Survey of drug use and its association with herd-level and farm-level characteristics on German dairy farms

The use of veterinary drugs is of similar importance to that of human drugs in addressing health challenges. In this context, pharmaceuticals and their metabolites inevitably enter soil and water in unknown quantities. Therefore, this study collects and analyzes drug data from 2020 for 50 dairy farms located in Germany. The most frequently used substance group is antibiotics (40.13%), followed by antiphlogistics (18.86%), antiparasitics (13.09%), and hormones (9.29%). Treatment frequencies record the number of days per year on which an average animal on a farm was treated with a substance. The calculated values range from 0.94 to 21.69 d/yr and are distributed heterogeneously across farms. In this study, on average, a cow was treated on 6 d in 2020: 2.34 d with antibiotics, 1.07 d with antiphlogistics, 0.76 d with antiparasitics, and 0.41 d with hormones. In addition to individual farm management practices, other factors are related to treatment frequency. Farms with a veterinary care contract used more hormonal substances than farms without a care contract. In addition, higher milk yield coincides with more frequent treatments with antiphlogistic or hormonal substances. Other related factors include grazing, longevity, farm size, and use of a claw bath. Our study represents an important first step in describing the amounts and determinants of veterinary drugs used in livestock farming. Such insights on magnitudes and farm parameters are essential to estimate potential environmental effects and derive strategies to reduce veterinary drug use.

Attempting to counteract vigilance decrement in older adults with brain stimulation

Introduction

Against the background of demographic change and the need for enhancement techniques for an aging society, we set out to repeat a study that utilized 40-Hz transcranial alternating current stimulation (tACS) to counteract the slowdown of reaction times in a vigilance experiment but with participants aged 65 years and older. On an oscillatory level, vigilance decrement is linked to rising occipital alpha power, which has been shown to be downregulated using gamma-tACS.

Method

We applied tACS on the visual cortex and compared reaction times, error rates, and alpha power of a group stimulated with 40 Hz to a sham and a 5-Hz-stimulated control group. All groups executed two 30-min-long blocks of a visual task and were stimulated according to group in the second block. We hypothesized that the expected increase in reaction times and alpha power would be reduced in the 40-Hz group compared to the control groups in the second block (INTERVENTION).

Results

Statistical analysis with linear mixed models showed that reaction times increased significantly over time in the first block (BASELINE) with approximately 3 ms/min for the SHAM and 2 ms/min for the 5-Hz and 40-Hz groups, with no difference between the groups. The increase was less pronounced in the INTERVENTION block (1 ms/min for SHAM and 5-Hz groups, 3 ms/min for the 40-Hz group). Differences among groups in the INTERVENTION block were not significant if the 5-Hz or the 40-Hz group was used as the base group for the linear mixed model. Statistical analysis with a generalized linear mixed model showed that alpha power was significantly higher after the experiment (1.37 μV2) compared to before (1 μV2). No influence of stimulation (40 Hz, 5 Hz, or sham) could be detected.

Discussion

Although the literature has shown that tACS offers potential for older adults, our results indicate that findings from general studies cannot simply be transferred to an old-aged group. We suggest adjusting stimulation parameters to the neurophysiological features expected in this group. Next to heterogeneity and cognitive fitness, the influence of motivation and medication should be considered.

Developing Advanced AI Ecosystems to Enhance Diagnosis and Care for Patients with Depression

Major Depressive Disorder (MDD) has a significant impact on the daily lives of those affected. This concept paper presents a project that aims at addressing MDD challenges through innovative therapy systems. The project consists of two use cases: a multimodal neurofeedback (NFB) therapy and an AI-based virtual therapy assistant (VTA). The multimodal NFB integrates EEG and fNIRS to comprehensively assess brain function. The goal is to develop an open-source NFB toolbox for EEG-fNIRS integration, augmented by the VTA for optimized efficacy. The VTA will be able to collect behavioral data, provide personalized feedback and support MDD patients in their daily lives. This project aims to improve depression treatment by bringing together digital therapy, AI and mobile apps to potentially improve outcomes and accessibility for people living with depression.

[Motivational Reasons and Perceptions about Future Participation of Older People in the Research and Development Process of Health Technologies: a Mixed Methods Study]

BACKGROUND

Although digital approaches for disease prevention in older people have a high potential and are being used more often, there are still inequalities in access and use. One reason could be that in technology development future users are insufficiently taken into consideration, or involved very late in the process using inappropriate methods. The aim of this work was to analyze the motivation of older people participating, and their perceptions of future participation in the research and development process of health technologies aimed at health care for older people.

METHODOLOGY

Quantitative and qualitative data from one needs assessment and two evaluation studies were analyzed. The quantitative data were analyzed descriptively and the qualitative data were analyzed content-analytically with inductive-deductive category formation.

RESULTS

The median age of the 103 participants (50 female) was 75 years (64-90), most of whom were interested in using technology and had prior experience of study participation. Nine categories for participation motivation were derived. A common motivation for participation was to promote and support their own health. Respondents were able to envision participation both at the beginning of the research process and at its end. In terms of technique development, different ideas were expressed, but there was a general interest in technological development. Methods that would enable exchange with others were favored most.

CONCLUSIONS

Differences in motivation to participate and ideas about participation were identified. The results provide important information from the perspective of older people and complement the existing state of research.

Influence of Long-Lasting Static Stretching Intervention on Functional and Morphological Parameters in the Plantar Flexors: A Randomized Controlled Trial

ABSTRACT

Warneke, K, Keiner, M, Wohlann, T, Lohmann, LH, Schmitt, T, Hillebrecht, M, Brinkmann, A, Hein, A, Wirth, K, and Schiemann, S. Influence of long-lasting static stretching intervention on functional and morphological parameters in the plantar flexors: a randomised controlled trial. J Strength Cond Res 37(10): 1993-2001, 2023-Animal studies show that long-lasting stretching training can lead to significant hypertrophy and increases in maximal strength. Accordingly, previous human studies found significant improvements in maximal voluntary contraction (MVC), flexibility, and muscle thickness (MTh) using constant angle long-lasting stretching. It was hypothesized that long-lasting stretching with high intensity will lead to sufficient mechanical tension to induce muscle hypertrophy and maximal strength gains. This study examined muscle cross-sectional area (MCSA) using magnetic resonance imaging (MRI). Therefore, 45 well-trained subjects (f: 17, m: 28, age: 27.7 ± 3.0 years, height: 180.8 ± 4.9 cm, mass: 80.4 ± 7.2 kg) were assigned to an intervention group (IG) that stretched the plantar flexors 6 × 10 minutes per day for 6 weeks or a control group (CG). Data analysis was performed using 2-way ANOVA. There was a significant Time × Group interaction in MVC ( p < 0.001-0.019, ƞ 2 = 0.158-0.223), flexibility ( p < 0.001, ƞ 2 = 0.338-0.446), MTh ( p = 0.002-0.013, ƞ 2 = 0.125-0.172), and MCSA ( p = 0.003-0.014, ƞ 2 = 0.143-0.197). Post hoc analysis showed significant increases in MVC ( d = 0.64-0.76), flexibility ( d = 0.85-1.12), MTh ( d = 0.53-0.6), and MCSA ( d = 0.16-0.3) in IG compared with CG, thus confirming previous results in well-trained subjects. Furthermore, this study improved the quality for the morphological examination by investigating both heads of the gastrocnemius with MRI and sonography. Because stretching can be used passively, an application in rehabilitation settings seems plausible, especially if no commonly used alternatives such as strength training are applicable.

