Development and technical validation of a smartphone-based cry detection algorithm

Introduction: The duration and frequency of crying of an infant can be indicative of its health. Manual tracking and labeling of crying is laborious, subjective, and sometimes inaccurate. The aim of this study was to develop and technically validate a smartphone-based algorithm able to automatically detect crying.Methods: For the development of the algorithm a training dataset containing 897 5-s clips of crying infants and 1,263 clips of non-crying infants and common domestic sounds was assembled from various online sources. OpenSMILE software was used to extract 1,591 audio features per audio clip. A random forest classifying algorithm was fitted to identify crying from non-crying in each audio clip. For the validation of the algorithm, an independent dataset consisting of real-life recordings of 15 infants was used. A 29-min audio clip was analyzed repeatedly and under differing circumstances to determine the intra- and inter- device repeatability and robustness of the algorithm.Results: The algorithm obtained an accuracy of 94% in the training dataset and 99% in the validation dataset. The sensitivity in the validation dataset was 83%, with a specificity of 99% and a positive- and negative predictive value of 75 and 100%, respectively. Reliability of the algorithm appeared to be robust within- and across devices, and the performance was robust to distance from the sound source and barriers between the sound source and the microphone.Conclusion: The algorithm was accurate in detecting cry duration and was robust to various changes in ambient settings.Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care

Theoretical Performance of Nonlinear Mixed-Effect Models Incorporating Saliva as an Alternative Sampling Matrix for Therapeutic Drug Monitoring in Pediatrics: A Simulation Study

Background: Historically, pharmacokinetic (PK) studies and therapeutic drug monitoring (TDM) have relied on plasma as a sampling matrix. Noninvasive sampling matrices, such as saliva, can reduce the burden on pediatric patients. The variable plasma-saliva relationship can be quantified using population PK models (nonlinear mixed-effect models). However, criteria regarding acceptable levels of variability in such models remain unclear. In this simulation study, the authors aimed to propose a saliva TDM evaluation framework and evaluate model requirements in the context of TDM, with gentamicin and lamotrigine as model compounds. Methods: Two population pharmacokinetic models for gentamicin in neonates and lamotrigine in pediatrics were extended with a saliva compartment including a delay constant (k(SALIVA)), a saliva:plasma ratio, and between-subject variability (BSV) on both parameters. Subjects were simulated using a realistic covariate distribution. Bayesian maximum a posteriori TDM was applied to assess the performance of an increasing number of TDM saliva samples and varying levels of BSV and residual variability. Saliva TDM performance was compared with plasma TDM performance. The framework was applied to a known voriconazole saliva model as a case study. Results: TDM performed using saliva resulted in higher target attainment than no TDM, and a residual proportional error <25% on saliva observations led to saliva TDM performance comparable with plasma TDM. BSV on k(SALIVA) did not affect performance, whereas increasing BSV on saliva:plasma ratios by >25% for gentamicin and >50% for lamotrigine reduced performance. The simulated target attainment for voriconazole saliva TDM was >90%. Conclusions: Saliva as an alternative matrix for noninvasive TDM is possible using nonlinear mixed-effect models combined with Bayesian optimization. This article provides a workflow to explore TDM performance for compounds measured in saliva and can be used for evaluation during model building

Co-Creation Approach with Action-Oriented Research Methods to Strengthen "Krachtvoer"; A School-Based Programme to Enhance Healthy Nutrition in Adolescents

In recent years, the nutritional pattern of the Dutch adolescent has cautiously improved. However, progress can be gained if more Dutch adolescents adhere to the nutritional guidelines. School-based initiatives offer opportunities to deal with the unhealthy eating behaviours of adolescents via nutrition educational interventions. In designing and/or re-designing school-based interventions, it is important to enhance optimal context-oriented implementation adaptation by involving the complex adaptive school system. This paper elaborates on the way of dealing with the dynamic implementation context of the educational programme “Krachtvoer” (ENG: “Power food”) for prevocational schools, how the programme can be adapted to each unique implementation context, and how the programme can be progressively kept up to date. Following a co-creation-guided approach with various intersectoral stakeholders within and outside the school setting, action-oriented mixed research methods (i.e., observations, semi-structured interviews, focus group interviews, programme usage monitoring, and questionnaires) constantly provide input to develop the programme and its implementation strategy via continuous micro-process cycles. Successful co-creation of school-based health promotion seems to be dependent on proper intersectoral cooperation between research and practice communities, a national partner network that can provide project-relevant insights and establish capacity building aimed at improving contextual fit, and a time-investment balance in and between sectors

Atomic beam brightener with a 1600-fold increase in intensity for Ne

The study of collisions between excited atoms requires high-intensity atomic beams to achieve detector signals of sufficient strength. Producing large densities of excited rare gas atoms R is especially difficult, since with conventional sources metastable atoms R make up a tiny fraction of ≈10-5 of the total beam flux. In such cases, 'brightening' the beam is the only way to achieve a sufficiently large flux. We have followed a scheme proposed by Metcalf to brighten an atomic beam of neon. The setup employs laser cooling on the Ne((3s)3P2 → (3p)3D3) cycling transition, and consists of three stages. First, we collimate all atoms emerging from a discharge source within a half-angle θ0 = 100 mrad. Second, the collimated beam is focused to a point. Third, the now converging beam is re-collimated to form a thin and bright atomic beam

