Roboethics principles and policies in Europe and North America.

Robotics and artificial intelligence (AI) are revolutionizing all spheres of human life. From industrial processes to graphic design, the implementation of automated intelligent systems is changing how industries work. The spread of robots and AI systems has triggered academic institutions to closely examine how these technologies may affect the humanity-this is how the fields of roboethics and AI ethics have been born. The identification of ethical issues for robotics and AI and creation of ethical frameworks were the first steps to creating a regulatory environment for these technologies. In this paper, we focus on regulatory efforts in Europe and North America to create enforceable regulation for AI and robotics. We describe and compare ethical principles, policies, and regulations that have been proposed by government organizations for the design and use of robots and AI. We also discuss proposed international regulation for robotics and AI. This paper tries to highlight the need for a comprehensive, enforceable, and agile policy to ethically regulate technology today and in the future. Through reviewing existing policies, we conclude that the European Unition currently leads the way in defining roboethics and AI ethical principles and implementing them into policy. Our findings suggest that governments in Europe and North America are aware of the ethical risks that robotics and AI pose, and are engaged in policymaking to create regulatory policies for these new technologies.

RoboEthics in COVID-19: A Case Study in Dentistry.

The COVID-19 pandemic has caused dramatic effects on the healthcare system, businesses, and education. In many countries, businesses were shut down, universities and schools had to cancel in-person classes, and many workers had to work remotely and socially distance in order to prevent the spread of the virus. These measures opened the door for technologies such as robotics and artificial intelligence to play an important role in minimizing the negative effects of such closures. There have been many efforts in the design and development of robotic systems for applications such as disinfection and eldercare. Healthcare education has seen a lot of potential in simulation robots, which offer valuable opportunities for remote learning during the pandemic. However, there are ethical considerations that need to be deliberated in the design and development of such systems. In this paper, we discuss the principles of roboethics and how these can be applied in the new era of COVID-19. We focus on identifying the most relevant ethical principles and apply them to a case study in dentistry education. DenTeach was developed as a portable device that uses sensors and computer simulation to make dental education more efficient. DenTeach makes remote instruction possible by allowing students to learn and practice dental procedures from home. We evaluate DenTeach on the principles of data, common good, and safety, and highlight the importance of roboethics in Canada. The principles identified in this paper can inform researchers and educational institutions considering implementing robots in their curriculum.

Calibration of surgical tools using multilevel modeling with LINEX loss function: Theory and experiment.

Quantifying the tool-tissue interaction forces in surgery can be used in the training process of novice surgeons to help them better handle surgical tools and avoid exerting excessive forces. A significant challenge concerns the development of proper statistical learning techniques to model the relationship between the true force exerted on the tissue and several outputs read from sensors mounted on the surgical tools. We propose a nonparametric bootstrap technique and a Bayesian multilevel modeling methodology to estimate the true forces. We use the linear exponential loss function to asymmetrically penalize the over and underestimation of the applied forces to the tissue. We incorporate the direction of the force as a group factor in our analysis. A weighted approach is used to account for the nonhomogeneity of read voltages from the surgical tool. Our proposed Bayesian multilevel models provide estimates that are more accurate than those under the maximum likelihood and restricted maximum likelihood approaches. Moreover, confidence bounds are much narrower and the biases and root mean squared errors are significantly smaller in our multilevel models with the linear exponential loss function.

Application of DenTeach in Remote Dentistry Teaching and Learning During the COVID-19 Pandemic: A Case Study.

