Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions

Purpose: Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to perform delicate procedures on a beating heart, avoiding the complications of cardiac arrest. This advantage comes with the price of having to deal with a dynamic target which presents technical challenges for the surgical system. In this work, we propose a solution for cardiac motion estimation. Methods: Our estimation approach uses a variational framework that guarantees preservation of the complex anatomy of the heart. An advantage of our approach is that it takes into account different disturbances, such as specular reflections and occlusion events. This is achieved by performing a preprocessing step that eliminates the specular highlights and a predicting step, based on a conditional restricted Boltzmann machine, that recovers missing information caused by partial occlusions. Results: We carried out exhaustive experimentations on two datasets, one from a phantom and the other from an in vivo procedure. The results show that our visual approach reaches an average minima in the order of magnitude of 10-7 while preserving the heart’s anatomical structure and providing stable values for the Jacobian determinant ranging from 0.917 to 1.015. We also show that our specular elimination approach reaches an accuracy of 99% compared to a ground truth. In terms of prediction, our approach compared favorably against two well-known predictors, NARX and EKF, giving the lowest average RMSE of 0.071. Conclusion: Our approach avoids the risks of using mechanical stabilizers and can also be effective for acquiring the motion of organs other than the heart, such as the lung or other deformable objects.Peer ReviewedPostprint (published version

The Position and Norms of Translated Children’s Literature in Saudi Arabia: A Multimodal Socio-cultural Approach

When examining the position and norms of translated children’s literature, researchers tend to speak of the ‘Arab world’ rather than a specific country. Although the Arab world shares a language, it does not have a single culture, economy, politics, etc. Variations between different countries are reflected in its translated children’s literature. Picturebooks are made up of a verbal mode, visual mode and the combination of these two modes (i.e. intermodal relations). Nonetheless, researchers tend only to consider the verbal mode in regard to picturebooks, ignoring the visual mode and the intermodal relations. In light of these gaps, this research aims to assess the position and norms of translated children’s literature within the Saudi market as well as examine picturebooks in their entirety. To do so, this thesis asks five main questions: 1) What is the position of translated children’s literature in Saudi Arabia? 2) How are textual, paratextual and metatextual aspects of Arabic target texts correlated to the position of translated children’s literature in Saudi Arabia? 3) What translational initial norms are adopted to translate elements in the verbal and visual modes? 4) Which intermodal relations can be identified in the source and target texts, and how are they approached in translation? 5) What norms govern children’s literature translated from English into Arabic in Saudi Arabia? Based on Even-Zohar’s polysystem theory (1990), Toury’s notion of norms (2012a) and Kress and van Leeuwen’s (2001) multimodal approach, a comparative multimodal analysis of elements, translation techniques and intermodal relations was carried out on twenty cases. All distributed in the Saudi market, these cases were published by four publishers originating from three different Arab countries: Saudi Arabia, Egypt and Lebanon. The analytical framework combines the Composite Translation Techniques Model, the Composite Elements Model and Nikolajeva and Scott’s (2000) typology of image-text relationships. To assess the position of translated children’s literature, this study looks at the volume of translated children’s literature from and into Saudi Arabia, as well as the volume of translated Saudi children’s literature in comparison to original Saudi children’s literature and Saudis’ perception of the state of the latter. To explore the hypothetical links to the position of translation, textual (i.e. initial norms), metatextual elements (i.e. perception) and paratextual elements (i.e. price, binding type, publishing format and the (in)visibility of translators’ and authors’ names) are examined. There are three types of norms in this research: elements, translation techniques and element-specific translation technique(s), which are extracted using a comparative multimodal analysis to identify regularities of behaviour and are argued based on Chesterman’s (2017) normative forces. The dynamicity of norms in translated children’s literature in Saudi Arabia is explained in terms of Chang’s (2000) macro-polysystem hypothesis. The results indicate that translated children’s literature in Saudi Arabia seems to occupy a central position in the children’s literature polysystem. However, contrary to Even-Zohar’s hypothesis, this position is mostly accompanied by a TL-oriented translation method. Similarly, metatextual and paratextual aspects examined in this research show no clear connection to the proposed position. Despite being multimodal, picturebooks are treated mainly as monomodal verbal texts in which each mode has a different translation method. The use of TL-oriented translation techniques, such as substitution, visual substitution, modulation and discursive creation has caused many intermodal relation shifts in TTs. A hypothetical link between a higher number of intermodal relation shifts and a higher degree of TL-orientation has been established, which is confirmed by an initial test. Results also identify several norms in translated children’s literature available in the Saudi market. Examples include the non-occurrence of alcohol, the clear presence of social and moral values, the adoption of visual repetition and the literal translation of elements involving mythical and magical creatures