A dynamic quality assessment tool for laparoscopic hysterectomy to measure surgical outcomes

GynecologyCervix cance

A dynamic quality assessment tool for laparoscopic hysterectomy to measure surgical outcomes

Action Contro

Development of Novel, Value-Based, Digital Endpoints for Clinical Trials: A Structured Approach Toward Fit-for-Purpose Validation

Novel digital endpoints gathered via wearables, small devices, or algorithms hold great promise for clinical trials. However, implementation has been slow because of a lack of guidelines regarding the validation process of these new measurements. In this paper, we propose a pragmatic approach toward selection and fit-for-purpose validation of digital endpoints. Measurements should be value-based, meaning the measurements should directly measure or be associated with meaningful outcomes for patients. Devices should be assessed regarding technological validity. Most importantly, a rigorous clinical validation process should appraise the tolerability, difference between patients and controls, repeatability, detection of clinical events, and correlation with traditional endpoints. When technically and clinically fit-for-purpose, case building in interventional clinical trials starts to generate evidence regarding the response to new or existing health-care interventions. This process may lead to the digital endpoint replacing traditional endpoints, such as clinical rating scales or questionnaires in clinical trials. We recommend initiating more data-sharing collaborations to prevent unnecessary duplication of research and integration of value-based measurements in clinical care to enhance acceptance by health-care professionals. Finally, we invite researchers and regulators to adopt this approach to ensure a timely implementation of digital measurements and value-based thinking in clinical trial design and health care.Significance Statement-Novel digital endpoints are often cited as promising for the clinical trial of the future. However, clear validation guidelines are lacking in the literature. This paper contains pragmatic criteria for the selection, technical validation, and clinical validation of novel digital endpoints and provides recommendations for future work and collaboration.Perioperative Medicine: Efficacy, Safety and Outcom

Postdischarge Recovery after Acute Pediatric Lung Disease Can Be Quantified with Digital Biomarkers

Background: Pediatric patients admitted for acute lung disease are treated and monitored in the hospital, after which full recovery is achieved at home. Many studies report in-hospital recovery, but little is known regarding the time to full recovery after hospital discharge. Technological innovations have led to increased interest in home-monitoring and digital biomarkers. The aim of this study was to describe at-home recovery of 3 common pediatric respiratory diseases using a questionnaire and wearable device. Methods: In this study, patients admitted due to pneumonia (n = 30), preschool wheezing (n = 30), and asthma exacerbation (AE; n = 11) were included. Patients were monitored with a smartwatch and a questionnaire during admission, with a 14-day recovery period and a 10-day "healthy" period. Median compliance was calculated, and a mixed-effects model was fitted for physical activity and heart rate (HR) to describe the recovery period, and the physical activity recovery trajectory was correlated to respiratory symptom scores. Results: Median compliance was 47% (interquartile range [IQR] 33-81%) during the entire study period, 68% (IQR 54-91%) during the recovery period, and 28% (IQR 0-74%) during the healthy period. Patients with pneumonia reached normal physical activity 12 days postdischarge, while subjects with wheezing and AE reached this level after 5 and 6 days, respectively. Estimated mean physical activity was closely correlated with the estimated mean symptom score. HR measured by the smartwatch showed a similar recovery trajectory for subjects with wheezing and asthma, but not for subjects with pneumonia. Conclusions: The digital biomarkers, physical activity, and HR obtained via smartwatch show promise for quantifying postdischarge recovery in a noninvasive manner, which can be useful in pediatric clinical trials and clinical care

Surgical flow disturbances in dedicated minimally invasive surgery suites: an observational study to assess its supposed superiority over conventional suites

GynecologyCervix cance

Development and Technical Validation of a Smartphone-Based Cry Detection Algorithm

Introduction: The duration and frequency of crying of an infant can be indicative of its health. Manual tracking and labeling of crying is laborious, subjective, and sometimes inaccurate. The aim of this study was to develop and technically validate a smartphone-based algorithm able to automatically detect crying.Methods: For the development of the algorithm a training dataset containing 897 5-s clips of crying infants and 1,263 clips of non-crying infants and common domestic sounds was assembled from various online sources. OpenSMILE software was used to extract 1,591 audio features per audio clip. A random forest classifying algorithm was fitted to identify crying from non-crying in each audio clip. For the validation of the algorithm, an independent dataset consisting of real-life recordings of 15 infants was used. A 29-min audio clip was analyzed repeatedly and under differing circumstances to determine the intra- and inter- device repeatability and robustness of the algorithm.Results: The algorithm obtained an accuracy of 94% in the training dataset and 99% in the validation dataset. The sensitivity in the validation dataset was 83%, with a specificity of 99% and a positive- and negative predictive value of 75 and 100%, respectively. Reliability of the algorithm appeared to be robust within- and across devices, and the performance was robust to distance from the sound source and barriers between the sound source and the microphone.Conclusion: The algorithm was accurate in detecting cry duration and was robust to various changes in ambient settings.Perioperative Medicine: Efficacy, Safety and Outcome (Anesthesiology/Intensive Care