Accuracy of Smartphone-Based Pulse Oximetry Compared with Hospital-Grade Pulse Oximetry in Healthy Children

Telemonitoring of pediatric asthma in outpatient settings: A systematic review

Telemonitoring technologies are rapidly evolving, offering a promising solution for remote monitoring and timely management of asthma acute episodes. We aimed to describe current pediatric asthma telemonitoring technologies. A systematic review was conducted until September 2023 on Medline, Scopus, and Web of Science. We included studies of children (0-18 years) with asthma or recurrent wheezing whose respiratory condition was telemonitored outside the healthcare setting. A narrative synthesis was performed. We identified 40 telemonitoring technologies described in 40 studies. The more frequently used technologies for telemonitoring were mobile applications (n = 21) and web-based systems (n = 14). Telemonitoring duration varied between 2 weeks and 32 months. Data collection included asthma symptoms (n = 30), patient-reported outcome measures (PROMs) (n = 11), spirometry/peak flow readings (n = 20), medication adherence (n = 17), inhaler technique (n = 3), air quality (n = 2), and respiratory sounds (n = 2). Both parents and children were the technology target users in most studies (n = 23). Technology training was reported in 23 studies of which 3 provided ongoing support. Automatic feedback was found in 30 studies, mostly related with asthma control. HCP were involved in data management in 27 studies. Technologies were tested in samples from 4 to 327 children, with most studies including school-aged children and/or adolescents (n = 38) and eight including preschool children. This review provides an overview of existing technologies for the outpatient telemonitoring of pediatric asthma. Specific technologies for preschool children represent a gap in the literature that needs to be specifically addressed in future research.

Wireless monitoring devices in hospitalized children: a scoping review

The purpose of this study is to provide a structured overview of existing wireless monitoring technologies for hospitalized children. A systematic search of the literature published after 2010 was conducted in Medline, Embase, Scielo, Cochrane, and Web of Science. Two investigators independently reviewed articles to determine eligibility for inclusion. Information on study type, hospital setting, number of participants, use of a reference sensor, type and number of vital signs monitored, duration of monitoring, type of wireless information transfer, and outcomes of the wireless devices was extracted. A descriptive analysis was applied. Of the 1130 studies identified from our search, 42 met eligibility for subsequent analysis. Most included studies were observational studies with sample sizes of 50 or less published between 2019 and 2022. Common problems pertaining to study methodology and outcomes observed were short duration of monitoring, single focus on validity, and lack information on wireless transfer and data management.  Conclusion: Research on the use of wireless monitoring for children in hospitals has been increasing in recent years but often limited by methodological problems. More rigorous studies are necessary to establish the safety and accuracy of novel wireless monitoring devices in hospitalized children. What is Known: • Continuous monitoring of vital signs using wired sensors is the standard of care for hospitalized pediatric patients. However, the use of wires may pose significant challenges to optimal care. What is New: • Interest in wireless monitoring for hospitalized pediatric patients has been rapidly growing in recent years. • However, most devices are in early stages of clinical testing and are limited by inconsistent clinical and technological reporting.

Smartphone camera oximetry in an induced hypoxemia study

Hypoxemia, a medical condition that occurs when the blood is not carrying enough oxygen to adequately supply the tissues, is a leading indicator for dangerous complications of respiratory diseases like asthma, COPD, and COVID-19. While purpose-built pulse oximeters can provide accurate blood-oxygen saturation (SpO₂) readings that allow for diagnosis of hypoxemia, enabling this capability in unmodified smartphone cameras via a software update could give more people access to important information about their health. Towards this goal, we performed the first clinical development validation on a smartphone camera-based SpO₂ sensing system using a varied fraction of inspired oxygen (FiO₂) protocol, creating a clinically relevant validation dataset for solely smartphone-based contact PPG methods on a wider range of SpO₂ values (70–100%) than prior studies (85–100%). We built a deep learning model using this data to demonstrate an overall MAE = 5.00% SpO₂ while identifying positive cases of low SpO₂ < 90% with 81% sensitivity and 79% specificity. We also provide the data in open-source format, so that others may build on this work.

