Biomechanical Computer Models

In the past decade computer models have become very popular in the field of biomechanics due to exponentially increasing computer power. Biomechanical computer models can roughly be subdivided into two groups: multi-body models and numerical models. The theoretical aspects of both modelling strategies will be introduced. However, the focus of this chapter lies on demonstrating the power and versatility of computer models in the field of biomechanics by presenting sophisticated finite element models of human body parts. Special attention is paid to explain the setup of individual models using medical scan data. In order to reach the goal of individualising the model a chain of tools including medical imaging, image acquisition and processing, mesh generation, material modelling and finite element simulation –possibly on parallel computer architectures- becomes necessary. The basic concepts of these tools are described and application results are presented. The chapter ends with a short outlook into the future of computer biomechanics

Pelatihan Inspection Preventive Maintenance (IPM) MRI

In Indonesia, the quality assurance of medical devices is carried out by the Hospital Facility Maintenance Installation, abbreviated as IPSRS. Generally, IPSRS staff consists of Human Resources (HR) who have qualifications in Electromedical, Public Health, and Management qualifications. Human resources in charge of carrying out maintenance and repairs, hereinafter referred to as Preventive Maintenance Inspections (IPM) of medical devices, are human resources with electromedical qualifications. Magnetic Resonance Imaging (MRI) is an advanced medical device that combines computer technology, high magnetic fields (0.067.0 Tesla) and radio waves to produce cross-sectional images of the muscles of the human body. To prepare patient services in hospitals using an MRI tool, reliable human resources are needed in carrying out their HDI. For this reason, training on the HDI of this MRI equipment is needed. This HDI training was attended by 534 participants from all over Indonesia which was carried out through the Zoom Meeting Application. This training succeeded in increasing the ability of participants by 27.98% while the average satisfaction of training participants was assessed from 5 aspects, namely at 86.65%, so that the training carried out is in the very satisfactory category.In Indonesia, the quality assurance of medical devices is carried out by the Hospital Facility Maintenance Installation, abbreviated as IPSRS. Generally, IPSRS staff consists of Human Resources (HR) who have qualifications in Electromedical, Public Health, and Management qualifications. Human resources in charge of carrying out maintenance and repairs, hereinafter referred to as Preventive Maintenance Inspections (IPM) of medical devices, are human resources with electromedical qualifications. Magnetic Resonance Imaging (MRI) is an advanced medical device that combines computer technology, high magnetic fields (0.067.0 Tesla) and radio waves to produce cross-sectional images of the muscles of the human body. To prepare patient services in hospitals using an MRI tool, reliable human resources are needed in carrying out their HDI. For this reason, training on the HDI of this MRI equipment is needed. This HDI training was attended by 534 participants from all over Indonesia which was carried out through the Zoom Meeting Application. This training succeeded in increasing the ability of participants by 27.98% while the average satisfaction of training participants was assessed from 5 aspects, namely at 86.65%, so that the training carried out is in the very satisfactory category

Investigating the User Experience with a 3D Virtual Anatomy Application

Decreasing hours dedicated to teaching anatomy courses and declining use of human cadavers have spurred the need for innovative solutions in teaching anatomy in medical schools. Advancements in virtual reality (VR), 3D visualizations, computer graphics, and medical graphic images have enabled the development of highly interactive 3D virtual applications. Over recent years, variations of interactive systems on computer-mediated environments have been used as supplementary resource for learners. However, despite the growing sophistication of these resources for learning anatomy, studies show that students predominantly prefer traditional methods of learning and hands-on cadaver-based learning over computer-mediated platforms. There is limited research on evaluating user experience in the use of interactive 3D anatomy systems, even though Human-Computer Interaction (HCI) studies show that usability (ease of use) and user engagement are essential to technology adoption and satisfaction. The addressable problem of the research was to investigate how ease of use and flow affected aspects of the students’ engagement experience with the use of a 3D virtual anatomy application. The aim of the study was to evaluate the use of a 3D virtual application in performing dissection learning tasks and to understand aspects of user engagement as assessed by ease of use and flow experience. The flow experience was quantified using the Short Flow State Scale (S FSS-2) and the System Usability Scale (SUS) to measure perceptions about ease of use and user satisfaction. The research questions included: (1) What consequences of flow do students experience? (2) What aspects of the 3D virtual platform are distracting to performing the learning tasks? (3) How do students’ perception of ease of use affect the flow experience based on the SUS and S FSS-2 scores? (4) How do students rate their level of engagement as measured by flow based on their S FSS-2 scores? (5) How does flow help explain student satisfaction and motivation? (6) How do students perceive use of the application to learn anatomy compared with cadaver-based dissection? The study consisted of medical student participants who were asked to complete virtual dissection activities associated with learning objectives in the Structure of the Human Body course to perform using a 3D virtual anatomy application. A subset of participants who completed the learning task and the surveys had a follow-up Cognitive Walkthrough with Think-Aloud Protocol observation activity with an interview segment to gain deeper insights into their user experience with the application. The data from the convergent mixed method analysis indicated that ease of use had some impact on the flow experience and that perceived user satisfaction and motivation were attributed to the interactive 3D visualization design. Seven super-ordinate themes were identified: Ease of Use, Learnability, Interface-Technical, User Satisfaction, Visuospatial, Focus/In the Zone, and CA vs Cadaver. The results have implications for educators (particularly anatomists), educational technologists, and HCI and UX practitioners. Additional research should be conducted using the long version of the Flow State Scale to provide a better understanding of each flow dimension. Further study is recommended with students who have hands-on experience with human cadaver dissection that are also able to compare their experience with the use of a 3D virtual anatomy platform for a direct side-by-side assessment. It would also be helpful to conduct the study as part of the entire duration of the anatomy course and assess how the flow experience impacts student learning performance

