Cala, S. J., C. M. Kenyon, G. Ferrigno, P. Carnevali, A. Aliverti, A. Pedotti, P. T. Macklem, and D. F. Rochester. Chest wall and lung volume estimation by optical reflectance motion analysis. J. Appl. Physiol. 81(6): 2680–2689, 1996.—Estimation of chest wall motion by surface measurements only allows one-dimensional measurements of the chest wall. We have assessed an optical reflectance system (OR), which tracks reflective markers in three dimensions (3-D) for respiratory use. We used 86 (6-mm-diameter) hemispherical reflective markers arranged circumferentially on the chest wall in seven rows between the sternal notch and the anterior superior iliac crest in two normal standing subjects. We calculated the volume of the entire chest wall and compared inspired and expired volumes with volumes obtained by spirometry. Marker positions were recorded by four TV cameras; two were 4 m in front of and two were 4 m behind the subject. The TV signals were sampled at 100 Hz and combined with grid calibration parameters on a personal computer to obtain the 3-D coordinates of the markers. Chest wall surfaces were reconstructed by triangulation through the point data, and chest wall volume was calculated. During tidal breathing and vital capacity maneuvers and during CO₂-stimulated hyperpnea, there was a very close correlation of the lung volumes (Vl) estimated by spirometry [Vl(SP)] and OR [Vl(OR)]. Regression equations of Vl(OR) ( y) vs. Vl(SP) ( x,btps in liters) for the two subjects were given by y = 1.01 x − 0.01 ( r = 0.996) and y = 0.96 x + 0.03 ( r = 0.997), and by y = 1.04 x + 0.25 ( r = 0.97) and y = 0.98 x + 0.14 ( r = 0.95) for the two maneuvers, respectively. We conclude spirometric volumes can be estimated very accurately and directly from chest wall surface markers, and we speculate that OR may be usefully applied to calculations of chest wall shape, regional volumes, and motion analysis.

Aliverti, A., S. J. Cala, R. Duranti, G. Ferrigno, C. M. Kenyon, A. Pedotti, G. Scano, P. Sliwinski, Peter T. Macklem, and S. Yan. Human respiratory muscle actions and control during exercise.J. Appl. Physiol. 83(4): 1256–1269, 1997.—We measured pressures and power of diaphragm, rib cage, and abdominal muscles during quiet breathing (QB) and exercise at 0, 30, 50, and 70% maximum workload (W˙max) in five men. By three-dimensional tracking of 86 chest wall markers, we calculated the volumes of lung- and diaphragm-apposed rib cage compartments (Vrc,p and Vrc,a, respectively) and the abdomen (Vab). End-inspiratory lung volume increased with percentage of W˙max as a result of an increase in Vrc,p and Vrc,a. End-expiratory lung volume decreased as a result of a decrease in Vab. ΔVrc,a/ΔVab was constant and independent ofW˙max. Thus we used ΔVab/time as an index of diaphragm velocity of shortening. From QB to 70%W˙max, diaphragmatic pressure (Pdi) increased ∼2-fold, diaphragm velocity of shortening 6.5-fold, and diaphragm workload 13-fold. Abdominal muscle pressure was ∼0 during QB but was equal to and 180° out of phase with rib cage muscle pressure at all percent W˙max. Rib cage muscle pressure and abdominal muscle pressure were greater than Pdi, but the ratios of these pressures were constant. There was a gradual inspiratory relaxation of abdominal muscles, causing abdominal pressure to fall, which minimized Pdi and decreased the expiratory action of the abdominal muscles on Vrc,a gradually, minimizing rib cage distortions. We conclude that from QB to 0% W˙max there is a switch in respiratory muscle control, with immediate recruitment of rib cage and abdominal muscles. Thereafter, a simple mechanism that increases drive equally to all three muscle groups, with drive to abdominal and rib cage muscles 180° out of phase, allows the diaphragm to contract quasi-isotonically and act as a flow generator, while rib cage and abdominal muscles develop the pressures to displace the rib cage and abdomen, respectively. This acts to equalize the pressures acting on both rib cage compartments, minimizing rib cage distortion .

Learning manipulation skills from open surgery provides more flexible access to the organ targets in the abdomen cavity and this could make the surgical robot working in a highly intelligent and friendly manner. Teaching by demonstration (TbD) is capable of transferring the manipulation skills from human to humanoid robots by employing active learning of multiple demonstrated tasks. This work aims to transfer motion skills from multiple human demonstrations in open surgery to robot manipulators in robot-assisted minimally invasive surgery (RA-MIS) by using TbD. However, the kinematic constraint should be respected during the performing of the learned skills by using a robot for minimally invasive surgery. In this article, we propose a novel methodology by integrating the cognitive learning techniques and the developed control techniques, allowing the robot to be highly intelligent to learn senior surgeons' skills and to perform the learned surgical operations in semiautonomous surgery in the future. Finally, experiments are performed to verify the efficiency of the proposed strategy, and the results demonstrate the ability of the system to transfer human manipulation skills to a robot in RA-MIS and also shows that the remote center of motion (RCM) constraint can be guaranteed simultaneously. Note to Practitioners-This article is inspired by limited access to the manipulation of laparoscopic surgery under a kinematic constraint at the point of incision. Current commercial surgical robots are mostly operated by teleoperation, which is representing less autonomy on surgery. Assisting and enhancing the surgeon's performance by increasing the autonomy of surgical robots has fundamental importance. The technique of teaching by demonstration (TbD) is capable of transferring the manipulation skills from human to humanoid robots by employing active learning of multiple demonstrated tasks. With the improved ability to interact with humans, such as flexibility and compliance, the new generation of serial robots becomes more and more popular in nonclinical research. Thus, advanced control strategies are required by integrating cognitive functions and learning techniques into the processes of surgical operation between robots, surgeon, and minimally invasive surgery (MIS). In this article, we propose a novel methodology to model the manipulation skill from multiple demonstrations and execute the learned operations in robot-assisted minimally invasive surgery (RA-MIS) by using a decoupled controller to respect the remote center of motion (RCM) constraint exploiting the redundancy of the robot. The developed control scheme has the following functionalities: 1) it enables the 3-D manipulation skill modeling after multiple demonstrations of the surgical tasks in open surgery by integrating dynamic time warping (DTW) and Gaussian mixture model (GMM)-based dynamic movement primitive (DMP) and 2) it maintains the RCM constraint in a smaller safe area while performing the learned operation in RA-MIS. The developed control strategy can also be potentially used in other industrial applications with a similar scenario.

An improved human-robot collaborative control (IHRCC) scheme is proposed in teleoperated Minimally Invasive Surgery (MIS) scenario, based on a hierarchical operational space formulation of a seven degrees of freedom (DoFs) redundant robot. Redundancy is exploited to guarantee a remote center of motion (RCM) constraint and to provide a compliant behavior for the medical staff. Based on the implemented hierarchical control framework, an RCM constraint and a safe constraint are applied to the null-space motion to achieve the surgical tasks with human-robot interaction. Due to the physical interactions, safety and accuracy of the surgery may be affected. The control framework integrates adaptive compensator to enhance the accuracy of surgical tip and to maintain the RCM constraint in a decoupled way avoiding any physical interactions. The system performance is verified on a patient phantom. Compared with the methods proposed in the literature, results show that the accuracy of both RCM constraint and surgical tip are improved. The compliant swivel motion of the robot arm is also constrained in a defined area, and the interaction force on the abdominal wall become smaller.