Usability and feasibility of a tablet-based e-coach for older adults in rehabilitation units to improve nutrition and physical activity: a prospective pilot study

BACKGROUND

For older adults (≥ 70 years), it is often challenging to maintain new nutrition and physical activity behaviours learned in rehabilitation. To minimize the risk of negative health consequences when returning home, an e-coach can be helpful. Aligning the program with an established concept such as the Transtheoretical Model of Behaviour Change (TTM) and guidance from healthcare professionals can optimize behaviour change.

OBJECTIVE

This prospective single-arm pilot study aimed to assess the usability and feasibility of a nutrition and mobility e-coach for older adults during and after rehabilitation for a period of 9 weeks. In addition, we examined the change in the TTM phase as an indicator of the participant's readiness to change or the changes made.

METHODS

Older adults (≥ 70 years) with nutrition deficits and/ or mobility limitations were recruited in a rehabilitation centre. Participants' phases of behaviour change in the TTM were identified by comparing current nutrition and physical activity habits via self-report with age-specific nutrition and physical activity recommendations. They received a tablet with the e-coach containing educational and interactive elements on the topics of nutrition and physical activity in older age. Participants used the e-coach and received support from healthcare professionals. The TTM phases were assessed at five times; the e-coach content was adjusted accordingly. Usability was assessed using the System Usability Scale (SUS, Score range: 0-100). Timestamps were used to evaluate how frequently participants used the e-coach: high (≥ 67% of the days), medium (66 - 33% of the days), and low (< 33% of the days).

RESULTS

Approximately 140 patients were approached and n = 30 recruited. Complete data sets of n = 21 persons were analysed (38% female, mean age 79.0 ± 6.0 years). The SUS was 78.6 points, 11 participants (42%) were classified as high users, 6 (39%) as medium users and 4 (19%) as low users. After nine weeks, 15 participants (71%) achieved the physical activity recommendations (baseline: 33%, n = 7). Nutrition recommendations were achieved by 14 participants (66%) after nine weeks (baseline: 24%, n = 5).

CONCLUSION

The e-coach seems to be usable and feasible for older adults. We identified some optimization potentials for our application that can be transferred to the development of comparable e-health interventions for vulnerable older adults.

A system for monitoring the functional status of older adults in daily life

Functional decline in older adults can lead to an increased need of assistance or even moving to a nursing home. Utilising home automation, power and wearable sensors, our system continuously keeps track of the functional status of older adults through monitoring their daily life and allows health care professionals to create individualised rehabilitation programmes based on the changes in the older adult's functional capacity and performance in daily life. The system uses the taxonomy of the International Classification of Functioning, Disability and Health (ICF) by the World Health Organization (WHO). It links sensor data to five ICF items from three ICF categories and measures their change over time. We collected data from 20 (pre-)frail older adults (aged [Formula: see text] 75 years) during a 10-month observational randomised pilot intervention study. The system successfully passed the first pre-clinical validation step on the real-world data of the OTAGO study. Furthermore, an initial test with a medical professional showed that the system is intuitive and can be used to design personalised rehabilitation measures. Since this research is in an early stage further clinical studies are needed to fully validate the system.

Comparison of machine learning approaches for near-fall-detection with motion sensors

Introduction

Falls are one of the most common causes of emergency hospital visits in older people. Early recognition of an increased fall risk, which can be indicated by the occurrence of near-falls, is important to initiate interventions.

Methods

In a study with 87 subjects we simulated near-fall events on a perturbation treadmill and recorded them with inertial measurement units (IMU) at seven different positions. We investigated different machine learning models for the near-fall detection including support vector machines, AdaBoost, convolutional neural networks, and bidirectional long short-term memory networks. Additionally, we analyzed the influence of the sensor position on the classification results.

Results

The best results showed a DeepConvLSTM with an F1 score of 0.954 (precision 0.969, recall 0.942) at the sensor position "left wrist."

Discussion

Since these results were obtained in the laboratory, the next step is to evaluate the suitability of the classifiers in the field.

AI-assisted ethics? considerations of AI simulation for the ethical assessment and design of assistive technologies

Current ethical debates on the use of artificial intelligence (AI) in healthcare treat AI as a product of technology in three ways. First, by assessing risks and potential benefits of currently developed AI-enabled products with ethical checklists; second, by proposing ex ante lists of ethical values seen as relevant for the design and development of assistive technology, and third, by promoting AI technology to use moral reasoning as part of the automation process. The dominance of these three perspectives in the discourse is demonstrated by a brief summary of the literature. Subsequently, we propose a fourth approach to AI, namely, as a methodological tool to assist ethical reflection. We provide a concept of an AI-simulation informed by three separate elements: 1) stochastic human behavior models based on behavioral data for simulating realistic settings, 2) qualitative empirical data on value statements regarding internal policy, and 3) visualization components that aid in understanding the impact of changes in these variables. The potential of this approach is to inform an interdisciplinary field about anticipated ethical challenges or ethical trade-offs in concrete settings and, hence, to spark a re-evaluation of design and implementation plans. This may be particularly useful for applications that deal with extremely complex values and behavior or with limitations on the communication resources of affected persons (e.g., persons with dementia care or for care of persons with cognitive impairment). Simulation does not replace ethical reflection but does allow for detailed, context-sensitive analysis during the design process and prior to implementation. Finally, we discuss the inherently quantitative methods of analysis afforded by stochastic simulations as well as the potential for ethical discussions and how simulations with AI can improve traditional forms of thought experiments and future-oriented technology assessment.