In December 2019, an outbreak of novel coronavirus pneumonia occurred, and subsequently attracted worldwide attention when it bloomed into the COVID-19 pandemic. To limit the spread and transmission of the novel coronavirus, governments, regulatory bodies, and health authorities across the globe strongly enforced shut down of educational institutions including medical and dental schools. The adverse effects of COVID-19 on dental education have been tremendous, including difficulties in the delivery of practical courses such as restorative dentistry. As a solution to help dental schools adapt to the pandemic, we have developed a compact and portable teaching-learning platform called DenTeach. This platform is intended for remote teaching and learning pertaining to dental schools at these unprecedented times. This device can facilitate fully remote and physical-distancing-aware teaching and learning in dentistry. DenTeach platform consists of an instructor workstation (DT-Performer), a student workstation (DT-Student), advanced wireless networking technology, and cloud-based data storage and retrieval. The platform procedurally synchronizes the instructor and the student with real-time video, audio, feel, and posture (VAFP). To provide quantitative feedback to instructors and students, the DT-Student workstation quantifies key performance indices (KPIs) related to a given task to assess and improve various aspects of the dental skills of the students. DenTeach has been developed for use in teaching, shadowing, and practice modes. In the teaching mode, the device provides each student with tactile feedback by processing the data measured and/or obtained from the instructor's workstation, which helps the student enhance their dental skills while inherently learning from the instructor. In the shadowing mode, the student can download the augmented videos and start watching, feeling, and repeating the tasks before entering the practice mode. In the practice mode, students use the system to perform dental tasks and have their dental performance skills automatically evaluated in terms of KPIs such that both the student and the instructor are able to monitor student's work. Most importantly, as DenTeach is packaged in a small portable suitcase, it can be used anywhere by connecting to the cloud-based data storage network to retrieve procedures and performance metrics. This paper also discusses the feasibility of the DenTeach device in the form of a case study. It is demonstrated that a combination of the KPIs, video views, and graphical reports in both teaching and shadowing modes effectively help the student understand which aspects of their work needs further improvement. Moreover, the results of the practice mode over 10 trials have shown significant improvement in terms of tool handling, smoothness of motion, and steadiness of the operation.

Challenges in developing a magnetic resonance-compatible haptic hand-controller for neurosurgical training.

A haptic device is an actuated human-machine interface utilized by an operator to dynamically interact with a remote environment. This interaction could be virtual (virtual reality) or physical such as using a robotic arm. To date, different mechanisms have been considered to actuate the haptic device to reflect force feedback from the remote environment. In a low-force environment or limited working envelope, the control of some actuation mechanisms such as hydraulic and pneumatic may be problematic. In the development of a haptic device, challenges include limited space, high accuracy or resolution, limitations in kinematic and dynamic solutions, points of singularity, dexterity as well as control system development/design. Furthermore, the haptic interface designed to operate in a magnetic resonance imaging environment adds additional challenges related to electromagnetic interference, static/variable magnetic fields, and the use of magnetic resonance-compatible materials. Such a device would allow functional magnetic resonance imaging to obtain information on the subject's brain activity while performing a task. When used for surgical trainees, functional magnetic resonance imaging could provide an assessment of surgical skills. In this application, the trainee, located supine within the magnet bore while observing the task environment on a graphical user interface, uses a low-force magnetic resonance-compatible haptic device to perform virtual surgical tasks in a limited space. In the quest to develop such a device, this review reports the multiple challenges faced and their potential solutions. The review also investigates efforts toward prototyping such devices and classifies the main components of a magnetic resonance-compatible device including actuation and sensory systems and materials used.

Nonparametric bootstrap technique for calibrating surgical SmartForceps: theory and application.

Knowledge of forces, exerted on the brain tissue during the performance of neurosurgical tasks, is critical for quality assurance, case rehearsal, and training purposes. Quantifying the interaction forces has been made possible by developing SmartForceps, a bipolar forceps retrofitted by a set of strain gauges. The forces are estimated using voltages read from strain gauges. We therefore need to quantify the force-voltage relationship to estimate the interaction forces during microsurgery. This problem has been addressed in the literature by following the physical and deterministic properties of the force-sensing strain gauges without obtaining the precision associated with each estimate. In this paper, we employ a probabilistic methodology by using a nonparametric Bootstrap approach to obtain both point and interval estimates of the applied forces at the tool tips, while the precision associated with each estimate is provided. To show proof-of-concept, the Bootstrap technique is employed to estimate unknown forces, and construct necessary confidence intervals using observed voltages in data sets that are measured from the performance of surgical tasks on a cadaveric brain. Results indicate that the Bootstrap technique is capable of estimating tool-tissue interaction forces with acceptable level of accuracy compared to the linear regression technique under the normality assumption.

Surgical Skill Assessment Using Motion Quality and Smoothness.