Detection and Monitoring of Viral Infections via Wearable Devices and Biometric Data

Mounting clinical evidence suggests that viral infections can lead to detectable changes in an individual's normal physiologic and behavioral metrics, including heart and respiration rates, heart rate variability, temperature, activity, and sleep prior to symptom onset, potentially even in asymptomatic individuals. While the ability of wearable devices to detect viral infections in a real-world setting has yet to be proven, multiple recent studies have established that individual, continuous data from a range of biometric monitoring technologies can be easily acquired and that through the use of machine learning techniques, physiological signals and warning signs can be identified. In this review, we highlight the existing knowledge base supporting the potential for widespread implementation of biometric data to address existing gaps in the diagnosis and treatment of viral illnesses, with a particular focus on the many important lessons learned from the coronavirus disease 2019 pandemic.

Prevalence, Presentation and Outcomes of Silent Hypoxemia in COVID-19

Dyspnea is reported in a minority of patients affected by coronavirus disease 2019 (COVID-19). Even patients with pneumonia can present hypoxemia without any respiratory distress, a phenomenon known as “silent” or “happy hypoxemia”. During the current pandemic there were only a few studies conducted on this subject and these were quite heterogeneous. Therefore, the prevalence of “silent hypoxemia” varied substantially. While studies did not show a clear tendency of “silent hypoxemia” to poorer outcomes compared to hypoxemia presenting with dyspnea, several showed that patients with “silent hypoxemia” are not protected from poor outcomes either. There is a need for a uniform definition of “silent hypoxemia”, in order to better guide clinicians and investigators. More studies are needed to shed light on the mechanisms of “silent hypoxemia”, as well as its presentation and influence in the disease's progression and outcomes, so as to better assist physicians in the care of COVID-19 patients.

Telemedicine in Cardiology: Modern Technologies to Improve Cardiovascular Patients’ Outcomes—A Narrative Review

The registration of physical signals has long been an important part of cardiological diagnostics. Current technology makes it possible to send large amounts of data to remote locations. Solutions that enable diagnosis and treatment without direct contact with patients are of enormous value, especially during the COVID-19 outbreak, as the elderly require special protection. The most important examples of telemonitoring in cardiology include the use of implanted devices such as pacemakers and defibrillators, as well as wearable sensors and data processing units. The arrythmia detection and monitoring patients with heart failure are the best studied in the clinical setting, although in many instances we still lack clear evidence of benefits of remote approaches vs. standard care. Monitoring for ischemia is less well studied. It is clear however that the economic and organizational gains of telemonitoring for healthcare systems are substantial. Both patients and healthcare professionals have expressed an enormous demand for the further development of such technologies. In addition to these subjects, in this paper we also describe the safety concerns associated with transmitting and storing potentially sensitive personal data.

Evaluating the robustness of a contact-less mHealth solution for personal and remote monitoring of blood oxygen saturation

MHealth technologies play a fundamental role in epidemiological situations such as the ongoing outbreak of COVID-19 because they allow people to self-monitor their health status (e.g. vital parameters) at any time and place, without necessarily having to physically go to a medical clinic. Among vital parameters, special care should be given to monitor blood oxygen saturation (SpO2), whose abnormal values are a warning sign for potential COVID-19 infection. SpO2 is commonly measured through the pulse oximeter that requires skin contact and hence could be a potential way of spreading contagious infections. To overcome this problem, we have recently developed a contact-less mHealth solution that can measure blood oxygen saturation without any contact device but simply processing short facial videos acquired by any common mobile device equipped with a camera. Facial video frames are processed in real-time to extract the remote photoplethysmographic signal useful to estimate the SpO2 value. Such a solution promises to be an easy-to-use tool for both personal and remote monitoring of SpO2. However, the use of mobile devices in daily situations holds some challenges in comparison to the controlled laboratory scenarios. One main issue is the frequent change of perspective viewpoint due to head movements, which makes it more difficult to identify the face and measure SpO2. The focus of this work is to assess the robustness of our mHealth solution to head movements. To this aim, we carry out a pilot study on the benchmark PURE dataset that takes into account different head movements during the measurement. Experimental results show that the SpO2 values obtained by our solution are not only reliable, since they are comparable with those obtained with a pulse oximeter, but are also insensitive to head motion, thus allowing a natural interaction with the mobile acquisition device.

