Human Memory B Cells Harbor Diverse Cross-Neutralizing Antibodies against BK and JC Polyomaviruses.

Human polyomaviruses cause a common childhood infection worldwide and typically elicit a neutralizing antibody and cellular immune response, while establishing a dormant infection in the kidney with minimal clinical manifestations. However, viral reactivation can cause severe pathology in immunocompromised individuals. We developed a high-throughput, functional antibody screen to examine the humoral response to BK polyomavirus. This approach enabled the isolation of antibodies from all peripheral B cell subsets and revealed the anti-BK virus antibody repertoire as clonally complex with respect to immunoglobulin sequences and isotypes (both IgM and IgG), including a high frequency of monoclonal antibodies that broadly neutralize BK virus subtypes and the related JC polyomavirus. Cryo-electron microscopy of a broadly neutralizing IgG single-chain variable fragment complexed with BK virus-like particles revealed the quaternary nature of a conserved viral epitope at the junction between capsid pentamers. These features unravel a potent modality for inhibiting polyomavirus infection in kidney transplant recipients and other immunocompromised patients.

Non-clinical and clinical characterization of MAU868, a novel human-derived monoclonal neutralizing antibody targeting BK polyomavirus VP1.

Reactivation of BK polyomavirus (BKPyV) can cause significant kidney and bladder disease in immunocompromised patients. There are currently no effective, BKPyV-specific therapies. MAU868 is a novel, human IgG1 monoclonal antibody that binds the major capsid protein VP1 of BKPyV with picomolar affinity, neutralizes infection by the four major BKPyV genotypes (EC50 ranging from 0.009 to 0.093 µg/ml; EC90 ranging from 0.102 to 4.160 µg/ml), and has comparable activity against variants with highly prevalent VP1 polymorphisms. No resistance-associated variants were identified in long-term selection studies, indicating a high in vitro barrier-to-resistance. The high-resolution crystal structure of MAU868 in complex with VP1 pentamer identified three key contact residues in VP1 (Y169, R170, K172). A first-in-human study was conducted to assess the safety, tolerability, and pharmacokinetics of MAU868 following intravenous and subcutaneous administration to healthy adults in a randomized, placebo-controlled, double-blinded, single ascending dose design. MAU868 was safe and well-tolerated. All adverse events were Grade 1 and resolved. The pharmacokinetics of MAU868 was typical of a human IgG, with dose-proportional systemic exposure and an elimination half-life ranging between 23 and 30 days. These results demonstrate the potential of MAU868 as a first-in-class therapeutic agent for the treatment or prevention of BKPyV disease.

Hammerstein-Wiener Motion Artifact Correction for Functional Near-Infrared Spectroscopy: A Novel Inertial Measurement Unit-Based Technique.

Participant movement is a major source of artifacts in functional near-infrared spectroscopy (fNIRS) experiments. Mitigating the impact of motion artifacts (MAs) is crucial to estimate brain activity robustly. Here, we suggest and evaluate a novel application of the nonlinear Hammerstein-Wiener model to estimate and mitigate MAs in fNIRS signals from direct-movement recordings through IMU sensors mounted on the participant's head (head-IMU) and the fNIRS probe (probe-IMU). To this end, we analyzed the hemodynamic responses of single-channel oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) signals from 17 participants who performed a hand tapping task with different levels of concurrent head movement. Additionally, the tapping task was performed without head movements to estimate the ground-truth brain activation. We compared the performance of our novel approach with the probe-IMU and head-IMU to eight established methods (PCA, tPCA, spline, spline Savitzky-Golay, wavelet, CBSI, RLOESS, and WCBSI) on four quality metrics: SNR, △AUC, RMSE, and R. Our proposed nonlinear Hammerstein-Wiener method achieved the best SNR increase (p < 0.001) among all methods. Visual inspection revealed that our approach mitigated MA contaminations that other techniques could not remove effectively. MA correction quality was comparable with head- and probe-IMUs.

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.

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.

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.

[Motivational Reasons and Perceptions about Future Participation of Older People in the Research and Development Process of Health Technologies: a Mixed Methods Study]. / Motivationsgründe und Vorstellungen über eine zukünftige Beteiligung älterer Menschen im Forschungs- und Entwicklungsprozess von Gesundheitstechnologien ­ eine Mixed Methods-Studie.

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.

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 4th November, 2021.

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 JP0,1 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.

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 ([Formula: see text] for the postures of the back, [Formula: see text] for the arms, and [Formula: see text] 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.

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.

Measurement System for Unsupervised Standardized Assessments of Timed Up and Go Test and 5 Times Chair Rise Test in Community Settings-A Usability Study.

Comprehensive measurements are needed in older populations to detect physical changes, initiate prompt interventions, and prevent functional decline. While established instruments such as the Timed Up and Go (TUG) and 5 Times Chair Rise Test (5CRT) require trained clinicians to assess corresponding functional parameters, the unsupervised screening system (USS), developed in a two-stage participatory design process, has since been introduced to community-dwelling older adults. In a previous article, we investigated the USS's measurement of the TUG and 5CRT in comparison to conventional stop-watch methods and found a high sensitivity with significant correlations and coefficients ranging from 0.73 to 0.89. This article reports insights into the design process and evaluates the usability of the USS interface. Our analysis showed high acceptance with qualitative and quantitative methods. From participant discussions, suggestions for improvement and functions for further development could be derived and discussed. The evaluated prototype offers a high potential for early detection of functional limitations in elderly people and should be tested with other target groups in other locations.

