Flexible systems such as endoscopes are widely used for performing minimally invasive surgical interventions, as in intraluminal procedures or single port laparoscopy. Surgical platforms have been developed by companies and by laboratories to improve the capabilities of these flexible systems, for instance by providing additional degrees of freedom (DoF) to the instruments or triangulation configurations [
1,
2]. In classic intraluminal procedures, the high number of DoF to be controlled represents a constraint, where several expert technicians, including the surgeon, have to work together in a complex environment. Robot assistance has been identified as a solution to this problem relative to the use of flexible systems in minimally invasive surgery [
3], which explains the motivation for developing the new, teleoperated robotic system put to work in this study here. The goal of
STRAS is to optimally assist the expert surgeon in minimally invasive procedures [
4], and the design is based on the Anubis
® platform developed by Karl Storz and the IRCAD [
5]. Previous studies on
STRAS were focused on the system architecture and the control theory of the application [
4,
5,
6]. In minimally invasive surgical systems for endoscopic surgery, surgeons need to operate master interfaces to control the endoscope and surgical instruments. They need to be able to have optimal skills in controlling the system and the user interface for targeted manipulation of the remote-controlled slave system as well as to cope with the overall complexity of the design. Such expertise can only be achieved by learning to optimally master the control mechanisms through practice in a simulator task and in vivo. Human control of endoscopic surgical systems may benefit from robotic surgical assistance [
7]. Previous studies were focused on tool-tip pressures and tactile feedback effects, rather than on the grip forces applied during manipulation of the handles [
8]. The system described here was designed without force feedback, and maneuver control is therefore based solely on visual feedback from the 2D images provided by an endoscopic fisheye camera and displayed on a screen. Anthropometric data from the literature suggest that, with or without force feed-back, dynamic changes in perceptual hand and body schema representations and cognitive motor programming occur inevitably after repeated tool use [
9,
10]. These cognitive changes reflect the processes which highly trained surgeons go through in order to adapt to the visual and tactile constraints of laparoscopic surgical interventions. Experts perform tool-mediated image-guided tasks significantly quicker than trainees, with significantly fewer tool movements, shorter tool trajectories, and fewer grasp attempts [
11]. Additionally, an expert tends to focus attention mainly on target locations, while novices split their attention between trying to focus on the targets and, at the same time, trying to track the surgical tools. This reflects a common strategy for controlling goal-directed hand movements in non-trained operators in various goal-directed manual tasks [
12], often considerably affecting task execution times. Such strategy variables are also likely to influence grip forces while manipulating the control sticks of a robotic device [
13]. This work here is focused on the analysis of expertise and sensor specific force profiles during execution of a four-step pick-and-drop task with the telemanipulation system of
STRAS. Pre-clinical testing of the
STRAS robotic system has permitted to demonstrate that an expert surgeon on his own can successfully perform all the steps of a complex endoscopic surgery task (colorectal endoscopic submucosal dissection) with the telemanipulation system [
14,
15]. Previously [
16], we had shown that proficiency (expertise) in the control of the
STRAS master/slave system is reflected by a lesser grip force during task execution as well as by a shorter task execution time. In the meantime, pre-clinical testing of the
STRAS robotic system has permitted to demonstrate major advantages of the system for expert endoscopic surgeons in comparison with classic procedures [
14,
15], and benchmark measures permitting to establish objective criteria for expertise in using the system need to be found to ensure effective training of future surgeons on the system. Experimental studies of grip force strength and control for lifting and manipulating objects strategically have provided an overview of the contributions of each finger to overall grip strength and fine grip force control [
17]. While the middle finger is the most important contributor to the gross total grip force and, therefore, most important for getting a good grip of heavy objects to lift or carry, the ring finger and the small (pinky) finger are most important for the fine control of subtle grip force modulations [
17], as those required for effectively manipulating the control handles of
STRAS. Moreover, it is well-documented in the literature that grip force is systematically stronger in the dominant hand compared with the non-dominant hand [
16,
18]. In this study here, the grip force profiles correspond to measurements collected from specific sensor positions on these anatomically relevant parts of the finger and hand regions of the dominant and non-dominant hands. The grip force profiles of an expert in controlling the master/slave system are compared to those of an absolute beginner, who manipulated the robotic device for the first time. The wireless sensor glove hardware-software system described in [
16], was improved and employed in this study here to collect force data from a novice trainee and an expert in various anatomical locations in the palm and on the phalanges of fingers of the right and left hands for detailed analyses in terms of sensor-specific grip force profiles.