Reliability of Smartphone Applications for the Quantification of Oxygen Saturation

Background

Smartphone technology is rapidly evolving and advancing, with many of them offering health applications being used for oximetry purposes, including the Samsung Health/S Health application. Measuring oxygen saturation is one of the important indications to monitor patients with COVID-19, as well as other health conditions. These applications can be used for measuring oxygen saturation to provide a convenient solution for clinical decisions.

Methods

Oxygen saturation measurements were collected using the Samsung Health application for Samsung Galaxy smartphone with a sensor and camera flash and a low-cost portable digital display (liquid crystal display (LCD)) finger pulse oximeter. Intra-session reliability was established to determine the consistency between the measures. Intra-class correlation coefficients (ICCs) were calculated with 95% confidence intervals (CIs) reported for both methods. The Bland-Altman plot was used to compare the level of agreement between the two measurement methods.

Results

There was a statistically significant average difference between pulse oximeter and Samsung Health application measurements (t₁₂₅ = 4.407, p < 0.001), and on average, pulse oximeter measurement was 0.510 points higher than Samsung Health application measurement (95% CI = 0.281-0.740). The pulse oximeter and Samsung Health application scores were moderately correlated (r = 0.462). The results of the intra-session reliability test produced an acceptable ICC value of 0.557, indicating moderate reliability and consistent results for the measurement of oxygen saturation with both methods. The Bland-Altman plot showed a consistently equal distribution of data points scattered above and below zero.

Conclusion

Smartphone health applications can be used with moderate reliability to measure oxygen saturation.

Comparison of SpO2 and heart rate values on Apple Watch and conventional commercial oximeters devices in patients with lung disease

Lung diseases have high mortality and morbidity, with an important impact on quality of life. Hypoxemic patients are advised to use oxygen therapy to prolong their survival, but high oxygen saturation (SpO2) levels can also have negative effects. Pulse oximeters are the most common way to assess oxygen levels and guide medical treatment. This study aims to assess whether wearable devices can provide precise SpO2 measurements when compared to commercial pulse oximeters. This is a cross-section study with 100 patients with chronic obstructive pulmonary disease and interstitial lung disease from an outpatient pneumology clinic. SpO2 and heart rate data were collected with an Apple Watch Series 6 (Apple) and compared to two commercial pulse oximeters. The Bland-Altman method and interclass correlation coefficient were used to compare their values. We observed strong positive correlations between the Apple Watch device and commercial oximeters when evaluating heart rate measurements (r = 0.995, p < 0.001) and oximetry measurements (r = 0.81, p < 0.001). There was no statistical difference in the evaluation of skin color, wrist circumference, presence of wrist hair, and enamel nail for SpO2 and heart rate measurements in Apple Watch or commercial oximeter devices (p > 0.05). Apple Watch 6 is a reliable way to obtain heart rate and SpO2 in patients with lung diseases in a controlled environment.

Machine Learning Prediction for Supplemental Oxygen Requirement in Patients with COVID-19

BACKGROUND

The coronavirus disease (COVID-19) poses an urgent threat to global public health and is characterized by rapid disease progression even in mild cases. In this study, we investigated whether machine learning can be used to predict which patients will have a deteriorated condition and require oxygenation in asymptomatic or mild cases of COVID-19.

METHODS

This single-center, retrospective, observational study included COVID-19 patients admitted to the hospital from February 1, 2020, to May 31, 2020, and who were either asymptomatic or presented with mild symptoms and did not require oxygen support on admission. Data on patient characteristics and vital signs were collected upon admission. We used seven machine learning algorithms, assessed their capability to predict exacerbation, and analyzed important influencing features using the best algorithm.

RESULTS

In total, 210 patients were included in the study. Among them, 43 (19%) required oxygen therapy. Of all the models, the logistic regression model had the highest accuracy and precision. Logistic regression analysis showed that the model had an accuracy of 0.900, precision of 0.893, and recall of 0.605. The most important parameter for predictive capability was SpO₂, followed by age, respiratory rate, and systolic blood pressure.

