Guanghao Sun

Fever screening of seasonal influenza patients using a cost-effective thermopile array with small pixels for close-range thermometry

Summary Objective Infrared thermography systems have been used for fever screening at many airports since the outbreak of severe acute respiratory syndrome (SARS) in 2003. However, many of these systems are expensive and non-portable. Therefore, we developed a cost-effective and compact (2.9 × 5.8 × 2.0cm) thermopile array for fever screening of patients with infectious diseases in the clinical setting. Methods The array was created with small pixels (48 × 47 = 2256 pixels) fabricated on a silicon wafer using microelectromechanical systems technology. We tested this array on 155 febrile and afebrile patients (35.4°C ≤ axillary temperature ≤ 39.3°C) with seasonal influenza at the Japan Self-Defense Forces Central Hospital. Results The maximum facial temperature, measured by the array at 0.3 m from the subject, exhibited a positive correlation with axillary temperature measured using a contact-type thermometer (r = 0.71, p < 0.01). The sensitivity and specificity of the thermopile array in identifying the febrile subjects were 80.5% and 93.3%, respectively, setting the threshold cut-off of maximum facial temperature at an appropriate value. Conclusions Our cost-effective thermopile array appears promising for future close-range fever screening of patients with infectious diseases at primary care doctor clinics, health care centers, and quarantine stations in developing and developed countries.

Non-contact measurement of respiratory and heart rates using a CMOS camera-equipped infrared camera for prompt infection screening at airport quarantine stations

Severe acute respiratory syndrome (SARS) was first reported in 2003 and quickly spread around the world. Therefore, many international airport quarantine stations launched fever-based screening to detect infected passengers using infrared (IR) cameras for preventing global pandemics. However, a screening method based on fever alone can be insufficient for detecting infected individuals because many factors, such as antipyretics uptake, can affect it. Our previous studies using compact radar revealed that simultaneous measurement of facial skin temperature and respiratory and heart rates drastically improved the sensitivity of infection screening compared to that achieved by facial skin temperature measurement alone. Using a CMOS camera-equipped IR camera (CMOS-IR camera), which most Japanese International Airports have adopted, we developed an enhanced thermal/RGB image processing method for non-contact measurement of facial skin temperature, and respiratory and heart rates. We conducted the image processing on the thermal/RGB image-fusion mode in real time; we determined the respiratory rate by thermal images of the IR camera and the heart rate by the RGB images of the CMOS camera. Using a CMOS-IR camera, we measured respiratory and heart rates of ten healthy subjects (23 ± 1 years), and compared them with those determined by a contact-type respiratory effort belt and electrocardiograms (ECGs) as references. The respiratory and heart rates obtained from the CMOS-IR camera exhibited strong positive correlations with those derived from the references, a respiratory effort belt: r = 0.99, p <; 0.01; ECG: r = 0.96, p <; 0.01, whereas the axillary temperature indicated a moderate degree of correlation to facial skin temperature (r = 0.6). Adopting this method into conventional CMOS-IR camera image processing at international airport quarantines will achieve higher infection screening sensitivity.

A Portable Infection Screening System Designed for Onboard Entry Screening Based on Multi-Parameter Vital Signs

After outbreak of severe acute respiratory syndrome (SARS) in 2003, many international airport quarantines adopted fever-based screening to identify infected individuals using infrared thermography to control global pandemic. Unfortunately, the sensitivity of fever-based screening system did not exceed 70.4% at Narita International Airport. In order to achieve accurate onboard entry screening for highly contagious infectious diseases, the authors developed a portable system designed for onboard entry screening with linear discriminant analysis. Within several tens of seconds, the system automatically discriminates infected individuals from normal subjects using measured heart rate, respiratory rate, as well as facial surface temperature determined by thermography. The size of system is small enough to be placed on airplane tray tables. The authors tested on 68 subjects including 12 influenza patients to evaluate the system. The result showed sensitivity of 91.7% and specificity of 92.9%. The system seems to be promising for onboard infection screening to safeguard public health.

