Studies in Health Technology and Informatics最新文献

NGS is increasingly used in precision medicine, but an automated sequencing pipeline that can detect different types of variants (single nucleotide - SNV, copy number - CNV, structural - SV) and does not rely on normal samples as germline comparison is needed. To address this, we developed Onkopipe, a Snakemake-based pipeline that integrates quality control, read alignments, BAM pre-processing, and variant calling tools to detect SNV, CNV, and SV in a unified VCF format without matched normal samples. Onkopipe is containerized and provides features such as reproducibility, parallelization, and easy customization, enabling the analysis of genomic data in precision medicine. Our validation and evaluation demonstrate high accuracy and concordance, making Onkopipe a valuable open-source resource for molecular tumor boards. Onkopipe is being shared as an open source project and is available at https://gitlab.gwdg.de/MedBioinf/mtb/onkopipe.

Introduction: Conducting research on human-computer interaction and information retrieval requires unobtrusive observations within existing network architectures.

State of the art: Most of the available tools are not suitable to be applied within restricted clinical systems. The specific requirements hinder analysis of the human factors in health sciences.

Concept: We identified extensions for popular web browsers as a suitable way to conduct studies in highly regulated environments.

Implementation: Considering the specialized requirements and an adequate level of transparency for the recorded clinician, we developed an open-source Web Extension compatible with major web browsers.

Lessons learned: We identified the challenges associated with the specific tool and are preparing its use to understand clinical reasoning in personalized oncology.

Introduction: Physical activity and health are closely linked. Therefore, monitoring movement behavior is of great interest e.g., to monitor a patient's physical state. Nowadays it is easy to record movement with a smartphone. The aim of this work was to develop a concept to detect trends based on personalized movement behavior recorded with a smartphone.

Methods: A first prototype with a control chart was designed. Since this approach did not prove suitable for analyzing activity data for trends in practice, a second prototype was subsequently developed with a statistical trend test (Mann-Kendall test (MK test)). It was extended by the Yue-Wang correction approach to be able to deal effectively with serial correlation. Furthermore, the traditional trend modeling using Theil-Sen slope was extended by three additional models to be able to represent non-linear trend shapes.

Results: Movement behavior can be highly variable, which leads to wide control limits when using control charts. As the lower control limit was always in the negative range the use of a control chart was impossible for this use case. The evaluation results of the second prototype confirm the choice of a non-parametric test, as well as the decision for the Yue-Wang correction factor. Furthermore, it could be determined that the MK test is robust against outliers. The number of detected trends increases with increasing significance level. The MK test is also suitable for detecting step-like trends.

Conclusion: Live trend detection is not straightforward with the MK test but can be simulated by overlapping time periods. In the future, trend modeling should be extended even further, as it plays a major role in the concept. The sensitivity of the test can be increased by means of various parameters.

Introduction: With increasing availability of reusable biomedical data - from cohort studies to clinical routine data, data re-users face the problem to manage transferred data according to the heterogeneous data use agreements. While structured metadata is addressed in many contexts including informed consent, contracts are to date still unstructured text documents. In particular within collaborative and active working groups the actual usage agreement's regulations are highly relevant for the daily practice - can I share the data with colleagues from the same university or the same research network, can they be stored on a PHD student's laptop, can I store the data for further approved data usage requests?

Methods: In this article, we inspect and review seven different data usage agreements. We focus on digital data that is copied and transferred to the requester's environment.

Results: We identified 24 metadata items in the four main categories data usage, storage, and sharing, as well as publication of results.

Discussion: While the topics are largely overlap in the data use agreements, the actual regulations of the topics are diverse. Although we do not explicitly investigate trusted research environments, where data is offered within an analytics platform, we consider them a as subgroup, where most of the practical questions from the data scientist's perspective also arise.

Conclusion: With a limited set of structured metadata items, data scientists could have information about the data use agreement at hand along with the transferred data in an easily accessible way.

Since there were no research data on the use of neuro service dogs (NSD) in 2018, a comparative case study research design was done. The cases comprised of a caregiver with a person with mild to moderate dementia, and either an NSD (n=5), a companion dog (n=28), or no dog (n=23). Monitor activity and online questionnaires were administrated. Interesting qualitative data on the roles of a NSD, advantages and inconvenients were fully described and published. Quantitative data could not confirm that NSD is benefit-cost, neither that it increases quality of sleep or level of exercise, compared to companion dogs.

