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

Yao, Yu; Sun, Guanghao; Matsui, Takemi; Hakozaki, Yukiya; Waasen, S. van; Schiek, M.

doi:10.1109/tbme.2015.2479716

Cited by 28 publications

(28 citation statements)

References 14 publications

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“…This clinical study had 20 participants, which was a small sample size compared with large scale clinical studies. Therefore, we adopted LOOCV analysis, which was appropriate for accurately estimating small datasets (Yao et al, 2016 ). The logit score could potentially be used as an index of depression or mental health severity because it indicates a positive correlation with the SDS score that was used to screen for MDD (Shinba, 2014 ).…”

Section: Resultsmentioning

confidence: 99%

“…Diagnostic systems for a variety of diseases are continually being improved and broadened. For instance, we have developed various infection screening systems using infrared cameras and microwave radars (Matsui et al, 2004 , 2010 ; Sun et al, 2014 ; Yao et al, 2016 ). However, for people who might have MDD, going to psychiatric facilities with experienced doctors is laborious and stressful (Westen, 2012 ; Culpepper et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

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Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor

Dagdanpurev

Sun

Shinba

et al. 2018

Front. Bioeng. Biotechnol.

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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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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor

Dagdanpurev

Sun

Shinba

et al. 2018

Front. Bioeng. Biotechnol.

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“…To overcome the drawbacks of fever-based screening, we previously proposed a screening method based on simultaneously measuring three vital signs-body temperature, heart rate (HR) and respiration rate (RR)-using multiple sensors, that is, medical radar, thermograph, photo-sensor and RGB cameras [8][9][10]. These three vital signs were included in the criteria of the systemic inflammatory response syndrome [11].…”

Section: Introductionmentioning

confidence: 99%

Contactless Vital Signs Measurement System Using RGB-Thermal Image Sensors and Its Clinical Screening Test on Patients with Seasonal Influenza

Negishi

Abe²,

Matsui

et al. 2020

Sensors

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Background: In the last two decades, infrared thermography (IRT) has been applied in quarantine stations for the screening of patients with suspected infectious disease. However, the fever-based screening procedure employing IRT suffers from low sensitivity, because monitoring body temperature alone is insufficient for detecting infected patients. To overcome the drawbacks of fever-based screening, this study aims to develop and evaluate a multiple vital sign (i.e., body temperature, heart rate and respiration rate) measurement system using RGB-thermal image sensors. Methods: The RGB camera measures blood volume pulse (BVP) through variations in the light absorption from human facial areas. IRT is used to estimate the respiration rate by measuring the change in temperature near the nostrils or mouth accompanying respiration. To enable a stable and reliable system, the following image and signal processing methods were proposed and implemented: (1) an RGB-thermal image fusion approach to achieve highly reliable facial region-of-interest tracking, (2) a heart rate estimation method including a tapered window for reducing noise caused by the face tracker, reconstruction of a BVP signal with three RGB channels to optimize a linear function, thereby improving the signal-to-noise ratio and multiple signal classification (MUSIC) algorithm for estimating the pseudo-spectrum from limited time-domain BVP signals within 15 s and (3) a respiration rate estimation method implementing nasal or oral breathing signal selection based on signal quality index for stable measurement and MUSIC algorithm for rapid measurement. We tested the system on 22 healthy subjects and 28 patients with seasonal influenza, using the support vector machine (SVM) classification method. Results: The body temperature, heart rate and respiration rate measured in a non-contact manner were highly similarity to those measured via contact-type reference devices (i.e., thermometer, ECG and respiration belt), with Pearson correlation coefficients of 0.71, 0.87 and 0.87, respectively. Moreover, the optimized SVM model with three vital signs yielded sensitivity and specificity values of 85.7% and 90.1%, respectively. Conclusion: For contactless vital sign measurement, the system achieved a performance similar to that of the reference devices. The multiple vital sign-based screening achieved higher sensitivity than fever-based screening. Thus, this system represents a promising alternative for further quarantine procedures to prevent the spread of infectious diseases.

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“…In our previous studies, we proposed a multiple vital sign-based infection screening system with sensor fusion technology that can rapidly perform medical inspections at places of mass gatherings, such as airport quarantine stations and outpatient units [7][8][9][10]. This multiple sensor system consists of a medical radar and an infrared thermographic camera.…”

Section: Introductionmentioning

confidence: 99%

Vital-SCOPE: Design and Evaluation of a Smart Vital Sign Monitor for Simultaneous Measurement of Pulse Rate, Respiratory Rate, and Body Temperature for Patient Monitoring

et al. 2018

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Consistent vital sign monitoring is critically important for early detection of clinical deterioration of patients in hospital settings. Mostly, nurses routinely measure and document the primary vital signs of all patients 2-3 times daily to assess their condition. To reduce nurse workload and thereby improve quality of patient care, a smart vital sign monitor named "Vital-SCOPE" for simultaneous measurement of vital signs was developed. Vital-SCOPE consists of multiple sensors, including a reflective photo sensor, thermopile, and medical radar, to be used in simultaneous pulse rate, respiratory rate, and body temperature monitoring within 10 s. It was tested in laboratory and hospital settings. Bland-Altman and Pearson's correlation analyses were used to compare the Vital-SCOPE results to those of reference measurements. The mean difference of the respiratory rate between respiratory effort belt and Vital-SCOPE was 0.47 breaths per minute with the 95% limit of agreement ranging from −7.4 to 6.5 breaths per minute. The Pearson's correlation coefficient was 0.63 (P < 0 05). Moreover, the mean difference of the pulse rate between electrocardiogram and Vital-SCOPE was 3.4 beats per minute with the 95% limit of agreement ranging from −13 to 5.8 beats per minute; the Pearson's correlation coefficient was 0.91 (P < 0 01), indicating strong linear relationship.

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

Abstract: Multimodal infection screening might be able to address the shortcomings of thermography.

Cited by 28 publications

References 14 publications

Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor

Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor

Contactless Vital Signs Measurement System Using RGB-Thermal Image Sensors and Its Clinical Screening Test on Patients with Seasonal Influenza

Vital-SCOPE: Design and Evaluation of a Smart Vital Sign Monitor for Simultaneous Measurement of Pulse Rate, Respiratory Rate, and Body Temperature for Patient Monitoring

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