Continuous identification of gait phase for robotics and rehabilitation using microsensors

Rodolphe Heliot (1, 2) , Roger Pissard-Gibollet (3) , Bernard Espiau (4) , François Favre-Reguilion (2)

1 BIPOP - Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems
2 CEA-LETI - Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information
3 SED [Grenoble] - Service Expérimentation et Développement
4 Inria Grenoble - Rhône-Alpes

Using microsensors for the robust and accurate analysis of human posture or gait is an interesting opportunity for rehabilitation and robotics applications. This paper describes a feasibility study in which the possibility of using a new type of embedded microsensors, based on the coupling of accelerometers and magnetometers, and developed by CEA/LETI is investigated. This study consists in identifying what part of the gait cycle is active by using a reconstruction of the knee joint angle by two microsensors fixed on tibia and thigh, during a steady- state sagittal walk. More than just an identification of a few gait states, this approach allows us to continuously extract the current position on the gait cycle. We compare the reconstructed knee joint angle with a stored reference taking into account uncertainties on the velocity and perturbations of the terrestrial magnetic field. To accurately identify the phase of the gait movement, we fuse different simple and complementary meth- ods: morphomathematics, cyclogram analysis, wavelet transform, qualitative analysis, crosscorrelation. These results encourage us to extend this work to explore the possibility of recognition of a larger set of human movements using more sensors and improved algorithms of signal processing.

Mots clés: gait analysis; mathematical morphology; medical robotics; patient rehabilitation; robot kinematics; wavelet transforms; accelerometer; cyclogram analysis; embedded microsensors; gait cycle; gait movement; gait phase identification; gait state; human movement; human posture; magnetometer; morphomathematics; qualitative analysis; reconstructed knee joint angle; rehabilitation; robotics; signal processing; steady-state sagittal walk; thigh; tibia; wavelet transform; Accelerometers; Couplings; Humans; Knee; Magnetic analysis; Magnetometers; Microsensors; Rehabilitation robotics; Robustness; Signal processing algorithms

Domaines: Robotique [cs.RO]

Rodolphe Heliot, Roger Pissard-Gibollet, Bernard Espiau, François Favre-Reguilion. Continuous identification of gait phase for robotics and rehabilitation using microsensors. Advanced Robotics, 2005. ICAR '05. Proceedings., 12th International Conference on, Jul 2005, Seattle, United States. pp.686-691, ⟨10.1109/ICAR.2005.1507483⟩. ⟨hal-00921282⟩