Improved Motion Artifact Correction in fNIRS Data by Combining Wavelet and Correlation-Based Signal Improvement

Functional near-infrared spectroscopy (fNIRS) is an optical non-invasive neuroimaging technique that allows participants to move relatively freely. However, head movements frequently cause optode movements relative to the head, leading to motion artifacts (MA) in the measured signal. Here, we propose an improved algorithmic approach for MA correction that combines wavelet and correlation-based signal improvement (WCBSI). We compare its MA correction accuracy to multiple established correction approaches (spline interpolation, spline-Savitzky-Golay filter, principal component analysis, targeted principal component analysis, robust locally weighted regression smoothing filter, wavelet filter, and correlation-based signal improvement) on real data. Therefore, we measured brain activity in 20 participants performing a hand-tapping task and simultaneously moving their head to produce MAs at different levels of severity. In order to obtain a "ground truth" brain activation, we added a condition in which only the tapping task was performed. We compared the MA correction performance among the algorithms on four predefined metrics (R, RMSE, MAPE, and ΔAUC) and ranked the performances. The suggested WCBSI algorithm was the only one exceeding average performance (p < 0.001), and it had the highest probability to be the best ranked algorithm (78.8% probability). Together, our results indicate that among all algorithms tested, our suggested WCBSI approach performed consistently favorably across all measures.

How the Processing Mode Influences Azure Kinect Body Tracking Results

The Azure Kinect DK is an RGB-D-camera popular in research and studies with humans. For good scientific practice, it is relevant that Azure Kinect yields consistent and reproducible results. We noticed the yielded results were inconsistent. Therefore, we examined 100 body tracking runs per processing mode provided by the Azure Kinect Body Tracking SDK on two different computers using a prerecorded video. We compared those runs with respect to spatiotemporal progression (spatial distribution of joint positions per processing mode and run), derived parameters (bone length), and differences between the computers. We found a previously undocumented converging behavior of joint positions at the start of the body tracking. Euclidean distances of joint positions varied clinically relevantly with up to 87 mm between runs for CUDA and TensorRT; CPU and DirectML had no differences on the same computer. Additionally, we found noticeable differences between two computers. Therefore, we recommend choosing the processing mode carefully, reporting the processing mode, and performing all analyses on the same computer to ensure reproducible results when using Azure Kinect and its body tracking in research. Consequently, results from previous studies with Azure Kinect should be reevaluated, and until then, their findings should be interpreted with caution.

A rule-based robotic assistance system providing physical relief for nurses during repositioning tasks at the care bed

In nursing care, physical overload is an important issue that plays a main role in adding to the number of sick days or even causing staff to withdrawal from the profession. In addition to existing physical aids, robotics in particular has the potential to provide general physical relief during extremely stressful care activities provided at the bedside by performing assistance activities. To shed more light on the relief potential offered, we conducted a study involving 12 caregivers who used a lightweight robot attached to a nursing care bed to assist in the repositioning process. We relied on a robot system architecture that enables rule-based movement adjustments in real time using the Robot Operating System and Unity. The study focused on the repositioning of a patient simulator from the supine to the lateral position. The comparison of the measured ground reaction forces and muscle activity data suggests that robotic assistance during the performance of the activity reduces load peaks and generally leads to more attenuated ground reaction force curves, which results overall in a healthier way of working. With robotic assistance, the average back extensor muscle activations were 25.7% lower compared to conventional repositioning. In addition, the measured maximum occurring muscle activations were reduced by 61.2% when the robotic assistance system was deployed.

Prozessmodularisierung und -standardisierung als Grundlage für die Digitalisierung von Prozessen im Öffentlichen Gesundheitsdienst

Die Digitalisierung des Öffentlichen Gesundheitsdienstes (ÖGD) in Deutschland weist nach wie vor Defizite auf, was nicht zuletzt im Kontext der Pandemiebewältigung zu Problemen führte. Zur Bewältigung ihrer Aufgaben benötigen die etwa 400 deutschen Gesundheitsämtern, eine entsprechende Softwareausstattung, deren Bereitstellung auch durch die Heterogenität des ÖGD erschwert wird. Entsprechend stellt die Standardisierung und Modularisierung von Prozessen die Grundlage für eine nachhaltige Digitalisierung des ÖGD dar. Aufbauend auf diesen Prozessmodellen können geeignete und breit anwendbare Softwaremodule für diverse Aufgabenbereiche der Gesundheitsämter entwickelt und bereitgestellt werden. Die durchgeführte Studie leistet einen ersten wichtigen Beitrag im Kontext der Digitalisierung des ÖGD, indem sie eine Vorgehensweise zur Prozessstandardisierung und -modularisierung entwickelt und beispielhaft anwendet. Im Rahmen dieser Studie erfolgte eine Standardisierung und Modularisierung von Prozessen im Bereich der Wasserhygiene basierend auf den Prozessen eines Gesundheitsamtes in Berlin. In einer Kombination von Design Science Research und Business Process Standardization (BPS) wurden stakeholderübergreifende Ende-zu-Ende Prozesse identifiziert, deren Ist-Zustände mit BPMN (Business Process Model and Notation) visualisiert und anschließend in generalisierbare Soll-Zustände überführt. Die Ergebnisse wurden schließlich mit zwei weiteren Gesundheitsämtern validiert. Die angewandte Methodik und die entwickelten Artefakte können einerseits zur Skalierung dieses Vorgehens in weiteren Gesundheitsämtern und andererseits als eine Grundlage für die Entwicklung von passenden und breit anwendbaren Softwarekomponenten genutzt werden.

Designing and applying technology for prevention-Lessons learned in AEQUIPA and its implications for future research and practice

Almost all Western societies are facing the challenge that their population structure is changing very dynamically. Already in 2019, ten countries had a population share of at least 20 percent in the age group of 64 years and older. Today's society aims to improve population health and help older people live active and independent lives by developing, establishing, and promoting safe and effective interventions. Modern technological approaches offer tremendous opportunities but pose challenges when preventing functional decline. As part of the AEQUIPA Prevention Research Network, the use of technology to promote physical activity in older people over 65 years of age was investigated in different settings and from various interdisciplinary perspectives, including technology development and evaluation for older adults. We present our findings in three main areas: (a) design processes for developing technology interventions, (b) older adults as a user group, and (c) implications for the use of technology in interventions. We find that cross-cutting issues such as time and project management, supervision of participants, ethics, and interdisciplinary collaboration are of vital importance to the success of the work. The lessons learned are discussed based on the experiences gained in the overall AEQUIPA network while building, particularly on the experiences from the AEQUIPA sub-projects TECHNOLOGY and PROMOTE. Our experiences can help researchers of all disciplines, industries, and practices design, study and implement novel technology-based interventions for older adults to avoid pitfalls and create compelling and meaningful solutions.