CONCLUSION

In this study, we developed a machine learning model that can be used as a triage tool by clinicians to detect high-risk patients and disease progression earlier. Prospective validation studies are needed to verify the application of the tool in clinical practice.

Ambulatory monitoring promises equitable personalized healthcare delivery in underrepresented patients

The pandemic has brought to everybody's attention the apparent need of remote monitoring, highlighting hitherto unseen challenges in healthcare. Today, mobile monitoring and real-time data collection, processing and decision-making, can drastically improve the cardiorespiratory-haemodynamic health diagnosis and care, not only in the rural communities, but urban ones with limited healthcare access as well. Disparities in socioeconomic status and geographic variances resulting in regional inequity in access to healthcare delivery, and significant differences in mortality rates between rural and urban communities have been a growing concern. Evolution of wireless devices and smartphones has initiated a new era in medicine. Mobile health technologies have a promising role in equitable delivery of personalized medicine and are becoming essential components in the delivery of healthcare to patients with limited access to in-hospital services. Yet, the utility of portable health monitoring devices has been suboptimal due to the lack of user-friendly and computationally efficient physiological data collection and analysis platforms. We present a comprehensive review of the current cardiac, pulmonary, and haemodynamic telemonitoring technologies. We also propose a novel low-cost smartphone-based system capable of providing complete cardiorespiratory assessment using a single platform for arrhythmia prediction along with detection of underlying ischaemia and sleep apnoea; we believe this system holds significant potential in aiding the diagnosis and treatment of cardiorespiratory diseases, particularly in underserved populations.

An analysis of clinical predictive values for radiographic pneumonia in children

Introduction

Healthcare providers in resource-limited settings rely on the presence of tachypnoea and chest indrawing to establish a diagnosis of pneumonia in children. We aimed to determine the test characteristics of commonly assessed signs and symptoms for the radiographic diagnosis of pneumonia in children 0–59 months of age.

Methods

We conducted an analysis using patient-level pooled data from 41 shared datasets of paediatric pneumonia. We included hospital-based studies in which >80% of children had chest radiography performed. Primary endpoint pneumonia (presence of dense opacity occupying a portion or entire lobe of the lung or presence of pleural effusion on chest radiograph) was used as the reference criterion radiographic standard. We assessed the sensitivity, specificity, and likelihood ratios for clinical findings, and combinations of findings, for the diagnosis of primary endpoint pneumonia among children 0–59 months of age.

Results

Ten studies met inclusion criteria comprising 15 029 children; 24.9% (n=3743) had radiographic pneumonia. The presence of age-based tachypnoea demonstrated a sensitivity of 0.92 and a specificity of 0.22 while lower chest indrawing revealed a sensitivity of 0.74 and specificity of 0.15 for the diagnosis of radiographic pneumonia. The sensitivity and specificity for oxygen saturation <90% was 0.40 and 0.67, respectively, and was 0.17 and 0.88 for oxygen saturation <85%. Specificity was improved when individual clinical factors such as tachypnoea, fever and hypoxaemia were combined, however, the sensitivity was lower.

Conclusions

No single sign or symptom was strongly associated with radiographic primary end point pneumonia in children. Performance characteristics were improved by combining individual signs and symptoms.

Influenza and Influenza Vaccine: A Review

Influenza is a highly contagious, deadly virus, killing nearly half a million people yearly worldwide. The classic symptoms of influenza are fever, fatigue, cough, and body aches. In the outpatient setting, diagnosis can be made by clinical presentation with optional confirmatory diagnostic testing. Antiviral medications should be initiated as soon as possible, preferably within 24 hours of initiation of symptoms. The primary preventive measure against influenza is vaccination, which is recommended for all people 6 months of age or older, including pregnant and postpartum women, unless the individual has a contraindication. Vaccination should occur at the beginning of flu season, which typically begins in October. It takes approximately 14 days after vaccination for a healthy adult to reach peak antibody protection. There are challenges associated with vaccine composition and vaccine uptake. It takes approximately 6 to 8 months to identify and predict which influenza strains to include in the upcoming season's vaccine. During this time, the influenza virus may undergo antigenic drift, that is, mutating to avoid a host immune response. Antigenic drift makes the vaccine less effective in some seasons. The influenza virus occasionally undergoes antigenic shift, in which it changes to a novel virus, creating potential for a pandemic. There are also barriers to vaccine uptake, including lack of or limited access to care and misconceptions about receiving the vaccine. Interventions that improve access to and uptake of the influenza vaccine must be initiated, targeting multiple levels, including health care policy, patients, health care systems, and the health care team. This article reviews information about influenza identification, management, and prevention.

