Using a graph-based image segmentation algorithm for remote vital sign estimation and monitoring.

Reliable and contactless measurements of vital signs, such as respiration and heart rate, are still unmet needs in clinical and home settings. Mm-wave radar and video-based technologies are promising, but currently, the signal processing-based vital sign extraction methods are prone to body motion disruptions or illumination variations in the surrounding environment. Here we propose an image segmentation-based method to extract vital signs from the recorded video and mm-wave radar signals. The proposed method analyses time-frequency spectrograms obtained from Short-Time Fourier Transform rather than individual time-domain signals. This leads to much-improved robustness and accuracy of the heart rate and respiration rate extraction over existing methods. The experiments were conducted under pre- and post-exercise conditions and were repeated on multiple individuals. The results are evaluated by using four metrics against the gold standard contact-based measurements. Significant improvements were observed in terms of precision, accuracy, and stability. The performance was reflected by achieving an averaged Pearson correlation coefficient (PCC) of 93.8% on multiple subjects. We believe that the proposed estimation method will help address the needs for the increasingly popular remote cardiovascular sensing and diagnosing posed by Covid-19.

Multi-ROI Spectral Approach for the Continuous Remote Cardio-Respiratory Monitoring from Mobile Device Built-In Cameras.

Heart rate (HR) and respiratory rate (fR) can be estimated by processing videos framing the upper body and face regions without any physical contact with the subject. This paper proposed a technique for continuously monitoring HR and fR via a multi-ROI approach based on the spectral analysis of RGB video frames recorded with a mobile device (i.e., a smartphone's camera). The respiratory signal was estimated by the motion of the chest, whereas the cardiac signal was retrieved from the pulsatile activity at the level of right and left cheeks and forehead. Videos were recorded from 18 healthy volunteers in four sessions with different user-camera distances (i.e., 0.5 m and 1.0 m) and illumination conditions (i.e., natural and artificial light). For HR estimation, three approaches were investigated based on single or multi-ROI approaches. A commercially available multiparametric device was used to record reference respiratory signals and electrocardiogram (ECG). The results demonstrated that the multi-ROI approach outperforms the single-ROI approach providing temporal trends of both the vital parameters comparable to those provided by the reference, with a mean absolute error (MAE) consistently below 1 breaths·min-1 for fR in all the scenarios, and a MAE between 0.7 bpm and 6 bpm for HR estimation, whose values increase at higher distances.

A proposed lung ultrasound and phenotypic algorithm for the care of COVID-19 patients with acute respiratory failure.

Pulmonary complications are the most common clinical manifestations of coronavirus disease (COVID-19). From recent clinical observation, two phenotypes have emerged: a low elastance or L-type and a high elastance or H-type. Clinical presentation, pathophysiology, pulmonary mechanics, radiological and ultrasound findings of these two phenotypes are different. Consequently, the therapeutic approach also varies between the two. We propose a management algorithm that combines the respiratory rate and oxygenation index with bedside lung ultrasound examination and monitoring that could help determine earlier the requirement for intubation and other surveillance of COVID-19 patients with respiratory failure.

RéSUMé: Les complications pulmonaires du coronavirus (COVID-19) constituent ses manifestations cliniques les plus fréquentes. De récentes observations cliniques ont fait émerger deux phénotypes : le phénotype à élastance faible ou type L (low), et le phénotype à élastance élevée, ou type H (high). La présentation clinique, la physiopathologie, les mécanismes pulmonaires, ainsi que les observations radiologiques et échographiques de ces deux différents phénotypes sont différents. L'approche thérapeutique variera par conséquent selon le phénotype des patients atteints de COVID-19 souffrant d'insuffisance respiratoire.

The association of admission random blood glucose concentration and body-mass index with mortality in COVID-19 patients.