OBJECTIVES: This article presents a quantitative technique to assess motion quality and smoothness during the performance of micromanipulation tasks common to surgical maneuvers. The objective is to investigate the effectiveness of the jerk index, a derivative of acceleration with respect to time, as a kinetostatic measure for assessment of surgical performance. DESIGN: A surgical forceps was instrumented with a position tracker and accelerometer that allowed measurement of position and acceleration relative to tool motion. Participants were asked to perform peg-in-hole tasks on a modified O'Connor Dexterity board and a Tweezer Dexterity pegboard (placed inside a skull). Normalized jerk index was calculated for each individual task to compare smoothness of each group. SETTING: This study was conducted at Project neuroArm, Cumming School of Medicine, the University of Calgary. PARTICIPANTS: Four groups of participants (surgeons, surgery residents, engineers, and gamers) participated in the tests. RESULTS: Results showed that the surgeons exhibited better jerk index performance in all tasks. Moreover, the residents experienced motions closer to the surgeons compared to the engineers and gamers. One-way analysis of variance test indicated a significant difference between the mean values of normalized jerk indices among 4 groups during the performance of all tasks. Moreover, the mean value of the normalized jerk index significantly varied for each group from one task to another. CONCLUSIONS: Normalized jerk index as an independent parameter with respect to time and amplitude is an indicator of motion smoothness and can be used to assess hand motion dexterity of surgeons. Furthermore, the method provides a quantifiable metrics for trainee assessment and proficiency, particularly relevant as surgical training shifts toward a competency-based paradigm.

Treatment of Glioma Using neuroArm Surgical System.

The use of robotic technology in the surgical treatment of brain tumour promises increased precision and accuracy in the performance of surgery. Robotic manipulators may allow superior access to narrow surgical corridors compared to freehand or conventional neurosurgery. This paper reports values and ranges of tool-tissue interaction forces during the performance of glioma surgery using an MR compatible, image-guided neurosurgical robot called neuroArm. The system, capable of microsurgery and stereotaxy, was used in the surgical resection of glioma in seven cases. neuroArm is equipped with force sensors at the end-effector allowing quantification of tool-tissue interaction forces and transmits force of dissection to the surgeon sited at a remote workstation that includes a haptic interface. Interaction forces between the tool tips and the brain tissue were measured for each procedure, and the peak forces were quantified. Results showed maximum and minimum peak force values of 2.89 N (anaplastic astrocytoma, WHO grade III) and 0.50 N (anaplastic oligodendroglioma, WHO grade III), respectively, with the mean of peak forces varying from case to case, depending on type of the glioma. Mean values of the peak forces varied in range of 1.27 N (anaplastic astrocytoma, WHO grade III) to 1.89 N (glioblastoma with oligodendroglial component, WHO grade IV). In some cases, ANOVA test failed to reject the null hypothesis of equality in means of the peak forces measured. However, we could not find a relationship between forces exerted to the pathological tissue and its size, type, or location.

Quantifying force and positional frequency bands in neurosurgical tasks.

To establish the design requirements for an MR-compatible haptic hand-controller, this paper measures magnitudes and frequency bands of three mechanical motion and interaction components during the performance of neurosurgical tasks on a cadaveric brain. The hand-controller would allow the performance of virtual neurosurgical tasks within the bore of a high field magnet during image acquisition, i.e., functional MRI. The components are the position and the orientation of a surgical tool, and the force interaction between the tool and the brain tissue. A bipolar forceps was retrofitted with a tracking system and a set of force sensing components to measure displacements and forces, respectively. Results showed working positional, rotational, and force frequency bands of 3, 3 and 5 Hz, respectively. Peak forces of 1.4, 2.9 and 3.0 N were measured in the Cartesian coordinate system. A workspace of 50.1 × 39.8 × 58.2 mm(3) and orientation ranges of 40.4°, 60.1° and 63.1° for azimuth, elevation, and roll angles were observed. The results contribute in providing information specific to neurosurgery that can be used to effectively design a compact and customized haptic hand-controller reflecting characteristics of neurosurgical tasks.

Quantifying workspace and forces of surgical dissection during robot-assisted neurosurgery.

BACKGROUND: A prerequisite for successful robot-assisted neurosurgery is to use a hand-controller matched with characteristics of real robotic microsurgery. This study reports quantified data pertaining to the required workspace and exerted forces of surgical tools during robot-assisted microsurgery. METHODS: A surgeon conducted four operations in which the neuroArm surgical system, an image-guided computer-assisted manipulator specifically designed to perform robot-assisted neurosurgery, was employed to surgically remove brain tumors. The position, orientation, and exerted force of surgical tools were measured during operations. RESULTS: Workspace of the neuroArm manipulators, for the cases studied, was 60×60×60 mm(3) while it offered orientation ranges of 103°, 62° and 112°. The surgical tools exerted a maximum force of 1.86 N with frequency band of less than 20 Hz. CONCLUSIONS: This data provides important information specific to neurosurgery that can be used to select among commercially available, or further design a customized, haptic hand-controller for robot-assisted neurosurgical systems. Copyright © 2015 John Wiley & Sons, Ltd.