Wearable Devices for Ambulatory Cardiac Monitoring: JACC State-of-the-Art Review

Ambulatory monitoring devices are enabling a new paradigm of health care by collecting and analyzing long-term data for reliable diagnostics. These devices are becoming increasingly popular for continuous monitoring of cardiac diseases. Recent advancements have enabled solutions that are both affordable and reliable, allowing monitoring of vulnerable populations from the comfort of their homes. They provide early detection of important physiological events, leading to timely alerts for seeking medical attention. In this review, the authors aim to summarize the recent developments in the area of ambulatory and remote monitoring solutions for cardiac diagnostics. The authors cover solutions based on wearable devices, smartphones, and other ambulatory sensors. The authors also present an overview of the limitations of current technologies, their effectiveness, and their adoption in the general population, and discuss some of the recently proposed methods to overcome these challenges. Lastly, we discuss the possibilities opened by this new paradigm, for the future of health care and personalized medicine.

Wearables for the Next Pandemic

This paper reviews the current state of the art in wearable sensors, including current challenges, that can alleviate the loads on hospitals and medical centers. During the COVID-19 Pandemic in 2020, healthcare systems were overwhelmed by people with mild to severe symptoms needing care. A careful study of pandemics and their symptoms in the past 100 years reveals common traits that should be monitored for managing the health and economic costs. Cheap, low power, and portable multi-modal-sensors that detect the common symptoms can be stockpiled and ready for the next pandemic. These sensors include temperature sensors for fever monitoring, pulse oximetry sensors for blood oxygen levels, impedance sensors for thoracic impedance, and other state sensors that can be integrated into a single system and connected to a smartphone or data center. Both research and commercial medically approved devices are reviewed with an emphasis on the electronics required to realize the sensing. The performance characteristics, such as accuracy, power, resolution, and size of each sensor modality are critically examined. A discussion of the characteristics, research challenges, and features of an ideal integrated wearable system is also presented.

Social Network Communications in Chilean Older Adults

The growth of older adults in new regions poses challenges for public health. We know that these seniors live increasingly alone, and this impairs their health and general wellbeing. Studies suggest that social networking sites (SNS) can reduce isolation, improve social participation, and increase autonomy. However, there is a lack of knowledge about the characteristics of older adult users of SNS in these new territories. Without this information, it is not possible to improve the adoption of SNS in this population. Based on decision trees, this study analyzes how the elderly users of various SNS in Chile are like. For this purpose, a segmentation of the different groups of elderly users of social networks was constructed, and the most discriminating variables concerning the use of these applications were classified. The results highlight the existence of considerable differences between the various social networks analyzed in their use and characterization. Educational level is the most discriminating variable, and gender influences the types of SNS use. In general, it is observed that the higher the educational level, the more the different social networking sites are used.

[eHealth-smart devices revolutionizing cardiology]

Hintergrund

Der Nutzen von Smart Devices wie Handys und Smartwatches in der Kardiologie nimmt deutlich zu. Der gehäufte Einsatz wird vor allem auch von Patienten und der Industrie vorangetrieben.

Fragestellung

Welche Möglichkeiten bieten Smart Devices in der Kardiologie?

Material und Methode

Es wurde eine selektive Literaturrecherche durchgeführt. Naturwissenschaftliche und klinische Studien über die verschiedenen Einsatzmöglichkeiten der technischen Mittel wurden interpretiert.

