Miniaturized wearable Inertial Measurement Units (IMU) offer new opportunities for the functional assessment of motor functions for medicine, sport, and ergonomics. Sparse reliability validation studies have been conducted without a common specific approach and protocol. A set of guidelines to design validation protocol for these systems is proposed hereafter. They are based on the comparison between video analysis and the gold standard optoelectronic motion capture system for Gait Analysis (GA). A setup of the protocol has been applied to a wearable device implementing an inertial measurement unit and a dedicated harmonic oscillator kinematic model of the center of mass. In total, 10 healthy volunteers took part in the study, and four trials of walking at a self-selected speed and step length have been simultaneously recorded by the two systems, analyzed, and compared blindly (40 datasets). The model detects the steps and the foot which supports body weight. The stride time and the cadence have a mean absolute percentage error of 5.7% and 4.9%, respectively. The mean absolute percentage error in the measurement of step's length and step's speed is 5.6% and 13.5%, respectively. Results confirm that the proposed methodology is complete and effective. It is demonstrated that the developed wearable system allows for a reliable assessment of human gait spatio-temporal parameters. Therefore, the goal of this paper is threefold. The first goal is to present and define structured Protocol Design Guidelines, where the related setup is implemented for the validation of wearable IMU systems particularly dedicated to GA and gait monitoring. The second goal is to apply these Protocol Design Guidelines to a case study in order to verify their feasibility, user-friendliness, and efficacy. The third goal is the validation of our biomechanical kinematic model with the gold standard reference.

Validation of a wearable IMU system for gait analysis: Protocol and application to a new system

Negrini F.;
2018-01-01

Abstract

Miniaturized wearable Inertial Measurement Units (IMU) offer new opportunities for the functional assessment of motor functions for medicine, sport, and ergonomics. Sparse reliability validation studies have been conducted without a common specific approach and protocol. A set of guidelines to design validation protocol for these systems is proposed hereafter. They are based on the comparison between video analysis and the gold standard optoelectronic motion capture system for Gait Analysis (GA). A setup of the protocol has been applied to a wearable device implementing an inertial measurement unit and a dedicated harmonic oscillator kinematic model of the center of mass. In total, 10 healthy volunteers took part in the study, and four trials of walking at a self-selected speed and step length have been simultaneously recorded by the two systems, analyzed, and compared blindly (40 datasets). The model detects the steps and the foot which supports body weight. The stride time and the cadence have a mean absolute percentage error of 5.7% and 4.9%, respectively. The mean absolute percentage error in the measurement of step's length and step's speed is 5.6% and 13.5%, respectively. Results confirm that the proposed methodology is complete and effective. It is demonstrated that the developed wearable system allows for a reliable assessment of human gait spatio-temporal parameters. Therefore, the goal of this paper is threefold. The first goal is to present and define structured Protocol Design Guidelines, where the related setup is implemented for the validation of wearable IMU systems particularly dedicated to GA and gait monitoring. The second goal is to apply these Protocol Design Guidelines to a case study in order to verify their feasibility, user-friendliness, and efficacy. The third goal is the validation of our biomechanical kinematic model with the gold standard reference.
2018
2018
Assessment protocol; Biomechanical modeling; Functional analysis; Gait analysis; Human kinematics; Reliability; System validation; Wearable sensors
Fusca, M.; Negrini, F.; Perego, P.; Magoni, L.; Molteni, F.; Andreoni, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2131406
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