This study explores the potential of using a sensor system and deep learning algorithm for automatic recognition and classification of human movement intentions to enhance the control of active orthopedic aids such as orthoses, prostheses, and exoskeletons. The sensor system consists of four inertial measurement units (IMU) attached to the thighs, lower back, and chest of a person, measuring acceleration and rotational velocity in three axes each. A dataset was generated from 20 healthy individuals performing various movements from a standing position, and preprocessed and segmented into time windows. The data was fed into a convolutional neural network (CNN) capable of classifying the time windows into seven classes. The network achieved a classification accuracy of up to 82 %. The results demonstrate the potential of the proposed system for successful application in the control of assistance systems, which can improve the operability and effectiveness of orthopedic aids.

In this paper, the development of a cost-effective assistance system for venipuncture is presented. The system locates forearm veins through near-infrared imaging, depth estimation, deep learning segmentation, and 3D reconstruction. A single-board computer was integrated with two infrared cameras and two 760 nm near-infrared (NIR) LEDs to capture and process stereo images. The depth estimation was achieved through stereo triangulation. A deep learning model based on the U-Net architecture with an attention mechanism and a training dataset of 900 images from 40 participants was used for vein segmentation. Depth information and segmented veins were combined to enable a 3D visualization of the veins. The results show a Jaccard-Score of 92.80 % for vein segmentation and an average reprojection error of 0.48 pixels for the 3D reconstruction.

Single port surgery is an innovative approach in the field of minimally invasive surgery. Although several telemanipulators exist to perform operations through only a single incision they all suffer from the lack of haptic feedback. To generate kinesthetic feedback the intracorporeal forces need to be measured, which is a challenging task. To overcome these limitations we investigate in this paper the force sensing capability of a new single port robot that has two parallelkinematic manipulators. Because of the rigidity and excellent controllability the tip force is measured using proximally arranged force sensors. To minimize friction effects a longitudinal vibration of 6 Hz with an amplitude of 20 µm is applied to the manipulator while the tip force is varied in the three main coordinate axes. Within the analysis 32320 values are investigated showing that a vibration has a significant impact and dramatically improves the signal quality by minimizing the crosstalk by a factor of up to 12.7 enabling to measure the tip force exactly.

In this paper we present a new single port robotic system particularly designed for single port access surgery in the field of colon cancer. In contrast to most state of the art systems the two intracorporeal manipulator arms are set up using a parallel kinematic structure with 5DOF, which are integrated into a shaft of 38mm in diameter. The parallel kinematic structure and its workspace are discussed in detail. As a unique feature, the kinematics uses the translation and rotation of three rods per manipulation arm. Using a parallel kinematic approach enables dynamic, stiff and precise movements which are needed to generate a realistic haptic feedback. The results of several performed circle tests are presented showing the ability of performing precise and dynamic movements with speeds of up to 327 mm/s and under load condition of 4 N.

Experimental results for a handheld six degrees of freedom parallel robot with realtime position control and disturbance attenuation are presented. The robot's base is freely movable in space by a human operator, while the tool is position controlled and stabilized relatively to a reference coordinate system. The challenge is to decouple the tool as far as possible from the user involved arm tremor and unintended motions. The robot is equipped with a camera-based position and orientation tracking system, linear actuators, and a realtime control system. Kinematics, co-ordinate transforms and workspace limits are presented with its specifications. Experiments with sinusoidal stimuli on a test stand and during the handheld operation are discussed with respect of stabilizing performance and work-space violation. The resulting error bounds of less than 0.5 mm in the Cartesian position demonstrate that such a robot device has the potential to improve the classical manual surgical interventions. Further, the paper demonstrates the compliance of the user motion to the workspace provided by the robot.

This paper describes an underwater robot navigation strategy in flow. Our aim is to demonstrate that knowing the relative flow speed is advantageous because it permits using more energy efficient and stable control for trajectory following. We use a biomimetic robot that moves in uniform flow using a side-slipping maneuver. Side-slipping permits the robot to move laterally with respect to the incoming flow by exploiting its passive dynamics. The side-slipping maneuver is controlled by adjusting the heading of the robot with respect to the flow. We implement simple PID controllers for controlling the motion of the side-slipping robot laterally and transversely. Also, we compare the performance of the robot in the case where the robot does not know the flow speed. In this latter case the robot's heading towards the waypoint is controlled and the flow effect is considered as a disturbance compensated by the control algorithm. Comparative experiments demonstrate that it is advantageous for a robot to know not just its speed and orientation with respect to the world's frame of reference but also its local flow-relative speed. It permits the robot to follow trajectories more stable and using less energy. In the discussion section we propose possible future directions for implementing the on board flow-relative control.