Should young athletes be screened for cardiomyopathies to reduce the burden of sudden cardiac death in athletes?

In this correspondence, we highlight the risk of sudden cardiac death associated with undiagnosed cardiomyopathies. Life-threatening arrhythmias, which underlie sudden cardiac death, can be triggered by high-intensity exercise. It raises the question whether, and if so, how athletes should be screened for cardiomyopathies. The example of practice from Italy is discussed. We also briefly discuss novel developments, such as wearable biosensors and machine learning, which could be applied to screening for cardiomyopathies in future.

Features from the photoplethysmogram and the electrocardiogram for estimating changes in blood pressure.

There is a growing emphasis being placed on the potential for cuffless blood pressure (BP) estimation through modelling of morphological features from the photoplethysmogram (PPG) and electrocardiogram (ECG). However, the appropriate features and models to use remain unclear. We investigated the best features available from the PPG and ECG for BP estimation using both linear and non-linear machine learning models. We conducted a clinical study in which changes in BP ([Formula: see text]BP) were induced by an infusion of phenylephrine in 30 healthy volunteers (53.8% female, 28.0 (9.0) years old). We extracted a large and diverse set of features from both the PPG and the ECG and assessed their individual importance for estimating [Formula: see text]BP through Shapley additive explanation values and a ranking coefficient. We trained, tuned, and evaluated linear (ordinary least squares, OLS) and non-linear (random forest, RF) machine learning models to estimate [Formula: see text]BP in a nested leave-one-subject-out cross-validation framework. We reported the results as correlation coefficient ([Formula: see text]), root mean squared error (RMSE), and mean absolute error (MAE). The non-linear RF model significantly ([Formula: see text]) outperformed the linear OLS model using both the PPG and the ECG signals across all performance metrics. Estimating [Formula: see text]SBP using the PPG alone ([Formula: see text] = 0.86 (0.23), RMSE = 5.66 (4.76) mmHg, MAE = 4.86 (4.29) mmHg) performed significantly better than using the ECG alone ([Formula: see text] = 0.69 (0.45), RMSE = 6.79 (4.76) mmHg, MAE = 5.28 (4.57) mmHg), all [Formula: see text]. The highest ranking features from the PPG largely modelled increasing reflected wave interference driven by changes in arterial stiffness. This finding was supported by changes observed in the PPG waveform in response to the phenylephrine infusion. However, a large number of features were required for accurate BP estimation, highlighting the high complexity of the problem. We conclude that the PPG alone may be further explored as a potential single source, cuffless, blood pressure estimator. The use of the ECG alone is not justified. Non-linear models may perform better as they are able to incorporate interactions between feature values and demographics. However, demographics may not adequately account for the unique and individualised relationship between the extracted features and BP.

Classifying nocturnal blood pressure patterns using photoplethysmogram features.

Circadian rhythms in blood pressure (BP) may in some cases be indicative of an increased risk of adverse cardiovascular events. However, current methods for assessing these rhythms can be disruptive to sleep, work, and daily activities. Features of the photoplethysmogram (PPG), which can be non-invasively and unobtrusively recorded, have been suggested as surrogate measures of BP. This work investigates the presence of a circadian rhythm in these features and evaluates their potential to classify nocturnal BP patterns. 742 patients who were discharged home from the ICU were selected from the MIMIC-III database. Our results show that a number of PPG features exhibit a clear and observable circadian rhythm. Of the 19 features evaluated, the circadian rhythms of 5 features outperformed heart rate (HR) in terms of correlation with the circadian rhythm of SBP ( ). We also present evidence that a metric combining the PPG features significantly improves BP phenotype classification accuracy. Clinical Relevance-This work suggests that a combined metric of PPG features may be able to accurately assess an individual's circadian rhythm of BP.

Longitudinal Monitoring of Progressive Supranuclear Palsy using Body-Worn Movement Sensors.