OBJECTIVE: This study aimed to investigate the association between hyperglycemia and body mass index (BMI), along with other associated comorbidities in hospitalized COVID-19 patients among the Indonesian population. PATIENTS AND METHODS: This was a retrospective study conducted at Hasan Sadikin Hospital, Bandung between March 1, 2020, and August 30, 2020. Data were analyzed using the chi-square test for categorical data and unpaired t-test and Mann-Whitney alternative test for numerical data using SPSS version 24.0 (IBM SPSS Statistics for Windows, Version 24.0. IBM, Armonk, NY, USA) and GraphPad Prism version 7.0 for Windows. RESULTS: A total of 142 hospitalized COVID-19 patients were documented between March and August 2020 at the Hasan Sadikin Hospital. Among the 142 patients, 116 (81.7%) survived, while 26 (18.3%) died. Sex, age, BMI, number of comorbidities, heart rate, respiratory rate, peripheral oxygen saturation, platelet count, random blood glucose (RBG), and length of stay (LOS) were significantly associated with mortality. Multivariate analyses demonstrated that admission RBG levels > 140 mg/dl were independently associated with an increased risk of mortality in COVID-19 patients (OR 4.3, 95% CI 1.1-17.5, p = 0.043), while BMI > 25 kg/m2 was significantly associated with reduced mortality (OR, 0.22; 95% CI 0.05-0.88, p = 0.033). CONCLUSIONS: Admission hyperglycemia, indicated by an increase in RBG levels >140 mg/dL, is independently associated with an increased risk of mortality in hospitalized COVID-19 patients, while obesity (BMI >25 kg/m2) might have protective properties against the risk of death.

Bedside clinical data subphenotypes of critically ill COVID-19 patients: a cohort study. / Subfenótipos baseados em dados clínicos de beira-leito de pacientes críticos com COVID-19: um estudo de coorte.

OBJECTIVE: To identify more severe COVID-19 presentations. METHODS: Consecutive intensive care unit-admitted patients were subjected to a stepwise clustering method. RESULTS: Data from 147 patients who were on average 56 ± 16 years old with a Simplified Acute Physiological Score 3 of 72 ± 18, of which 103 (70%) needed mechanical ventilation and 46 (31%) died in the intensive care unit, were analyzed. From the clustering algorithm, two well-defined groups were found based on maximal heart rate [Cluster A: 104 (95%CI 99 - 109) beats per minute versus Cluster B: 159 (95%CI 155 - 163) beats per minute], maximal respiratory rate [Cluster A: 33 (95%CI 31 - 35) breaths per minute versus Cluster B: 50 (95%CI 47 - 53) breaths per minute], and maximal body temperature [Cluster A: 37.4 (95%CI 37.1 - 37.7)°C versus Cluster B: 39.3 (95%CI 39.1 - 39.5)°C] during the intensive care unit stay, as well as the oxygen partial pressure in the blood over the oxygen inspiratory fraction at intensive care unit admission [Cluster A: 116 (95%CI 99 - 133) mmHg versus Cluster B: 78 (95%CI 63 - 93) mmHg]. Subphenotypes were distinct in inflammation profiles, organ dysfunction, organ support, intensive care unit length of stay, and intensive care unit mortality (with a ratio of 4.2 between the groups). CONCLUSION: Our findings, based on common clinical data, revealed two distinct subphenotypes with different disease courses. These results could help health professionals allocate resources and select patients for testing novel therapies.

OBJETIVO: Identificar apresentações mais graves de COVID-19. MÉTODOS: Pacientes consecutivamente admitidos à unidade de terapia intensiva foram submetidos à análise de clusters por meio de método de explorações sequenciais. RESULTADOS: Analisamos os dados de 147 pacientes, com média de idade de 56 ± 16 anos e Simplified Acute Physiological Score 3 de 72 ± 18, dos quais 103 (70%) demandaram ventilação mecânica e 46 (31%) morreram na unidade de terapia intensiva. A partir do algoritmo de análise de clusters, identificaram-se dois grupos bem definidos, com base na frequência cardíaca máxima [Grupo A: 104 (IC95% 99 - 109) batimentos por minuto versus Grupo B: 159 (IC95% 155 - 163) batimentos por minuto], frequência respiratória máxima [Grupo A: 33 (IC95% 31 - 35) respirações por minuto versus Grupo B: 50 (IC95% 47 - 53) respirações por minuto] e na temperatura corpórea máxima [Grupo A: 37,4 (IC95% 37,1 - 37,7)ºC versus Grupo B: 39,3 (IC95% 39,1 - 39,5)ºC] durante o tempo de permanência na unidade de terapia intensiva, assim como a proporção entre a pressão parcial de oxigênio no sangue e a fração inspirada de oxigênio quando da admissão à unidade de terapia intensiva [Grupo A: 116 (IC95% 99 - 133) mmHg versus Grupo B: 78 (IC95% 63 - 93) mmHg]. Os subfenótipos foram distintos em termos de perfis inflamatórios, disfunções orgânicas, terapias de suporte, tempo de permanência na unidade de terapia intensiva e mortalidade na unidade de terapia intensiva (com proporção de 4,2 entre os grupos). CONCLUSÃO: Nossos achados, baseados em dados clínicos universalmente disponíveis, revelaram dois subfenótipos distintos, com diferentes evoluções de doença. Estes resultados podem ajudar os profissionais de saúde na alocação de recursos e seleção de pacientes para teste de novas terapias.