The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry

Introduction to the ACM TIST Special Issue on Intelligent Healthcare Informatics

Healthcare Informatics is a research area dealing with the study and application of computer science and information and communication technology to face both theoretical/methodological and practical issues in healthcare, public health, and everyday wellness. Intelligent Healthcare Informatics may be defined as the specific area focusing on the use of artificial intelligence (AI) theories and techniques to offer important services (such as a component of complex systems) to allow integrated systems to perceive, reason, learn, and act intelligently in the healthcare arena. One of the many peculiarities of healthcare is that decision support systems need to be integrated with several heterogeneous systems supporting both collaborative work and process coordination and the management and analysis of a huge amount of clinical and health data, to compose intelligent, process-aware health information systems. After some pioneering work focusing explicitly on specific medical aspects and providing some efficient, even ad hoc, solutions, in recent years, AI in healthcare has been faced by researchers with different backgrounds and interests, taking into consideration the main results obtained in the more general and theoretical/methodological area of intelligent systems. Moreover, from a focus on reasoning strategies and deep knowledge representation, research in healthcare intelligent systems moved to data-intensive clinical tasks, where there is the need for supporting healthcare decision making in the presence of overwhelming amounts of clinical data. Significant solutions have been provided through a multidisciplinary combination of the results from the different research areas and their associated cultures, ranging from algorithms, to information systems and databases, to human-computer interaction, to medical informatics. To this regard, it is interesting to observe that, from one side, medical informaticians benefited by the general solutions coming from the generic computer science area, tailoring them to specific medical domains, while from the other side, computer scientists found several (still open) challenges in the medical and, more generally, health domains. This ACM Transactions on Intelligent Systems and Technology (ACM TIST) special issue contains articles discussing fundamental principles, algorithms, or applications for process-aware health information systems. Such articles are a sound answer to the research challenges for novel techniques, combinations of tools, and so forth to build effective ways to manage and deal in an integrated way with healthcare processes and data

Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Ontologies for Intelligent e-Theraoy: Application to Obesity

[EN] In this paper we propose a new approach for mental e-health treatments named intelligent e-therapy (e-it) with capabilities for ambient intelligence and ubiquitous computing. The proposed e-it system supposes an evolution of cybertherapy and telepsychology tools used up to now. The e-it system is based in a knowledge base that includes all the knowledge related to the disorder and its treatment. We introduce the use of ontologies as the best option for the design of this knowledge base. We also present a fist e-it system for obesity treatment called etiobeZaragozá Álvarez, I.; Guixeres Provinciale, J.; Alcañiz Raya, ML. (2009). Ontologies for Intelligent e-Theraoy: Application to Obesity. Lecture Notes in Computer Science. 5518:894-901. doi:10.1007/978-3-642-02481-8_136S8949015518Baños, R.M., Botella, C., Perpiñá, C., Alcañiz, M., Lozano, J.A., Osma, J., Gallardo, M.: Virtual reality treatment of flying phobia. IEEE Transactions on Information Technology in Biomedicine 6(3), 206–212 (2002)Botella, C., Baños, R.M., Perpiña, C., et al.: Virtual reality treatment of claustrophobia: a case report. Behaviour Research & Therapy 36, 239–246 (1998)Hu, B., Dasmahapatra, S., Dupplaw, D., Lewis, P., Shadbolt, N.: Reflections on a medical ontology. International Journal of Human- Computer Studies 65(2007), 569–582 (2007)Rubin, D.L., Shah, N.H., Noy, N.F.: Biomedical ontologies: a functional perspective. Briefings in bioinformatics 9(1), 75–90 (2007)Stevens, R., Egaña Aranguren, M., Wolstencroft, K., Sattler, U., Drummond, N., Horridge, M., Rector, A.: Using OWL to model biological knowledge. International Journal of Human-Computer Studies 65(2007), 583–594 (2007)Park, S., Lee, J.K.: Rule identification using ontology while acquiring rules from Web pages. International Journal of Human-Computer Studies 65(2007), 644–658 (2007)Clark, K.L., McCabe, F.G.: Ontology schema for an agent belief store. International Journal of Human-Computer Studies 65(2007), 625–643 (2007)Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)Franco, C., Bengtsson, B., Johannsson, G.: The GH/IGF-1 Axis in Obesity: Physiological and Pathological aspects. Metabolic syndrome and Related Disorders 4, 51–56 (2006