[Family Medicine in the Digital Age: Scenarios and Recommendations]. / Hausärztliche Medizin im digitalen Zeitalter: Szenarien und Empfehlungen.

AIMS: The aim of this study was to examine the situation of family medicine in the digital age in order to discuss future trends and outline recommendations for action. METHODS: We conducted a structured deliberative process employing elements of the scenario method and involving relevant stakeholder perspectives. Based on an empirically informed analysis of current situations and trends, the scenario method allows the formation of practical recommendations. RESULTS: Extrapolating current trends in the medical profession, the patients, the technological development, and the healthcare system, we developed a best case and a worst case scenario of family medicine in the year 2050. From the analysis and discussion of the scenarios, we derived recommendations for practitioners and decision makers. CONCLUSIONS: Based on the developed scenarios, we recommend twelve measures towards a model of future healthcare that is centered on family medicine and enables a comprehensive, digitally supported holistic and patient-oriented service provision.

MAA868, a novel FXI antibody with a unique binding mode, shows durable effects on markers of anticoagulation in humans.

A large unmet medical need exists for safer antithrombotic drugs because all currently approved anticoagulant agents interfere with hemostasis, leading to an increased risk of bleeding. Genetic and pharmacologic evidence in humans and animals suggests that reducing factor XI (FXI) levels has the potential to effectively prevent and treat thrombosis with a minimal risk of bleeding. We generated a fully human antibody (MAA868) that binds the catalytic domain of both FXI (zymogen) and activated FXI. Our structural studies show that MAA868 traps FXI and activated FXI in an inactive, zymogen-like conformation, explaining its equally high binding affinity for both forms of the enzyme. This binding mode allows the enzyme to be neutralized before entering the coagulation process, revealing a particularly attractive anticoagulant profile of the antibody. MAA868 exhibited favorable anticoagulant activity in mice with a dose-dependent protection from carotid occlusion in a ferric chloride-induced thrombosis model. MAA868 also caused robust and sustained anticoagulant activity in cynomolgus monkeys as assessed by activated partial thromboplastin time without any evidence of bleeding. Based on these preclinical findings, we conducted a first-in-human study in healthy subjects and showed that single subcutaneous doses of MAA868 were safe and well tolerated. MAA868 resulted in dose- and time-dependent robust and sustained prolongation of activated partial thromboplastin time and FXI suppression for up to 4 weeks or longer, supporting further clinical investigation as a potential once-monthly subcutaneous anticoagulant therapy.

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.

HRDepthNet: Depth Image-Based Marker-Less Tracking of Body Joints.

With approaches for the detection of joint positions in color images such as HRNet and OpenPose being available, consideration of corresponding approaches for depth images is limited even though depth images have several advantages over color images like robustness to light variation or color- and texture invariance. Correspondingly, we introduce High- Resolution Depth Net (HRDepthNet)-a machine learning driven approach to detect human joints (body, head, and upper and lower extremities) in purely depth images. HRDepthNet retrains the original HRNet for depth images. Therefore, a dataset is created holding depth (and RGB) images recorded with subjects conducting the timed up and go test-an established geriatric assessment. The images were manually annotated RGB images. The training and evaluation were conducted with this dataset. For accuracy evaluation, detection of body joints was evaluated via COCO's evaluation metrics and indicated that the resulting depth image-based model achieved better results than the HRNet trained and applied on corresponding RGB images. An additional evaluation of the position errors showed a median deviation of 1.619 cm (x-axis), 2.342 cm (y-axis) and 2.4 cm (z-axis).

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.

[Feasibility and acceptance of video-based physiotherapy : New medical care provision for older people during the COVID-19 pandemic]. / Machbarkeit und Akzeptanz videobasierter Physiotherapie : Neues Versorgungsangebot für ältere Menschen während der COVID-19-Pandemie.

BACKGROUND AND OBJECTIVE: Restrictions in public life during the COVID-19 pandemic mainly addressed the safety of high-risk older multimorbid patients to protect them from infection. Nevertheless, detrimental aspects of the lockdown for older people are a reduction in physical activity and limited access to physiotherapy, which are likely to have a negative impact on the health status. This study examined the feasibility of video-based physiotherapy (VT) and the subjective rating of VT by patients and therapists. METHODS: From April to June 2020, 4 facilities with 9 patients (6 women, 64-82 years old) participated in the study and were provided with technical equipment. Semistructured telephone interviews were conducted in eight patients to assess physical activity, functional ability and participation before and during the restrictions. Both patients and therapists were asked about their subjective experiences with VT. RESULTS: A total of 92 VT sessions took place. Performance of the exercises and comprehension of instructions were rated as good to very good. The level of acceptance was high. Of the patients four described a perceived reduction in their physical activities due to the public restrictions; however, in the questionnaires no substantial differences in participation and physical activity were found. DISCUSSION: The use of VT is feasible in older patients. Only minor technical support is needed. In pandemic situations or in other contexts VT appears to be a promising supplement or alternative to normal physiotherapy. Further studies are needed to identify suitable patient groups, to prove efficacy and to develop further content-related aspects of VT.

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.