COVID-19 Pneumonia and ROX index: Time to set a new threshold for patients admitted outside the ICU.

High flow nasal cannula (HFNC) is used to treat acute hypoxemic respiratory failure (AHRF) even outside the ICU and the ROX index (pulse oximetry/fraction of inspired oxygen/respiratory rate) may predict HFNC failure. OBJECTIVE: The purpose of this investigation was therefore to verify whether the ROX index is an accurate predictor of HFNC failure for COVID-19 patients treated outside the intensive care unit (ICU) and to evaluate the validity of the previously suggested threshold. DESIGN: Multicenter study. Retrospective observational analysis of prospectively collected data. SETTING: 3 centres specialized in non-invasive respiratory support (Buenos Aires, Argentina; Bolzano and Treviso, Italy). Patients treated outside the ICU were analysed MEASUREMENTS: The variables to calculate the ROX index were collected during the first day of therapy at 2, 6, 12 and 24 hours and then recorded every 24 hours. HFNC failure was defined as escalation of respiratory support to invasive mechanical ventilation (IMV) or death. MAIN RESULTS: A total of 35 (29%) patients failed HFNC and required intubation. ROC analysis identified the 12-hour ROX index as the best predictor of intubation with an AUC of 0.7916[CI 95% 0.6905-0.8927] and the best threshold to be 5.99[Specificity 96% Sensitivity 62%]. In the survival analysis, a ROX value <5.99 was associated with an increased risk of failure (p = 0008 log - rank test). The threshold of 4,9 identified by Roca as the best predictor in non-COVID patients, was not able to discriminate between success and failure (p = 0.4 log-rank test) in our patients. CONCLUSIONS: ROX index may be useful in guiding the clinicians in their decision to intubate patients, especially in patients with moderate ARF, treated therefore outside the ICU. Indeed, it also demonstrates a different threshold value than reported for non-COVID patients, possibly related to the different mechanisms of hypoxia.

Delta-range coupling between prefrontal cortex and hippocampus supported by respiratory rhythmic input from the olfactory bulb in freely behaving rats.

Respiratory rhythm (RR) during sniffing is known to couple with hippocampal theta rhythm. However, outside of the short sniffing bouts, a more stable ~ 2 Hz RR was recently shown to rhythmically modulate non-olfactory cognitive processes, as well. The underlying RR coupling with wide-spread forebrain activity was confirmed using advanced techniques, creating solid premise for investigating how higher networks use this mechanism in their communication. Here we show essential differences in the way prefrontal cortex (PFC) and hippocampus (HC) process the RR signal from the olfactory bulb (OB) that may support dynamic, flexible PFC-HC coupling utilizing this input. We used inter-regional coherences and their correlations in rats, breathing at low rate (~ 2 Hz), outside of the short sniffing bouts. We found strong and stable OB-PFC coherence in wake states, contrasting OB-HC coherence which was low but highly variable. Importantly, this variability was essential for establishing PFC-HC synchrony at RR, whereas variations of RRO in OB and PFC had no significant effect. The findings help to understand the mechanism of rhythmic modulation of non-olfactory cognitive processes by the on-going regular respiration, reported in rodents as well as humans. These mechanisms may be impaired when nasal breathing is limited or in OB-pathology, including malfunctions of the olfactory epithelium due to infections, such as in Covid-19.

Case Reports of Implantable Cardiac Device Physiologic Sensor Changes in Subjects with Coronavirus Disease-2019 Infection.

