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Abstract Purpose Blood-flow restriction (BFR) endurance training may increase endurance performance and muscle strength similar to traditional endurance training while requiring a lower training intensity. We aimed to compare acute cardiorespiratory responses to low-intensity interval exercise under BFR with moderate-intensity traditional interval exercise (TRA). Methods We conducted a randomized crossover study. The protocol involved three cycling intervals interspersed with 1 min resting periods. With a 48-h washout period, individuals performed the protocol twice in random order: once as BFR-50 (i.e., 50% incremental peak power output [IPPO] and 50% limb occlusion pressure [LOP]) and once as TRA-65 (65% IPPO without occlusion). TRA-65 intervals lasted 2 min, and time-matched BFR-50 lasted 2 min and 18 s. Respiratory parameters were collected by breath-by-breath analysis. The ratings of perceived breathing and leg exertion (RPE, 0 to 10) were assessed. Linear mixed models were used for analysis. Results Out of the 28 participants initially enrolled in the study, 24 healthy individuals (18 males and 6 females) completed both measurements. Compared with TRA-65, BFR-50 elicited lower minute ventilation (VE, primary outcome) (-3.1 l/min [-4.4 to -1.7]), oxygen consumption (-0.22 l/min [-0.28 to -0.16]), carbon dioxide production (-0.25 l/min [-0.29 to -0.20]) and RPE breathing (-0.9 [-1.2 to -0.6]). RPE leg was significantly greater in the BFR-50 group (1.3 [1.0 to 1.7]). Conclusion BFR endurance exercise at 50% IPPO and 50% LOP resulted in lower cardiorespiratory work and perceived breathing effort compared to TRA at 65% IPPO. BFR-50 could be an attractive alternative for TRA-65, eliciting less respiratory work and perceived breathing effort while augmenting perceived leg muscle effort. Trial registration NCT05163600; December 20, 2021.

The Probabilistic Reward Task (PRT) is widely used to investigate the impact of Major Depressive Disorder (MDD) on reinforcement learning (RL), and recent studies have used it to provide insight into decision-making mechanisms affected by MDD. The current project used PRT data from unmedicated, treatment-seeking adults with MDD to extend these efforts by: (1) providing a more detailed analysis of standard PRT metrics—response bias and discriminability—to better understand how the task is performed; (2) analyzing the data with two computational models and providing psychometric analyses of both; and (3) determining whether response bias, discriminability, or model parameters predicted responses to treatment with placebo or the atypical antidepressant bupropion. Analysis of standard metrics replicated recent work by demonstrating a dependency between response bias and response time (RT), and by showing that reward totals in the PRT are governed by discriminability. Behavior was well-captured by the Hierarchical Drift Diffusion Model (HDDM), which models decision-making processes; the HDDM showed excellent internal consistency and acceptable retest reliability. A separate “belief” model reproduced the evolution of response bias over time better than the HDDM, but its psychometric properties were weaker. Finally, the predictive utility of the PRT was limited by small samples; nevertheless, depressed adults who responded to bupropion showed larger pre-treatment starting point biases in the HDDM than non-responders, indicating greater sensitivity to the PRT’s asymmetric reinforcement contingencies. Together, these findings enhance our understanding of reward and decision-making mechanisms that are implicated in MDD and probed by the PRT.

The Orthelligent Pro sensor is a practicable, portable measuring instrument. This study assessed the validity and reliability of this sensor in measuring single-leg countermovement jumps. Fifty healthy athletic adults participated in two measurement sessions a week apart in time. They performed single-leg countermovement jumps on the force plate while wearing the Orthelligent Pro sensor on their lower leg. During the first measurement session, Tester 1 invited the participants to make three single-leg countermovement jumps; subsequently, Tester 2 did the same. For assessing the sensor’s intratester reliability, Tester 1 again invited the participants to make three single-leg countermovement jumps during the second measurement session. The sensor’s validity was assessed by using the force plate results as the gold standard. To determinate the agreement between two measurements, Bland–Altman plots were created. The intertester reliability (ICC = 0.99; 0.97) and intratester reliability (ICC = 0.96; 0.82) were both excellent. The validity calculated (i) on the basis of the mean value of three jumps and (ii) on the basis of the maximum value of three jumps was very high, but it showed a systematic error. Taking this error into account, physiotherapists can use the Orthelligent Pro sensor as a valid and reliable instrument for measuring the jump height of countermovement jumps.

