Gracebenton4544

A lower-extremity exoskeleton can facilitate the lower limbs' rehabilitation by providing additional structural support and strength. This article discusses the design and implementation of a functional prototype of lower extremity brace actuation and its wireless communication control system. The design provides supportive torque and increases the range of motion after complications reducing muscular strength. The control system prototype facilitates elevating a leg, gradually followed by standing and slow walking. The main control modalities are based on an Artificial Neural Network (ANN). The prototype's functionality was tested by time-angle graphs. The final prototype demonstrates the potential application of the ANN in the control system of exoskeletons for joint impairment therapy.In healthcare settings, questionnaires are used to collect information from a patient. A standard method for this are paper-based questionnaires, but they are often complex to understand or long and frustrating to fill. To increase motivation, we developed a chatbot-based system Ana that asks questions that are normally asked using paper forms or in face-to-face encounters. Ana has been developed for the specific use case of collecting the music biography in the context of music therapy. In this paper, we compare user motivation, relevance of answers and time needed to answer the questions depending on the data entry method (i.e. app Ana versus paper-based questionnaire). A randomised trial was performed with 26 students of music therapy. The results show that the chatbot is more motivating and answers are given faster than on paper. No differences in answer relevance could be determined between the two means. We conclude that a chatbot could become an additional data entry method for collecting personal health information.The value of data models in general and information models in specific has been evaluated by many scientific papers. UML as one modelling notation has documented its value as a foundation for precise specifications. Analyzing implementation guides for data exchange, they rarely include or are based on information models but simple data sets, if at all, as simple technical representation thereof. see more This paper wants to argue in favor of information models as a basis for creating interoperability specifications using a quite simple example and to include - or at least reference - them when providing implementation guides. The reader is invited to transfer this example to even more complex scenarios.Today's digital information systems and applications collect every day a huge amount of personal health information (PHI) from sensor and surveillance systems, and every time we use personal computers or mobile phones. Collected data is processed in clouds, platforms and ecosystems by digital algorithms and machine learning. Pervasive technology, insufficient and ineffective privacy legislation, strong ICT industry and low political will to protect data subject's privacy have together made it almost impossible for a user to know what PHI is collected, how it is used and to whom it is disclosed. Service providers' and organizations' privacy policy documents are cumbersome and they do not guarantee that PHI is not misused. Instead, service users are expected to blindly trust in privacy promises made. In spite of that, majority of individuals are concerned of their privacy, and governments' assurance that they meet the responsibility to protect citizens in real life privacy is actually dead. Because PHI is probably the most sensitive data we have, and the authors claim it cannot be a commodity or public good, they have studied novel privacy approaches to find a way out from the current unsatisfactory situation. Based on findings got, the authors have developed a promising solution for privacy-enabled use of PHI. It is a combination of the concept of information fiduciary duty, Privacy as Trust approach, and privacy by smart contract. This approach shifts the onus of privacy protection onto data collectors and service providers. A specific information fiduciary duty law is needed to harmonize privacy requirements and force the acceptance of proposed solutions. Furthermore, the authors have studied strengths and weaknesses of existing or emerging solutions.The International Patient Summary Standard (EN 17269) normalizes the dataset within the European Guideline on cross-border exchange of a patient summary. This dataset has been widely appreciated and been taken as the basis for projects in both Europe and wider afield, e.g. U.S.A, Canada and more. The dataset is a relatively mature dataset and it is currently in its third iteration (i.e., 2013, 2016, 2020). Even so, to move from a policy-driven guideline to a formal standard was not straight forward. The paper describes how the 'minimal and non-exhaustive' dataset could be the basis for a reference standard; one that was intended to facilitate both an 'implementable' and 'sustainable' solution. In particular, the requirement of 'extensibility' for the standard dataset had to be addressed.Medical data can be represented in various forms. The most common is visualization, but recent work started to also add sonic representation - sonification. In this study we start with a theoretical background, then focus on medical applications. The discussion synthesizes the authors view about the present state of the domain and tries to foresee future potential developments in medicine. In conclusion we present a set of original recommendations for developing new applications with potential use in medicine and healthcare.The paper describes the concept of the Industry 4.0 and its reflection in health care. Industry 4.0 connects intelligent production concepts with external factors, including those linked with the production and those linked more with human, as for example intelligent homes or social web systems. Communication, data and information play an important role in the whole system. After explaining basic characteristics of the Industry 4.0 concept and its main parts, we show how they can be utilized in the health care sector and what their advantages are. Key technologies and techniques include Internet of Things, big data, artificial intelligence, data integration, robotization, virtual reality, and 3D printing. Finally, we identify the main challenges and research directions. Among the most important ones are interoperability, standardization, reliability, security and privacy, ethical and legal issues.