Motion Prediction Using Dual Kalman Filter for Robust Beating Heart Tracking

Abstract : A novel prediction method for robust beating heart tracking is proposed. The dual time-varying Fourier series is used to model the heart motion. The frequency parameters and Fourier coefficients in the model are estimated respectively by using a dual Kalman filter scheme. The instantaneous frequencies of breathing and heartbeat motion are measured online from the 3D trajectory of the point of interest using an orthogonal decomposition algorithm. The proposed method is evaluated based on both the simulated signals and the real motion signals, which are measured from the videos recorded using the da Vinci surgical system.
Type de document :
Communication dans un congrès
EMBC: Engineering in Medicine and Biology Conference, Aug 2015, Milan, Italy. 37th International Conference of the IEEE Engineering in Medicine and Biology Society, pp.4875-4878, 2015, 〈10.1109/EMBC.2015.7319485〉
Liste complète des métadonnées

https://hal-lirmm.ccsd.cnrs.fr/lirmm-01275441
Contributeur : Chao Liu <>
Soumis le : mercredi 17 février 2016 - 14:35:59
Dernière modification le : mercredi 5 septembre 2018 - 10:54:01

Identifiants

Collections

Citation

Bo Yang, Chao Liu, Philippe Poignet, Zheng Wenfeng, Shan Liu. Motion Prediction Using Dual Kalman Filter for Robust Beating Heart Tracking. EMBC: Engineering in Medicine and Biology Conference, Aug 2015, Milan, Italy. 37th International Conference of the IEEE Engineering in Medicine and Biology Society, pp.4875-4878, 2015, 〈10.1109/EMBC.2015.7319485〉. 〈lirmm-01275441〉

Partager

Métriques

Consultations de la notice

124