BACKGROUND: We have previously shown that wearable technology and machine learning techniques can accurately discriminate between progressive supranuclear palsy (PSP), Parkinson's disease, and healthy controls. To date these techniques have not been applied in longitudinal studies of disease progression in PSP. OBJECTIVES: We aimed to establish whether data collected by a body-worn inertial measurement unit (IMU) network could predict clinical rating scale scores in PSP and whether it could be used to track disease progression. METHODS: We studied gait and postural stability in 17 participants with PSP over five visits at 3-month intervals. Participants performed a 2-minute walk and an assessment of postural stability by standing for 30 seconds with their eyes closed, while wearing an array of six IMUs. RESULTS: Thirty-two gait and posture features were identified, which progressed significantly with time. A simple linear regression model incorporating the three features with the clearest progression pattern was able to detect statistically significant progression 3 months in advance of the clinical scores. A more complex linear regression and a random forest approach did not improve on this. CONCLUSIONS: The reduced variability of the models, in comparison to clinical rating scales, allows a significant change in disease status from baseline to be observed at an earlier stage. The current study sheds light on the individual features that are important in tracking disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Non-contact physiological monitoring of post-operative patients in the intensive care unit.

Prolonged non-contact camera-based monitoring in critically ill patients presents unique challenges, but may facilitate safe recovery. A study was designed to evaluate the feasibility of introducing a non-contact video camera monitoring system into an acute clinical setting. We assessed the accuracy and robustness of the video camera-derived estimates of the vital signs against the electronically-recorded reference values in both day and night environments. We demonstrated non-contact monitoring of heart rate and respiratory rate for extended periods of time in 15 post-operative patients. Across day and night, heart rate was estimated for up to 53.2% (103.0 h) of the total valid camera data with a mean absolute error (MAE) of 2.5 beats/min in comparison to two reference sensors. We obtained respiratory rate estimates for 63.1% (119.8 h) of the total valid camera data with a MAE of 2.4 breaths/min against the reference value computed from the chest impedance pneumogram. Non-contact estimates detected relevant changes in the vital-sign values between routine clinical observations. Pivotal respiratory events in a post-operative patient could be identified from the analysis of video-derived respiratory information. Continuous vital-sign monitoring supported by non-contact video camera estimates could be used to track early signs of physiological deterioration during post-operative care.

The presence of a circadian rhythm in pulse arrival time and its application for classifying blood pressure night-time dip.

Circadian rhythms of blood pressure (BP) have key diagnostic significance in the assessment of hypertension. The night-time dip or rise in BP (10-20% decrease or increase compared to daytime BP), for example, has been shown to be a strong indicator for cardiovascular disease. However, current methods for assessing the circadian rhythms of BP can be disruptive to sleep, work, and daily activities. Pulse arrival time (PAT) has been suggested as a surrogate measure of BP. This work investigates the presence of a circadian rhythm in PAT and evaluates its application to classify nocturnal BP dip or rise. 769 patients who were discharged home from the ICU were selected from the MIMIC database. Our results show a clear and observable circadian rhythm of PAT that is strongly inversely correlated with BP (r = -0.89). The ratios between nocturnal and diurnal changes in PAT accurately classifies an individual as a nocturnal BP dipper (AUC = 0.72) or a riser (AUC = 0.71).Clinical Relevance-This work shows that you can accurately assess an individuals's circadian rhythm of BP using PAT.

New method to measure interbreath intervals in infants for the assessment of apnoea and respiration.

