Review and Evaluation of Heart Rate Monitoring Based Vital Signs, A case Study: Covid-19 Pandemic

Bella, Abdoullah; Latif, Rachid; Saddik, Amine; Jamad, Laila

doi:10.1109/cist49399.2021.9357302

Cited by 10 publications

(4 citation statements)

References 21 publications

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“…Over recent developments of COVID-19, breathing rate detection and monitoring have become more essential leading to more research in respiration rate monitoring [16], [17]. In [18], the authors have focused on the drawbacks of contactbased systems and presented a contactless approach to measure the breathing rate using a video to analyze the signals.…”

Section: Non-contactmentioning

confidence: 99%

Breathing Rate Classification Using Piezoresistive Sensor Utilizing Continuous Wavelet Transform and Lightweight CNN

Gupta,

Yeduri,

Cenkeramaddi

2024

IEEE Access

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The breath rate can now be monitored remotely due to the advancements in digital stethoscope sensor technology, signal processing, and machine learning. Automatic breathing rate classification, on the other hand, provides additional benefits in medical diagnostics. In this paper, a lightweight convolutional neural network is proposed for automatic breathing rate classification utilizing the piezoresistive sensor data. In the proposed work, the raw signals from the piezoresistive sensor are pre-processed using a continuous wavelet transform to generate the corresponding images. These images are then fed into a lightweight convolutional neural network, which efficiently classifies the breathing rate into six classes based on the number of breaths per minute. Through extensive results, we show that the proposed model results in a classification accuracy of 96.40% which is higher than all the benchmark models considered in this paper. We also evaluate the performance of the proposed model using edge computing devices such as Raspberry Pi, Nvidia AGX Xavier, and Nvidia Jetson Nano.

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Section: Non-contactmentioning

confidence: 99%

Breathing Rate Classification Using Piezoresistive Sensor Utilizing Continuous Wavelet Transform and Lightweight CNN

Gupta,

Yeduri,

Cenkeramaddi

2024

IEEE Access

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“…Currently wearable devices have been proposed so that persons can easily monitors there body temperature, oxygen meter and so on which is directly related to healthcare concern by using Wi-Fi module or Bluetooth devices easily [19]. Remote monitoring system is also developing so that doctors or hospital administration can monitor the respiratory or heart rate and by using thermal sensor the body temperature of patients remotely [20]. By accessing these data for formation of prescription and sharing it via tablet or smart phone.…”

Section: Motivationmentioning

confidence: 99%

A Novel Smart Hospital for Isolation of COVID-19 Patients

Utsav¹,

Abhishek²,

Priya³

et al. 2021

2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)

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In this paper we describe a smart and innovative system which provides prime contribution to our society in this pandemic situation. We propose a novel smart hospital with multi featured equipments along with fashionable isolation ward for COVID-19 patients. A website interface has been proposed under anyone can visit and after knowing the status of the beds either for the isolation or emergency ward they can easily book from remote location. A QR code with registration number will be provided to the users. These users may reach to the hospital and have to pass through the QR code scanner for verification and sanitization process. A preevaluation section has been defined where proper mask at face will be detected with thermal scanner facility. All the designed section is controlled and monitor by control unit through server. Well featured with multiple sensors a unique ward is designed where oxygen level sensor is used to sense the level of oxygen and if the level of oxygen of patient is less than defined value supply of oxygen will switch on the supply automatically. Doctor will monitor and take care of patients through CCTV and video conferencing. The entire sub design unit is controlled and monitored via hybrid network and IoT.

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“…The measurement of the respiratory rate is achieved using sensors, employing a technique that doesn't require direct contact. It quantifies the variation in the reflection of green, blue, and red light from the skin's surface, based on the distinction between specular and diffused reflections [4]. Remote plethysmography (rPPG) is a non-contact method widely used.…”

Section: Introductionmentioning

confidence: 99%

Non-contact Respiratory Rate Monitoring Based on the Principal Component Analysis

Boussaki,

Latif,

Saddik

et al. 2023

IJACSA

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Assessing respiratory rate is a critical determinant of one's health status. The proposed approach relies on principal component analysis (PCA) for the continuous monitoring of breathing rate using an RGB camera. This method employs remote plethysmography, a video-based technique enabling contactless tracking of blood volume fluctuations by detecting variations in pixel intensity on the skin. These pixels encompass the red, blue, and green channels, whose values, post-PCA dimensionality reduction, encode the signal containing vital information about the breathing rate. To assess the method's performance, it was tested on a group of seven volunteers, including individuals of both genders. The results reveal a Mean Absolute Deviation of 0.714 BPM and a Root Mean Square Error of 2.035 BPM when comparing the experimental measurements to the actual readings.

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Review and Evaluation of Heart Rate Monitoring Based Vital Signs, A case Study: Covid-19 Pandemic

Cited by 10 publications

References 21 publications

Breathing Rate Classification Using Piezoresistive Sensor Utilizing Continuous Wavelet Transform and Lightweight CNN

Breathing Rate Classification Using Piezoresistive Sensor Utilizing Continuous Wavelet Transform and Lightweight CNN

A Novel Smart Hospital for Isolation of COVID-19 Patients

Non-contact Respiratory Rate Monitoring Based on the Principal Component Analysis

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