Towards active tracking of beating heart motion in the presence of arrhythmia for robotic assisted beating heart surgery

Name: Towards active tracking of beating heart motion in the presence of arrhythmia for robotic assisted beating heart surgery
Author: Tuna, E. E., Karimov, J. H., Liu, T., Bebek, Özkan, Fukamachi, K., Çavuşoğlu, M. C.

İsim	Towards active tracking of beating heart motion in the presence of arrhythmia for robotic assisted beating heart surgery
Yazar	Tuna, E. E., Karimov, J. H., Liu, T., Bebek, Özkan, Fukamachi, K., Çavuşoğlu, M. C.
Basım Tarihi:	2014-07-21
Basım Yeri	- Plos
Konu	Atrial-fibrillation, Predictive control, Cardiac-surgery, Sonomicrometry, Feasiblity, Algorithms
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1932-6203
Kayıt Numarası	5ceea36c-05e8-43a1-bc15-44829882948b
Lokasyon	Mechanical Engineering
Tarih	2014-07-21
Örnek Metin	In robotic assisted beating heart surgery, the control architecture for heart motion tracking has stringent requirements in terms of bandwidth of the motion that needs to be tracked. In order to achieve sufficient tracking accuracy, feed-forward control algorithms, which rely on estimations of upcoming heart motion, have been proposed in the literature. However, performance of these feed-forward motion control algorithms under heart rhythm variations is an important concern. In their past work, the authors have demonstrated the effectiveness of a receding horizon model predictive control-based algorithm, which used generalized adaptive predictors, under constant and slowly varying heart rate conditions. This paper extends these studies to the case when the heart motion statistics change abruptly and significantly, such as during arrhythmias. A feasibility study is carried out to assess the motion tracking capabilities of the adaptive algorithms in the occurrence of arrhythmia during beating heart surgery. Specifically, the tracking performance of the algorithms is evaluated on prerecorded motion data, which is collected in vivo and includes heart rhythm irregularities. The algorithms are tested using both simulations and bench experiments on a three degree-of-freedom robotic test bed. They are also compared with a position-plus-derivative controller as well as a receding horizon model predictive controller that employs an extended Kalman filter algorithm for predicting future heart motion.
DOI	10.1371/journal.pone.0102877
Cilt	9

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Towards active tracking of beating heart motion in the presence of arrhythmia for robotic assisted beating heart surgery

Yazar Tuna, E. E., Karimov, J. H., Liu, T., Bebek, Özkan, Fukamachi, K., Çavuşoğlu, M. C.

Basım Tarihi 2014-07-21

Basım Yeri - Plos

Konu Atrial-fibrillation, Predictive control, Cardiac-surgery, Sonomicrometry, Feasiblity, Algorithms

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1932-6203

Kayıt Numarası 5ceea36c-05e8-43a1-bc15-44829882948b

Lokasyon Mechanical Engineering

Tarih 2014-07-21

Örnek Metin In robotic assisted beating heart surgery, the control architecture for heart motion tracking has stringent requirements in terms of bandwidth of the motion that needs to be tracked. In order to achieve sufficient tracking accuracy, feed-forward control algorithms, which rely on estimations of upcoming heart motion, have been proposed in the literature. However, performance of these feed-forward motion control algorithms under heart rhythm variations is an important concern. In their past work, the authors have demonstrated the effectiveness of a receding horizon model predictive control-based algorithm, which used generalized adaptive predictors, under constant and slowly varying heart rate conditions. This paper extends these studies to the case when the heart motion statistics change abruptly and significantly, such as during arrhythmias. A feasibility study is carried out to assess the motion tracking capabilities of the adaptive algorithms in the occurrence of arrhythmia during beating heart surgery. Specifically, the tracking performance of the algorithms is evaluated on prerecorded motion data, which is collected in vivo and includes heart rhythm irregularities. The algorithms are tested using both simulations and bench experiments on a three degree-of-freedom robotic test bed. They are also compared with a position-plus-derivative controller as well as a receding horizon model predictive controller that employs an extended Kalman filter algorithm for predicting future heart motion.

DOI 10.1371/journal.pone.0102877

Cilt 9