Approximately, half of COPD patients die from cardiovascular diseases. A prolongation of cardiac repolarization (measured as QTc interval) is associated with cardiovascular events or cardiovascular deaths in populations of older adults and COPD. One way to reduce the QTc could be to increase physical activity (PA). We investigated whether QTc can be reduced by an increase in PA in patients with severe COPD. This is a secondary outcome analysis from a randomized controlled trial investigating the effects of a 3 months pedometer based program to improve PA. 12-lead ECG was assessed at baseline and after 3 months. We measured PA using a validated triaxial accelerometer. Data were analyzed from 59 participants. Multiple regression modeling, including adjustment for baseline QTc, sex, QT prolonging medications, BMI, smoking status and FEV1%, showed no evidence for an association between an improvement of ≥15% PA and QTc reduction. A 15% improvement in PA according to step counts over 3 months seems not to reduce QTc interval by its MCID of 20 ms in patients with severe to very severe COPD.

Research question The assessment of cough frequency in clinical practice relies predominantly on the patient's history. Currently, objective evaluation of cough is feasible with bulky equipment during a brief time (i.e. hours up to 1 day). Thus, monitoring of cough has been rarely performed outside clinical studies. We developed a small wearable cough detector (SIVA-P3) that uses deep neural networks for the automatic counting of coughs. This study examined the performance of the SIVA-P3 in an outpatient setting. Methods We recorded cough epochs with SIVA-P3 over eight consecutive days in patients suffering from chronic cough. During the first 24 h, the detector was validated against cough events counted by trained human listeners. The wearing comfort and the device usage were assessed using a questionnaire. Results In total, 27 participants (mean±sd age 50±14 years) with either chronic unexplained cough (n=12), COPD (n=4), asthma (n=5) or interstitial lung disease (n=6) were studied. During the daytime, the sensitivity of SIVA-P3 cough detection was 88.5±2.49% and the specificity was 99.97±0.01%. During the night-time, the sensitivity was 84.15±5.04% and the specificity was 99.97±0.02%. The wearing comfort and usage of the device was rated as very high by most participants. Conclusion SIVA-P3 enables automatic continuous cough monitoring in an outpatient setting for objective assessment of cough over days and weeks. It shows comparable sensitivity or higher sensitivity than other devices with fully automatic cough counting. Thanks to its wearing comfort and the high performance for cough detection, it has the potential for being used in routine clinical practice.

Fear extinction is the basis of exposure therapies for posttraumatic stress disorder (PTSD), but half of patients do not improve. Predicting fear extinction in individuals with PTSD may inform personalized exposure therapy development. The participants were 125 trauma-exposed adults (96 female) with a range of PTSD symptoms. Electromyography, electrocardiogram, and skin conductance were recorded at baseline, during dark-enhanced startle, and during fear conditioning and extinction. Using a cross-validated, hold-out sample prediction approach, three penalized regressions and conventional ordinary least squares were trained to predict fear-potentiated startle during extinction using 50 predictor variables (5 clinical, 24 self-reported, and 21 physiological). The predictors, selected by penalized regression algorithms, were included in multivariable regression analyses, while univariate regressions assessed individual predictors. All the penalized regressions outperformed OLS in prediction accuracy and generalizability, as indexed by the lower mean squared error in the training and holdout subsamples. During early extinction, the consistent predictors across all the modeling approaches included dark-enhanced startle, the depersonalization and derealization subscale of the dissociative experiences scale, and the PTSD hyperarousal symptom score. These findings offer novel insights into the modeling approaches and patient characteristics that may reliably predict fear extinction in PTSD. Penalized regression shows promise for identifying symptom-related variables to enhance the predictive modeling accuracy in clinical research.

