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General information |
| Author |
Liang, Fan; Meng, Xiaofeng; Yu, Yang |
| Published |
InTech Open Access Publisher, 2013
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| Abstract |
A robotic tool can enable a surgeon to conduct
off‐pump coronary artery graft bypass surgery on a
beating heart. The robotic tool actively alleviates the
relative motion between the point of interest (POI) on the
heart surface and the surgical tool and allows the surgeon
to operate as if the heart were stationary. Since the
beating heart‘s motion is relatively high‐band, with
nonlinear and nonstationary characteristics, it is difficult
to follow. Thus, precise beating heart motion prediction is
necessary for the tracking control procedure during the
surgery. In the research presented here, we first observe
that Electrocardiography (ECG) signal contains the causal
phase information on heart motion and non‐stationary
heart rate dynamic variations. Then, we investigate the
relationship between ECG signal and beating heart
motion using Granger Causality Analysis, which
describes the feasibility of the improved prediction of
heart motion. Next, we propose a nonlinear time‐varying
multivariate vector autoregressive (MVAR) model based
adaptive prediction method. In this model, the significant
correlation between ECG and heart motion enables the
improvement of the prediction of sharp changes in heart
motion and the approximation of the motion with
sufficient detail. Dual Kalman Filters (DKF) estimate the
states and parameters of the model, respectively. Last, we
evaluate the proposed algorithm through comparative
experiments using the two sets of collected vivo data. |
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International Journal of Advanced Robotic Systems
Author: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Published: 2004
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