A Novel Framework for Quantifying Accuracy and Precision of Event Detection Algorithms in FES-Cycling.

Functional electrical stimulation (FES) is a technique used in rehabilitation, allowing the recreation or facilitation of a movement or function, by electrically inducing the activation of targeted muscles. FES during cycling often uses activation patterns which are based on the crank angle of the pedals. Dynamic changes in their underlying predefined geometrical models (e.g., change in seating position) can lead to desynchronised contractions. Adaptive algorithms with a real-time interpretation of anatomical segments can avoid this and open new possibilities for the automatic design of stimulation patterns. However, their ability to accurately and precisely detect stimulation triggering events has to be evaluated in order to ensure their adaptability to real-case applications in various conditions. In this study, three algorithms (Hilbert, BSgonio, and Gait Cycle Index (GCI) Observer) were evaluated on passive cycling inertial data of six participants with spinal cord injury (SCI). For standardised comparison, a linear phase reference baseline was used to define target events (i.e., 10%, 40%, 60%, and 90% of the cycle's progress). Limits of agreement (LoA) of ±10% of the cycle's duration and Lin's concordance correlation coefficient (CCC) were used to evaluate the accuracy and precision of the algorithm's event detections. The delays in the detection were determined for each algorithm over 780 events. Analysis showed that the Hilbert and BSgonio algorithms validated the selected criteria (LoA: +5.17/-6.34% and +2.25/-2.51%, respectively), while the GCI Observer did not (LoA: +8.59/-27.89%). When evaluating control algorithms, it is paramount to define appropriate criteria in the context of the targeted practical application. To this end, normalising delays in event detection to the cycle's duration enables the use of a criterion that stays invariable to changes in cadence. Lin's CCC, comparing both linear correlation and strength of agreement between methods, also provides a reliable way of confirming comparisons between new control methods and an existing reference.

Tracking Clinical Staff Behaviors in an Operating Room.

Inadequate staff behaviors in an operating room (OR) may lead to environmental contamination and increase the risk of surgical site infection. In order to assess this statement objectively, we have developed an approach to analyze OR staff behaviors using a motion tracking system. The present article introduces a solution for the assessment of individual displacements in the OR by: (1) detecting human presence and quantifying movements using a motion capture (MOCAP) system and (2) observing doors' movements by means of a wireless network of inertial sensors fixed on the doors and synchronized with the MOCAP system. The system was used in eight health care facilities sites during 30 cardiac and orthopedic surgery interventions. A total of 119 h of data were recorded and analyzed. Three hundred thirty four individual displacements were reconstructed. On average, only 10.6% individual positions could not be reconstructed and were considered undetermined, i.e., the presence in the room of the corresponding staff member could not be determined. The article presents the hardware and software developed together with the obtained reconstruction performances.

Motion-capture system to assess intraoperative staff movements and door openings: Impact on surrogates of the infectious risk in surgery.

OBJECTIVES: We longitudinally observed and assessed the impact of the operating room (OR) staff movements and door openings on surrogates of the exogenous infectious risk using a new technology system. DESIGN AND SETTING: This multicenter observational study included 13 ORs from 10 hospitals, performing planned cardiac and orthopedic surgery (total hip or knee replacement). Door openings during the surgical procedure were obtained from data collected by inertial sensors fixed on the doors. Intraoperative staff movements were captured by a network of 8 infrared cameras. For each surgical procedure, 3 microbiological air counts, longitudinal particles counts, and 1 bacteriological sample of the wound before skin closure were performed. Statistics were performed using a linear mixed model for longitudinal data. RESULTS: We included 34 orthopedic and 25 cardiac procedures. The median frequency of door openings from incision to closure was independently associated with an increased log10 0.3 µm particle (ß, 0.03; standard deviation [SD], 0.01; P = .01) and air microbial count (ß, 0.07; SD, 0.03; P = .03) but was not significantly correlated with the wound contamination before closure (r = 0.13; P = .32). The number of persons (ß, -0.08; SD, 0.03; P < .01), and the cumulated movements by the surgical team (ß, 0.0004; SD, 0.0005; P < .01) were associated with log10 0.3 µm particle counts. CONCLUSIONS: This study has demonstrated a previously missing association between intraoperative staff movements and surrogates of the exogenous risk of surgical site infection. Restriction of staff movements and door openings should be considered for the control of the intraoperative exogenous infectious risk.

Continuous gait cycle index estimation for electrical stimulation assisted foot drop correction.

BACKGROUND: Walking impairment after stroke can be addressed with the use of drop foot stimulators (DFS). Many studies have demonstrated that DFS improves walking speed, reduces spasticity and reduces the physiologic effort of walking. Current DFS, through activation of the common peroneal nerve, elicit ankle dorsiflexion during swing phase of gait. DFS are generally piloted by force sensing resistor placed in the shoe of the affected side with stimulation triggered ON by heel rise and triggered OFF by heel strike. A tilt sensor can also be used with stimulation triggered by the tilt of the shank of the affected leg. These triggering approaches are the standard for initiating stimulation. However, the real-time modulation of FES intensity to provide more optimized delivery of stimulation and also to regulate dorsiflexion in the presence of disturbances, such as fatigue and spasticity may increase the number of potential users of DFS. Concerning research domain, stimulators that would allow modulating the stimulation pattern in between heel rise and strike events would allow exploring new stimulation strategies. We propose to extract continuous information: the gait cycle index (GCI), from one inertial measurement unit (IMU) measuring shank tilt angle. In order to illustrate the use of this real-time information, we show the feasibility of piloting an electrical stimulator. METHODS: 12 subjects with post-stroke hemiplegia participated. A wireless IMU was placed on the unaffected shank and was used to estimate GCI. Subjects performed 3 trials in each of the 3 conditions: C1 no stimulation aid, C2 electrical stimulation assistance triggered by heel switch, C3 electrical stimulation assistance triggered from GCI. RESULTS: 1) the proposed algorithm was able to real-time estimate GCI, 2) events could be extracted from GCI information in order to trig a DFS. CONCLUSION: The estimation of the continuous GCI in individuals with stroke is possible. Events can be extracted from this information in order to trig a stimulator. These results are a first step towards the possibility to investigate new DFS paradigms based on real-time modulation of stimulation parameters.

Detection of freezing of gait in Parkinson disease: preliminary results.

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.

Attitudes, risk of infection and behaviours in the operating room (the ARIBO Project): a prospective, cross-sectional study.

INTRODUCTION: Inappropriate 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 ANALYSIS: This 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 DISSEMINATION: Approbation 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.