V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery

Accurate and robust estimation of applied forces in Robotic-Assisted Minimally Invasive Surgery is a very challenging task. Many vision-based solutions attempt to estimate the force by measuring the surface deformation after contacting the surgical tool. However, visual uncertainty, due to tool occlusion, is a major concern and can highly affect the results' precision. In this paper, a novel design of an adaptive neuro-fuzzy inference strategy with a voting step (V-ANFIS) is used to accommodate with this loss of information. Experimental results show a significant accuracy improvement from 50% to 77% with respect to other proposals.Peer ReviewedPostprint (published version

Towards retrieving force feedback in robotic-assisted surgery: a supervised neuro-recurrent-vision approach

Robotic-assisted minimally invasive surgeries have gained a lot of popularity over conventional procedures as they offer many benefits to both surgeons and patients. Nonetheless, they still suffer from some limitations that affect their outcome. One of them is the lack of force feedback which restricts the surgeon's sense of touch and might reduce precision during a procedure. To overcome this limitation, we propose a novel force estimation approach that combines a vision based solution with supervised learning to estimate the applied force and provide the surgeon with a suitable representation of it. The proposed solution starts with extracting the geometry of motion of the heart's surface by minimizing an energy functional to recover its 3D deformable structure. A deep network, based on a LSTM-RNN architecture, is then used to learn the relationship between the extracted visual-geometric information and the applied force, and to find accurate mapping between the two. Our proposed force estimation solution avoids the drawbacks usually associated with force sensing devices, such as biocompatibility and integration issues. We evaluate our approach on phantom and realistic tissues in which we report an average root-mean square error of 0.02 N.Peer ReviewedPostprint (author's final draft

COVID-19 knowledge and perception among healthcare professionals in two Arabian Gulf countries

Introduction: The WHO announced on 30 January 2020 the respiratory tract infection outbreak caused by Coronavirus 2019 (COVID-19) that was first recognized in China to be a global public health emergency. Objective: To investigate healthcare professional's knowledge and awareness about COVID-19. Methods: The study was conducted across four hospitals in Saudi Arabia and two hospitals in Kuwait. The questionnaire was completed between 18th May and the end of June 2020. Results: A total of 460 healthcare professionals completed the questionnaire, 37.8%(n=174) were males. The age of the participants ranged from 18 to 64 and 80.4% (n=370) of the participants were aged 34 or below. Official government websites 54.8% (n=252) and social media 43.3% (n=199) were the major reliable information sources related to COVID-19. only 37% (n=170) mentioned that the coronavirus disease could transmit through contact. In addition, only 42% (n=191) of the study participants had the correct knowledge about the incubation period of the disease. Moreover, 43.5% (n=200) of the participants were able to identify the symptoms of COVID-19. Conclusion: The study recommended the need to focus more on educational and awareness programs targeting all healthcare professionals to ensure the best practice and provide the optimal care

Brain-computer interface technology for speech recognition: A review

This paper presents an overview of the studies that have been conducted with the purpose of understanding the use of brain signals as input to a speech recogniser. The studies have been categorised based on the type of the technology used with a summary of the methodologies used and achieved results. In addition, the paper gives an insight into some studies that examined the effect of the chosen stimuli on brain activities as an important factor in the recognition process. The remaining part of this paper lists the limitations of the available studies and the challenges for future work in this area

Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions.

