Computer Science

— Virtual Reality Cardiac Stent Simulator is a module under development for Virtual SugerySIM: a proposed Virtual Reality Surgical Simulation Rehearsal Platform that aims to drastically reduce the 440,000[1] deaths caused by medical error in the US each year. The platform will eventually combine the use of haptics (sensory touch and feel) with a 3D immersive environment that will train surgeons to practice surgical procedures in a virtual operating theatre (OR) environment that will look and feel like the real thing. The vision for the virtual OR room in the system is for it to look and feel like a contemporary operation room that is augmented with a 3D virtual patient. The virtual patient will be dynamic and will react to interactions with the surgeons touch (blood flow, bruising). The virtual layer will be networked so that all of the participants in the simulated surgical OR room will see these dynamic changes to the virtual patient in real time. The end result will be a platform that can be used multiple times and that will provide haptic feedback to build the users muscle memory. It will eventually decrease the need for cadavers (saving costs) and result in better trained surgeons.

Percutaneous Nephrolithotomy is the standard surgical procedure used to remove large kidney stones. PCNL procedures have a steep learning curve; a physician needs to complete between 36 and 60 procedures, to achieve clinical proficiency. Marion Surgical K181 is a virtual reality surgical simulator, which emulates the PCNL procedures without compromising the well-being of patients. The simulator uses a VR headset to place a user in a realistic and immersive operating theater, and haptic force-feedback robots to render physical interactions between surgical tools and the virtual patient. The simulator has two modules for two different aspects of PCNL kidney stone removal procedure: kidney access module where the user must insert a needle into the kidney of the patient, and a kidney stone removal module where the user removes the individual stones from the organ. In this paper, we present user trials to validate the face and construct validity of the simulator. The results, based on the data gathered from 4 groups of users independently, indicate that Marion's surgical simulator is a useful tool for teaching and practicing PCNL procedures. The kidney stone removal module of the simulator has proven construct validity by identifying the skill level of different users based on their tool path. We plan to continue evaluating the simulator with a larger sample of users to reinforce our findings.

Percutaneous Nephrolithotomy is the standard surgical procedure used to remove large kidney stones. PCNL procedures have a steep learning curve; a physician needs to complete between 36 and 60 procedures, to achieve clinical proficiency. Marion Surgical K181 is a virtual reality surgical simulator, which emulates the PCNL procedures without compromising the well-being of patients. The simulator uses a VR headset to place a user in a realistic and immersive operating theater, and haptic force-feedback robots to render physical interactions between surgical tools and the virtual patient. The simulator has two modules for two different aspects of PCNL kidney stone removal procedure: kidney access module where the user must insert a needle into the kidney of the patient, and a kidney stone removal module where the user removes the individual stones from the organ. In this paper, we present user trials to validate the face and construct validity of the simulator. The results, based on the data gathered from 4 groups of users independently, indicate that Marion's surgical simulator is a useful tool for teaching and practicing PCNL procedures. The kidney stone removal module of the simulator has proven construct validity by identifying the skill level of different users based on their tool path. We plan to continue evaluating the simulator with a larger sample of users to reinforce our findings.

Percutaneous nephrolithotomy is the leading treatment for large or irregularly shaped kidney stones. Nevertheless, gaining access to the kidney remains a challenging component of the procedure with a steep learning curve. As a result, the procedure would benefit from robotic assistance to partially or fully automate this critical component of the intervention. A key component of automated kidney access, using a robotic manipulator, is to define and follow a tool path planning based on preoperative imaging and a target entry point. In this paper, the use of the multiobjective non-dominated sorting genetic algorithm II (NSGA-II) is proposed to plan a Bspline curve that will be used as the tool trajectory during the procedure. Here, NSGA-II is used to determine the anchor point locations for a uniform 3rd order B-spline curve. The optimal path minimizes path length, tissue potential energy due to tissue compression, and path smoothness while maximizing the distance to obstacles. The multiobjective optimization is evaluated using simulations and physical trials. The results show that the planned trajectories show minimal tissue deformation, are relatively short and smooth and do not collide with the internal kidney structures. We acknowledge the support of Marion Surgical and the Natural Sciences and Engineering Research Council of Canada (NSERC), [funding reference number 2018-06074]. Cette recherche aété menée en collaboration avec Marion Surgical et á eté financée par le Conseil de recherches en sciences naturelles et en génie du Canada (CRSNG), [numéro de référence 2018-06074].

Percutaneous Nephrolithotomy (PCNL) is a procedure used to treat kidney stones. In PCNL, a needle punctures the kidney through an incision in a patient’s back and thin tools are threaded through the incision to gain access to kidney stones for removal. Despite being one of the main endoscopic procedures for managing kidney stones, PCNL remains a difficult procedure to learn with a long and steep learning curve. Virtual reality simulation with haptic feedback is emerging as a new method for PCNL training. It offers benefits for both novices and experienced surgeons. In the first case, novices can practice and gain kidney access in a variety of simulation scenarios without offering any risk to patients. In the second case, surgeons can use the simulator for preoperative surgical rehearsal. This paper proposes the first preliminary study of PCNL surgical rehearsal using the Marion Surgical PCNL simulator. Preoperative CT scans of a patient scheduled to undergo PCNL are used in the simu...