Classification of body postures using smart workwear

Background

Despite advancing automation, employees in many industrial and service occupations still have to perform physically intensive work that may have negative effects on the health of the musculoskeletal system. For targeted preventive measures, precise knowledge of the work postures and movements performed is necessary.

Methods

Prototype smart work clothes equipped with 15 inertial sensors were used to record reference body postures of 20 subjects. These reference postures were used to create a software-based posture classifier according to the Ovako Working Posture Analysing System (OWAS) by means of an evolutionary training algorithm.

Results

A total of 111,275 posture shots were recorded and used for training the classifier. The results show that smart workwear, with the help of evolutionary trained software classifiers, is in principle capable of detecting harmful postures of its wearer. The detection rate of the evolutionary trained classifier (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{a}_{ccr} = 0.35$$\end{document}a¯ccr=0.35 for the postures of the back, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{a}_{ccr} = 0.64$$\end{document}a¯ccr=0.64 for the arms, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{a}_{ccr} = 0.25$$\end{document}a¯ccr=0.25 for the legs) outperforms that of a TensorFlow trained classifying neural network.

Conclusions

In principle, smart workwear – as prototypically shown in this paper – can be a helpful tool for assessing an individual’s risk for work-related musculoskeletal disorders. Numerous potential sources of error have been identified that can affect the detection accuracy of software classifiers required for this purpose.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05821-9.

Needs of Lung Cancer Patients Receiving Immunotherapy and Acceptance of Digital and Sensor-Based Scenarios for Monitoring Symptoms at Home—A Qualitative-Explorative Study

Background: The development of immunotherapy in the treatment for lung cancer has changed the outlook for both patients and health care practitioners. However, reporting and management of side effects are crucial to ensure effectiveness and safety of treatment. The aim of this study was to learn about the subjective experiences of patients with lung cancer receiving immunotherapy and to explore their potential acceptance of digital and sensor-based systems for monitoring treatment-related symptoms at home. Methods: A qualitative-explorative interview study with patients with lung cancer (n = 21) applying qualitative content analysis. Results: Participants had trouble to classify and differentiate between symptoms they experienced and it seemed challenging to assess whether symptoms are serious enough to be reported and to figure out the right time to report symptoms to health care practitioners. We identified four basic needs: (1) the need to be informed, (2) the need for a trustful relationship, (3) the need to be taken seriously, and (4) the need for needs-oriented treatment concepts. The idea of digital and sensor-based monitoring initially provoked rejection, but participants expressed more differentiated attitudes during the interviews, which could be integrated into a preliminary model to explain the acceptance of digital and sensor-based monitoring scenarios. Conclusions: Supporting lung cancer patients and their health care providers in communicating about treatment-related symptoms is important. Technology-based monitoring systems are considered to be potentially beneficial. However, in view of the many unfulfilled information needs and the unsatisfactory reporting of symptoms, it must be critically questioned what these systems can and should compensate for, and where the limits of such monitoring lie.

Sentinel fall presenting to the emergency department (SeFallED) - protocol of a complex study including long-term observation of functional trajectories after a fall, exploration of specific fall risk factors, and patients' views on falls prevention

BACKGROUND

Falls are a leading cause for emergency department (ED) visits in older adults. As a fall is associated with a high risk of functional decline and further falls and many falls do not receive medical attention, the ED is ideal to initiate secondary prevention, an opportunity generally not taken. Data on trajectories to identify patients, who would profit the most form early intervention and to examine the impact of a fall event, are lacking. To tailor interventions to the individual's needs and preferences, and to address the whole scope of fall risks, we developed this longitudinal study using an extensive assessment battery including dynamic balance and aerobic fitness, but also sensor-based data. Additionally, participative research will contribute valuable qualitative data, and machine learning will be used to identify trips, slips, and falls in sensor data during daily life.

METHODS

This is a mixed-methods study consisting of four parts: (1) an observational prospective study, (2) a randomized controlled trial (RCT) to explore whether a diagnostic to measure reactive dynamic balance influences fall risk, (3) machine learning approaches and (4) a qualitative study to explore patients' and their caregivers' views. We will target a sample size of 450 adults of 60 years and older, who presented to the ED of the Klinikum Oldenburg after a fall and are not hospitalized. The participants will be followed up over 24 months (within four weeks after the ED, after 6, 12 and 24 months). We will assess functional abilities, fall risk factors, participation, quality of life, falls incidence, and physical activity using validated instruments, including sensor-data. Additionally, two thirds of the patients will undergo intensive testing in the gait laboratory and 72 participants will partake in focus group interviews.

DISCUSSION

The results of the SeFallED study will be used to identify risk factors with high predictive value for functional outcome after a sentinel fall. This will help to (1) establish a protocol adapted to the situation in the ED to identify patients at risk and (2) to initiate an appropriate care pathway, which will be developed based on the results of this study.

TRIAL REGISTRATION

DRKS (Deutsches Register für klinische Studien, DRKS00025949 ). Prospectively registered on 4^th November, 2021.

[Family Medicine in the Digital Age: Scenarios and Recommendations]

Ziel Der Beitrag nimmt die Situation der hausärztlichen Medizin im digitalen Zeitalter in den Blick, um künftige Entwicklungsperspektiven zu erörtern und Handlungsmöglichkeiten aufzuzeigen.

Methodik Es wurde ein strukturierter Verständigungsprozess unter Einbeziehung relevanter Stakeholder-Perspektiven durchgeführt, der sich konzeptioneller Ansätze und methodischer Elemente der Szenario-Technik bediente. Diese Technik ermöglicht auf der Grundlage einer empirisch informierten Analyse gegenwärtiger Sachlagen und Entwicklungstrends die Formulierung von Zukunftsszenarien und die Ableitung praktischer Handlungsempfehlungen.

Ergebnisse In Verlängerung gegenwärtiger Tendenzen im Bereich der Ärzteschaft, der Patientinnen und Patienten, der technischen Entwicklung und des Gesundheitswesens wurden ein Best- und ein Worst-Case-Szenario zur hausärztlichen Medizin im Jahr 2050 entwickelt. Aus der Analyse und Erörterung der Szenarien ließen sich Handlungsempfehlungen für die Gegenwart ableiten.

