The paper aims to propose a magnetic actuated capsule microrobotic system, which is composed of a magnetically actuated microrobot with a screw jet mechanism, a driving system, and a positioning system. The magnetically actuated microrobot embedded an O-ring magnet as an actuator has potential for achieving a particular task, such as medical diagnose or drug delivery. The driving system composes of a three axes Helmholtz coils to generate a rotational magnetic field for controlling the magnetically actuated microrobot to realize the basic motion in pipe, e.g., forward/backward motion and upward/downward motion. The positioning system is used to detect the pose of the magnetically actuated microrobot in pipe. We will discuss the shape of the Helmholtz coils and the magnetic field around the O-ring magnet to obtain an optimal performance of the magnetically actuated microrobot. The experimental result indicated that the microrobot with screw jet motion has a flexible movement in pipe by adjusting the rotational magnetic field plane and the magnetic field changing frequency.

This paper proposes a new robotic rehabilitation training platform that is motivated by the requirement for adjusting the training strategy and intensity in a patient-specific manner. The platform is implemented for tele-rehabilitation and is comprised of a haptic device operated by therapists, a lightweight exoskeleton worn by patients and a visually shared model. Through the visually shared model, the motion of the therapist and patient are measured and mapped to the motion of the corresponding object. Thus, the force generated by the therapist can be transferred to the patient for delivering training, while real-time force feedback with high transparency can be provided to the therapist so they know the amount of force being applied to patients in real time. In particular, both assistive therapy in the early stages and resistive therapy in the later stages of stroke can be performed. The home-use exoskeleton device is specifically designed to be light-weight and compliant for safety. The patient-exoskeleton and therapist-haptic interaction performance is evaluated by observing the muscle activities and interaction force. Two volunteers were requested to imitate the process of the therapist-in-the-loop training to evaluate the proposed platform.

According to the neuro-rehabilitation theory, compared with unilateral training, bilateral training is proven to be an effective method for hemiparesis, which affects the most part of stroke patients. In this study, a novel bilateral rehabilitation training system, which incorporates a lightweight exoskeleton device worn on the affected limb; a haptic device (Phantom Premium), which is used for generating a desired tactile feedback for the affected limb; and a VR (virtual reality) graphic interface, has been developed. The use of VR technology during rehabilitation can provide goal directed tasks with rewards and motivate the patient to undertake extended rehabilitation. This paper is mainly focused on elbow joint training, and other independent joints can be trained by easily changing the VR training interface. The haptic device is adopted to enable patients to use their own decision making abilities with a tactical feedback. Integrated with a VR-based graphic interface, the goal-oriented task can help to gradually recovery their motor function with a coordinative motion between two limbs. In particular, the proposed system can accelerate neural plasticity and motor recovery in those patients with little muscle strength by using the exoskeleton device. The exoskeleton device can provide from relatively high joint impedance to near-zero impedance, and can provide a partial assist as the patient requires.

Given that the current microrobot cannot achieve fixed-point and quantitative drug application in the gastrointestinal (GI) tract, a targeted drug delivery microrobot is proposed, and its principle and characteristics are studied. Through the control of an external magnetic field, it can actively move to the affected area to realize the targeted drug delivery function. The microrobot has a cam structure connected with a radially magnetized permanent magnet, which can realize two movement modes: movement and targeted drug delivery. Firstly, the magnetic actuated capsule microrobotic system (MACMS) is analyzed. Secondly, the dynamic model and quantitative drug delivery model of the targeted drug delivery microrobot driven by the spiral jet structure are established, and the motion characteristics of the targeted drug delivery microrobot are simulated and analyzed by the method of Computational Fluid Dynamics (CFD). Finally, the whole process of the targeted drug delivery task of the microrobot is simulated. The results show that the targeted drug delivery microrobot can realize basic movements such as forward, backward, fixed-point parking and drug delivery through external magnetic field control, which lays the foundation for gastrointestinal diagnosis and treatment.

To explore the positioning tracking problem of capsule endoscopy, the advantages of magnetic positioning technology as a solution are highlighted. Considering that the capsule robot is small and cannot have enough built-in driving and positioning tracking devices, new technical means are needed to solve this problem. Therefore, we propose a prediction method based on the BP neural network model to locate the position of the robot in the magnetic field. To evaluate the accuracy of a BP neural network model with three hidden layers, the predicted results of the model, the results of the nonlinear algorithm, and the actual coordinate points were compared to determine whether it could accurately predict the actual coordinate points. We set the criterion for correct localization as the Euclidean distance between the predicted coordinate point and the actual coordinate point being less than 0.01 mm, and obtained the localization rates of the nonlinear localization algorithm and the neural network prediction method as 46.7% and 95.2%, respectively. By comparing the results, it is found that the positioning accuracy predicted by the BP neural network is higher and has higher accuracy. This shows that the prediction accuracy of the algorithm is more optimized, which can meet the real-time and positioning accuracy requirements of the capsule endoscope.

A magnetic actuated capsule microrobotic system (MACMS) is proposed to control the microrobot to complete specific medical tasks, such as medical diagnosis or drug delivery. The structure design and control of the microrobot are optimized. By establishing the dynamic model of the microrobot with spiral structure, the optimal structure parameters are analyzed, and the fluid simulation of the propulsive force and the resistance of the microrobot are carried out by the finite element analysis software to obtain the optimal performance. During the experiment, the peristaltic pump was used for imitating the environment of the gastrointestinal tract, because the human intestinal tract is constantly peristaltic at random speeds. The experimental results indicated that by adjusting the rotational velocity and frequency of the rotating magnetic field, the magnetic actuated spiral jet microrobot could move flexibly in the pipeline where the fluid’s peristaltic velocity is constantly changing medical functions at the desired area for diagnosis. The proposed microrobot and its optimization method make it possible for microrobot to be applied in medical practice.