Journey Map Guidelines

The Journey Map tool provides a graphic and structured visualization about all the factors that can influence the User Experience, directly constructed from the user's perspective. Basically it is a schematization of the user path, crossing different service touchpoints1, as the user starts to use a service until some goals are achieved. Into the user journey also the emotional aspects that affect the quality of the user experience and its level of satisfaction are considered. Graphically the Journey Map is a matrix composed by columns and rows. The columns, from left to right, show all the steps that form the user journey, a timeline that provides a sequential and chronological disposition of each stage for further details. In horizontal are displayed several rows, representing the research areas of interests (eg. Where the action takes place, the touchpoints involved in the context considered, the unexpressed needs of the user, his/her level of confidence to technology, etc…). All these elements together usually have different impacts along the journey steps; in this way the Journey Map can better track them and represent and identify these changes that interact with the user experience. In this specific occasion, the Journey Map will be used with the purpose to extrapolate qualitative and quantitative data about the User Experience of children with T1DM aged 8-10 in using the first prototype of the MyPAL app , as a graphical facilitator for an interactive discussion. In order to obtain reliable proofs of children’s experience, the Journey Map activity will be exploited with a co-creation methodological approach, where interactivity is essential and represents a great tool to collect insights in a playful and stimulating environment. In fact, this activity will involve directly our users (children) by mapping his/her experience and telling indirectly to us his/her feedbacks and expectations. This tool allows both individual and choral sessions and participatory techniques between deductive and analytical thinking. In this context, the Journey Map will be used as an individual explorative tool of investigation (one child per time)

An Embodied AI Approach to Individual Differences : Supporting Self-Efficacy in Diabetic Children with an Autonomous Robot

In this paper we discuss how a motivationally autonomous robot, designed using the principles of embodied AI, provides a suitable approach to address individual differences of children interacting with a robot, without having to explicitly modify the system. We do this in the context of two pilot studies using Robin, a robot to support self-confidence in diabetic children.Final Accepted Versio

Technical and Functional Validation of a Teleoperated Multirobots Platform for Minimally Invasive Surgery

Nowadays Robotic assisted Minimally Invasive Surgeries (R-MIS) are the elective procedures for treating highly accurate and scarcely invasive pathologies, thanks to their abil- ity to empower surgeons\u2019 dexterity and skills. The research on new Multi-Robots Surgery (MRS) platform is cardinal to the development of a new SARAS surgical robotic platform, which aims at carrying out autonomously the assistants tasks during R- MIS procedures. In this work, we will present the SARAS MRS platform validation protocol, framed in order to assess: (i) its technical performances in purely dexterity exercises, and (ii) its functional performances. The results obtained show a prototype able to put the users in the condition of accomplishing the tasks requested (both dexterity- and surgical-related), even with rea- sonably lower performances respect to the industrial standard. The main aspects on which further improvements are needed result to be the stability of the end effectors, the depth per- ception and the vision systems, to be enriched with dedicated virtual fixtures. The SARAS\u2019 aim is to reduce the main surgeon\u2019s workload through the automation of assistive tasks which would benefit both surgeons and patients by facilitating the surgery and reducing the operation time

Towards long-term social child-robot interaction: using multi-activity switching to engage young users

Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI

Car seat comfort assessment based on objective and subjective measurements in elderly population

n important role in ensuring a comfortable driving experience is represented by a properly designed car seat, especially for elderly drivers. A seat prototype with easily interchangeable pads of cushion and backrest (e.g. thickness, lift at 40%) was realized to meet elderly needs. In this study both a subjective assessment, by means of selected surveys and checklists as well as an objective evaluation, throughout a pressure distribution evaluation, of an existing car seat and the new developed one, in three different pads configurations, has been performed. Thirteen healthy elderly subjects aged between 65 and 83 y.o. have been included in the study. Results showed that the new developed seat ensured a minor discomfort, both perceived (i.e. measured throughout the checklists) and objective (i.e. measured throughout pressure distribution measures) one, with respect to the pre-existing seat, for all the tested subjects. One of the tested configuration seemed to perform better in terms of perceived comfort while showing a uniform pressure distribution

