A Non-Array Type Cut to Shape Soft Slip Detection Sensor Applicable to Arbitrary Surface

The presence of a tactile sensor is essential to hold an object and manipulate it without damage. The tactile information helps determine whether an object is stably held. If a tactile sensor is installed at wherever the robot and the object touch, the robot could interact with more objects. In this paper, a skin type slip sensor that can be attached to the surface of a robot with various curvatures is presented. A simple mechanical sensor structure enables the cut and fit of the sensor according to the curvature. The sensor uses a non-array structure and can operate even if a part of the sensor is cut off. The slip was distinguished using a simple vibration signal received from the sensor. The signal is transformed into the time-frequency domain, and the slippage was determined using an artificial neural network. The accuracy of slip detection was compared using four artificial neural network models. In addition, the strengths and weaknesses of each neural network model were analyzed according to the data used for training. As a result, the developed sensor detected slip with an average of 95.73% accuracy at various curvatures and contact points.

An Automated Data Acquisition System for Pinch Grip Assessment Based on Fugl Meyer Protocol: A Feasibility Study

The Upper Extremity Fugl Meyer Assessment (UE-FMA) is the most comprehensive assessment for pinch impairment after stroke. The pinch test of UE-FMA is manually performed by pulling a pincer object away from the patient’s fingers while providing a visual observation that results in a subjective assessment. In this study, an automated data acquisition system that consists of a linear electric actuator applying automatic pulling to the customized pincer object held by the volunteer was developed. The pinch force was measured such that a strain gauge was placed on the pincer object while pulling force was measured using pulling force load cell connected in between the linear electric actuator and customized pincer object. The pincer object’s slip onset was detected using a displacement slip sensor. The mean pinch and pulling force values at the slip onset were 12.17 and 6.25 N for right hands, while mean pinch and pulling force values were 11.67 and 5.92 N for left hands of 50 healthy volunteers, respectively. Based on the paired t-test, there is no significant difference between right and left hands. The automated data acquisition system can objectively apply a pulling force, detect the slip onset, and measure the pinch and pulling forces.

The Role of Tissue Slip Feedback in Robot-Assisted Surgery

Slip, or accidental loss, of grasped biological tissue can have negative consequences in all types of surgery (open, laparoscopic, robot-assisted). This work focuses on slip in robot-assisted surgery (RAS) with the goal of improving the quality of grasping and tool–tissue interactions. We report on a survey of 112 RAS surgeons, the results of which support the value of detecting and reducing slip in a variety of procedures. We conducted validation tests using a thermal slip sensor in a surgical grasper on tissue in vivo and ex vivo. The results of the survey and validation informed a user study to assess whether tissue slip feedback can improve performance and reduce effort in a phantom tissue manipulation task. With slip feedback, experienced subjects were significantly faster to complete the task, dropped tissue less (3% versus 38%), and experienced decreased mental demands and situational stress. These results provide motivation to further develop the sensor technology and incorporate it in robotic surgical equipment.