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The ORCCAD programming environment for robotic systems allows users to address automatic control laws in continuous time at the lower levels, and aspects of discrete-time logic at the higher lev els. ORCCAD provides tools of specification, formal verification, simulation, and real-time code generation integrated within a set of dedicated graphical interfaces. Basic robot actions, which are in trinsically hybrid entities, are handled by the ROBOT-TASK struc ture, which smartly interfaces aspects of continuous and discrete time. ROBOT-TASKS are further logically composed into more complex actions, ROBOT-PROCEDURES, through a dedicated lan guage. While system performance can be checked using simula tions, crucial properties such as deadlock avoidance, safety, and liveness can be formally verified at both levels. The approach is illustrated with an underwater inspection mission.

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IntroductionInappropriate staff behaviours can lead to environmental contamination in the operating room (OR) and subsequent surgical site infection (SSI). This study will focus on the continued assessment of OR staff behaviours using a motion tracking system and their impact on the SSI risk during surgical procedures.Methods and analysisThis multicentre prospective cross-sectional study will include 10 ORs of cardiac and orthopaedic surgery in 12 healthcare facilities (HCFs). The staff behaviour will be assessed by an objective, continued and prolonged quantification of movements within the OR. A motion tracking system including eight optical cameras (VICON-Bonita) will record the movements of reflective markers placed on the surgical caps/hoods of each person entering the room. Different configurations of markers positioning will be used to distinguish between the staff category. Doors opening will be observed by means of wireless inertial sensors fixed on the doors and synchronised with the motion tracking system. We will collect information on the OR staff, surgical procedures and surgical environment characteristics. The behavioural data obtained will be compared (1) to the ‘best behaviour rules’ in the OR, pre-established using a Delphi method and (2) to surrogates of the infectious risk represented by microbiological air counts, particle counts, and a bacteriological sample of the wound at closing. Statistics will be performed using univariate and multivariate analysis to adjust on the aerolic and architectural characteristics of the OR. A multilevel model will allow including surgical specialty and HCFs effects. Through this study, we will develop an original approach using high technology tools associated to data processing techniques to evaluate ‘automatically’ the behavioural dynamics of the OR staff and their impact on the SSI risk.Ethics and disseminationApprobation of the Institutional Review Board of Paris North Hospitals, Paris 7 University, AP-HP (no 11-113, 6 April 2012). The findings will be disseminated through peer-reviewed journals, and national and international conference presentations.

Freezing of gait (FOG) is a common symptom in Parkinsonism, which affects the gait pattern and is associated to a fall risk. Automatized FOG episode detection would allow systematic assessment of patient state and objective evaluation of the clinical effects of treatments. Techniques have been proposed in the literature to identify FOG episodes based on the frequency properties of inertial sensor signals. Our objective here is to adapt and extend these FOG detectors in order to include other associated gait pattern changes, like festination. The proposed approach is based on a single wireless inertial sensor placed on the patient's lower limbs. The preliminary experimental results show that existing frequency-based freezing detectors are not sufficient to detect all FOG and festination episodes and that the observation of some gait parameters such as stride length and cadence are valuable inputs to anticipate the occurrence of upcoming FOG events.