A data-driven performance dashboard for surgical dissection.

Surgical error and resulting complication have significant patient and economic consequences. Inappropriate exertion of tool-tissue force is a common variable for such error, that can be objectively monitored by sensorized tools. The rich digital output establishes a powerful skill assessment and sharing platform for surgical performance and training. Here we present SmartForceps data app incorporating an Expert Room environment for tracking and analysing the objective performance and surgical finesse through multiple interfaces specific for surgeons and data scientists. The app is enriched by incoming geospatial information, data distribution for engineered features, performance dashboard compared to expert surgeon, and interactive skill prediction and task recognition tools to develop artificial intelligence models. The study launches the concept of democratizing surgical data through a connectivity interface between surgeons with a broad and deep capability of geographic reach through mobile devices with highly interactive infographics and tools for performance monitoring, comparison, and improvement.

Data analytics interrogates robotic surgical performance using a microsurgery-specific haptic device.

OBJECTIVES: With the increase in robot-assisted cases, recording the quantifiable dexterity of surgeons is essential for proficiency evaluations. The present study employs sensor-based kinematics and recorded surgeon experience for evaluating a new haptic device. METHODS: Thirty surgeons performed a task simulating micromanipulation with neuroArmPLUSHD and two commercially available hand-controllers. The surgical performance was evaluated based on subjective measures obtained from survey and objective features derived from the sensors. Statistical analyses were performed to assess the hand-controllers and regression analysis was used to identify the key features and develop a machine learning model for surgical skill assessment. FINDINGS: MANCOVA tests on objective features demonstrated significance (α = 0.05) for time (p = 0.02), errors (p = 0.01), distance (p = 0.03), clutch incidents (p = 0.03), and forces (p = 0.00). The majority of metrics were in favor of neuroArmPLUSHD. The surgeons found it smoother, more comfortable, less tiring, and easier to maneuver with more realistic force feedback. The ensemble machine learning model trained with 5-fold cross-validation showed an accuracy (SD) of 0.78 (0.15) in surgeon skill classification. CONCLUSIONS: This study validates the importance of incorporating a superior haptic device in telerobotic surgery for standardization of surgical education and patient care.

Evaluation of haptic devices and end-users: Novel performance metrics in tele-robotic microsurgery.

BACKGROUND: Here, we present performance evaluation methodology that distinguishes the performance of a haptic device from end-user skill level in a tele-robotic system. METHODS: A pick-&-place experiment was designed and eight participants micromanipulated cotton strips, similar to maneuvers performed during microsurgery. Using three nonredundant haptic devices: neuroArmPLUS HD , a custom developed master manipulator, and two commercially available products, sigma.7 and HD2 , several features including the speed, effort, consistency, hand/gimbal agility, and force characteristics were measured and recorded for each participant and device. RESULTS: The participants showed variable skill level. For consistency, hand/gimbal agility and force characteristics, they performed significantly better when using neuroArmPLUS HD prototype. Based on the experimental data, performance metrics for both the device and the end-users were established. CONCLUSIONS: The integrated performance metrics allows independent evaluation of both the user and haptic device, thereby quantifying human-machine interactions.

Temperature Effects on Electromechanical Response of Deposited Piezoelectric Sensors Used in Structural Health Monitoring of Aerospace Structures.

Turbomachine components used in aerospace and power plant applications preferably require continuous structural health monitoring at various temperatures. The structural health of pristine and damaged superalloy compressor blades of a gas turbine engine was monitored using real electro-mechanical impedance of deposited thick film piezoelectric transducers at 20 and 200 °C. IVIUM impedance analyzer was implemented in laboratory conditions for damage detection in superalloy blades, while a custom-architected frequency-domain transceiver circuit was used for semi-field circumstances. Recorded electromechanical impedance signals at 20 and 200 °C acquired from two piezoelectric wafer active sensors bonded to an aluminum plate, near and far from the damage, were initially utilized for accuracy and reliability verification of the transceiver at temperatures >20 °C. Damage formation in both the aluminum plate and blades showed a peak shift in the swept frequency along with an increase in the amplitude and number of impedance peaks. The thermal energy at 200 °C, on the other hand, enforces a further subsequent peak shift in the impedance signal to pristine and damaged parts such that the anti-resonance frequency keeps reducing as the temperature increases. The results obtained from the impedance signals of both piezoelectric wafers and piezo-films, revealed that increasing the temperature somewhat decreased the real impedance amplitude and the number of anti-resonance peaks, which is due to an increase in permittivity and capacitance of piezo-sensors. A trend is also presented for artificial intelligence training purposes to distinguish the effect of the temperature versus damage formation in sample turbine compressor blades. Implementation of such a monitoring system provides a distinct advantage to enhance the safety and functionality of critical aerospace components working at high temperatures subjected to crack, wear, hot-corrosion and erosion.

PZT/PZT and PZT/BiT Composite Piezo-Sensors in Aerospace SHM Applications: Photochemical Metal Organic + Infiltration Deposition and Characterization.

The composition of fine-ground lead zirconate-titanate powder Pb(Zr0.52Ti0.48)O3, suspended in PZT and bismuth titanate (BiT) solutions, is deposited on the curved surface of IN718 and IN738 nickel-based supper alloy substrates up to 100 µm thickness. Photochemical metal organic and infiltration techniques are implemented to produce smooth, semi-dense, and crack-free random orientated thick piezoelectric films as piezo-sensors, free of any dopants or thickening polymers. Every single layer of the deposited films is heated at 200 °C with 10 wt.% excess PbO, irradiated by ultraviolet lamp (365 nm, 6 watt) for 10 min, pyrolyzed at 400 °C, and subsequently annealed at 700 °C for one hour. This process is repeated successively until reaching the desired thickness. Au and Pt thin films are deposited as the bottom and top electrodes using evaporation and sputtering methods, respectively. PZT/PZT and PZT/BiT composite films are then characterized and compared to similar PZT and BiT thick films deposited on the similar substrates. The effect of the composition and deposition process is also investigated on the crystalline phase development and microstructure morphology as well as the dielectric, ferroelectric, and piezoelectric properties of piezo-films. The maximum remnant polarization of Pr = 22.37 ± 0.01, 30.01 ± 0.01 µC/cm², the permittivity of εr = 298 ± 3, 566 ± 5, and piezoelectric charge coefficient of d33 = 126, 148 m/V were measured versus the minimum coercive field of Ec = 50, 20 kV/cm for the PZT/PZT and PZT/BiT thick films, respectively. The thick film piezo-sensors are developed to be potentially used at frequency bandwidth of 1⁻5 MHz for rotary structural health monitoring and also in other industrial or medical applications as a transceiver.