Hand Gesture Interaction in Medicine

Nowadays, fields that employ gestures in the execution of certain procedures or actions include the medical field (surgical procedures, recovery, training) and engineering (IT, mechanics, robotics – controlling a robotic arm). Research has been conducted in the medical field (surgeons) to observe their main actions during a procedure. It is vital in this domain to implement gestures in the execution of specific procedures to ease the workload of surgeons. Certain actions that can be replaced by gestures lend themselves to be addressed. An example of interaction between a surgeon and a computer is the selection of an area in an image. The most commonly used device for capturing/processing gestures is the Leap Motion sensor. With its help, dynamic gestures can be created and then used in controlling interfaces or rehabilitating hand mobility. Among the most commonly used gestures in hand mobility rehabilitation are pronation and supination gestures, hand/finger flexion and extension gestures, and hand rotation gestures. Accurately and precisely capturing gestures created for this device is a challenge. Gesture processing can be done either through mathematical formulas, such as distance calculations between fingers and the palm center, hand rotation angles, finger surfaces, and directions. Another method involves the use of neural networks in classifying created gestures. Among the most commonly used classifiers for dynamic gestures are K-neighbors Classifier, Linear Discriminant Analysis, and Decision Tree Classifier. This paper will emphasize the importance of using gestures in the medical field and capturing them with high precision for the Leap Motion device

Extracting and Structuring Drug Information to Improve e-Prescription and Streamline Medical Treatment

Currently, physicians are using the patient electronic health record (EHR) to support their practice. The Romanian healthcare system switched to the electronic prescription starting with 2012. Physicians use the electronic medical record and health card to access patient data whenever available. To improve the medical act, we propose a tool supporting the prescription process, structuring and extracting important information from drug characteristics leaflets (prospectus). The application processes data extracted from around 3.000 medical prospectuses using several Romanian language Web sources. The drug leaflet data is structured on sections: therapeutic action, contraindications, mode of administration, adverse reactions, etc. A stemming algorithm has been applied to each section, extracting the root of the word for an easy search. The result is a text in an *.xml file. After structuring step, the application searches in the structured file the necessary information to prescribe the patient’s medication as closely as possible related to patient state. The application suggests all the drugs matching the patient's disease and are not contraindicated, or enter in conflict with other diseases, treatments or allergies of the patient, and the physician may select the best solution for the given situation

Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription

Prescribing medicines for certain illnesses as correctly as possible is a challenge for all doctors and healthcare providers worldwide, and a big problem for the inexperienced ones. In this age of technology, we are confronted with a great deal of medical information from different sources. For physicians to have access to this ocean of information, structuring and compaction is needed. Many papers in the scientific literature propose the structuring and use of medical information from clinical texts or other sources. We want to develop a medical information system that extracts specific drug information from Romanian pill leaflets. We intend to create a structured database and raise the interoperability degree for the system to communicate with other medical applications. First, we collect as much information as possible about Romanian drugs from different free online sources, from the leaflets of medicines in Romanian from ANMDMR - Nomenclature of medicines for human use and from scientific publications. We clean and structure the collected data by using machine learning techniques, especially natural language processing techniques. Next, we create ontologies and a complex database with the drug information’s and relationships between the information extracted about drugs (indications, contraindications, dosage according to age, side effects, etc.), and finally, we develop an application respecting the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles that have as inputs the profile of a patient, and as outputs the drugs indicated for certain diseases, an explainable module for the drugs selected for physicians and an adverse drug reaction adding module. From the clinical perspective, this application will help improve the quality of prescriptions and provide a better knowledge database that can help physicians avoid prescription errors

Digital Technology Supporting Children's Speech Therapy

Considering that all children are attracted to technology and spend a lot of time using digital technology, it would be advisable to use IT support for education and/or therapy. The advantage is that the speech therapist may start with face-to-face therapy sessions and ensure continuity remotely from home in a familiar and comfortable environment. Language gives the child autonomy and the possibility to socialize better. Acquiring from the preschool age the ability to communicate with persons around her/him, to express thoughts, ideas, and impressions, the child forms a basis for school activity and for later social life. In the instructional-educational process, language represents a fundamental mean of communication, but also an important mean of facilitating knowledge. Through knowledge, the children's horizons are broadened with new representations. This work presents the professional evaluation of 10 speech therapists and the perception from 60 parents with children participating in speech therapy using an application to improve the language behavior of children with speech disorder. The results of the interviews show that speech therapists are open to use digital applications as a tool in speech therapy. Using this type of tool in speech therapy engages the children more in the activity. The interview results show that 88.3% of parents agree to use digital apps at home, between face to face speech therapy sessions coordinated by speech therapist, and 75% of parents agree to use them several days a week. 68.3% of parents believe that digital applications would increase children’s motivation and commitment to speech therapy. Almost forty-seven parents take into consideration interactive apps, instructional videos, educational games and digital books as useful digital resources: 21.7% prefer educational games, 16.7% interactive apps, 8.3% instructional videos and 6.7% digital books. Using these types of applications may provide multiple benefits for children and speech therapists, having a high degree of customization to children's specific needs