Schlussfolgerung Ausgehend von den entwickelten Szenarien formulieren wir zwölf Empfehlungen zur künftigen Stärkung einer hausärztlich-zentrierten Medizin, die eine flächendeckende, digital unterstützte holistisch-patientenorientierte Gesundheitsversorgung ermöglicht.

Providing physical relief for nurses by collaborative robotics

Manual patient handling is one of the most significant challenges leading to musculoskeletal burden among healthcare workers. Traditional working techniques could be enhanced by innovations that can be individually adapted to the physical capacity of nurses. We evaluated the use of a robotic system providing physical relief by collaboratively assisting nurses in manual patient handling tasks. By quantifying kinetic and muscle activity data, it was possible to distinguish two kinds of movement patterns. Highly asymmetric postures and movements corresponded to distinct extremes in lower limb and spine muscle activity data. The use of collaborative robotics significantly reduced maximum force exertion in the caregiving process by up to 51%. Lateral flexion and torsion of the trunk were reduced by up to 54% and 87%, respectively, leading to a significant reduction in mean spine muscle activity of up to 55%. These findings indicate the feasibility of collaborative robot-assisted patient handling and emphasize the need for future individual intervention programs to prevent physical burden in care.

A Survey of Robotic Systems for Nursing Care

An increase of the aging population with a decrease in the available nursing staff has been seen in recent years. These two factors combined present a challenging problem for the future and has since become a political issue in many countries. Technological advances in robotics have made its use possible in new application fields like care and thus it appears to be a viable technological avenue to address the projected nursing labor shortage. The introduction of robots in nursing care creates an active triangular collaboration between the patient, nurse, and robot, which makes this area significantly different from traditional human–robot interaction (HRI) settings. In this review, we identify 133 robotic systems addressing nursing. We classify them according to two schemes: 1) a technical classification extended to include both patient and nurse and 2) a novel data-derived hierarchical classification based on use cases. We then analyze their intersection and build a multidimensional view of the state of technology. With this analytical tool, we describe an observed skew of the distribution of systems and identify gaps for future research. We also describe a link between the novel hierarchical use case classification and the typical phases of nursing care from admission to recovery.

Iterative Development and Applicability of a Tablet-Based e-Coach for Older Adults in Rehabilitation Units to Improve Nutrition and Physical Activity: Usability Study

BACKGROUND

Maintaining nutrition and exercise strategies after rehabilitation can be difficult for older people with malnutrition or limited mobility. A technical assistance system such as an e-coach could help to positively influence changes in dietary and exercise behavior and contribute to a sustainable improvement in one's nutrition and mobility status. Most apps do not provide a combination of nutrition and exercise content. In most cases, these apps were evaluated with healthy individuals aged <70 years, making transferability to vulnerable patients, with functional limitations and an assumed lower affinity for technology, in geriatric rehabilitation unlikely.

OBJECTIVE

This study aims to identify the potential for optimization and enhance usability through iterative test phases to develop a nutrition and mobility e-coach suitable for older adults (≥65 years) based on individual health behavior change stages in a rehabilitation setting.

METHODS

Iterative testing was performed with patients aged ≥65 years in a rehabilitation center. During testing, participants used an e-coach prototype with educational elements and active input options on nutrition and mobility as a 1-time application test. The participants performed navigation and comprehension tasks and subsequently provided feedback on the design aspects. Hints were provided by the study team when required, documented, and used for improvements. After testing, the participants were asked to rate the usability of the prototype using the System Usability Scale (SUS).

RESULTS

In all, 3 iterative test phases (T1-T3) were conducted with 49 participants (24/49, 49% female; mean 77.8, SD 6.2 years). Improvements were made after each test phase, such as adding explanatory notes on overview screens or using consistent chart types. The use of the user-centered design in this specific target group facilitated an increase in the average SUS score from 69.3 (SD 16.3; median 65) at T1 to 78.1 (SD 11.8; median 82.5) at T3. Fewer hints were required for navigation tasks (T1: 14.1%; T2: 26.5%; T3: 17.2%) than for comprehension questions (T1: 30.5%; T2: 21.6%; T3: 20%). However, the proportion of unsolved tasks, calculated across all participants in all tasks, was higher for navigation tasks (T1: 0%, T2: 15.2%, T3: 4.3%) than for comprehension tasks (T1: 1.9%, T2: 0%, T3: 2.5%).

CONCLUSIONS

The extensive addition of explanatory sentences and terms, instead of shorter keywords, to make it easier for users to navigate and comprehend the content was a major adjustment. Thus, good usability (SUS: 80th-84th percentile) was achieved using iterative optimizations within the user-centered design. Long-term usability and any possible effects on nutritional and physical activity behavior need to be evaluated in an additional study in which patients should be able to use the e-coach with increasing independence, thereby helping them to gain access to content that could support their long-term behavior change.

A Novel Digital Nutrition Diary for Geriatric Patients at High Risk of Frailty Syndrome

Due to the physical, psychological, or socioeconomic changes that accompany aging, many people will be affected by geriatric frailty syndrome, which can lead to multimorbidity and premature death. Nutrition counseling is often used to prevent and intervene in frailty syndrome, especially in geriatric rehabilitation. To this end, the consumption behavior of geriatric patients is recorded using paper-based, as well as retrospective memory logs in face-to-face interviews between patients and nutritionists. To simplify this procedure, a digital nutrition diary was developed that is specially adapted to the needs of geriatric patients (>=70 years), enabling them to record their consumption behavior themselves. In an initial study (Study 1), conducted in a geriatric rehabilitation division with twelve subjects (ten male, two female, mean age 79.2 ±5.9 years), feedback about the usability of the digital nutrition diary, and how to improve it, was surveyed. In addition, the usability of an activity tracker and a body composition scale was surveyed to determine whether geriatric patients are generally able to use these devices. In a second study (Study 2), also conducted in the geriatric rehabilitation division, this time with sixteen subjects (ten male, six female, mean age 79.3 ±3.9 years), the usability of the digital nutrition diary was surveyed again to evaluate its modifications based on the feedback from Study 1. In Study 1, the usability rating of the system (0−100) was 82.5 for the activity tracker, 29.71 for the body composition scale, and 51.66 initially for the digital nutrition diary, which increased to 76.41 in Study 2.

Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults

The OTAGO exercise program is effective in decreasing the risk for falls of older adults. This research investigated if there is an indication that the OTAGO exercise program has a positive effect on the capacity and as well as on the performance in mobility. We used the data of the 10-months observational OTAGO pilot study with 15 (m = 1, f = 14) (pre-)frail participants aged 84.60 y (SD: 5.57 y). Motion sensors were installed in the flats of the participants and used to monitor their activity as a surrogate variable for performance. We derived a weighted directed multigraph from the physical sensor network, subtracted the weights of one day from a baseline, and used the difference in percent to quantify the change in performance. Least squares was used to compute the overall progress of the intervention (n = 9) and the control group (n = 6). In accordance with previous studies, we found indication for a positive effect of the OTAGO program on the capacity in both groups. Moreover, we found indication that the OTAGO program reduces the decline in performance of older adults in daily living. However, it is too early to conclude causalities from our findings because the data was collected during a pilot study.

Are vertical jumps able to predict 24-month follow-up functional geriatric assessment in a healthy community-dwelling older cohort?

BACKGROUND

When older adults fall below the thresholds of functional geriatric assessment (FGA), they may already be at risk of mobility impairment. A reduction in (jumping) power could be an indication of functional decline, one of the main risk factors for falls.

OBJECTIVE

This paper explores whether six-month delta (∆) values of muscle power can predict 24-month follow-up FGA in older adults.

METHODS

This observational study of independent, healthy, high-performing community-dwelling adults aged 70 + years involved FGA (mobility, balance, and endurance tests) at baseline (t₀), after 6 months (t₁), and after 24 months (t₂); maximum jumping power (max JP) was determined at t₀ and t₁. A predictive linear model was developed in which the percentage change of Δmax JP_0,1 was transferred to all FGA (t₀) values. The results were compared with measured FGA values at t₂ via sensitivity and specificity in terms of the clinically meaningful change (CMC) or the minimal detectable change (MDC).

RESULTS

In 176 individuals (60% female, mean age 75.3 years) the mean percentage (SD) between predicted and measured FGA ranged between 0.4 (51.3) and 18.11 (51.9). Sensitivity to identify the CMC or MDC of predicted FGA tests at t₂ ranged between 17.6% (Timed up and go) and 75.0% (5-times-chair-rise) in a test-to-test comparison and increased to 97.6% considering clinically conspicuousness on global FGA.

CONCLUSION

The potential of jumping power to predict single tests of FGA was low regarding sensitivity and specificity of CMC (or MDC). 6 months Δmax JP seem to be suitable for predicting physical function, if the measured and predicted tests were not compared at the test level, but globally, in the target group in the long term.

An evolutionary approach to continuously estimate CPR quality parameters from a wrist-worn inertial sensor

Cardiopulmonary resuscitation (CPR) is one of the most critical emergency interventions for sudden cardiac arrest. In this paper, a robust sinusoidal model-fitting method based on a Evolution Strategy inspired algorithm for CPR quality parameters – naming chest compression frequency and depth – as measured by an inertial measurement unit (IMU) attached to the wrist is presented. The proposed approach will allow bystanders to improve CPR as part of a continuous closed-loop support system once integrated into a smartphone or smartwatch application. By evaluating the model’s precision with data recorded by a training mannequin as reference standard, a variance for the compression frequency of $$\pm 2.22$$ ± 2.22 compressions per minute (cpm) has been found for the IMU attached to the wrist. It was found that this previously unconsidered position and thus, the use of smartwatches is a suitable alternative to the typical placement of phones in hand for CPR training.

What do geriatric rehabilitation patients and experts consider relevant? Requirements for a digitalised e-coach for sustainable improvement of nutrition and physical activity in older adults - a qualitative focus group study

Background

During geriatric rehabilitation, attempts are made to increase the patients’ health and functional capacity. In order to maintain these improvements in the medium- and long-term, behavioural changes regarding mobility and nutrition are also targeted, but these are often not sustainable. International studies show positive effects on the sustainability of the improvement of physical activity behaviour in healthy seniors through the use of electronic devices and software applications. Comparable approaches that include nutrition topics or combine them and were additionally developed for geriatric rehabilitation patients (≥70 years) to date are not known. The aim of this study was to identify what geriatric rehabilitation patients require from an electronic coaching system (e-coach) to support them in improving their nutritional and physical activity behaviour, and what content and features physiotherapists and dieticians consider relevant.

Method

Focus group interviews (09–11/2019) were conducted in a geriatric rehabilitation centre in Germany with patients aged 70 years and older, relatives and experts (physiotherapists and nutritionists). The focus groups were recorded, transcribed verbatim and analysed using content analysis.

Results

Three focus groups with patients and relatives (n = 17, 65% female, 16 (94%) in age category 70–99 years) and one focus group with experts (2 dieticians and 1 physiotherapist) were conducted. Relevant contents and feedback elements for nutrition and physical activity in old age were identified. The patients’ comments show that an e-coach must offer obvious benefits for the older persons and promote motivation in order to be used. The willingness to change nutrition and physical activity behaviour and the previous experiences in these areas are very heterogeneous, therefore content should be adaptable to different requirements.

Conclusion

Experts and patients identified quite similar contents, barriers and facilitators for a nutrition and physical activity e-coach. The e-coach needs to be able to address different points of behaviour change, enable adaptations to the individual patient and convince the older person that using it will help them to improve their nutrition and physical activity. It is also important that the e-coach is easy to use and can be easily integrated into the patient’s everyday life after rehabilitation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02692-y.

Activity Space and Functional Outcomes in Frail Older Persons Using GPS analysis

With increasing age, walking becomes a main functional ability to participate in activities of daily living and supports independence and mobility. Frailty in older, multimorbid patients has a negative impact on physical activity and may reduce the personal activity space (AS). In this pilot study, GPS data were used to identify walking tracks to define individual AS and to compare functional performance in frail older persons. GPS data of 20 community-dwelling adults (84.5(±5.2)years, 85% women, mean frailty phenotype 1.9 (70% ≥2)points) were analyzed using a customized software to assess individual AS over a ten-months period. A geriatric home assessment including Short Physical Performance Battery (SPPB), gait speed (GS) and Timed-up-and-Go (TUG) was conducted monthly. GPS analysis revealed three different walking types presenting AS similarities: Type A walkers prefer smaller short walks nearby the home while Type B can be characterized by taking larger regular walks. Type C presents the widest AS using different transportation modes, but only a moderate number of walks. Mean group difference in functional performance of Type A walkers showed significantly reduced GS (0.45(±0.1)m/s), TUG (23.4s(±4.9)) and SPPB scores (3.8(±0.8) points; p<0.05) compared to Type C (0.82(±0.1)m/s (GS); 13.2(±1.4)s (TUG); 7.0(±1.3) points (SPPB)). Functional performance of Type B walkers (0.63(±0.2)m/s (GS); 17.1(±4.4)s (TUG); 6.5(±2.4)points (SPPB)) revealed significantly higher SPPB scores compared to Type A (p<0.05). Walks and individual AS can be mapped via GPS under everyday conditions. High heterogeneity within frail older people was observed. Persons with lower functional performance showed a reduced AS and physical activity.