The severe acute respiratory syndrome novel coronavirus-2 pandemic has established a new set of challenges to health care delivery. Remotely monitored physiologic sensors on implantable cardiac devices can provide insight into the differential diagnosis of dyspnea in the heart failure population. We report on a unique pattern of sensor deviations that seem to occur specifically with severe acute respiratory syndrome novel coronavirus-2 infection.

Rise in nocturnal respiratory rate during CPAP may be an early sign of COVID-19 in patients with obstructive sleep apnea.

None: A middle-aged man with obstructive sleep apnea who had been treated with continuous positive airway pressure developed COVID-19. An analysis of airflow records from the continuous positive airway pressure machine revealed a rise in his respiratory rate on the night before the onset of COVID-19-related symptoms, while his nocturnal respiratory rate had been stable during the 18-month period prior to the presently reported episode. The present case suggests that a rise in respiratory rate detected using continuous positive airway pressure machine data could be an important sign of impending acute illness, such as COVID-19. Studies to elucidate the usefulness of this method are warranted.

Emergency ventilator for COVID-19.

The COVID-19 pandemic disrupted the world in 2020 by spreading at unprecedented rates and causing tens of thousands of fatalities within a few months. The number of deaths dramatically increased in regions where the number of patients in need of hospital care exceeded the availability of care. Many COVID-19 patients experience Acute Respiratory Distress Syndrome (ARDS), a condition that can be treated with mechanical ventilation. In response to the need for mechanical ventilators, designed and tested an emergency ventilator (EV) that can control a patient's peak inspiratory pressure (PIP) and breathing rate, while keeping a positive end expiratory pressure (PEEP). This article describes the rapid design, prototyping, and testing of the EV. The development process was enabled by rapid design iterations using additive manufacturing (AM). In the initial design phase, iterations between design, AM, and testing enabled a working prototype within one week. The designs of the 16 different components of the ventilator were locked by additively manufacturing and testing a total of 283 parts having parametrically varied dimensions. In the second stage, AM was used to produce 75 functional prototypes to support engineering evaluation and animal testing. The devices were tested over more than two million cycles. We also developed an electronic monitoring system and with automatic alarm to provide for safe operation, along with training materials and user guides. The final designs are available online under a free license. The designs have been transferred to more than 70 organizations in 15 countries. This project demonstrates the potential for ultra-fast product design, engineering, and testing of medical devices needed for COVID-19 emergency response.

The value of high-flow nasal cannula oxygen therapy in treating novel coronavirus pneumonia.

OBJECTIVE: This study aimed to investigate the value of high-flow nasal cannula (HNFC) oxygen therapy in treating patients with severe novel coronavirus pneumonia (COVID-19). METHODS: The clinical data of 22 patients with severe COVID-19 were collected. The heart rate (HR), respiratory rate (RR) and oxygenation index (PO2 /FiO2 ) at 0, 6, 24 and 72 hours after treatment were compared between the HFNC oxygen therapy group and the conventional oxygen therapy (COT) group. In addition, the white blood cell (WBC) count, lymphocyte (L) count, C-reactive protein (CRP) and procalcitonin (PCT) were compared before and at 72 hours after oxygen therapy treatment. RESULTS: The differences at 0 hours between the two groups were not statistically significant. Compared with COT group,in the HFNC oxygen therapy group, HR, RR and PaO2 /FiO2 were better at 6 hours after treatment, PaO2 /FiO2 was better at 24 and 72 hours. After 72 hours, L and CRP had improved in the HFNC oxygen therapy group compared with the COT group, but the differences in WBC and PCT were not statistically significant. The length of stay in the intensive care unit (ICU) and the total length of hospitalization was shorter in the HFNC oxygen therapy group than in the COT group. CONCLUSION: Compared with COT, early application of HFNC oxygen therapy in patients with severe COVID-19 can improve oxygenation and RR, and HFNC oxygen therapy can improve the infection indexes of patients and reduce the length of stay in the ICU of patients. Therefore, it has high clinical application value.

A lung for all: Novel mechanical ventilator for emergency and low-resource settings.

