scholarly journals A new collaborative-shared control strategy for continuous elder/robot assisted navigation

2008 ◽  
Vol 7 (2) ◽  
Author(s):  
C. Urdiales ◽  
J. Peula ◽  
C. Barrué ◽  
E. Pérez
Keyword(s):  
Control Strategy ◽  
Shared Control ◽  
Robot Assisted ◽  
Assisted Navigation

scholarly journals Robot-Assisted Navigation versus Computer-Assisted Navigation in Primary Total Knee Arthroplasty: Efficiency and Accuracy

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Tanner C. Clark ◽  
Frank H. Schmidt
Keyword(s):  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Primary Total Knee Arthroplasty ◽  
Secondary Outcome ◽  
Computer Assisted ◽  
Robot Assisted ◽  
Tourniquet Time ◽  
Assisted Navigation ◽  
Total Knee ◽  
Primary Total Knee

Background. Since the introduction of robot-assisted navigation in primary total knee arthroplasty (TKA), there has been little research conducted examining the efficiency and accuracy of the system compared to computer-assisted navigation systems. Objective. To compare the efficiency and accuracy of Praxim robot-assisted navigation (RAN) and Stryker computer-assisted navigation (CAN) in primary TKA. Methods. This was a retrospective study consisting of 52 patients who underwent primary TKA utilizing RAN and 29 patients utilizing CAN. The primary outcome measure was navigation time. Secondary outcome measures included intraoperative final mechanical axis alignment, intraoperative robot-assisted bone cut accuracy, tourniquet time, and hospitalization length. Results. RAN navigation times were, on average, 9.0 minutes shorter compared to CAN after adjustment. The average absolute intraoperative malalignment was 0.5° less in the RAN procedures compared to the CAN procedures after adjustment. Patients in the RAN group tended to be discharged 0.6 days earlier compared to patients in the CAN group after adjustment. Conclusions. Among patients undergoing TKA, there was decreased navigation time, decreased final malalignment, and decreased hospitalization length associated with the use of RAN when compared to CAN independent of age, BMI, and pre-replacement alignment.

scholarly journals Evaluation of Telerobotic Shared Control Strategy for Efficient Single-Cell Manipulation

2012 ◽  
Vol 9 (2) ◽  
pp. 402-406 ◽  
Author(s):  
Jungsik Kim ◽  
Hamid Ladjal ◽  
David Folio ◽  
Antoine Ferreira ◽  
Jung Kim
Keyword(s):  
Single Cell ◽  
Control Strategy ◽  
Shared Control ◽  
Cell Manipulation ◽  
Single Cell Manipulation

scholarly journals Customizing Robot-Assisted Passive Neurorehabilitation Exercise Based on Teaching Training Mechanism

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yingnan Lin ◽  
Qingming Qu ◽  
Yifang Lin ◽  
Jieying He ◽  
Qi Zhang ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Control Strategy ◽  
Early Stage ◽  
Passive Movement ◽  
Interactive System ◽  
Stroke Survivors ◽  
Robot Assisted ◽  
Patient Centeredness ◽  
Training Trajectory ◽  
Clinical Experiments

Passive movement is an important mean of rehabilitation for stroke survivors in the early stage or with greater paralysis. The upper extremity robot is required to assist therapists with passive movement during clinical rehabilitation, while customizing is one of the crucial issues for robot-assisted upper extremity training, which fits the patient-centeredness. Robot-assisted teaching training could address the need well. However, the existing control strategies of teaching training are usually commanded by position merely, having trouble to achieve the efficacy of treatment by therapists. And deficiency of flexibility and compliance comes to the training trajectory. This research presents a novel motion control strategy for customized robot-assisted passive neurorehabilitation. The teaching training mechanism is developed to coordinate the movement of the shoulder and elbow, ensuring the training trajectory correspondence with human kinematics. Furthermore, the motion trajectory is adjusted by arm strength to realize dexterity and flexibility. Meanwhile, the torque sensor employed in the human-robot interactive system identifies movement intention of human. The goal-directed games and feedbacks promote the motor positivity of stroke survivors. In addition, functional experiments and clinical experiments are investigated with a healthy adult and five recruited stroke survivors, respectively. The experimental results present that the suggested control strategy not only serves with safety training but also presents rehabilitation efficacy.

Master-slave control and evaluation of force sensing for robot-assisted minimally invasive surgery

2020 ◽  
Vol 47 (6) ◽  
pp. 903-914
Author(s):  
Kun Li ◽  
Shuai Ji ◽  
Guojun Niu ◽  
Yue Ai ◽  
Bo Pan ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Control Strategy ◽  
Force Feedback ◽  
Ex Vivo ◽  
Force Sensing ◽  
Surgical Instrument ◽  
Blunt Dissection ◽  
Robot Assisted ◽  
Interaction Forces ◽  
Content Type

Purpose Existing robot-assisted minimally invasive surgery (RMIS) system lacks of force feedback, and it cannot provide the surgeon with interaction forces between the surgical instruments and patient’s tissues. This paper aims to restore force sensation for the RMIS system and evaluate effect of force sensing in a master-slave manner. Design/methodology/approach This paper presents a four-DOF surgical instrument with modular joints and six-axis force sensing capability and proposes an incremental position mode master–slave control strategy based on separated position and orientation to reflect motion of the end of master manipulator to the end of surgical instrument. Ex-vivo experiments including tissue palpation and blunt dissection are conducted to verify the effect of force sensing for the surgical instrument. An experiment of trajectory tracking is carried out to test precision of the control strategy. Findings Results of trajectory tracking experiment show that this control strategy can precisely reflect the hand motion of the operator, and the results of the ex-vivo experiments including tissue palpation and blunt dissection illustrate that this surgical instrument can measure the six-axis interaction forces successfully for the RMIS. Originality/value This paper addresses the important role of force sensing and force feedback in RMIS, clarifies the feasibility to apply this instrument prototype in RMIS for force sensing and provides technical support of force feedback for further clinical application.

Hierarchical safety supervisory control strategy for robot-assisted rehabilitation exercise

Robotica ◽  
2013 ◽  
Vol 31 (5) ◽  
pp. 757-766 ◽  
Author(s):  
Lizheng Pan ◽  
Aiguo Song ◽  
Guozheng Xu ◽  
Huijun Li ◽  
Baoguo Xu ◽  
...  
Keyword(s):  
Control Strategy ◽  
Therapeutic Process ◽  
Hierarchical Control ◽  
Hierarchical Architecture ◽  
Robot Assisted ◽  
Low Level ◽  
Emergency Situations ◽  
Impaired Limb ◽  
High Level ◽  
Rehabilitation Exercise

SUMMARYClinical outcomes have shown that robot-assisted rehabilitation is potential of enhancing quantification of therapeutic process for patients with stroke. During robotic rehabilitation exercise, the assistive robot must guarantee subject's safety in emergency situations, e.g., sudden spasm or twitch, abruptly severe tremor, etc. This paper presents a hierarchical control strategy, which is proposed to improve the safety and robustness of the rehabilitation system. The proposed hierarchical architecture is composed of two main components: a high-level safety supervisory controller (SSC) and low-level position-based impedance controller (PBIC). The high-level SSC is used to automatically regulate the desired force for a reasonable disturbance or timely put the emergency mode into service according to the evaluated physical state of training impaired limb (PSTIL) to achieve safety and robustness. The low-level PBIC is implemented to achieve compliance between the robotic end-effector and the impaired limb during the robot-assisted rehabilitation training. The results of preliminary experiments demonstrate the effectiveness and potentiality of the proposed method for achieving safety and robustness of the rehabilitation robot.

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