Detecting Impending Malnutrition of (Pre-) Frail Older Adults in Domestic Smart Home Environments

Malnutrition is a well-known risk factor for deteriorated physical function, disability and loss in independence in older adults. An unintended loss in body weight of more than 5% in 3 months is one indicator for malnutrition. In this study we examined the relationship between meal preparation time, hand grip strength, and body weight in order to map impending nutritional problems using ambient sensors. Data were collected in the domestic environments of 20 (pre-) frail older adults aged 85.75 y (Standard Deviation: 5.19 y) over 10-months of observation. Collecting included physical function and nutritional status of the participants and meal preparation time by a combination of motion and power sensor events. Analysis was done by rank correlation of hand grip strength, body weight, and meal preparation time. Ten participants aged 85.1 years (Standard Deviation: 4.6 y) were included. The results show a significant correlation (≥0.99) of the meal preparation time with the hand grip strength. This result validated the meal preparation time as a suitable measure for analysing the correlation between meal preparation time and body weight, and a significant correlation (≥0.99) found. Hence the meal preparation time could be used as an indicator for malnutrition. However, causalities have to be conducted by further clinical studies.

OWAS inter-rater reliability

The Ovako Working posture Assessment System (OWAS) is a commonly used observational assessment method for determining the risk of work-related musculoskeletal disorders. OWAS claims to be suitable in the application for untrained persons but there is not enough evidence for this assumption. In this paper, inter-rater (inter-observer) reliability (agreement) is examined down to the level of individual postures and categories. For this purpose, the postures of 20 volunteers have been observed by 3 varying human raters in a laboratory setting and the inter-rater agreement against reference values was determined. A high agreement of over 98%(κ=0.98) was found for the postures of the arms but lower agreements were found for posture classification of the legs (66-97%,κ=0.85) and the upper body (80-96%,κ=0.85). No significant difference was found between raters with and without intense prior training in physical therapy. Consequently, the results confirm the general reliability of the OWAS method especially for raters with non-specialized background but suggests weaknesses in the reliable detection of a few particular postures.

[Feasibility and acceptance of video-based physiotherapy : New medical care provision for older people during the COVID-19 pandemic]

Hintergrund und Ziel

Einschränkungen des öffentlichen Lebens durch die COVID-19-Pandemie dienen insbesondere dazu, Risikogruppen vor einer Ansteckung zu schützen. Darunter fallen auch ältere, multimorbide Patienten, für die körperliche Inaktivität und Auslassen von Maßnahmen wie Physiotherapie jedoch negative Folgen haben können. Die vorliegende Studie untersucht die Machbarkeit und die subjektive Bewertung videobasierter Physiotherapie (VT).

Methoden

Von April bis Juni 2020 nahmen 4 Einrichtungen mit 9 Patienten (6 Frauen, 64 bis 82 Jahre) an der Studie teil, die mit Tablets ausgestattet wurden. Durch semistrukturierte Telefoninterviews wurden körperliche Aktivität, funktionelle Kompetenz und Partizipation vor und während den Einschränkungen bei 8 Patienten erfasst. Patienten und Therapeuten wurden zu ihren subjektiven Erfahrungen mit der VT befragt.

Ergebnisse

Es fanden insgesamt 92 VT-Einheiten statt. Die Umsetzung der Übungen wurde als gut bis sehr gut bewertet. Insgesamt zeigte sich eine hohe Akzeptanz der VT. Vier von 8 Patienten beschrieben eine subjektive Reduzierung ihrer körperlichen Aktivitäten aufgrund der Einschränkungen. Diese Veränderungen wurden über die verwendeten Fragebogen zur Partizipation und zur körperlichen Aktivität nicht abgebildet.

Diskussion

Bei älteren Patienten ist VT mit geringer technischer Unterstützung machbar. Sowohl in Pandemiesituationen als auch in anderen Kontexten stellt sich VT als eine realisierbare Ergänzung oder Alternative zur normalen Physiotherapie dar. Weitere Studien zur Identifikation von geeigneten Patientengruppen, Effektivität der VT und Weiterentwicklung inhaltlicher Aspekte sind dringend notwendig.

Zusatzmaterial online

Zusätzliche Informationen sind in der Online-Version dieses Artikels (10.1007/s00391-021-01899-3) enthalten.

Tunable electrochromic filter for in situ Fourier spatial frequency filtering

Spatial optical Fourier filtering is a widespread technique for in situ image or light field processing. However, conventional fixed absorbing patterns or mechanical irises only allow an inflexible, very restricted control. Thus, we present two electrochromic spatial filters with ring-shaped or directional segments, which can be individually addressed and continuously tuned in transmission resulting in up to 512 different filtering states. For realization of the electrochromic devices, we overcome technical obstacles to realize seamless, gap-free electrochromic segments. We describe this novel fabrication process and demonstrate the successful application in an optical Fourier transform set-up.

Validation of a Laser Ranged Scanner-Based Detection of Spatio-Temporal Gait Parameters Using the aTUG Chair

This article covers the suitability to measure gait-parameters via a Laser Range Scanner (LRS) that was placed below a chair during the walking phase of the Timed Up&Go Test in a cohort of 92 older adults (mean age 73.5). The results of our study demonstrated a high concordance of gait measurements using a LRS in comparison to the reference GAITRite walkway. Most of aTUG's gait parameters demonstrate a strong correlation coefficient with the GAITRite, indicating high measurement accuracy for the spatial gait parameters. Measurements of velocity had a correlation coefficient of 99%, which can be interpreted as an excellent measurement accuracy. Cadence showed a slightly lower correlation coefficient of 96%, which is still an exceptionally good result, while step length demonstrated a correlation coefficient of 98% per leg and stride length with an accuracy of 99% per leg. In addition to confirming the technical validation of the aTUG regarding its ability to measure gait parameters, we compared results from the GAITRite and the aTUG for several parameters (cadence, velocity, and step length) with results from the Berg Balance Scale (BBS) and the Activities-Specific Balance Confidence-(ABC)-Scale assessments. With confidence coefficients for BBS and velocity, cadence and step length ranging from 0.595 to 0.798 and for ABC ranging from 0.395 to 0.541, both scales demonstrated only a medium-sized correlation. Thus, we found an association of better walking ability (represented by the measured gait parameters) with better balance (BBC) and balance confidence (ABC) overall scores via linear regression. This results from the fact that the BBS incorporates both static and dynamic balance measures and thus, only partly reflects functional requirements for walking. For the ABC score, this effect was even more pronounced. As this is to our best knowledge the first evaluation of the association between gait parameters and these balance scores, we will further investigate this phenomenon and aim to integrate further measures into the aTUG to achieve an increased sensitivity for balance ability.

