Multiple vital-sign-based screening efficiently detected patients with suspected infectious diseases. It offers a promising alternative to conventional fever-based screening.

Over 350 million people across the world suffer from major depressive disorder (MDD). More than 10% of MDD patients have suicide intent, while it has been reported that more than 40% patients did not consult their doctors for MDD. In order to increase consultation rate of potential MDD patients, we developed a novel MDD screening system which can be used at home without help of health-care professionals. Using a fingertip photoplethysmograph (PPG) sensor as a substitute of electrocardiograph (ECG), the system discriminates MDD patients from healthy subjects using autonomic nerve transient responses induced by a mental task (random number generation) via logistic regression analysis. The nine logistic regression variables are averages of heart rate (HR), high frequency (HF) component of heart rate variability (HRV), and the low frequency (LF)/HF ratio of HRV before, during, and after the mental task. We conducted a clinical test of the proposed system. Participants were 6 MDD patients (4 females and 2 males, aged 23–60 years) from Shizuoka Saiseikai General Hospital psychiatry outpatient unit and 14 healthy volunteers from University of Electro-Communications (6 females and 8 males, aged 21–63 years). The average PPG- and ECG (as a reference)-derived HR, HF and LF/HF were significantly correlated with each other (HR; r = 1.00, p < 0.0001, HF; r = 0.98, p < 0.0001, LF/HF; r = 0.98, p < 0.0001). Leave-one-out cross validation (LOOCV) revealed 83% sensitivity and 93% specificity. The proposed system appears promising for future MDD self-screening at home and are expected to encourage psychiatric visits for potential MDD patients.

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Despite a reduction in pneumonia-related mortality, pneumonia remains a leading cause of death among children aged 0-5 years. Most of these deaths occur in developing countries. However, more than half of pneumonia-related deaths are preventable with improved facilities and health strategies. Early rapid diagnosis is important to decrease pneumonia mortality. We developed a portable, cost-effective, rapid pneumonia screening system using a random tree algorithm to support early detection of pneumonia in children. We enrolled 105 participants: 57 patients aged 1-13 years (33 boys, 24 girls) diagnosed with pneumonia by chest radiograph and 48 normal volunteers aged 2-14 years (25 boys, 22 girls). We conducted a clinical trial in the Bayangol District Geriatric and Pediatric Hospital, Ulaanbaatar, Mongolia from January 12-19, 2019. Our screening system measured heart rate, respiration rate and skin temperature within 10 seconds and used a random tree algorithm to distinguish patients with pneumonia and normal volunteers. The system uses a photosensor, Doppler radar, and infrared thermophile to determine vital signs and an Arduino Nano microprocessor to perform computations. Paired t-tests were used to compare vital signs between patients with pneumonia and normal volunteers. The random tree algorithm achieved sensitivity of 96.5%, specificity of 81.3%, positive predictive value of 85.9%, and negative predictive value of 95.1%. The paired t-tests showed strong statistically significant differences in all three vital signs between patients with pneumonia and normal volunteers. Our random tree algorithm-based screening system offers an effective, rapid, and convenient tool for early detection of pneumonia in children. Its cost-effectiveness enables application in low-income countries. The system measures multiple vital signs simultaneously within 10 seconds, which may be useful for initial physical examinations in pediatric hospitals.

The primary cause of death among children under age 5 years is acute respiratory infection, such as pneumonia. Detection of infection at the earliest point of contagion is necessary, to reduce morbidity and prevent infectious disease epidemics; therefore, identifying abnormal vital signs is essential. For early detection of pediatric infections, we developed a low-cost, portable, rapid screening system of pediatric infection. The system simultaneously measures three vital signs: heart rate (HR), respiration rate (RR), and body temperature (Temp) within 10 seconds using a pulse sensor, Doppler radar, and an infrared thermopile. Vital sign signal processing and computation are conducted using an Arduino Nano microprocessor, enabling the small, lightweight, and portable design of this system. Moreover, the cost-effectiveness of the system facilitates system applications in developing countries, which have the highest levels of pediatric mortality. We conducted trial measurement in Bayangol Health Center, Ulaanbaatar, Mongolia in 2019. A total of 50 children (age 1-14 years, 26 boys/24 girls) were enrolled in this study. Bland-Altman plot and Pearson correlation methods were used to evaluate the accuracy of the proposed system. The correlation coefficients were calculated as HR: r=0.92, RR: r=0.8, and Temp: r=0.82, with p<0.01. The system appears promising for rapid and convenient detection of infection in children.