Infection Screening System Using Thermography and CCD Camera with Good Stability and Swiftness for Non-contact Vital-Signs Measurement by Feature Matching and MUSIC Algorithm

Negishi, Toshiaki; Sun, Guanghao; Sato, Soichi; Liu, He; Matsui, Takemi; Abe, Shigeto; Nishimura, Hidekazu; Kirimoto, Tetsuo

doi:10.1109/embc.2019.8857027

Cited by 18 publications

(31 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, the MUSIC method was introduced to realize HR and RR measurements within a short time period. This method permits the realization of high-resolution HR and RR frequency estimation based on short-period measurement data Equation (5) expresses the spectrum estimation formula of the MUSIC method [14]: Tapered window, which is a general window function, was applied to the detected facial ROI (Figure 4b). In facial ROI, the edge area suffers from the lag affected by the face tracker.…”

Section: Rgb Sensor Processing For Hr Estimation Using Tapered Windowmentioning

confidence: 99%

Section: Rgb Sensor Processing For Hr Estimation Using Tapered Windowmentioning

confidence: 99%

“…We proposed a signal processing method for reconstructing the BVP waveform using all RGB channels and selecting nasal or oral breathing based on signal quality index (SQI), for improving the signal-to-noise ratio. To enable a real-time system, we implemented a multiple signal classification (MUSIC) algorithm to estimate the pseudo-spectrum from limited time-domain BVP and respiration signals within 15 s [14]. Finally, we tested the system on 22 healthy subjects and 41 patients with influenza-like symptoms (28 diagnosed influenza patients and 13 undiagnosed patients).…”

Section: Introductionmentioning

confidence: 99%

“…Feature matching for region-of-interest (ROI) detection in thermal image. The figure reproduced with copyright permission from Reference[14].…”

mentioning

confidence: 99%

See 3 more Smart Citations

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

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Rgb Sensor Processing For Hr Estimation Using Tapered Windowmentioning

confidence: 99%

Section: Rgb Sensor Processing For Hr Estimation Using Tapered Windowmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Feature matching for region-of-interest (ROI) detection in thermal image. The figure reproduced with copyright permission from Reference[14].…”

mentioning

confidence: 99%

See 2 more Smart Citations

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

Self Cite

View full text Add to dashboard Cite

show abstract

“…The system was used on 72,327 patients and visitors entering Taipei Medical University-Wan Fang Hospital in Taiwan for 1 month. Negishi et al [116] proposed a vision-based framework which can monitor respiration and heart-rate along with skin temperature.…”

Section: Infection Prevention and Controlmentioning

confidence: 99%

Contactless Human Activity Analysis: An Overview of Different Modalities

Abir

Faisal

Shahid

et al. 2021

Contactless Human Activity Analysis

View full text Add to dashboard Cite

Human Activity Analysis (HAA) is a prominent research field in this modern era which has enlightened us with the opportunities of monitoring regular activities or the surrounding environment as per our desire. In recent times, Contactless Human Activity Analysis (CHAA) has added a new dimension in this domain as these systems perform without any wearable device or any kind of physical contact with the user. We have analyzed different modalities of CHAA and arranged them into three major categories: RF-based, sound-based, and vision-based modalities. In this chapter, we have presented state-of-the-art modalities, frequently faced challenges with some probable solutions, and currently used applications of CHAA with future directions.

show abstract

Development of a stand‐alone portable respiratory rate monitor using a Doppler radar

Katoh,

Kanazawa,

Abe

et al. 2023

Elect Comm in Japan

View full text Add to dashboard Cite

Respiratory rate (RR) is known to be a more accurate predictor of clinical deterioration than other vital signs. However, there were few respiration measurement devices certified as medical devices that could be used in daily clinical settings. Therefore, using a bult‐in microcontroller (72×57×12 mm) instead of a personal computer, we developed a portable stand‐alone respiration measurement device with minimum workload in computing that can be used for non‐contact measurement in 30 s using a Doppler radar. In this study, the problems of respiration measurement using a Doppler radar, such as miscounting of respiratory peaks were clarified, and proposed device with respiratory peaks miscount prevention algorithm achieved high accuracy RR measurement. Clinical testing was conducted on pediatric outpatients of Children's Medical Center, Showa University Koto Toyosu Hospital. The measurement accuracy of the system was confirmed to be comparable to the respiration measurement accuracy of stationary certified medical devices used in hospital, such as capnometers and the chest wall impedance method used in bedside monitors.

show abstract

Infection Screening System Using Thermography and CCD Camera with Good Stability and Swiftness for Non-contact Vital-Signs Measurement by Feature Matching and MUSIC Algorithm

Cited by 18 publications

References 14 publications

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

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

Contactless Human Activity Analysis: An Overview of Different Modalities

Development of a stand‐alone portable respiratory rate monitor using a Doppler radar

Contact Info

Product

Resources

About