Sensory-Glove-Based Open Surgery Skill Evaluation

Manual dexterity is one of the most important surgical skills, and yet there are limited instruments to evaluate this ability objectively. In this paper, we propose a system designed to track surgeons’ hand movements during simulated open surgery tasks and to evaluate their manual expertise. Eighteen participants, grouped according to their surgical experience, performed repetitions of two basic surgical tasks, namely single interrupted suture and simple running suture. Subjects’ hand movements were measured with a sensory glove equipped with flex and inertial sensors, tracking flexion/extension of hand joints, and wrist movement. The participants’ level of experience was evaluated discriminating manual performances using linear discriminant analysis, support vector machines, and artificial neural network classifiers. Artificial neural networks showed the best performance, with a median error rate of 0.61% on the classification of single interrupted sutures and of 0.57% on simple running sutures. Strategies to reduce sensory glove complexity and increase its comfort did not affect system performances substantially

A 10-17 DOF Sensory Gloves with Harvesting Capability for Smart Healthcare

We here present a 10-17 Degrees of Freedom (DoF) sensory gloves for Smart Healthcare implementing an energy harvesting architecture, aimed at enhancing the battery lasting when powering the electronics of the two different types of gloves, used to sense fingers movements. In particular, we realized a comparison in terms of measurement repeatability and reliability, as well as power consumption and battery lasting, between two sensory gloves implemented by means of different technologies. The first is a 3D printed glove with 10 DoF, featuring low-cost, low-effort fabrication and low-power consumption. The second is a classical Lycra® glove with 14 DoF suitable for a more detailed assessment of the hand postures, featuring a relatively higher cost and power consumption. An electronic circuitry was designed to gather and elaborate data from both types of sensory gloves, differing for number of inputs only. Both gloves are equipped with flex sensors and in addiction with the electronics (including a microcontroller and a transmitter) allow the control of hand virtual limbs or mechanical arts in surgical, military, space and civil applications.Six healthy subjects were involved in tests suitable to evaluate the performances of the proposed gloves in terms of repeatability, reproducibility and reliability. Particular effort was devoted to increase battery lasting for both glove-based systems, with the electronics relaying on Radio Frequency, Piezoelectric and Thermoelectric harvesters. The harvesting part was built and tested as a prototype discrete element board, that is interfaced with an external microcontroller and a radiofrequency transmitter board. Measurement results demonstrated a meaningful improvement in battery operation time up to 25%, considering different operating scenarios

Modified constraint-induced movement therapy or bimanual occupational therapy following injection of Botulinum toxin-A to improve bimanual performance in young children with hemiplegic cerebral palsy: a randomised controlled trial methods paper

<p>Abstract</p> <p>Background</p> <p>Use of Botulinum toxin-A (BoNT-A) for treatment of upper limb spasticity in children with cerebral palsy has become routine clinical practice in many paediatric treatment centres worldwide. There is now high-level evidence that upper limb BoNT-A injection, in combination with occupational therapy, improves outcomes in children with cerebral palsy at both the body function/structure and activity level domains of the International Classification of Functioning, Disability and Health. Investigation is now required to establish what amount and specific type of occupational therapy will further enhance functional outcomes and prolong the beneficial effects of BoNT-A.</p> <p>Methods/Design</p> <p>A randomised, controlled, evaluator blinded, prospective parallel-group trial. Eligible participants were children aged 18 months to 6 years, diagnosed with spastic hemiplegic cerebral palsy and who were able to demonstrate selective motor control of the affected upper limb. Both groups received upper limb injections of BoNT-A. Children were randomised to either the modified constraint-induced movement therapy group (experimental) or bimanual occupational therapy group (control). Outcome assessments were undertaken at pre-injection and 1, 3 and 6 months following injection of BoNT-A. The primary outcome measure was the Assisting Hand Assessment. Secondary outcomes included: the Quality of Upper Extremity Skills Test; Pediatric Evaluation of Disability Inventory; Canadian Occupational Performance Measure; Goal Attainment Scaling; Pediatric Motor Activity Log; modified Ashworth Scale and; the modified Tardieu Scale.</p> <p>Discussion</p> <p>The aim of this paper is to describe the methodology of a randomised controlled trial comparing the effects of modified constraint-induced movement therapy (a uni-manual therapy) versus bimanual occupational therapy (a bimanual therapy) on improving bimanual upper limb performance of children with hemiplegic cerebral palsy following upper limb injection of BoNT-A. The paper outlines the background to the study, the study hypotheses, outcome measures and trial methodology. It also provides a comprehensive description of the interventions provided.</p> <p>Trial Registration</p> <p>ACTRN12605000002684</p