Falls are a serious problem in the hospital setting and home environments. However, this problem does not only affect the elderly, but also people who have had surgery, have disabling problems, have associated diagnoses (such as poor eyesight, confusion, etc.) or are dizzy or have walking aids. The aim of research was to find, compare and implement fall detectors especially for the hospital environment. This paper summarizes possible fall detectors. Various technological solutions were selected for testing, including wearable technologies as well as contactless technologies based on PIR detectors and mmWave technologies. The selected fall detectors were tested in living laboratory of HEALTHLab.vsb.cz and then in Hospital AGEL Třinec - Podlesí. The best result of the testing was the use of two Vayyar Home Care devices in one room, thus achieving a detection accuracy of 92.50 % and a sensitivity of 92.50 %.

The Nordic healthcare system is well-established, taxation-based, and locally administered, featuring person-centered care as a social welfare pillar. Public provision of assistive technology and welfare technology within healthcare systems means every citizen has equal access to services. But how well are policies and procedures keeping pace with demographic changes and technology developments?. This study critically analyses qualitative data from 24 stakeholders involved in municipal-level procurement and allocation of assistive and welfare technology in Sweden with a specific focus on emerging digital technology. An extant analysis framework was used: the World Health Organization-GATE 5P framework for strengthening access to AT. Recommendations are made for agile procurement and an outcome-based decision frame. The voice of the AT user may be a valuable addition to inform policy.

The phenomenal increase in technological capabilities that allow the design and training of systems to cope with the complexities of natural language and visual representation in order to develop other formats is remarkable. It has made it possible to make use of image to image and text to image technologies to support those with disabilities in ways not previously explored. It has opened the world of adaptations from one picture to another in a design style of a user's choosing. Automated text simplification alongside graphical symbol representations to enhance understanding of complex content is already being used to support those with cognitive impairments and learning difficulties. Symbol sets have become embedded within applications as dictionaries and look up systems, but the need for flexibility and personalization remains a challenge. Most pictographic symbols are created over time within the bounds of a certain style and schema for particular groups such as those who use augmentative and alternative forms of communication (AAC). By using generative artificial intelligence, it is proposed that symbols could be produced based on the style of those already used by an individual or adapted to suit different requirements within local contexts, cultures and communities. This paper explores these ideas at the start of a small six-month pilot study to adapt a number of open licensed symbols based on the symbol set's original style. Once a collection has been automatically developed from image to image and text descriptions, potential stakeholders will evaluate the outcomes using an online voting system. Successful symbols will be made available and could potentially be added to the original symbol set offering a flexible personalized approach to AAC symbol generation hitherto not experienced by users.

Augmented reality is increasingly becoming significant in people's everyday life in different sectors. Particularly to users with disabilities, augmented reality can be an instructional tool and assistive technology, making it worth a vital tool for users with disabilities. For such an important tool, it is essential to understand how these applications are evaluated in order to improve their throughput and extend their accessibility. In that regard, a systematic literature review for peer-reviewed articles published between 2012 and 2022 was conducted to discover which methods, metrics, and tools/techniques researchers use during the accessibility evaluation of augmented reality applications. The PRISMA methodology allowed us to identify, screen, and include 60 articles from three databases. The finding shows that most researchers use task scenarios as the method, qualitative feedback as the metric, and questionnaire as a tool to collect data for accessibility evaluation. The conclusion and future studies are also discussed.

The successful adoption of assistive technologies for older adults requires considering and evaluating many different factors and dimensions such as effectiveness, usability, cost and equity of access, to name some of the most relevant. In line with this, the energy requirements to power such assistive technologies remains a hidden factor that might to some extent influence the success in their adoption and the user experience in a wider sense. Very often energy availability is taken for granted and its associated costs and operational requirements are mostly neglected. In this paper, the energy-related requirements of assistive technologies are analysed from a general perspective. This analysis is subsequently particularised for a use case within the SHAPES project, in the context of active and healthy ageing. This use case includes a wide variety of assistive technologies, namely: wearable devices, home sensors and a smart mirror, which provides connectivity and a set of software services. The energy requirements of all these technologies are evaluated and analysed to investigate their impact and relevance on the overall cost and user experience, following the proposed protocol.