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

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

Phase matters: A role for the subthalamic network during gait.

The role of the subthalamic nucleus in human locomotion is unclear although relevant, given the troublesome management of gait disturbances with subthalamic deep brain stimulation in patients with Parkinson's disease. We investigated the subthalamic activity and inter-hemispheric connectivity during walking in eight freely-moving subjects with Parkinson's disease and bilateral deep brain stimulation. In particular, we compared the subthalamic power spectral densities and coherence, amplitude cross-correlation and phase locking value between resting state, upright standing, and steady forward walking. We observed a phase locking value drop in the β-frequency band (≈13-35Hz) during walking with respect to resting and standing. This modulation was not accompanied by specific changes in subthalamic power spectral densities, which was not related to gait phases or to striatal dopamine loss measured with [123I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane and single-photon computed tomography. We speculate that the subthalamic inter-hemispheric desynchronization in the β-frequency band reflects the information processing of each body side separately, which may support linear walking. This study also suggests that in some cases (i.e. gait) the brain signal, which could allow feedback-controlled stimulation, might derive from network activity

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

Sit-to-walk performance in Parkinson's disease: A comparison between faller and non-faller patients

Abstract Background Falls are one of the main concerns in people with Parkinson's disease, leading to poor quality of life and increased mortality. The sit-to-walk movement is the most frequent postural transition task during daily life and is highly demanding in terms of balance maintenance and muscular strength. Methods With the aim of identifying biomechanical variables of high risk of falling, we investigated the sit-to-walk task performed by 9 Parkinson's disease patients with at least one fall episode in the six months preceding this study, 15 Parkinson's disease patients without previous falls, and 20 healthy controls. Motor performance was evaluated with an optoelectronic system and two dynamometric force plates after overnight suspension of all dopaminergic drugs and one hour after consumption of a standard dose of levodopa/benserazide. Findings Poor trunk movements critically influenced the execution of the sit-to-walk movement in patients with a history of falling. The peak velocity of the trunk in the anterior-posterior direction discriminated faller from non-faller patients, with high specificity and sensitivity in both the medication-off and -on state. Interpretation Our results confirm the difficulties in merging consecutive motor tasks in patients with Parkinson's disease. Trunk movements during the sit-to-walk can provide valuable measurements to monitor and possibly predict the risk of falling

ESAD: Endoscopic Surgeon Action Detection dataset

In this work, we take aim towards increasing the effectiveness of surgical assistant robots. We intended to make assistant robots safer by making them aware about the actions of surgeon, so it can take appropriate assisting actions. In other words, we aim to solve the problem of surgeon action detection in endoscopic videos. To this, we introduce a challenging dataset for surgeon action detection in real world endoscopic videos. Action classes are picked based on the feedback of surgeons and annotated by medical professional. Given a video frame, we draw bounding box around surgical tool which is performing action and label it with action label. Finally, we present a frame-level action detection baseline model based on recent advances in object detection. Results on our new dataset show that our presented dataset provides enough interesting challenges for future method and it can serve as strong benchmark corresponding research in surgeon action detection in endoscopic videos

Anthropometric and kinematic data.

<p>Anthropometric and kinematic data.</p

Modulation of the spectral power during the gait cycle.

<p>Event related synchronization (ERS) and desynchronization (ERD) in low <i>β-</i> (top) high <i>β-</i> (middle) and <i>γ</i>-frequency band (bottom). Subthalamic power changes of the phases of gait are shown as the average relative change of the whole stride of all subjects. Shaded areas represent the confidence intervals (5–95%) of the group mean. We analyzed the power changes of STN–and STN+ during the gait cycle of the contralateral foot (but they could be also referred to the matched gait phases of the ipsilateral one). Stance is the period during which the foot is on the ground (dark and light orange bars). The stance phase includes a period of bilateral foot contact with the floor (double-support phases [dark orange bars]), and a period of unilateral foot contact (single-support phase [light orange bar]). The swing phase (light green and dark green bars) is the interval in which the foot is lifted from the floor. Thanks to the velocity peak (VP) of the marker placed on the lateral malleolus, we identified an acceleration (light green) a deceleration (dark green) sub-phase of the swing phase. HS = heel strike; TO = toe off; VP = velocity peak; lower case subscript indicates the foot contralateral _(contra) or ipsilateral _(ipsi) to STN–or STN+.</p

Spectral profiles (single subject) during resting, upright standing and gait.

<p>Single subject spectral power of the STN local field potential during resting (blue line), standing (pink line) and gait for the two hemispheres, with less (–) and more (+) striatal dopamine innervation. Axial slices are left-right flipped to match the corresponding STN. The peak at 32 Hz is a known artefact of the Activa PC+S^® system tied to clock settings or due to a triggered check of the battery status. SPECT scans (central column) show striatal dopaminergic loss as percentage decline with respect to healthy subjects (calculated from BP_ND of DAT, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198691#pone.0198691.t003" target="_blank">Table 3</a>).</p