Ergebnisse

Der Besitz und Gebrauch von Smartphones in Deutschland ist im weltweiten Vergleich sehr hoch. Dies ermöglicht einen sehr breiten Einsatz dieser Technologie auch im medizinischen Bereich. Die Anwendungsmöglichkeiten sind vielfältig und reichen von der Nutzung als Nachschlagewerk über einen „clinical decision support“ bis hin zur Erfassung von Biosignalen. Gerade die Kombination aus Biosignalmessung und Weiterverarbeitung der Information durch künstliche Intelligenz (KI) ermöglicht eine deutliche Verbesserung der bisherigen Diagnosemethoden und erlaubt extrem genaue Vorhersagen verschiedener kardiovaskulärer Krankheitsverläufe.

Schlussfolgerung

Smart Devices werden in der Kardiologie zunehmend im klinischen Alltag genutzt. Aufgrund der technischen Möglichkeiten wird der Einsatz sehr wahrscheinlich weiter steigen und einige Bereiche der Kardiologie deutlich verändern.

Wearable Sensors for COVID-19: A Call to Action to Harness Our Digital Infrastructure for Remote Patient Monitoring and Virtual Assessments

The COVID-19 pandemic has brought into sharp focus the need to harness and leverage our digital infrastructure for remote patient monitoring. As current viral tests and vaccines are slow to emerge, we see a need for more robust disease detection and monitoring of individual and population health, which could be aided by wearable sensors. While the utility of this technology has been used to correlate physiological metrics to daily living and human performance, the translation of such technology toward predicting the incidence of COVID-19 remains a necessity. When used in conjunction with predictive platforms, users of wearable devices could be alerted when changes in their metrics match those associated with COVID-19. Anonymous data localized to regions such as neighborhoods or zip codes could provide public health officials and researchers a valuable tool to track and mitigate the spread of the virus, particularly during a second wave. Identifiable data, for example remote monitoring of cohorts (family, businesses, and facilities) associated with individuals diagnosed with COVID-19, can provide valuable data such as acceleration of transmission and symptom onset. This manuscript describes clinically relevant physiological metrics which can be measured from commercial devices today and highlights their role in tracking the health, stability, and recovery of COVID-19+ individuals and front-line workers. Our goal disseminating from this paper is to initiate a call to action among front-line workers and engineers toward developing digital health platforms for monitoring and managing this pandemic.

Coronavirus Disease 2019 in Pregnancy: A Clinical Management Protocol and Considerations for Practice

The coronavirus disease 2019 (COVID-19) pandemic has represented a major impact to health systems and societies worldwide. The generation of knowledge about the disease has occurred almost as fast as its global expansion. The mother and fetus do not seem to be at particularly high risk. Nevertheless, obstetrics and maternal-fetal medicine practice have suffered profound changes to adapt to the pandemic. In addition, there are aspects specific to COVID-19 and gestation that should be known by specialists in order to correctly diagnose the disease, classify the severity, distinguish specific signs of COVID-19 from those of obstetric complications, and take the most appropriate management decisions. In this review we present in a highly concise manner an evidence-based protocol for the management of COVID-19 in pregnancy. We briefly contemplate all relevant aspects that we believe a specialist in obstetrics and maternal medicine should know, ranging from basic concepts about the disease and protection measures in the obstetric setting to more specific aspects related to maternal-fetal management and childbirth.

The Use of Smartphone-Based Triage to Reduce the Rate of Outpatient Error Registration: Cross-Sectional Study

BACKGROUND

In many clinics, patients now have the option to make Web-based appointments but doing so according to their own judgment may lead to wrong registration and delayed medical services. We hypothesized that smartphone-based triage in outpatient services is superior to Web-based self-appointment registration guided by the medical staff.

OBJECTIVE

This study aimed to investigate smartphone-based triage in outpatient services compared with Web-based self-appointment registration and to provide a reference for improving outpatient care under appointment registration.

METHODS

The following parameters in Guangzhou Women and Children's Medical Center were analyzed: wrong registration rate, the degree of patient satisfaction, outpatient visits 6 months before and after smartphone-based triage, queries after smartphone-based triage, number of successful registrations, inquiry content, and top 10 recommended diseases and top 10 recommended departments after queries.