A survey of haptics in serious gaming

Serious gaming often requires high level of realism for training and learning purposes. Haptic technology has been proved to be useful in many applications with an additional perception modality complementary to the audio and the vision. It provides novel user experience to enhance the immersion of virtual reality with a physical control-layer. This survey focuses on the haptic technology and its applications in serious gaming. Several categories of related applications are listed and discussed in details, primarily on haptics acts as cognitive aux and main component in serious games design. We categorize haptic devices into tactile, force feedback and hybrid ones to suit different haptic interfaces, followed by description of common haptic gadgets in gaming. Haptic modeling methods, in particular, available SDKs or libraries either for commercial or academic usage, are summarized. We also analyze the existing research difficulties and technology bottleneck with haptics and foresee the future research directions

POV-Surgery: A Dataset for Egocentric Hand and Tool Pose Estimation During Surgical Activities

The surgical usage of Mixed Reality (MR) has received growing attention in areas such as surgical navigation systems, skill assessment, and robot-assisted surgeries. For such applications, pose estimation for hand and surgical instruments from an egocentric perspective is a fundamental task and has been studied extensively in the computer vision field in recent years. However, the development of this field has been impeded by a lack of datasets, especially in the surgical field, where bloody gloves and reflective metallic tools make it hard to obtain 3D pose annotations for hands and objects using conventional methods. To address this issue, we propose POV-Surgery, a large-scale, synthetic, egocentric dataset focusing on pose estimation for hands with different surgical gloves and three orthopedic surgical instruments, namely scalpel, friem, and diskplacer. Our dataset consists of 53 sequences and 88,329 frames, featuring high-resolution RGB-D video streams with activity annotations, accurate 3D and 2D annotations for hand-object pose, and 2D hand-object segmentation masks. We fine-tune the current SOTA methods on POV-Surgery and further show the generalizability when applying to real-life cases with surgical gloves and tools by extensive evaluations. The code and the dataset are publicly available at batfacewayne.github.io/POV_Surgery_io/