Remote sensing of multiple vital signs using a CMOS camera-equipped infrared thermography system and its clinical application in rapidly screening patients with suspected infectious diseases

Summary Background Infrared thermography (IRT) is used to screen febrile passengers at international airports, but it suffers from low sensitivity. This study explored the application of a combined visible and thermal image processing approach that uses a CMOS camera equipped with IRT to remotely sense multiple vital signs and screen patients with suspected infectious diseases. Methods An IRT system that produced visible and thermal images was used for image acquisition. The subjects’ respiration rates were measured by monitoring temperature changes around the nasal areas on thermal images; facial skin temperatures were measured simultaneously. Facial blood circulation causes tiny color changes in visible facial images that enable the determination of the heart rate. A logistic regression discriminant function predicted the likelihood of infection within 10s, based on the measured vital signs. Sixteen patients with an influenza-like illness and 22 control subjects participated in a clinical test at a clinic in Fukushima, Japan. Results The vital-sign-based IRT screening system had a sensitivity of 87.5% and a negative predictive value of 91.7%; these values are higher than those of conventional fever-based screening approaches. Conclusions Multiple vital-sign-based screening efficiently detected patients with suspected infectious diseases. It offers a promising alternative to conventional fever-based screening.

Multiple Vital-Sign-Based Infection Screening Outperforms Thermography Independent of the Classification Algorithm

Goal: Thermography-based infection screening at international airports plays an important role in the prevention of pandemics. However, studies show that thermography suffers from low sensitivity and specificity. To achieve higher screening accuracy, we developed a screening system based on the acquisition of multiple vital-signs. This multimodal approach increases accuracy, but introduces the need for sophisticated classification methods. This paper presents a comprehensive analysis of the multimodal approach to infection screening from a machine learning perspective. Methods: We conduct an empirical study applying six classification algorithms to measurements from the multimodal screening system and comparing their performance among each other, as well as to the performance of thermography. In addition, we provide an information theoretic view on the use of multiple vital-signs for infection screening. The classification methods are tested using the same clinical data, which has been analyzed in our previous study using linear discriminant analysis. A total of 92 subjects were recruited for influenza screening using the system, consisting of 57 inpatients diagnosed to have seasonal influenza and 35 healthy controls. Results: Our study revealed that the multimodal screening system reduces the misclassification rate by more than 50% compared to thermography. At the same time, none of the multimodal classifiers needed more than 6 ms for classification, which is negligible for practical purposes. Conclusion: Among the tested classifiers k-nearest neighbors, support vector machine and quadratic discriminant analysis achieved the highest cross-validated sensitivity score of 93%. Significance: Multimodal infection screening might be able to address the shortcomings of thermography.Goal: Thermography-based infection screening at international airports plays an important role in the prevention of pandemics. However, studies show that thermography suffers from low sensitivity and specificity. To achieve higher screening accuracy, we developed a screening system based on the acquisition of multiple vital-signs. This multimodal approach increases accuracy, but introduces the need for sophisticated classification methods. This paper presents a comprehensive analysis of the multimodal approach to infection screening from a machine learning perspective. Methods: We conduct an empirical study applying six classification algorithms to measurements from the multimodal screening system and comparing their performance among each other, as well as to the performance of thermography. In addition, we provide an information theoretic view on the use of multiple vital-signs for infection screening. The classification methods are tested using the same clinical data, which has been analyzed in our previous study using linear discriminant analysis. A total of 92 subjects were recruited for influenza screening using the system, consisting of 57 inpatients diagnosed to have seasonal influenza and 35 healthy controls. Results: Our study revealed that the multimodal screening system reduces the misclassification rate by more than 50% compared to thermography. At the same time, none of the multimodal classifiers needed more than 6 ms for classification, which is negligible for practical purposes. Conclusion: Among the tested classifiers k-nearest neighbors, support vector machine and quadratic discriminant analysis achieved the highest cross-validated sensitivity score of 93%. Significance: Multimodal infection screening might be able to address the shortcomings of thermography.