Kinesthetic Device vs. Keyboard/Mouse: A Comparison in Home Care Telemanipulation

Ensuring care is one of the biggest humanitarian challenges of the future since an acute shortage in nursing staff is expected. At the same time, this offers the opportunity for new technologies in nursing, as the use of robotic systems. One potential use case is outpatient care, which nowadays involves traveling long distances. Here, the use of telerobotics could provide a major relief for the nursing staff, as it could spare them many of those-partially far-journeys. Since autonomous robotic systems are not desired at least in Germany for ethical reasons, this paper evaluates the design of a telemanipulation system consisting of off-the-shelf components for outpatient care. Furthermore, we investigated the suitability of two different input devices for control, a kinesthetic device, and a keyboard plus mouse. We conducted the investigations in a laboratory study. This laboratory represents a realistic environment of an elderly home and a remote care service center. It was carried out with 25 nurses. Tasks common in outpatient care, such as handing out things (manipulation) and examining body parts (set camera view), were used in the study. After a short training period, all nurses were able to control a manipulator with the two input devices and perform the two tasks. It was shown that the Falcon leads to shorter execution times (on average 0:54.82 min, compared to 01:10.92 min with keyboard and mouse), whereby the participants were more successful with the keyboard plus mouse, in terms of task completion. There is no difference in usability and cognitive load. Moreover, we pointed out, that the access to this kind of technology is desirable, which is why we identified further usage scenarios.

Acceptance of Industrial Collaborative Robots by People With Disabilities in Sheltered Workshops

The integration of people with disabilities into the working world is an important, yet challenging field of research. While different inclusion efforts exist, people with disabilities are still under-represented in the open labor market. This paper investigates the approach of using a collaborative robot arm to support people with disabilities with their reintegration into the workplace. However, there is currently little literature about the acceptance of an industrial robot by people with disabilities and in cases where a robot leads to stress, fear, or any other form of discomfort, this approach is not feasible. For this reason, a first user study was performed in a sheltered workshop to investigate the acceptance of a robot arm by workers with disabilities. As a first step in this underdeveloped field, two main aspects were covered. Firstly, the reaction and familiarization to the robot arm within a study situation was closely examined in order to separate any effects that were not caused by the moving robot. Secondly, the reaction toward the robot arm during collaboration was investigated. In doing so, five different distances between the robot arm and the participants were considered to make collaboration in the workplace as pleasant as possible. The results revealed that it took the participants about 20 min to get used to the situation, while the robot was immediately accepted very well and did not cause fear or discomfort at any time. Surprisingly, in some cases, short distances were accepted even better than the larger distances. For these reasons, the presented approach showed to promise for future investigations.

Analyzing the Importance of Sensors for Mode of Transportation Classification

The broad availability of smartphones and Inertial Measurement Units in particular brings them into the focus of recent research. Inertial Measurement Unit data is used for a variety of tasks. One important task is the classification of the mode of transportation. In the first step, we present a deep-learning-based algorithm that combines long-short-term-memory (LSTM) layer and convolutional layer to classify eight different modes of transportation on the Sussex–Huawei Locomotion-Transportation (SHL) dataset. The inputs of our model are the accelerometer, gyroscope, linear acceleration, magnetometer, gravity and pressure values as well as the orientation information. In the second step, we analyze the contribution of each sensor modality to the classification score and to the different modes of transportation. For this analysis, we subtract the baseline confusion matrix from a confusion matrix of a network trained with a left-out sensor modality (difference confusion matrix) and we visualize the low-level features from the LSTM layers. This approach provides useful insights into the properties of the deep-learning algorithm and indicates the presence of redundant sensor modalities.

Practical Implementation of Receiver-Oriented Encryption in STROKE OWL

New forms of care for complex chronic diseases require substantial efforts in the collection, storage, and analysis of privacy sensible medical data. Additionally, providing practical support for those who coordinate the actual care management process within a diversified network of regional service providers is beneficial. In this paper, we present a follow-up with the current status, lessons learned, and preliminary results of the IT infrastructure in project STROKE OWL. The project aims at a comprehensive implementation of cross-sector care management for stroke patients. Patients are accompanied in their recovery by stroke pilots, who use a specially designed tablet app for the piloting. It is shown how the tablet app uses receiver-oriented encryption to support the piloting process while ensuring privacy.

Discovery and Characterization of Clinical Candidate LXE408 as a Kinetoplastid-Selective Proteasome Inhibitor for the Treatment of Leishmaniases

Visceral leishmaniasis is responsible for up to 30,000 deaths every year. Current treatments have shortcomings that include toxicity and variable efficacy across endemic regions. Previously, we reported the discovery of GNF6702, a selective inhibitor of the kinetoplastid proteasome, which cleared parasites in murine models of leishmaniasis, Chagas disease, and human African trypanosomiasis. Here, we describe the discovery and characterization of LXE408, a structurally related kinetoplastid-selective proteasome inhibitor currently in Phase 1 human clinical trials. Furthermore, we present high-resolution cryo-EM structures of the Leishmania tarentolae proteasome in complex with LXE408, which provides a compelling explanation for the noncompetitive mode of binding of this novel class of inhibitors of the kinetoplastid proteasome.

Quantification of Lower Limb and Spine Muscle Activity in Manual Patient Handling - A Case Study

Manual patient handling is one of the physiological risk factors in care. The scientific focus so far, has primarily been on the analysis of lumbar compression during manual caregiving in order to improve the transfer facilitation of caregivers through technical systems. Reference is made in this context to the supportive functional role of the muscles of the lower limb. To assess biomechanical data for the quantification of lower limb and spine muscle activity in manual patient handling, an experimental study was conducted. A quantitative basis for the analysis of caregiving processes and its risk factors is established by evaluating caregivers' posture, ground reaction force components, and muscle activities during ergonomic and non-ergonomic manual patient handling in a laboratory setting.