Comfort and learnability assessment of a new soft robotic manipulator for minimally invasive surgery.

Laparoscopic surgeons perform precise and time consuming procedures while holding awkward poses in their upper body and arms. There is an ongoing effort to produce robotic tools for laparoscopic surgery that will simplify these tasks and reduce risk of errors to help both the surgeon and the patient. STIFF-FLOP is an ongoing EU FP7 project focusing on this by creating a stiffness controllable soft robotic manipulator. This paper reports on a study to test the soft manipulator's learnability and the effort associated with its use. The tests involved a limited prototype of the manipulator with a custom built test rig and EMG acquisition system. Task times and video recordings along with EMG waveforms from the forearm muscles of participants (n=25) were measured for objective assessment. A questionnaire was also provided to the participants for subjective assessment. The data shows that in average EMG levels were 25.9% less in RMS when using the STIFF-FLOP arm than when conventional laparoscopic tools were used. In terms of learnability, from the first to the second attempt on the STIFF-FLOP manipulator, elapsed time was reduced by an average of 32.1%. Further details and analysis of the EMG signals as well as time and questionnaire results is presented in the paper.

Endoscopic add-on stiffness probe for real-time soft surface characterisation in MIS.

This paper explores a novel stiffness sensor which is mounted on the tip of a laparoscopic camera. The proposed device is able to compute stiffness when interacting with soft surfaces. The sensor can be used in Minimally Invasive Surgery, for instance, to localise tumor tissue which commonly has a higher stiffness when compared to healthy tissue. The purely mechanical sensor structure utilizes the functionality of an endoscopic camera to the maximum by visually analyzing the behavior of trackers within the field of view. Two pairs of spheres (used as easily identifiable features in the camera images) are connected to two springs with known but different spring constants. Four individual indenters attached to the spheres are used to palpate the surface. During palpation, the spheres move linearly towards the objective lens (i.e. the distance between lens and spheres is changing) resulting in variations of their diameters in the camera images. Relating the measured diameters to the different spring constants, a developed mathematical model is able to determine the surface stiffness in real-time. Tests were performed using a surgical endoscope to palpate silicon phantoms presenting different stiffness. Results show that the accuracy of the sensing system developed increases with the softness of the examined tissue.