European Federation of Medical Informatics Participation in European Projects – HosmartAI Project as an Experience

The European Federation for Medical Informatics Association (EFMI) is the leading organisation in medical informatics in Europe and represents 29 countries, RSMI being an active and valuable member. EFMI is organized as a nonprofit organisation concerned with the theory and practice of Information Science and Technology within Health and Health Science in a European context. The objectives when founded in 1976 were: to advance international cooperation and dissemination of information in Medical Informatics on a European basis; to promote high standards in the application of medical informatics; to promote research and development in medical informatics; to encourage high standards in education in medical informatics; to function as the autonomous European Regional Council of IMIA. Since 2018 EFMI participates actively in European financed projects contributing with its members’ expertise in dissemination, education, data processing, user experience, and several other domains. HosmartAI (2020-2024) is a H2020 project with 24 partners, 12 EU countries, 10 mil Euros funding. In the HosmartAI project – AI for the Smart Hospital of the future - EFMI is leading in WP6 the T6.3 task - Standardization and Legislation, T6.4 task -  Certification, Staff training & education and alignment with existing practice and had a consistent contribution in WP2 with EFMI MIMO tool. The EFMI team will present the solutions developed during the project and invite audience to give feedback

A Multi-Lingual Dictionary for Health Informatics as an International Cooperation Pillar.

International audienceEven if, English is generally used for international communication, it is essential to keep in mind that research is running at the local level by local teams generally communicating in their local/national language. Bearing these in mind, the "European Federation for Medical Informatics Working Group on Health Informatics for Inter-regional Cooperation" has as one of its objectives, to develop a multilingual dictionary focusing on Health Informatics as a collaboration tool allowing improving international and more particularly European cooperation. This dictionary is implemented as a part of HeTOP (Health Terminology/Ontology Portal) which is currently integrating more than 70 terminologies and ontologies in 32 languages. The EFMI Dictionary main aims are helping medical librarians, translators, academic and industrial researchers understanding better one another and supporting students self-learning

BRAIN Journal - Generative Learning Objects Instantiated with Random Numbers Based Expressions

<div><i>Abstract</i></div><div><br></div><div>The development of interactive e-learning content requires special skills like programming techniques, web integration, graphic design etc. Generally, online educators do not possess such skills and their e-learning products tend to be static like presentation slides and textbooks. In this paper we propose a new interactive model of generative learning objects as a compromise between</div><div>static, dull materials and dynamic, complex software e-learning materials developed by specialized teams. We find that random numbers based automatic initialization learning objects increases content diversity, interactivity thus enabling learners’ engagement. The resulted learning object model is at a limited level of complexity related to special e-learning software, intuitive and capable of increasing learners’ interactivity, engagement and motivation through dynamic content. The approach was applied successfully on several computer programing disciplines.</div><div><br></div><div><b>Find more at:</b></div><div><b>https://www.edusoft.ro/brain/index.php/brain/article/view/510<br></b></div><div><br></div

A Practical Experience on the Amazon Alexa Integration in Smart Offices

Smart offices are dynamically evolving spaces meant to enhance employees’ efficiency, but also to create a healthy and proactive working environment. In a competitive business world, the challenge of providing a balance between the efficiency and wellbeing of employees may be supported with new technologies. This paper presents the work undertaken to build the architecture needed to integrate voice assistants into smart offices in order to support employees in their daily activities, like ambient control, attendance system and reporting, but also interacting with project management services used for planning, issue tracking, and reporting. Our research tries to understand what are the most accepted tasks to be performed with the help of voice assistants in a smart office environment, by analyzing the system based on task completion and sentiment analysis. For the experimental setup, different test cases were developed in order to interact with the office environment formed by specific devices, as well as with the project management tool tasks. The obtained results demonstrated that the interaction with the voice assistant is reasonable, especially for easy and moderate utterances

A Practical Experience on the Amazon Alexa Integration in Smart Offices

Smart offices are dynamically evolving spaces meant to enhance employees&rsquo; efficiency, but also to create a healthy and proactive working environment. In a competitive business world, the challenge of providing a balance between the efficiency and wellbeing of employees may be supported with new technologies. This paper presents the work undertaken to build the architecture needed to integrate voice assistants into smart offices in order to support employees in their daily activities, like ambient control, attendance system and reporting, but also interacting with project management services used for planning, issue tracking, and reporting. Our research tries to understand what are the most accepted tasks to be performed with the help of voice assistants in a smart office environment, by analyzing the system based on task completion and sentiment analysis. For the experimental setup, different test cases were developed in order to interact with the office environment formed by specific devices, as well as with the project management tool tasks. The obtained results demonstrated that the interaction with the voice assistant is reasonable, especially for easy and moderate utterances