BACKGROUND: Respiratory disorders, including apnoea, are common in preterm infants due to their immature respiratory control compared with term-born infants. However, our inability to accurately measure respiratory rate in hospitalised infants results in unreported episodes of apnoea and an incomplete picture of respiratory activity. METHODS: We develop, validate and use a novel algorithm to identify interbreath intervals (IBIs) and apnoeas in preterm infants. In 42 preterm infants (1600 hours of recordings), we assess IBIs from the chest electrical impedance pneumograph using an adaptive amplitude threshold for the detection of breaths. The algorithm is refined by comparing its accuracy with clinically observed breaths and pauses in breathing. We develop an automated classifier to differentiate periods of true apnoea from artefactually low amplitude signal. We assess the performance of this algorithm in the detection of morphine-induced respiratory depression. Finally, we use the algorithm to investigate whether retinopathy of prematurity (ROP) screening alters the IBI distribution. RESULTS: Individual breaths were detected with a false-positive rate of 13% and a false-negative rate of 12%. The classifier identified true apnoeas with an accuracy of 93%. As expected, morphine caused a significant shift in the IBI distribution towards longer IBIs. Following ROP screening, there was a significant increase in pauses in breathing that lasted more than 10 s (t-statistic=1.82, p=0.023). This was not reflected by changes in the monitor-derived respiratory rate and no episodes of apnoea were recorded in the medical records. CONCLUSIONS: We show that our algorithm offers an improved method for the identification of IBIs and apnoeas in preterm infants. Following ROP screening, increased respiratory instability can occur even in the absence of clinically significant apnoeas. Accurate assessment of infant respiratory activity is essential to inform clinical practice.

Profile of morphology teachers in Chilean universities / Perfil de los docentes de morfología en universidades chilenas

SUMMARY: University teaching in Chile has been influenced in recent decades by changes to the education system, which has increased universities and academic offerings and, therefore, the demand for new instructors. Teaching morphological sciences has not been exempt from these changes, with new instructors needed to fill the growing offerings of programs that include anatomy, embryology and histology. The aim was to understand the profile of the academics teaching morphology in Chile in 2020. A voluntary online survey was applied to 213 university morphology teachers, in which information was collected on professional and academic training, geographical distribution, gender, continuing academic education and employment situation. Overall, the results show that 65.9 % of instructors were men and 35.1 % women, and most (34.6 %) had between 5 and 10 years in morphology, and a master's degree was predominant (53.27 %). In the area of anatomy, 46 % of instructors were physiotherapists and 24.6 % dentists, whereas in the areas of histology and embryology, the group was diverse. In terms of employment, 49.06 % stated they worked full time, mainly in teaching.41.31 % of the instructors were concentrated in the Metropolitan Region. There was no association between gender and graduate training, maximum academic degree attained, type of workday or academic profile, but there was one by disciplinary area. The conclusion drawn is that morphology teachers in Chilean universities are part of a wide range of professionals dedicated to different disciplinary areas, with master's degree and/or specialization, located mainly in the Metropolitan Region. This multidisciplinary profile demonstrates the mainstreaming of morphology teaching in Chile.

RESUMEN: La docencia universitaria en Chile se ha visto influenciada en las últimas décadas por modificaciones del sistema educativo, las cuales generaron un incremento de universidades y oferta académica y, por ende, demanda de nuevos docentes. La enseñanza de las ciencias morfológicas no ha quedado exenta de estos cambios, teniendo que enfrentar la necesidad de nuevos docentes requeridos para suplir la creciente oferta de programas que incluyen a la anatomía, embriología e histología. El objetivo fue conocer el perfil de los académicos que realizaron docencia de morfología en Chile el año 2020. Se aplicó una encuesta online voluntaria a 213 académicos universitarios de morfología, en la cual se recopiló información sobre formación profesional, académica, distribución geográfica, género, perfeccionamiento académico y situación laboral. Los resultados, en general, muestran que el 65,9 % de los docentes eran hombres y un 35,1 % mujeres, los que en su mayoría (34,6 %) tenían entre 5 y 10 años vinculados a la morfología y donde prevalecía el grado académico de magíster (53,27 %). En el área de la anatomía el 46 % de los docentes correspondió a kinesiólogos y el 24,6 % a odontólogos, mientras que, en las áreas de histología y embriología el grupo fue misceláneo. En el ámbito laboral el 49,06 % declaró tener jornada completa, destinada principalmente a la docencia. El 41,31 % de los docentes se concentró en la Región Metropolitana. No hubo asociación entre género y formación de postgrado, máximo grado académico alcanzado, tipo de jornada y perfil académico, pero si hubo por área disciplinar. Se concluye que los docentes de morfología en Chile pertenecen a un amplio espectro de profesionales dedicados a distintas áreas disciplinares, con formación de magíster y/o especialización, ubicados principalmente en la Región Metropolitana. Este perfil multidisciplinar demuestra la transversalidad de la docencia morfológica en Chile.

