Due to a lack of transparency in both algorithm and validation methodology, it is diffcult for researchers and clinicians to select the appropriate tracker for their application. The aim of this work is to transparently present an adjustable physical activity classification algorithm that discriminates between dynamic, standing, and sedentary behavior. By means of easily adjustable parameters, the algorithm performance can be optimized for applications using different target populations and locations for tracker wear. Concerning an elderly target population with a tracker worn on the upper leg, the algorithm is optimized and validated under simulated free-living conditions. The fixed activity protocol (FAP) is performed by 20 participants; the simulated free-living protocol (SFP) involves another 20. Data segmentation window size and amount of physical activity threshold are optimized. The sensor orientation threshold does not vary. The validation of the algorithm is performed on 10 participants who perform the FAP and on 10 participants who perform the SFP. Percentage error (PE) and absolute percentage error (APE) are used to assess the algorithm performance. Standing and sedentary behavior are classified within acceptable limits (+/- 10% error) both under fixed and simulated free-living conditions. Dynamic behavior is within acceptable limits under fixed conditions but has some limitations under simulated free-living conditions. We propose that this approach should be adopted by developers of activity trackers to facilitate the activity tracker selection process for researchers and clinicians. Furthermore, we are convinced that the adjustable algorithm potentially could contribute to the fast realization of new applications.
This introduction to the special issue on events as platforms, networks, and communities reviews recent research on these subjects. It outlines the previous work of the ATLAS Events Group in developing a “network approach to events,” as well as conceptualizing the differences between event networks and platforms.
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The Junior Adverse Drug Event Manager (J-ADEM) team is a multifaceted intervention focusing on real-life education for medical students that has been shown to assist healthcare professionals in managing and reporting suspected adverse drug reactions (ADRs) to the Netherlands Pharmacovigilance Centre Lareb. The aim of this study was to quantify and describe the ADRs reported by the J-ADEM team and to determine the clinical potential of this approach. The J-ADEM team consisted of medical students tasked with managing and reporting ADRs in hospitalized patients. All ADRs screened and reported by J-ADEM team were recorded anonymously, and categorized and analysed descriptively. From August 2018 through January 2020, 209 patients on two wards in an academic hospital were screened for ADR events. The J-ADEM team reported 101 ADRs. Although most ADRs (67%) were first identified by healthcare professionals and then reported by the J-ADEM team, the team also reported an additional 33 not previously identified serious ADRs. In 10% of all reported ADRs, the J-ADEM team helped optimize ADR treatment. The ADR reports were largely well-documented (78%), and ADRs were classified as type A (66%), had a moderate or severe severity (85%) and were predominantly avoidable reactions (69%). This study shows that medical students are able to screen patients for ADRs, can identify previously undetected ADRs and can help optimize ADR management. They significantly increased (by 300%) the number of ADR reports submitted, showing that the J-ADEM team can make a valuable clinical contribution to hospital care.
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Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology which uses strong electric fields to manipulate liquid atomization. Among many other areas, electrospray is used as an important tool for biomedical application (droplet encapsulation), water technology (thermal desalination and metal recovery) and material sciences (nanofibers and nano spheres fabrication, metal recovery, selective membranes and batteries). A complete review about the particularities of this tool and its application was recently published (2018), as an especial edition of the Journal of Aerosol Sciences. One of the main known bottlenecks of this technique, it is the fact that the necessary strong electric fields create a risk for electric discharges. Such discharges destabilize the process but can also be an explosion risk depending on the application. The goal of this project is to develop a reliable tool to prevent discharges in electrospray applications.