Quantification of Forces During a Neurosurgical Procedure: A Pilot Study.

OBJECTIVE: Knowledge of tool-tissue interaction is mostly taught and learned in a qualitative manner because a means to quantify the technical aspects of neurosurgery is currently lacking. Neurosurgeons typically require years of hands-on experience, together with multiple initial trial and error, to master the optimal force needed during the performance of neurosurgical tasks. The aim of this pilot study was to develop a novel force-sensing bipolar forceps for neurosurgery and obtain preliminary data on specific tasks performed on cadaveric brains. METHODS: A novel force-sensing bipolar forceps capable of measuring coagulation and dissection forces was designed and developed by installing strain gauges along the length of the bipolar forceps prongs. The forceps was used in 3 cadaveric brain experiments and forces applied by an experienced neurosurgeon for 10 surgical tasks across the 3 experiments were quantified. RESULTS: Maximal peak (effective) forces of 1.35 N and 1.16 N were observed for dissection (opening) and coagulation (closing) tasks, respectively. More than 70% of forces applied during the neurosurgical tasks were less than 0.3 N. Mean peak forces ranged between 0.10 N and 0.41 N for coagulation of scalp vessels and pia-arachnoid, respectively, and varied from 0.16 N for dissection of small cortical vessel to 0.65 N for dissection of the optic chiasm. CONCLUSIONS: The force-sensing bipolar forceps were able to successfully measure and record real-time tool-tissue interaction throughout the 3 experiments. This pilot study serves as a first step toward quantification of tool-tissue interaction forces in neurosurgery for training and improvement of instrument handling skills.

Robotics in the neurosurgical treatment of glioma.

BACKGROUND: The treatment of glioma remains a significant challenge with high recurrence rates, morbidity, and mortality. Merging image guided robotic technology with microsurgery adds a new dimension as they relate to surgical ergonomics, patient safety, precision, and accuracy. METHODS: An image-guided robot, called neuroArm, has been integrated into the neurosurgical operating room, and used to augment the surgical treatment of glioma in 18 patients. A case study illustrates the specialized technical features of a teleoperated robotic system that could well enhance the performance of surgery. Furthermore, unique positional and force information of the bipolar forceps during surgery were recorded and analyzed. RESULTS: The workspace of the bipolar forceps in this robot-assisted glioma resection was found to be 25 × 50 × 50 mm. Maximum values of the force components were 1.37, 1.84, and 2.01 N along x, y, and z axes, respectively. The maximum total force was 2.45 N. The results indicate that the majority of the applied forces were less than 0.6 N. CONCLUSION: Robotic surgical systems can potentially increase safety and performance of surgical operation via novel features such as virtual fixtures, augmented force feedback, and haptic high-force warning system. The case study using neuroArm robot to resect a glioma, for the first time, showed the positional information of surgeon's hand movement and tool-tissue interaction forces.

Performance evaluation of haptic hand-controllers in a robot-assisted surgical system.

BACKGROUND: This paper presents the experimental evaluation of three commercially available haptic hand-controllers to evaluate which was more suitable to the participants. METHODS: Two surgeons and seven engineers performed two peg-in-hole tasks with different levels of difficulty. Each operator guided the end-effector of a Kuka manipulator that held surgical forceps and was equipped with a surgical microscope. Sigma 7, HD(2) and PHANToM Premium 3.0 hand-controllers were compared. Ten measures were adopted to evaluate operators' performances with respect to effort, speed and accuracy in completing a task, operator improvement during the tests, and the force applied by each haptic device. RESULTS: The best performance was observed with the Premium 3.0; the hand-piece was able to be held in a similar way to that used by surgeons to hold conventional tools. CONCLUSIONS: Hand-controllers with a linkage structure similar to the human upper extremity take advantage of the inherent human brain connectome, resulting in improved surgeon performance during robotic-assisted surgery.