RESULTS

Smartphone-based triage showed significant effects on average daily queries, which accounted for 16.15% (1956/12,112) to 29.46% (3643/12,366) of daily outpatient visits. The average daily successful registration after queries accounted for 56.14% (1101/1961) to 60.92% (1437/2359) of daily queries and 9.33% (1130/12,112) to 16.83% (2081/12,366) of daily outpatient visits. The wrong registration rate after smartphone-based triage was reduced from 0.68% (12,810/1,895,829) to 0.12% (2379/2,017,921) (P<.001), and the degree of patient satisfaction was improved. Monthly outpatient visits were increased by 0.98% (3192/325,710) to 13.09% (42,939/328,032) compared with the same period the preceding year (P=.02).

CONCLUSIONS

Smartphone-based triage significantly reduces the wrong registration rate caused by patient Web-based appointment registration and improves the degree of patient satisfaction. Thus, it is worth promoting.

The utility of iPhone oximetry apps: A comparison with standard pulse oximetry measurement in the emergency department

OBJECTIVES

To determine if a correlation exists between 3 iphone pulse ox applications' measurements and the standard pulse oximetry (SpO2) and whether these applications can accurately determine hypoxia.

METHODS

Three applications reportedly measuring SpO2 were downloaded onto an iPhone 5s. Two of these applications used the onboard light and camera lens "Pulse Oximeter" (Pox) and "Heart Rate and Pulse Oximeter" (Ox) and one used an external device that plugged into the iphone (iOx). Patients in the ED were enrolled with chief complaints of cardiac/pulmonary origin or a SpO2 ≤ 94%. All measurements were compared to controls. Concordance correlation coefficients, sensitivity, and specificity were calculated.

RESULTS

A total of 191 patients were enrolled. The concordance correlation of iOx with control was 0.55 (CI 0.46, 0.63), POx was 0.01 (CI -0.09, 0.11), and Ox was 0.07 (CI -0.02, 0.15). 68/191 patients (35%) were found to have hypoxemia. Sensitivities for detecting hypoxia were 69%, 0%, and 7% for iOx, POx, and Ox, respectively. Specificities were 89%, 100%, and 89%. Even iOx (the most accurate) 21 (11%) were incorrectly classified nonhypoxic, and 22 (12%) were incorrectly classified hypoxic.

CONCLUSIONS

While iOx has modest concordance with control, Ox and POx showed almost none. The iOx device was best in correctly identifying hypoxia patients, but almost 1/4 of patients were incorrectly classified. The three apps provided inaccurate SpO2 measurements and had limited to no ability to accurately detect hypoxia. These apps should not be relied upon to provide accurate SpO2 measurements in emergent, even austere conditions.

Performance of a novel reusable pediatric pulse oximeter probe

OBJECTIVE

To assess the performance of reusable pulse oximeter probe and microprocessor box combinations, of varying price-points, in the context of a low-income pediatric setting.

METHODS

A prospective, randomized cross-over study comparing time to biologically plausible oxygen saturation (SpO₂ ) between: (1) Lifebox LB-01 probe with Masimo Rad-87 box (L + M) and (2) a weight-appropriate reusable Masimo probe with Masimo Rad-87 box (M + M). A post hoc secondary analysis comparison with historical usability testing data with the Lifebox LB-01 probe and Lifebox V1.5 box (L + L) was also conducted. Participants, children aged 0 to 35 months, were recruited from pediatric wards and outpatient clinics in the central region of Malawi. The primary outcome was time taken to achieve a biologically plausible SpO ₂ measurement, compared using t tests for equivalence.

RESULTS

We recruited 572 children. Plausible SpO₂ measurements were obtained in less than 1 minute, 71%, 70%, and 63% for the M + M, L + M, and L + L combinations, respectively. A similar pattern was seen for less than 2 minutes, however, this effect disappeared at less than 5 minutes with 96%, 96%, and 95% plausible measurements. Using a ±10 second threshold for equivalence, we found L + M and M + M to be equivalent, but were under-powered to assess equivalence for L + L.

CONCLUSIONS

The novel reusable pediatric Lifebox probe can achieve a quality SpO₂ measurement within a pragmatic time range of weight-appropriate Masimo equivalent probes. Further research, which considers the cost of the devices, is needed to assess the added value of sophisticated motion tolerance software.