Pulse arrival time as a surrogate of blood pressure.

Various models have been proposed for the estimation of blood pressure (BP) from pulse transit time (PTT). PTT is defined as the time delay of the pressure wave, produced by left ventricular contraction, measured between a proximal and a distal site along the arterial tree. Most researchers, when they measure the time difference between the peak of the R-wave in the electrocardiogram signal (corresponding to left ventricular depolarisation) and a fiducial point in the photoplethysmogram waveform (as measured by a pulse oximeter attached to the fingertip), describe this erroneously as the PTT. In fact, this is the pulse arrival time (PAT), which includes not only PTT, but also the time delay between the electrical depolarisation of the heart's left ventricle and the opening of the aortic valve, known as pre-ejection period (PEP). PEP has been suggested to present a significant limitation to BP estimation using PAT. This work investigates the impact of PEP on PAT, leading to a discussion on the best models for BP estimation using PAT or PTT. We conducted a clinical study involving 30 healthy volunteers (53.3% female, 30.9 ± 9.35 years old, with a body mass index of 22.7 ± 3.2 kg/m[Formula: see text]). Each session lasted on average 27.9 ± 0.6 min and BP was varied by an infusion of phenylephrine (a medication that causes venous and arterial vasoconstriction). We introduced new processing steps for the analysis of PAT and PEP signals. Various population-based models (Poon, Gesche and Fung) and a posteriori models (inverse linear, inverse squared and logarithm) for estimation of BP from PTT or PAT were evaluated. Across the cohort, PEP was found to increase by 5.5 ms ± 4.5 ms from its baseline value. Variations in PTT were significantly larger in amplitude, - 16.8 ms ± 7.5 ms. We suggest, therefore, that for infusions of phenylephrine, the contribution of PEP on PAT can be neglected. All population-based models produced large BP estimation errors, suggesting that they are insufficient for modelling the complex pathways relating changes in PTT or PAT to changes in BP. Although PAT is inversely correlated with systolic blood pressure (SBP), the gradient of this relationship varies significantly from individual to individual, from - 2946 to - 470.64 mmHg/s in our dataset. For the a posteriori inverse squared model, the root mean squared errors (RMSE) for systolic and diastolic blood pressure (DBP) estimation from PAT were 5.49 mmHg and 3.82 mmHg, respectively. The RMSEs for SBP and DBP estimation by PTT were 4.51 mmHg and 3.53 mmHg, respectively. These models take into account individual calibration curves required for accurate blood pressure estimation. The best performing population-based model (Poon) reported error values around double that of the a posteriori inverse squared model, and so the use of population-based models is not justified.

Day-to-day progression of vital-sign circadian rhythms in the intensive care unit.

BACKGROUND: Disrupted vital-sign circadian rhythms in the intensive care unit (ICU) are associated with complications such as immune system disruption, delirium and increased patient mortality. However, the prevalence and extent of this disruption is not well understood. Tools for its detection are currently limited. METHODS: This paper evaluated and compared vital-sign circadian rhythms in systolic blood pressure, heart rate, respiratory rate and temperature. Comparisons were made between the cohort of patients who recovered from the ICU and those who did not, across three large, publicly available clinical databases. This comparison included a qualitative assessment of rhythm profiles, as well as quantitative metrics such as peak-nadir excursions and correlation to a demographically matched 'recovered' profile. RESULTS: Circadian rhythms were present at the cohort level in all vital signs throughout an ICU stay. Peak-nadir excursions and correlation to a 'recovered' profile were typically greater throughout an ICU stay in the cohort of patients who recovered, compared to the cohort of patients who did not. CONCLUSIONS: These results suggest that vital-sign circadian rhythms are typically present at the cohort level throughout an ICU stay and that quantitative assessment of these rhythms may provide information of prognostic use in the ICU.