Perception and Orientation in Minimally Invasive Surgery

During the last two decades, we have seen a revolution in the way that we perform abdominal surgery with increased reliance on minimally invasive techniques. This paradigm shift has come at a rapid pace, with laparoscopic surgery now representing the gold standard for many surgical procedures and further minimisation of invasiveness being seen with the recent clinical introduction of novel techniques such as single-incision laparoscopic surgery and natural orifice translumenal endoscopic surgery. Despite the obvious benefits conferred on the patient in terms of morbidity, length of hospital stay and post-operative pain, this paradigm shift comes at a significantly higher demand on the surgeon, in terms of both perception and manual dexterity. The issues involved include degradation of sensory input to the operator compared to conventional open surgery owing to a loss of three-dimensional vision through the use of the two-dimensional operative interface, and decreased haptic feedback from the instruments. These changes have led to a much higher cognitive load on the surgeon and a greater risk of operator disorientation leading to potential surgical errors. This thesis represents a detailed investigation of disorientation in minimally invasive surgery. In this thesis, eye tracking methodology is identified as the method of choice for evaluating behavioural patterns during orientation. An analysis framework is proposed to profile orientation behaviour using eye tracking data validated in a laboratory model. This framework is used to characterise and quantify successful orientation strategies at critical stages of laparoscopic cholecystectomy and furthermore use these strategies to prove that focused teaching of this behaviour in novices can significantly increase performance in this task. Orientation strategies are then characterised for common clinical scenarios in natural orifice translumenal endoscopic surgery and the concept of image saliency is introduced to further investigate the importance of specific visual cues associated with effective orientation. Profiling of behavioural patterns is related to performance in orientation and implications on education and construction of smart surgical robots are drawn. Finally, a method for potentially decreasing operator disorientation is investigated in the form of endoscopic horizon stabilization in a simulated operative model for transgastric surgery. The major original contributions of this thesis include: Validation of a profiling methodology/framework to characterise orientation behaviour Identification of high performance orientation strategies in specific clinical scenarios including laparoscopic cholecystectomy and natural orifice translumenal endoscopic surgery Evaluation of the efficacy of teaching orientation strategies Evaluation of automatic endoscopic horizon stabilization in natural orifice translumenal endoscopic surgery The impact of the results presented in this thesis, as well as the potential for further high impact research is discussed in the context of both eye tracking as an evaluation tool in minimally invasive surgery as well as implementation of means to combat operator disorientation in a surgical platform. The work also provides further insight into the practical implementation of computer-assistance and technological innovation in future flexible access surgical platforms

An empirical examination of feedback : user control and performance in a hapto-audio-visual training environment

Utilising advanced technologies, such as virtual environments (VEs), is of importance to training and education. The need to develop and effectively apply interactive, immersive 3D VEs continues to grow. As with any emerging technology, user acceptance of new software and hardware devices is often difficult to measure and guidelines to introduce and ensure adequate and correct usage of such technologies are lacking. It is therefore imperative to obtain a solid understanding of the important elements that play a role in effective learning through VEs. In particular, 3D VEs may present unusual and varied interaction and adoption considerations. The major contribution of this study is to investigate a complex set of interrelated factors in the relatively new sphere of VEs for training and education. Although many of the factors appears to be important from past research, researcher have not explicitly studied a comprehensive set of inter-dependant, empirically validated factors in order to understand how VEs aid complex procedural knowledge and motor skill learning. By integrating theory from research on training, human computer interaction (HCI), ergonomics and cognitive psychology, this research proposes and validates a model that contributes to application-specific VE efficacy formation. The findings of this study show visual feedback has a significant effect on performance. For tactile/force feedback and auditory feedback, no significant effect were found. For satisfaction, user control is salient for performance. Other factors such as interactivity and system comfort, as well as level of task difficulty, also showed effects on performance.<br /

A comparative analysis of haptic and EEG devices for evaluation and training of post-stroke patients within a virtual environment

Virtual Rehabilitation benefits from the usage of interfaces other than the mouse and keyboard, but also possess disadvantages: haptic peripherals can utilize the subject\u27s hand to provide position information or joint angles, and allow direct training for specific movements; but can also place unneeded strain on the limbs; brain-machine interfaces (BMI) can provide direct connections from the user to external hardware or software, but are currently inaccurate for the full diversity of user movements in daily life and require invasive surgery to implement. A compromise between these two extremes is a BMI that can be adapted to specific users, can function with a wide range of hardware and software, and is both noninvasive and convenient to wear for extended periods of time. A suitable BMI using Electroencephalography (EEG) input, known as the Emotiv EPOC™ by Emotiv Systems was evaluated using multiple input specializations and tested with an external robotic arm to determine if it was suitable for control of peripherals. Users were given a preset periodicity to follow in order to evaluate their ability to translate specific facial movements into commands as well as their responsiveness to change the robot arm\u27s direction. Within 2 weeks of training, they maintained or improved axial control of the robot arm, and reduced their overall performance time. Although the EPOC™ does require further testing and development, its adaptability to multiple software programs, users and peripherals allows it to serve both Virtual Rehabilitation and device control in the immediate future