Explaining the Use of Social Network Sites as Seen by Older Adults: The Enjoyment Component of a Hedonic Information System

Previous studies suggest that older adults are living increasingly alone and without the company of their close relatives, which cause them depression problems and a detriment to their health and general wellbeing. The use of social network sites (SNS) allows them to reduce their isolation, improve their social participation, and increase their autonomy. Although the adoption of various information technologies by older adults has been studied, some assumptions still predominate, for example, that older adults use SNS only for utilitarian purposes. However, considering SNS as hedonic information systems, and in order to extend the theoretical explanation of the intention to use hedonic systems to their actual use, this study aims to determine the influence of perceived enjoyment, perceived usefulness, and perceived ease of use on the use of SNS by elders in Concepción, Chile. Two hundred fifty-three older adults participated in the cross-sectional study. The results indicate that perceived ease of use is the variable that has the greatest total effect in explaining the use of SNS and that by adding the perceived enjoyment construct, the explanatory power of the model increases significantly. Therefore, advancement in user acceptance models, especially in the use of SNS by elders, can be made by focusing on the type of system, hedonic or utilitarian.

Reliability of smartphone measurements of vital parameters: A prospective study using a reference method

OBJECTIVE

In this study, we aimed to evaluate the accuracy of HR and SaO₂ data obtained using a smartphone compared with the measurements of a vital signs monitor (VSM) and an arterial blood gas (ABG) device, respectively.

MATERIAL AND METHODS

In this single-center prospective study, the HR and SaO₂ measurements were performed using the built-in sensor and light source of a Samsung Galaxy S8 smartphone and compared to the results of VSM and ABG device. The Bland-Altman analysis was used to evaluate and visualize the agreement between the methods.

RESULTS

The data of 101 patients were analyzed. There was a high correlation between HR measured by smartphone and HR measured by VSM [P < 0.0001; 0.9918 (95% CI = 0.987-0.994)]. In addition, the SaO₂ values obtained by smartphone were highly correlated with those by ABG (P < 0.0001; 0.968 (95% CI = 0.952-0.978)).

CONCLUSION

The HR and SaO₂ values obtained by smartphone were found to be consistent with the measurements of the reference devices. With the growing use of smartphone technology in the health field, we foresee that patients will be able to make their own triage assessment before presenting to the hospital.

A Novel Approach to Evaluating Mobile Smartphone Screen Time for iPhones: Feasibility and Preliminary Findings

BACKGROUND

Increasingly high levels of smartphone ownership and use pose the potential risk for addictive behaviors and negative health outcomes, particularly among younger populations. Previous methodologies to understand mobile screen time have relied on self-report surveys or ecological momentary assessments (EMAs). Self-report is subject to bias and unreliability, while EMA can be burdensome to participants. Thus, a new methodology is needed to advance the understanding of mobile screen time.

OBJECTIVE

The objective of this study was to test the feasibility of a novel methodology to record and evaluate mobile smartphone screen time and use: battery use screenshot (BUS).

METHODS

The BUS approach, defined for this study as uploading a mobile phone screenshot of a specific page within a smartphone, was utilized within a Web-based cross-sectional survey of adolescents aged 12-15 years through the survey platform Qualtrics. Participants were asked to provide a screenshot of their battery use page, a feature within an iPhone, to upload within the Web-based survey. Feasibility was assessed by smartphone ownership and response rate to the BUS upload request. Data availability was evaluated as apps per BUS, completeness of data within the screenshot, and five most used apps based on battery use percentage.

RESULTS

Among those surveyed, 26.73% (309/1156) indicated ownership of a smartphone. A total of 105 screenshots were evaluated. For data availability, screenshots contained an average of 10.2 (SD 2.0) apps per screenshot and over half (58/105, 55.2%) had complete data available. The most common apps or functions included Safari and Home and Lock Screen.

CONCLUSIONS

Study findings describe the BUS as a novel approach for real-time data collection focused on iPhone screen time and use among young adolescents. Although feasibility showed some challenges in the upload capacity of young teens, data availability was generally strong across this large dataset. These data from screenshots have the potential to provide key insights into precise mobile smartphone screen use and time spent per mobile app. Future studies could explore the use of the BUS methodology on other mobile smartphones such as Android phones to correlate mobile smartphone screen time with health outcomes.