Non-Contact Assessment of Peripheral Artery Haemodynamics Using Infrared Video Thermography.

Skin temperature has long been used as a natural indicator of vascular diseases in the extremities. Considerable correlation between oscillations in skin surface temperature and oscillations of skin blood flow has previously been demonstrated. We hypothesised that the impairment of blood flow in stenotic (subcutaneous) peripheral arteries would influence cutaneous temperature such that, by measuring gradients in the temperature distribution over skin surfaces, one may be able to diagnose or quantify the progression of vascular conditions in whose pathogenesis a reduction in subcutaneous blood perfusion plays a critical role (e.g. peripheral artery disease). As proof of principle, this study investigates the local changes in the skin temperature of healthy humans (15 male, [Formula: see text] years old, BMI [Formula: see text] kg/m 2) undergoing two physical challenges designed to vary their haemodynamic status. Skin temperature was measured in four central regions (forehead, neck, chest, and left shoulder) and four peripheral regions (left upper arm, forearm, wrist, and hand) using an infrared thermal camera. We compare inter-region patterns. Median temperature over the peripheral regions decreased from baseline after both challenges (maximum decrease: [Formula: see text] °C at 60 s after exercise; [Formula: see text] and [Formula: see text] °C at 180 s of cold-water immersion; [Formula: see text]). Median temperature over the central regions showed no significant changes. Our results show that the non-contact measurement of perfusion-related changes in peripheral temperature from infrared video data is feasible. Further research will be directed towards the thermographic study of patients with symptomatic peripheral vascular disease.

Non-contact vital-sign monitoring of patients undergoing haemodialysis treatment.

A clinical study was designed to record a wide range of physiological values from patients undergoing haemodialysis treatment in the Renal Unit of the Churchill Hospital in Oxford. Video was recorded for a total of 84 dialysis sessions from 40 patients during the course of 1 year, comprising an overall video recording time of approximately 304.1 h. Reference values were provided by two devices in regular clinical use. The mean absolute error between the heart rate estimates from the camera and the average from two reference pulse oximeters (positioned at the finger and earlobe) was 2.8 beats/min for over 65% of the time the patient was stable. The mean absolute error between the respiratory rate estimates from the camera and the reference values (computed from the Electrocardiogram and a thoracic expansion sensor-chest belt) was 2.1 breaths/min for over 69% of the time for which the reference signals were valid. To increase the robustness of the algorithms, novel methods were devised for cancelling out aliased frequency components caused by the artificial light sources in the hospital, using auto-regressive modelling and pole cancellation. Maps of the spatial distribution of heart rate and respiratory rate information were developed from the coefficients of the auto-regressive models. Most of the periods for which the camera could not produce a reliable heart rate estimate lasted under 3 min, thus opening the possibility to monitor heart rate continuously in a clinical environment.

[Coronary artery disease in pre and postmenopausal women. The influence of type 2 diabetes mellitus]. / Enfermedad coronaria en mujeres pre y postmenopáusicas y su relación con la diabetes mellitus tipo 2.