Here, we follow the call to target measurement reliability as a key prerequisite for individual-level predictions in translational neuroscience by investigating (1) longitudinal reliability at the individual and (2) group level, (3) internal consistency and (4) response predictability across experimental phases. One hundred and twenty individuals performed a fear conditioning paradigm twice 6 months apart. Analyses of skin conductance responses, fear ratings and blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI) with different data transformations and included numbers of trials were conducted. While longitudinal reliability was rather limited at the individual level, it was comparatively higher for acquisition but not extinction at the group level. Internal consistency was satisfactory. Higher responding in preceding phases predicted higher responding in subsequent experimental phases at a weak to moderate level depending on data specifications. In sum, the results suggest that while individual-level predictions are meaningful for (very) short time frames, they also call for more attention to measurement properties in the field.

BackgroundResearch integrating multisensory home-monitoring in respiratory disease is scarce. Therefore, we created a novel multisensory home-monitoring device tailored for long-term respiratory disease management (named the CAir-Desk). We hypothesize that recent technological accomplishments can be integrated into a multisensory participant-driven platform. We also believe that this platform could improve chronic disease management and be accessible to large groups at an acceptable cost. ObjectiveThis study aimed to report on user adherence and acceptance as well as system functionality of the CAir-Desk in a sample of participants with stable chronic obstructive pulmonary disease (COPD) or asthma. MethodsWe conducted an observational usability study. Participants took part in 4 weeks of home-monitoring with the CAir-Desk. The CAir-Desk recorded data from all participants on symptom burden, physical activity, spirometry, and environmental air quality; data on sputum production, and nocturnal cough were only recorded for participants who experienced symptoms. After the study period, participants reported on their perceptions of the usability of the monitoring device through a purpose-designed questionnaire. We used descriptive statistics and visualizations to display results. ResultsTen participants, 5 with COPD and 5 with asthma took part in this study. They completed symptom burden questionnaires on a median of 96% (25th percentile 14%, 75th percentile 96%), spirometry recordings on 55% (20%, 94%), wrist-worn physical activity recordings on 100% (97%, 100%), arm-worn physical activity recordings on 45% (13%, 63%), nocturnal cough recordings on 34% (9%, 54%), sputum recordings on 5% (3%, 12%), and environmental air quality recordings on 100% (99%, 100%) of the study days. The participants indicated that the measurements consumed a median of 13 (10, 15) min daily, and that they preferred the wrist-worn physical activity monitor to the arm-worn physical activity monitor. ConclusionsThe CAir-Desk showed favorable technical performance and was well-accepted by our sample of participants with stable COPD and asthma. The obtained insights were used in a redesign of the CAir-Desk, which is currently applied in a randomized controlled trial including an interventional program.