New horizons for patient safety: LIGRA (LIfe Guard for Robotic surgery Assistance) An interactive platform centralizing information and control in robotic surgery Operating Rooms

The present paper describes LIGRA, an innovative technological solution developed in the context of the SAFROS co-funded EU project. Its general goal is to improve patient safety during minimal invasive robotic surgery. Focusing on the risks introduced in the surgical workflow by new robotic technologies, the LIGRA project consists in the design and implementation of a graphical user interface (GUI), on top of a dedicated middleware for message transport. This GUI is intuitive, non-invasive and versatile. Being visible to the whole surgical staff and easily understandable, the interface monitors the status of all robotic components, informs about any potential dangerous situation and displays the needed steps to recover. In addition, LIGRA records the data sent by the components, allowing retrieving technical and procedural information about the surgery and the staff afterwards. Furthermore, it gives access to an interactive version of the World Health Organization Patient Safety Checklist that recalls the essential checks and verifications to be made prior, during, and after the surgery. The approach adopted during this contribution, justified by the lack of a similar tool in OR nowadays, is to establish a common framework, which could have an important positive impact on patient safety

A Multirobots Teleoperated Platform for Artificial Intelligence Training Data Collection in Minimally Invasive Surgery

Dexterity and perception capabilities of surgical robots may soon be improved by cognitive functions that can support surgeons in decision making and performance monitoring, and enhance the impact of automation within the operating rooms. Nowadays, the basic elements of autonomy in robotic surgery are still not well understood and their mutual interaction is unexplored. Current classification of autonomy encompasses six basic levels: Level 0: no autonomy; Level 1: robot assistance; Level 2: task autonomy; Level 3: conditional autonomy; Level 4: high autonomy. Level 5: full autonomy. The practical meaning of each level and the necessary technologies to move from one level to the next are the subject of intense debate and development. In this paper, we discuss the first outcomes of the European funded project Smart Autonomous Robotic Assistant Surgeon (SARAS). SARAS will develop a cognitive architecture able to make decisions based on pre-operative knowledge and on scene understanding via advanced machine learning algorithms. To reach this ambitious goal that allows us to reach Level 1 and 2, it is of paramount importance to collect reliable data to train the algorithms. We will present the experimental setup to collect the data for a complex surgical procedure (Robotic Assisted Radical Prostatectomy) on very sophisticated manikins (i.e. phantoms of the inflated human abdomen). The SARAS platform allows the main surgeon and the assistant to teleoperate two independent two-arm robots. The data acquired with this platform (videos, kinematics, audio) will be used in our project and will be released (with annotations) for research purposes

Enhancing Surgical Process Modeling for Artificial Intelligence development in robotics: the SARAS case study for Minimally Invasive Procedures

Nowadays Minimally Invasive Surgery (MIS) is playing an increasingly major role in the clinical practice also thanks to a rapid evolution of the available medical technologies, especially surgical robotics. A new challenge in this respect is to equip robots with cognitive capabilities, in order to make them able to act autonomously and cooperate with human surgeons. In this paper we describe the methodological approach developed to comprehensively describe a specific surgical knowledge, to be transferred to a complex Artificial Intelligence (AI) integrating Perception, Cognitive and Planning modules. Starting from desk researches and a strict cooperation with expert surgeons, the surgical process is framed on a high-level perspective, which is then deepened into a granular model through a Surgical Process Modelling approach, so as to embed all of the needed information by the AI to properly work. The model is eventually completed adding the corresponding Process Risk Analysis. We present the results obtained with the application of the aforementioned methodology to a Laparoscopic Radical Nephrectomy (LRN) procedure and discuss on the next technical implementation of this model