A portable screening system for onboard entry screening at international airports using a microwave radar, reflective photo sensor and thermography

We developed a portable screening system designed for onboard entry screening at international airports. The system can identify passengers who are potentially infected with epidemic diseases such as severe acute respiratory syndrome (SARS) or pandemic influenza. With its size being small enough to be placed on airplane tray tables, the system enables entry screening while passengers are onboard. In addition, this automatic system may greatly reduce time and effort required for screening.

An Objective Screening Method for Major Depressive Disorder Using Logistic Regression Analysis of Heart Rate Variability Data Obtained in a Mental Task Paradigm

Background and objectives Heart rate variability (HRV) has been intensively studied as a promising biological marker of major depressive disorder (MDD). Our previous study confirmed that autonomic activity and reactivity in depression revealed by HRV during rest and mental task (MT) conditions can be used as diagnostic measures and in clinical evaluation. In this study, logistic regression analysis (LRA) was utilized for the classification and prediction of MDD based on HRV data obtained in an MT paradigm. Methods Power spectral analysis of HRV on R–R intervals before, during, and after an MT (random number generation) was performed in 44 drug-naïve patients with MDD and 47 healthy control subjects at Department of Psychiatry in Shizuoka Saiseikai General Hospital. Logit scores of LRA determined by HRV indices and heart rates discriminated patients with MDD from healthy subjects. The high frequency (HF) component of HRV and the ratio of the low frequency (LF) component to the HF component (LF/HF) correspond to parasympathetic and sympathovagal balance, respectively. Results The LRA achieved a sensitivity and specificity of 80.0 and 79.0%, respectively, at an optimum cutoff logit score (0.28). Misclassifications occurred only when the logit score was close to the cutoff score. Logit scores also correlated significantly with subjective self-rating depression scale scores (p < 0.05). Conclusion HRV indices recorded during a MT may be an objective tool for screening patients with MDD in psychiatric practice. The proposed method appears promising for not only objective and rapid MDD screening but also evaluation of its severity.

Clinical evaluation of the newly developed infectious disease/fever screening radar system using the neural network and fuzzy grouping method for travellers with suspected infectious diseases at Narita International Airport Clinic

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Rapid and stable measurement of respiratory rate from Doppler radar signals using time domain autocorrelation model

Noncontact measurement of respiratory rate using Doppler radar will play a vital role in future clinical practice. Doppler radar remotely monitors the tiny chest wall movements induced by respiration activity. The most competitive advantage of this technique is to allow users fully unconstrained with no biological electrode attachments. However, the Doppler radar, unlike other contact-type sensors, is easily affected by the random body movements. In this paper, we proposed a time domain autocorrelation model to process the radar signals for rapid and stable estimation of the respiratory rate. We tested the autocorrelation model on 8 subjects in laboratory, and compared the respiratory rates detected by noncontact radar with reference contact-type respiratory effort belt. Autocorrelation model showed the effects of reducing the random body movement noise added to Doppler radars respiration signals. Moreover, the respiratory rate can be rapidly calculated from the first main peak in the autocorrelation waveform within 10 s.

Development of an infection screening system for entry inspection at airport quarantine stations using ear temperature, heart and respiration rates

After the outbreak of severe acute respiratory syndrome (SARS) in 2003, many international airport quarantine stations conducted fever-based screening to identify infected passengers using infrared thermography for preventing global pandemics. Due to environmental factors affecting measurement of facial skin temperature with thermography, some previous studies revealed the limits of authenticity in detecting infectious symptoms. In order to implement more strict entry screening in the epidemic seasons of emerging infectious diseases, we developed an infection screening system for airport quarantines using multi-parameter vital signs. This system can automatically detect infected individuals within several tens of seconds by a neural-network-based discriminant function using measured vital signs, i.e., heart rate obtained by a reflective photo sensor, respiration rate determined by a 10-GHz non-contact respiration radar, and the ear temperature monitored by a thermography. In this paper, to reduce the environmental effects on thermography measurement, we adopted the ear temperature as a new screening indicator instead of facial skin. We tested the system on 13 influenza patients and 33 normal subjects. The sensitivity of the infection screening system in detecting influenza were 92.3%, which was higher than the sensitivity reported in our previous paper (88.0%) with average facial skin temperature.