Teaching Microsurgical Breast Reconstruction—A Retrospective Cohort Study

Microsurgical breast reconstruction demands the highest level of expertise in both reconstructive and aesthetic plastic surgery. Implementation of such a complex surgical procedure is generally associated with a learning curve defined by higher complication rates at the beginning. The aim of this study was to present an approach for teaching deep inferior epigastric artery perforator (DIEP) and transverse upper gracilis (TUG) flap breast reconstruction, which can diminish complications and provide satisfying outcomes from the beginning. DIEP and TUG flap procedures for breast reconstruction were either performed by a senior surgeon (>200 DIEP/TUG, ”no-training group”), or taught to one of five trainees (>80 breast surgeries; >50 free flaps) in a step-wise approach. The latter were either performed by the senior surgeon, and a trainee was assisting the surgery (“passive training”); by the trainee, and a senior surgeon was supervising (“active training”); or by the trainee without a senior surgeon (“after training”). Surgeries of each group were analyzed regarding OR-time, complications, and refinement procedures. A total of 95 DIEP and 93 TUG flaps were included into this study. Before the first DIEP/TUG flap without supervision, each trainee underwent a mean of 6.8 DIEP and 7.3 TUG training surgeries (p > 0.05). Outcome measures did not reveal any statistically significant differences (passive training/active training/after training/no-training: OR-time (min): DIEP: 331/351/338/304 (p > 0.05); TUG: 229/214/239/217 (p > 0.05); complications (n): DIEP: 6/13/16/11 (p > 0.05); TUG: 6/19/23/11 (p > 0.05); refinement procedures (n): DIEP:71/63/49/44 (p > 0.05); TUG: 65/41/36/56 (p > 0.05)), indicating safe and secure implementation of this step-wise training approach for microsurgical breast reconstruction in both aesthetic and reconstructive measures. Of note, despite being a perforator flap, DIEP flap required no more training than TUG flap, highlighting the importance of flap inset at the recipient site.

Design and Passive Training Control of Elbow Rehabilitation Robot

In this paper, a rehabilitation robot driven by multifilament muscles is designed based on the rehabilitation robot motion model and a system elbow joint model. The passive training mode of rehabilitation robots were researched, and active disturbance rejection control (ADRC) leveraged to improve the tracking angle of robot joints. In the no-load motion simulation of rehabilitation robots, disturbances are added to the control variables to complete the ADRC and Proportional Integral Differential (PID) position control simulation. The simulation results indicate that the auto disturbance rejection control can quickly keep up the expected signal without overshoot, solve the contradiction between the system rapidity and overshoot. Moreover, it can better suppress the interference even if the external load changes. The upper limbs of the human body are used as the load on the robot body to complete the simulation of ADRC and PID position control objects of different weights. Finally, a passive rehabilitation training experiment was conducted to verify the safety of the rehabilitation robot, the rationality, comfort, and robustness of the mechanism design, and the effectiveness and feasibility of the ADRC.

A Cable-Driven Three-DOF Wrist Rehabilitation Exoskeleton With Improved Performance

This paper developed a cable-driven three-degree-of-freedom (DOF) wrist rehabilitation exoskeleton actuated by the distributed active semi-active (DASA) system. Compared with the conventional cable-driven robots, the workspace of this robot is increased greatly by adding the rotating compensation mechanism and by optimizing the distribution of the cable attachment points. In the meanwhile, the efficiency of the cable tension is improved, and the parasitic force (the force acting on the joint along the limb) is reduced. Besides, in order to reduce the effects of compliant elements (e.g., cables or Bowden cables) between the actuators and output, and to improve the force bandwidth, we designed the DASA system composed of one geared DC motor and four magnetorheological (MR) clutches, which has low output inertia. A fast unbinding strategy is presented to ensure safety in abnormal conditions. A passive training algorithm and an assist-as-needed (AAN) algorithm were implemented to control the exoskeleton. Several experiments were conducted on both healthy and impaired subjects to test the performance and effectiveness of the proposed system for rehabilitation. The results show that the system can meet the needs of rehabilitation training for workspace and force-feedback, and provide efficient active and passive training.

Internal Model Control and Experimental Study of Ankle Rehabilitation Robot

SUMMARYIn the present work, the ankle rehabilitation robot (ARR) dynamic model that implements a new series of connection control strategies is introduced. The dynamic models are presented in this regard. This model analyzes the robot LuGre friction model and the nonlinear disturbance model. To improve the ARR system’s rapidity and robustness, a composite 2-degree of freedom (2-DOF) internal model control (IMC) controller is presented. The control performance of the compound 2-DOF IMC controller is simulated and analyzed in the present work. The simulation shows that the composite 2-DOF IMC controller has high following performance. For practical testing purposes, 1-DOF passive training and predetermined trajectory following have been completed for different swing amplitudes and frequencies. Moreover, the thrust and tension torque of the robotic dynamic and static loading characteristics are studied in active control mode. The experimental results show the effectiveness of passive training of the given trajectory and impedance training active control strategy. This paper gives the specific functions of ARR.

Development, Dynamic Modeling, and Multi-Modal Control of a Therapeutic Exoskeleton for Upper Limb Rehabilitation Training

Robot-assisted training is a promising technology in clinical rehabilitation providing effective treatment to the patients with motor disability. In this paper, a multi-modal control strategy for a therapeutic upper limb exoskeleton is proposed to assist the disabled persons perform patient-passive training and patient-cooperative training. A comprehensive overview of the exoskeleton with seven actuated degrees of freedom is introduced. The dynamic modeling and parameters identification strategies of the human-robot interaction system are analyzed. Moreover, an adaptive sliding mode controller with disturbance observer (ASMCDO) is developed to ensure the position control accuracy in patient-passive training. A cascade-proportional-integral-derivative (CPID)-based impedance controller with graphical game-like interface is designed to improve interaction compliance and motivate the active participation of patients in patient-cooperative training. Three typical experiments are conducted to verify the feasibility of the proposed control strategy, including the trajectory tracking experiments, the trajectory tracking experiments with impedance adjustment, and the intention-based training experiments. The experimental results suggest that the tracking error of ASMCDO controller is smaller than that of terminal sliding mode controller. By optimally changing the impedance parameters of CPID-based impedance controller, the training intensity can be adjusted to meet the requirement of different patients.