This work addresses the gravity balancing of a 2R1T (2 rotations – 1 translation) mechanism with remote center of motion. A previously developed balancing solution is modified and applied to a prototype, and test results are presented. The mechanism is an endoscope holder for minimally invasive transnasal pituitary gland surgery. In this surgery, the endoscope is inserted through a nostril of the patient through a natural path to the pituitary gland. During the surgery, it is vital for the manipulator to be statically balanced so that in case of a motor failure, the patient is protected against any harmful motion of the endoscope. Additionally, static balancing takes the gravitational load from the actuators and hence facilitates the control of the mechanism. The mechanism is a 2URRR-URR type parallel manipulator with three legs. The payload mass is distributed to the legs on the sides. By using counter-masses for two links of each leg, the center of mass of each leg is lumped on the proximal link which simplifies the problem of balancing of a two degree-of-freedom inverted pendulum. The two proximal links with the lumped mass are statically balanced via springs. Dynamic simulations indicate that when the mechanism is statically balanced, generated actuator torques are reduced by 93.5%. Finally, the balancing solution is implemented on the prototype of the manipulator. The tests indicate that the manipulator is statically balanced within its task space when the actuators are disconnected. When the actuators are connected, the torque requirements decrease by about 37.8% with balancing.

Exoskeleton robot can assist people and reduce energy consumption when they walk with heavy weight, so as to protect their health and travel longer distances. This work analyzes the cross gait during walking and designs a dual-drive four joint time-sharing assistance exoskeleton system, which controls the four joints through two motors to realize the assistance to the wearer’s movement process. The control curve and adaptive control algorithm are designed to help different people with various walking gaits and speeds, the effectiveness of exoskeleton system is proved by testing metabolism. When the exoskeleton wearer carries 25 kg weight (load equal to 36% of body mass) and travels at the average speed of 5 km/h, the metabolic rate of the exoskeleton wearers decreases by an average of 7.79%, the reduction magnitude is comparable to the effect of taking off 7.33 kg during walking.

Clinical observations and subjective judgements have traditionally been used to evaluate patients with muscular and neurological disorders. As a result, identifying and analyzing functional improvements are difficult, especially in the absence of expertise. Quantitative assessment, which serves as the motivation for this study, is an essential prerequisite to forecast the task of the rehabilitation device in order to develop rehabilitation training. This work provides a quantitative assessment tool for muscle weakness in the human upper limbs for robotic-assisted rehabilitation. The goal is to map the assessment metrics to the recommended rehabilitation exercises. Measurable interaction forces and muscle correlation factors are the selected parameters to design a framework for muscular nerve cell condition detection and appropriate limb trajectory selection. In this work, a data collection setup is intended for extracting muscle intervention and assessment using MyoMeter, Goniometer and surface electromyography data for upper limbs. Force signals and human physiological response data are evaluated and categorized to infer the relevant progress. Based upon the most influencing muscles, curve fitting is performed. Trajectory-based data points are collected through a scaled geometric Open-Sim musculoskeletal model that fits the subject’s anthropometric data. These data are found to be most suitable to prescribe relevant exercise and to design customized robotic assistance. Case studies demonstrate the approach’s efficacy, including optimally synthesized automated configuration for the desired trajectory.

Cable-driven parallel robots (CDPRs) are still gaining attention thanks to their interesting characteristics compared to serial or classic parallel manipulators. However, the limited range of rotation of their end-effectors reduces their application fields to predominantly translational movements. In this context, the issue of extending the rotational workspace of a CDPR while maintaining a compact robot structure is addressed in this paper. This work is motivated by the need to find the optimal CDPR for upper limb rehabilitation allowing to assist the patient’s hand along a set of prescribed tasks. Firstly, a reconfigurable robot, where the motors’ locations are movable, is proposed in order to help reaching all the prescribed poses. Although this solution presents promising results compared to classical CDPRs, it involves a sizable robot structure inadequate to rehabilitation application. To improve the obtained solution, another approach is proposed, based on combining the large translational workspace of CDPRs and the large rotational workspace of serial manipulators. The optimal structure of a hybrid robot will be considered for the prototype design.

Although robotic or robot-assisted surgery has been increasingly used by many surgical disciplines, its application in cranial or skull base surgery is still in its infancy. Master-slave teleoperation setting of these robotic systems enables these surgical procedures to be replicated in a virtual reality environment for surgeon training purposes. A variety of teleoperation modes were previously determined with respect to the motion capability of the surgeon’s hand that wears the ring as the surgeon handles a surgical tool inside the surgical workspace. In this surgery training simulator developed for a robot-assisted endoscopic skull base surgery, a new strategy is developed to identify the preferred motion axes of the surgeon. This simulator is designed specifically for tuning the teleoperation system for each surgeon via the identification. This tuning capability brings flexibility to adjust the system operation with respect to the motion characteristics of the surgeon.