Percutaneous Nephrolithotomy is the standard surgical procedure used to remove large kidney stones. PCNL procedures have a steep learning curve; a physician needs to complete between 36 and 60 procedures, to achieve clinical proficiency. Marion Surgical K181 is a virtual reality surgical simulator, which emulates the PCNL procedures without compromising the well-being of patients. The simulator uses a VR headset to place a user in a realistic and immersive operating theater, and haptic force-feedback robots to render physical interactions between surgical tools and the virtual patient. The simulator has two modules for two different aspects of PCNL kidney stone removal procedure: kidney access module where the user must insert a needle into the kidney of the patient, and a kidney stone removal module where the user removes the individual stones from the organ. In this paper, we present user trials to validate the face and construct validity of the simulator. The results, based on the data gathered from 4 groups of users independently, indicate that Marion's surgical simulator is a useful tool for teaching and practicing PCNL procedures. The kidney stone removal module of the simulator has proven construct validity by identifying the skill level of different users based on their tool path. We plan to continue evaluating the simulator with a larger sample of users to reinforce our findings.

An exquisite music performance can move an audience to tears of joy, or those of sorrow. The job of a good performer then is to convey not just the music’s notated structure, but also its emotional metadata. In time, the performer will also learn to respond musically to the state of a live audience; matching their emotional ebb and flow to maintain interest for the concert’s entirety. This work will discuss an Affective Performance framework in which compositions are marked up with emotional intent, or narrative. This mark-up directs the emotive adaptation of the symbolic score’s reproduction, enhancing the computer music’s realism. Examining the cognitive model of emotions appraisal theory, we highlight some key evidence underlying the principle of music expectancy and its central role in maintaining a listener’s musical interest. This knowledge will play a significant role in developing an adaptive music engine in which the traditionally static score is manipulated in real time. We will also show how new Affective Computing technologies for reading the emotional state of users can be employed to further adapt the performance to account for audience emotional state. We end with an illustration of the framework, with examples in computer gaming engines and enhanced live performances for a distributed audience.

Music plays an enormous role in today's computer games; it serves to elicit emotion, generate interest and convey important information. Traditional gaming music is fixed at the event level, where tracks loop until a state change is triggered. This behaviour however does not reflect musically the in-game state between these events. We propose a dynamic music environment, where music tracks adjust in real-time to the emotion of the in game state. We are looking to improve the affective response to symbolic music through the modification of structural and performative characteristics through the application of rule-based techniques. In this paper we undertake a multidiscipline approach, and present a series of primary music-emotion structural rules for implementation. The validity of these rules was tested in small study involving eleven participants, each listening to six permutations from two musical works. Preliminary results indicate that the environment was generally successful in influencing the emotion of the musical works for three of the intended four directions (happy, sad and content/dreamy). Our secondary aim of establishing that the use of music-emotion rules, sourced predominantly from Western classical music, could be applied with comparable results to modern computer gaming music was also generally successfully.

The rigors of establishing innateness and domain
specificity pose challenges to adaptationist models of
music evolution. In articulating a series of constraints,
the authors of the target articles provide strategies for
investigating the potential origins of music.We propose
additional approaches for exploring theories based on
exaptation.We discuss a view of music as a multimodal
system of engaging with affect, enabled by capacities of
symbolism and a theory of mind.

Emotions are a key part of creative endeavours, and a core problem for computational models of creativity. In this paper we discuss an affective computing architecture for the dynamic modification of music with a view to predictably affecting induced musical emotions. Extending previous work on the modification of perceived emotions in music, our system architecture aims to provide reliable control of both perceived and induced musical emotions: its emotionality. A rule-based system is used to modify a subset of musical features at two processing levels, namely score and performance. The interactive model leverages sensed listener affect by adapting the emotionality of the music modifications in real-time to assist the listener in reaching a desired emotional state.

Two experiments examined the effects of repetition on listeners' emotional response to music. Listeners heard recordings of orchestral music that contained a large section repeated twice. The music had a symmetric phrase structure (same-length phrases) in Experiment 1 and an asymmetric phrase structure (different-length phrases) in Experiment 2, hypothesized to alter the predictability of sensitivity to musical repetition. Continuous measures of arousal and valence were compared across music that contained identical repetition, variation (related), or contrasting (unrelated) structure. Listeners' emotional arousal ratings differed most for contrasting music, moderately for variations, and least for repeating musical segments. A computational model for the detection of repeated musical segments was applied to the listeners' emotional responses. The model detected the locations of phrase boundaries from the emotional responses better than from performed tempo or physical intensity in both experiments. These findings indicate the importance of repetition in listeners' emotional response to music and in the perceptual segmentation of musical structure.