AIMS: To create a low-cost ventilator that could be constructed with readily-available hospital equipment for use in emergency or low-resource settings. MAIN METHODS: The novel ventilator consists of an inspiratory limb composed of an elastic flow-inflating bag encased within a non-compliant outer sheath and an expiratory limb composed of a series of two, one-way bidirectional splitter valves derived from a self-inflating bag system. An Arduino Uno microcontroller controls a solenoid valve that can be programmed to open and close to produce a set respiratory rate and inspiratory time. Using an ASL 5000 Lung Simulator, we obtained flow, pressure, and volume waveforms at different lung compliances. KEY FINDINGS: At a static lung compliance of 50 mL/cm H2O and an airway resistance of 6 cm H2O/L/s, ventilated at a PIP and PEEP of 16 and 5 cm H2O, respectively, tidal volumes of approximately 540 mL were achieved. At a static lung compliance of 20 mL/cm H2O and an airway resistance of 6 cm H2O/L/s, ventilated at a PIP and PEEP of 38 and 15 cm H2O, respectively, tidal volumes of approximately 495 mL were achieved. SIGNIFICANCE: This novel ventilator is able to safely and reliably ventilate patients with a range of pulmonary disease in a simulated setting. Opportunities exist to utilize our ventilator in emergency situations and low-resource settings.

Increasing ventilator surge capacity in COVID 19 pandemic: design, manufacture and in vitro-in vivo testing in anaesthetized healthy pigs of a rapid prototyped mechanical ventilator.

OBJECTIVE: The advent of new technologies has made it possible to explore alternative ventilator manufacturing to meet the worldwide shortfall for mechanical ventilators especially in pandemics. We describe a method using rapid prototyping technologies to create an electro-mechanical ventilator in a cost effective, timely manner and provide results of testing using an in vitro-in vivo testing model. RESULTS: Rapid prototyping technologies (3D printing and 2D cutting) were used to create a modular ventilator. The artificial manual breathing unit (AMBU) bag connected to wall oxygen source using a flow meter was used as air reservoir. Controlled variables include respiratory rate, tidal volume and inspiratory: expiratory (I:E) ratio. In vitro testing and In vivo testing in the pig model demonstrated comparable mechanical efficiency of the test ventilator to that of standard ventilator but showed the material limits of 3D printed gears. Improved gear design resulted in better ventilator durability whilst reducing manufacturing time (< 2-h). The entire cost of manufacture of ventilator was estimated at 300 Australian dollars. A cost-effective novel rapid prototyped ventilator for use in patients with respiratory failure was developed in < 2-h and was effective in anesthetized, healthy pig model.

Inspiratory effort and breathing pattern change in response to varying the assist level: A physiological study.

AIM: To describe the response of breathing pattern and inspiratory effort upon changes in assist level and to assesss if changes in respiratory rate may indicate changes in respiratory muscle effort. METHODS: Prospective study of 82 patients ventilated on proportional assist ventilation (PAV+). At three levels of assist (20 %-50 %-80 %), patients' inspiratory effort and breathing pattern were evaluated using a validated prototype monitor. RESULTS: Independent of the assist level, a wide range of respiratory rates (16-35br/min) was observed when patients' effort was within the accepted range. Changing the assist level resulted in paired changes in inspiratory effort and rate of the same tendency (increase or decrease) in all but four patients. Increasing the level in assist resulted in a 31 % (8-44 %) decrease in inspiratory effort and a 10 % (0-18 %) decrease in respiratory rate. The change in respiratory rate upon the change in assist correlated modestly with the change in the effort (R = 0.5). CONCLUSION: Changing assist level results in changes in both respiratory rate and effort in the same direction, with change in effort being greater than that of respiratory rate. Yet, neither the magnitude of respiratory rate change nor the resulting absolute value may reliably predict the level of effort after a change in assist.

Innovative Use of High-Fidelity Lung Simulators to Test a Ventilator Splitter Device.

The coronavirus disease 2019 (COVID-19) pandemic has rapidly exposed health care system inadequacies. Hospital ventilator shortages in Italy compelled US physicians to consider creative solutions, such as using Y-pieces or T-pieces, to preclude the need to make decisions of life or death based on medical equipment availability. We add to current knowledge and testing capacity for ventilator splitters by reporting the ability to examine the functionality of ventilator splitters by using 2 high-fidelity lung simulators. Data obtained by the high-fidelity lung simulators included: tidal volume, respiratory rate, minute ventilation, peak inspiratory pressure, peak plateau pressure, and positive end-expiratory pressure.