Background: We aimed to longitudinally monitor the recovery in breathlessness, symptom burden, health-related quality-of-life, and mental health status in individuals hospitalised due to SARS-CoV-2 associated respiratory failure.Methods: Individuals hospitalised due to SARS-CoV-2 associated respiratory failure were recruited at hospital discharge in three participating centres. During the 90 day follow-up, European Quality of Life−5 Dimensions−5 Levels Instrument (EQ-5D-5L), modified Medical Research Council (mMRC) Dyspnoea Scale, COPD Assessment Test (CAT), and weekly Hospital Anxiety and Depression Scale (HADS) questionnaires were assessed using a smartphone application. The results were presented using descriptive statistics and graphics. Linear mixed models with random intercept were fitted to analyse differences of intensive-care unit status on the recovery course in each outcome.Results: We included 58 participants, 40 completed the study. From hospital discharge until 90 days post-discharge, EQ-5D-5L index changed from 0.83 (0.66, 0.92) to 0.96 (0.82, 1.0), VAS rating on general health status changed from 62 (50, 75) % to 80 (74, 94) %, CAT changed from 13 (10, 21) to 7 (3, 11) points, mMRC changed from 1 (0, 2) to 0 (0, 1) points, HADS depression subscale changed from 6 (4, 9) to 5 (1, 6) points, HADS anxiety subscale changed from 7 (3, 9) to 2 (1, 8) points. Differences in the recovery courses were observed between intensive-care and ward participants. Participants that were admitted to an intensive-care unit during their hospitalisation (n = 16) showed increases in CAT, mMRC, HADS scores, and decreases in EQ-5D-5L 30 days after hospital discharge.Conclusion: Being admitted to an ICU led to statistically significant reductions in recovery in the EQ-5D-5L and the CAT. Furthermore, the flare-up in symptom burden and depression scores, accompanied by an attenuated recovery in HrQoL and general health status in the ICU-group suggests that a clinical follow-up 1 month after hospital discharge can be recommended, evaluating further treatments.Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT04365595].

Abstract Aim of the study Artificial intelligence (AI) chatbots are established as tools for answering medical questions worldwide. Healthcare trainees are increasingly using this cutting-edge technology, although its reliability and accuracy in the context of healthcare remain uncertain. This study evaluated the suitability of Chat-GPT versions 3.5 and 4 for healthcare professionals seeking up-to-date evidence and recommendations for resuscitation by comparing the key messages of the resuscitation guidelines, which methodically set the gold standard of current evidence and recommendations, with the statements of the AI chatbots on this topic. Methods This prospective comparative content analysis was conducted between the 2021 European Resuscitation Council (ERC) guidelines and the responses of two freely available ChatGPT versions (ChatGPT-3.5 and the Bing version of the ChatGPT-4) to questions about the key messages of clinically relevant ERC guideline chapters for adults. (1) The content analysis was performed bidirectionally by independent raters. The completeness and actuality of the AI output were assessed by comparing the key message with the AI-generated statements. (2) The conformity of the AI output was evaluated by comparing the statements of the two ChatGPT versions with the content of the ERC guidelines. Results In response to inquiries about the five chapters, ChatGPT-3.5 generated a total of 60 statements, whereas ChatGPT-4 produced 32 statements. ChatGPT-3.5 did not address 123 key messages, and ChatGPT-4 did not address 132 of the 172 key messages of the ERC guideline chapters. A total of 77% of the ChatGPT-3.5 statements and 84% of the ChatGPT-4 statements were fully in line with the ERC guidelines. The main reason for nonconformity was superficial and incorrect AI statements. The interrater reliability between the two raters, measured by Cohen’s kappa, was greater for ChatGPT-4 (0.56 for completeness and 0.76 for conformity analysis) than for ChatGPT-3.5 (0.48 for completeness and 0.36 for conformity). Conclusion We advise healthcare professionals not to rely solely on the tested AI-based chatbots to keep up to date with the latest evidence, as the relevant texts for the task were not part of the training texts of the underlying LLMs, and the lack of conceptual understanding of AI carries a high risk of spreading misconceptions. Original publications should always be considered for comprehensive understanding.

This tutorial describes the necessary steps for designing and conducting a perception experiment in order to obtain design parameters for human–machine interactions. It is intended for engineers and product designers, which require design parameters not included in the current state of the art. Topics addressed are the preposition of hypotheses, the selection of parameters, psychophysical measurement procedures and the calculation of sample sizes. Relevant steps for data analysis from psychology and social sciences are applied to the engineering and design context and guidelines for reporting results are given. The required steps are illustrated with an example experiment assessing detection thresholds of damping parameters of haptic automotive rotary controls with regard to parameters like knob diameter and distraction. Results imply significant effects of knob diameter on both absolute and differential thresholds, but no effect of distraction, implying a good transferability of laboratory results to real-world applications.