodology is applicable. In a second stage, the rollator is used in combination with two lab-based gait analysis systems to assess the rollator estimation error. Our results show that: (i) there is an inverse relation between the variance in the force difference between handlebars and support on the handlebars-related to the user condition-and the estimation error; and (ii) this error is lower than 10% when the variation in the force difference is above 7 N. This lower limit was exceeded by the 95.83% of our challenged volunteers. In conclusion, rollators are useful for gait characterization as long as users really need the device for ambulation.
Department of Electronic Technology, University of Malaga, 29071 Malaga, Spain. jballesteros@uma.es.
Joaquin
J
Ballesteros
Department of Electronic Technology, University of Malaga, 29071 Malaga, Spain. acurdiales@uma.es.
Cristina
C
Urdiales
Department of Automatic Control, Polytechnic University of Catalonia, 08034 Barcelona, Spain. antonio.b.martinez@upc.edu.
Antonio B
AB
Martinez
MOVE Research Institute Amsterdam, Department of Human Movement Sciences, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands. j.van.dieen@vu.nl.
Jaap H
JH
van Dieën
D000203:Activities of Daily Living; D015374:Biosensing Techniques / Q000379:methods*; D004867:Equipment Design; D005684:Gait / Q000502:physiology*; D006801:Humans; D012656:Self-Help Devices
assistive devices; disability profiling; gait characterization; smart rollator