One of the major challenges in the science of maxillofacial radiology imaging is the various artifacts created in images taken by cone beam computed tomography (CBCT) imaging systems. Among these artifacts, motion artifact, which is created by the patient, has adverse effects on image quality. In this paper, according to the conditions and limitations of the CBCT imaging room, the goal is the design and development of a cable-driven parallel robot to create repeatable movements of a dry skull inside a CBCT scanner for studying motion artifacts and building up reference datasets with motion artifacts. The proposed robot allows a dry skull to execute motions, which were selected on the basis of clinical evidence, with 3-degrees of freedom during imaging in synchronous manner with the radiation beam. The kinematic model of the robot is presented to investigate and describe the correlation between the amount of motion and the pulse width applied to DC motors. This robot can be controlled by the user through a smartphone or laptop wirelessly via a Wi-Fi connection. Using wireless communication protects the user from harmful radiation during robot driving and functioning. The results show that the designed robot has a reproducibility above 95% in performing various movements.

The lack of specialized personnel and assistive technology to assist in rehabilitation therapies is one of the challenges facing the health sector today, and it is projected to increase. For researchers and engineers, it represents an opportunity to innovate and develop devices that improve and optimize rehabilitation services for the benefit of society. Among the different types of injuries, hand injuries occur most frequently. These injuries require a rehabilitation process in order for the hand to regain its functionality. This article presents the fabrication and instrumentation of an end-effector prototype, based on a five-bar configuration, for finger rehabilitation that executes a natural flexion-extension movement. The dimensions were obtained through the gradient method optimization and evaluated through Matlab. Experimental tests were carried out to demonstrate the prototype’s functionality and the effectiveness of a five-bar mechanism acting in a vertical plane, where gravity influences the mechanism’s performance. Position control using fifth-order polynomials with via points was implemented in the joint space. The design of the end-effector was also evaluated by performing a theoretical comparison, calculated as a function of a real flexion-extension trajectory of the fingers and the angle of rotation obtained through an IMU. As a result, controlling the two degrees of freedom of the mechanism at several points of the trajectory assures the end-effector trajectory and therefore the fingers’ range of motion, which helps for full patient recovery.

Minimally invasive surgery (MIS) has been an essential tool in the surgical sector for many years due to its crucial advantages compared to open surgery. To overcome remaining limitations, teleoperated MIS experienced a strong emergence. However, the widespread usage of such systems is hindered by the enormous financial hurdle. The use of standard components and conventional tools for teleoperated MIS can facilitate integration into existing hospital workflows and can be a cost-efficient and versatile approach for research purposes. To compensate for the lack of haptic feedback, some teleoperation setups inherit a sensor system allowing them to record interaction forces and display them at the user interface. In research and in commercially available systems, different positions for the sensor can be found. In this paper, mechanical interfaces for the guidance and actuation of non-wristed and wristed standard instruments are presented. Furthermore, a method for the extracorporeal measurement of interaction forces is presented, characterized, and discussed. The overall mean relative error of the magnitude of the interaction force is 9.4%, while the overall mean absolute error of the force vector is 14.4$^{\circ }$, both below the respective human differential perception threshold. The presented measurement method is a simple, yet sufficiently accurate approach to measure interaction forces in surgical telemanipulation.

This paper’s content focuses on designing and prototyping a robotic brace dedicated to treating scoliosis. Scoliosis is an abnormal spinal curvature affecting 1–3% of children and constitutes a major therapeutic problem. In moderate cases of deformity, passive brace treatment is performed. However, this approach can lead to important patient discomfort. So, we propose a robotic solution providing greater mobility and the possibility of adapting the procedure to each patient. The robotic brace we built and tested is composed of three specific rings adapted to the patient’s torso. Each independent module of two consecutive rings is movable through a Stewart–Gough platform-type mechanism. As the robotic brace is lightweight, it brings better portability and improves the patient’s comfort.

The first part of the paper shows the state of the art of bracing techniques: from passive to active orthoses. Next, the mechatronics of the device is detailed, and the robot’s kinematic models are developed. The motion control principle is given. In the last part, motion tests were administered with a healthy human to validate the brace architecture choice and its position and motion control strategies.

With diverse areas of applications, wearable robotic exoskeleton devices have gained attention in the past decade. These devices cover one or more human limbs/joints and have been presented for rehabilitation, strength augmentation and interaction with virtual reality. This research is focused towards design, modeling and control of a novel series elastic actuation (SEA) based index finger exoskeleton with a targeted torque rendering capability of 0.3 Nm and a force control bandwidth of 3 Hz. The proposed design preserves the natural range of motion of the finger by incorporating five passive and two actively actuated joints and provides active control of metacarpophalangeal and proximal interphalangeal joints. Forward and inverse kinematics for both position and velocity have been solved using closed loop vector analysis by including human finger as an integral part of the system. For accurate force control, a cascaded control structure has been presented. Force controlled trajectories have been proposed to guide the finger along preprogrammed virtual paths. Such trajectories serve to gently guide the finger towards the correct rehabilitation protocol, thus acting as an effective replacement of intervention by a human therapist. Extensive computer simulations have been performed before fabricating a prototype and performing experimental validation. Results show accurate modeling and control of the proposed design.