BACKGROUND: Postmenopausal women have higher severity of coronary heart disease (CHD) than premenopausal women and type 2 diabetes mellitus (T2DM) is an independent risk factor. AIM: To assess the severity of CHD in pre and postmenopausal patients undergoing coronary angiography and the impact of T2DM in both groups. MATERIAL AND METHODS: A coronary angiography was performed to 707 women due to suspected CHD during 2013 and 2014. Of these, 579 were older than 55 years and were considered as postmenopausal. Factors such as hypertension, obesity, smoking, creatinine and T2DM were registered. The severity of CHD in coronary angiography was evaluated according to the number of vessels with more than 50% stenosis. RESULTS: Compared to their postmenopausal counterparts, premenopausal women had less frequency of T2DM (31% and 42% p < 0.033), hypertension (52 and 78%, p < 0.001) and alteration of renal function (11 vs. 39%, p < 0.001). Absence of coronary lesions was found in 44 and 32% of premenopausal and postmenopausal women, respectively (p < 0.01). Premenopausal women with T2DM had a higher frequency of multi-vessel disease than those without the disease (25 and 4.5%, p < 0.001). The frequency of multi-vessel disease was higher in postmenopausal than premenopausal women (24 and 11%, p < 0.01). Hypertension, T2DM and renal involvement were associated with a higher frequency multiple vessel disease. CONCLUSIONS: The severity of CHD is higher in postmenopausal women and T2DM is associated with the disease.

Study protocol for an exploratory interventional study investigating the feasibility of video-based non-contact physiological monitoring in healthy volunteers by Mapping Of Lower Limb skIn pErfusion (MOLLIE).

INTRODUCTION: Skin perfusion varies in response to changes in the circulatory status. Blood flow to skin is reduced during haemodynamic collapse secondary to peripheral vasoconstriction, whereas increased skin perfusion is frequently observed when haemodynamics improve with resuscitation. These changes in perfusion may be monitored using non-contact image-based methods. Previous camera-derived physiological measurements have focused on accurate vital signs monitoring and extraction of physiological signals from environmental noise. One of the biggest challenges of camera-derived monitoring is artefacts from motion, which limits our understanding of what parameters may be derived from skin. In this study, we use phenylephrine and glyceryl trinitrate (GTN) to cause vasoconstriction and vasodilation in stationary healthy volunteers to describe directional changes in skin perfusion pattern. METHODS AND ANALYSIS: We aim to recruit 30 healthy volunteers who will undergo protocolised infusions of phenylephrine and GTN, followed by the monitored and timed release of a thigh tourniquet. The experimental timeline will be identical for all participants. Measurements of traditionally used haemodynamic markers (heart rate, blood pressure and stroke volume) and camera-derived measurements will be taken concurrently throughout the experimental period. The parameters of interest from the image data are skin colour and pattern, skin surface temperature, pulsatile signal detected at the skin surface and skin perfusion index. ETHICS AND DISSEMINATION: This study was reviewed and approved by the Oxford University Research and Ethics Committee and Clinical Trials and Research Governance teams (R63796/RE001). The results of this study will be presented at scientific conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ISRCTN10417167.

Enfermedad coronaria en mujeres pre y postmenopáusicas y su relación con la diabetes mellitus tipo 2 / Coronary artery disease in pre and postmenopausal women. The influence of type 2 diabetes mellitus

Background: Postmenopausal women have higher severity of coronary heart disease (CHD) than premenopausal women and type 2 diabetes mellitus (T2DM) is an independent risk factor. Aim: To assess the severity of CHD in pre and postmenopausal patients undergoing coronary angiography and the impact of T2DM in both groups. Material and Methods: A coronary angiography was performed to 707 women due to suspected CHD during 2013 and 2014. Of these, 579 were older than 55 years and were considered as postmenopausal. Factors such as hypertension, obesity, smoking, creatinine and T2DM were registered. The severity of CHD in coronary angiography was evaluated according to the number of vessels with more than 50% stenosis. Results: Compared to their postmenopausal counterparts, premenopausal women had less frequency of T2DM (31% and 42% p < 0.033), hypertension (52 and 78%, p < 0.001) and alteration of renal function (11 vs. 39%, p < 0.001). Absence of coronary lesions was found in 44 and 32% of premenopausal and postmenopausal women, respectively (p < 0.01). Premenopausal women with T2DM had a higher frequency of multi-vessel disease than those without the disease (25 and 4.5%, p < 0.001). The frequency of multi-vessel disease was higher in postmenopausal than premenopausal women (24 and 11%, p < 0.01). Hypertension, T2DM and renal involvement were associated with a higher frequency multiple vessel disease. Conclusions: The severity of CHD is higher in postmenopausal women and T2DM is associated with the disease.

Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care Unit.

The implementation of video-based non-contact technologies to monitor the vital signs of preterm infants in the hospital presents several challenges, such as the detection of the presence or the absence of a patient in the video frame, robustness to changes in lighting conditions, automated identification of suitable time periods and regions of interest from which vital signs can be estimated. We carried out a clinical study to evaluate the accuracy and the proportion of time that heart rate and respiratory rate can be estimated from preterm infants using only a video camera in a clinical environment, without interfering with regular patient care. A total of 426.6 h of video and reference vital signs were recorded for 90 sessions from 30 preterm infants in the Neonatal Intensive Care Unit (NICU) of the John Radcliffe Hospital in Oxford. Each preterm infant was recorded under regular ambient light during daytime for up to four consecutive days. We developed multi-task deep learning algorithms to automatically segment skin areas and to estimate vital signs only when the infant was present in the field of view of the video camera and no clinical interventions were undertaken. We propose signal quality assessment algorithms for both heart rate and respiratory rate to discriminate between clinically acceptable and noisy signals. The mean absolute error between the reference and camera-derived heart rates was 2.3 beats/min for over 76% of the time for which the reference and camera data were valid. The mean absolute error between the reference and camera-derived respiratory rate was 3.5 breaths/min for over 82% of the time. Accurate estimates of heart rate and respiratory rate could be derived for at least 90% of the time, if gaps of up to 30 seconds with no estimates were allowed.

Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.

Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO2), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospital ward, the main challenges in the development of continuous and robust non-contact monitoring techniques are the identification of time periods and the segmentation of skin regions of interest (ROIs) from which vital signs can be estimated. We propose a deep learning framework to tackle these challenges. APPROACH: This paper presents two convolutional neural network (CNN) models. The first network was designed for detecting the presence of a patient and segmenting the patient's skin area. The second network combined the output from the first network with optical flow for identifying time periods of clinical intervention so that these periods can be excluded from the estimation of vital signs. Both networks were trained using video recordings from a clinical study involving 15 pre-term infants conducted in the high dependency area of the neonatal intensive care unit (NICU) of the John Radcliffe Hospital in Oxford, UK. MAIN RESULTS: Our proposed methods achieved an accuracy of 98.8% for patient detection, a mean intersection-over-union (IOU) score of 88.6% for skin segmentation and an accuracy of 94.5% for clinical intervention detection using two-fold cross validation. Our deep learning models produced accurate results and were robust to different skin tones, changes in light conditions, pose variations and different clinical interventions by medical staff and family visitors. SIGNIFICANCE: Our approach allows cardio-respiratory signals to be continuously derived from the patient's skin during which the patient is present and no clinical intervention is undertaken.

Assessment of Signal Processing Methods for Measuring the Respiratory Rate in the Neonatal Intensive Care Unit.

Knowledge of the pathological instabilities in the breathing pattern can provide valuable insights into the cardiorespiratory status of the critically-ill infant as well as their maturation level. This paper is concerned with the measurement of respiratory rate in premature infants. We compare the rates estimated from the chest impedance pneumogram, the ECG-derived respiratory rhythms, and the PPG-derived respiratory rhythms against those measured in the reference standard of breath detection provided by attending clinical staff during 165 manual breath counts. We demonstrate that accurate RR estimates can be produced from all sources for RR in the 40-80 bpm (breaths per min) range. We also conclude that the use of indirect methods based on the ECG or the PPG poses a fundamental challenge in this population due to their poor behavior at fast breathing rates (upward of 80 bpm).