PURPOSE: Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to perform delicate procedures on a beating heart, avoiding the complications of cardiac arrest. This advantage comes with the price of having to deal with a dynamic target which presents technical challenges for the surgical system. In this work, we propose a solution for cardiac motion estimation. METHODS: Our estimation approach uses a variational framework that guarantees preservation of the complex anatomy of the heart. An advantage of our approach is that it takes into account different disturbances, such as specular reflections and occlusion events. This is achieved by performing a preprocessing step that eliminates the specular highlights and a predicting step, based on a conditional restricted Boltzmann machine, that recovers missing information caused by partial occlusions. RESULTS: We carried out exhaustive experimentations on two datasets, one from a phantom and the other from an in vivo procedure. The results show that our visual approach reaches an average minima in the order of magnitude of [Formula: see text] while preserving the heart's anatomical structure and providing stable values for the Jacobian determinant ranging from 0.917 to 1.015. We also show that our specular elimination approach reaches an accuracy of 99% compared to a ground truth. In terms of prediction, our approach compared favorably against two well-known predictors, NARX and EKF, giving the lowest average RMSE of 0.071. CONCLUSION: Our approach avoids the risks of using mechanical stabilizers and can also be effective for acquiring the motion of organs other than the heart, such as the lung or other deformable objects

The Use of a Mobile-Based Telehealth Service During the COVID-19 Pandemic: Provider Experience and Satisfaction

Background: Telehealth is a promising healthcare delivery model that uses telecommunication technologies to improve healthcare access by remotely offering health care services to people with limited access to these services. Due to the lockdown and restrictions caused by the COVID-19 pandemic, many healthcare organizations are now utilizing telehealth systems to remotely provide health care services and mitigate the spread of COVID-19 by minimizing physical interactions. Objective: To assess the providers’ experience and satisfaction with a telehealth technology “Sehha” being used by physicians during COVID-19, examine the challenges faced by the providers, and identify possible opportunities to improve the use of telehealth in Saudi Arabia. Method: With the collaboration of the Saudi Ministry of Health, a 30-item questionnaire consisting of quantitative and qualitative questions was distributed to 362 physicians using the Sehha telehealth app. The questionnaire items were adapted from previous studies and then tested for content validity and reliability (α = 0.88). Results: One hundred fourteen out of 362 questionnaires were analyzed with a response rate of 31%. The study showed that 67.6% of the physicians were satisfied with the work they have done through Sehha. Forty-four percent of the physicians preferred telehealth visits over traditional visits, while 35.1% did not prefer telehealth, and 21.1% reported to be neutral. However, the most commonly perceived challenge by the physicians using Sehha was difficulty in providing accurate medical assessments (73.7%), followed by overlapping of consultations (71.1%), while the most frequently cited area of the platform needed for improvement was integration with other systems (86.8%), followed by involvement of other medical specialists (81.6%). Conclusion: Telehealth is the new norm of delivering health care service, and its benefits have been realized worldwide. Telehealth can increase access to care, improve the quality of care, and reduce cost. Besides face-to-face visits, health care providers are now embracing telehealth technologies and showing interest in virtual care. Thus, telehealth should remain sustained after the era of COVID-19, and healthcare leaders should reconsider the status of telehealth

Sight to touch: 3D diffeomorphic deformation recovery with mixture components for perceiving forces in robotic-assisted surgery

Robotic-assisted minimally invasive surgical sys-tems suffer from one major limitation which is the lack of interaction forces feedback. The restricted sense of touch hinders the surgeons’ performance and reduces their dexterity and precision during a procedure. In this work, we present a sensory substitution approach that relies on visual stimuli to transmit the tool-tissue interaction forces to the operating surgeon. Our approach combines a 3D diffeomorphic defor-mation mapping with a generative model to precisely label the force level. The main highlights of our approach are that the use of diffeomorphic transformation ensures anatomical structure preservation and the label assignment is based on a parametric form of several mixture elements. We performed experimentations on both ex-vivo and in-vivo datasets and offer careful numerical results evaluating our approach. The results show that our solution has an error measure less than 1mm in all directions and an average labeling error of 2.05%. It can also be applicable to other scenarios that require force feedback such as microsurgery, knot tying or needle-based procedures.Peer ReviewedPostprint (author's final draft