scholarly journals Design and Implementation of Breathing Rate Measurement SystemBased on Accelerometer Sensor

2020 ◽  
Vol 745 ◽  
pp. 012100
Author(s):  
Ali Ghazi Shabeeb ◽  
Ali J Al-Askery ◽  
Abbas Fadhal Humadi
Keyword(s):  
Breathing Rate ◽  
Rate Measurement ◽  
Accelerometer Sensor ◽  
Design And Implementation

scholarly journals C-Band FMCW Radar Design and Implementation for Breathing Rate Estimation

2020 ◽  
Vol 5 (5) ◽  
pp. 1299-1307
Author(s):  
Mohammad Mohammad Abdul-Atty ◽  
Ahmed Sayed Ismail Amar ◽  
Mohamed Mabrouk
Keyword(s):  
Breathing Rate ◽  
Fmcw Radar ◽  
Rate Estimation ◽  
Design And Implementation

scholarly journals Methods for Breathing Rate Measurement through Mobile Platform: a Review

2019 ◽  
Author(s):  
Diego O. Lemos ◽  
Clauirton A. Siebra
Keyword(s):  
Main Tool ◽  
Breathing Rate ◽  
Rate Measurement ◽  
Clinical Environment ◽  
Review Of The Literature ◽  
Mobile Health Applications ◽  
Pros And Cons ◽  
Respiratory Measurement ◽  
Combination Of Methods ◽  
Health Applications

Breathing rate is a vital sign that can indicate someone’s health status and even detect early diseases. Mobile health applications might become the main tool for estimating breathing rate out of the clinical environment. In this research, a review of the literature is conducted, aiming at finding out the most recent researches that have been proposed as solutions for respiratory measurement or monitoring using mobile devices. We discuss and compare their methods, highlighting pros and cons regarding ubiquity and feasibility. The results indicate that the combination of methods is a key aspect to improve measurements.

scholarly journals Design and Implementation of Respiration Rate Measurement System Using Information Filter on Embedded Device

2018 ◽  
Author(s):  
Radius Bhayu Prasetiyo ◽  
Kyu-Sang Choi ◽  
Gi-Hun Yang
Keyword(s):  
Blood Flow ◽  
Respiration Rate ◽  
Intensity Variation ◽  
Major Peak ◽  
Rate Measurement ◽  
Embedded Device ◽  
Design And Implementation ◽  
Information Filter ◽  
Respiration Rate Measurement ◽  
Fft Analysis

In this work, an algorithm was developed to measure the respiration rate for an embedded device that can be used by a field robot for relief operation. With this algorithm, the rate measurement was calculated based on direct influences of respiratory-induced intensity variation (RIIV) on blood flow in cardiovascular pathways. For that, a photoplethysmogram (PPG) sensor was used to determine changes in heartbeat frequencies. The PPG sensor readings were filtered using an Information Filter and a Fast Fourier transform (FFT) to determine the state of RIIV. With a relatively light initialization, the information filter can estimate unknown variables based on a series of measurements containing noise and other inaccuraties. Therefore, this filter is suitable for application on an embedded device. For faster calculation time in the implementation, the FFT analysis was calculated only for a major peak in the frequency domain. Test and measurement of respiration rate was conducted based on the device algorithm and spirometer. Heartbeat measurement was also evaluated by comparing the heartbeat data of the PPG sensor and the medical tool kit. Based on the test, the implemented algorithm can measure respiration rate with about 80% accuracy compared with the spirometer.

Influence of image resolution on the performance of remote breathing rate measurement using thermal imaging technique

2018 ◽  
Vol 93 ◽  
pp. 63-69 ◽  
Author(s):  
Menghan Hu ◽  
Guangtao Zhai ◽  
Duo Li ◽  
Hanqi Li ◽  
Mengxin Liu ◽  
...  
Keyword(s):  
Thermal Imaging ◽  
Imaging Technique ◽  
Image Resolution ◽  
Breathing Rate ◽  
Rate Measurement

scholarly journals Design and Implementation of Respiration Rate Measurement System Using an Information Filter on an Embedded Device

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4208 ◽  
Author(s):  
Radius Prasetiyo ◽  
Kyu-Sang Choi ◽  
Gi-Hun Yang
Keyword(s):  
Respiration Rate ◽  
Intensity Variation ◽  
Major Peak ◽  
Rate Measurement ◽  
Embedded Device ◽  
Design And Implementation ◽  
Information Filter ◽  
Relief Operations ◽  
Respiration Rate Measurement ◽  
Fft Analysis

In this work, an algorithm was developed to measure respiration rate for an embedded device that can be used by a field robot for relief operations. With this algorithm, the rate measurement was calculated based on direct influences of respiratory-induced intensity variation (RIIV) on blood flow in cardiovascular pathways. For this, a photoplethysmogram (PPG) sensor was used to determine changes in heartbeat frequencies. The PPG sensor readings were filtered using an Information Filter and a fast Fourier transform (FFT) to determine the state of RIIV. With a relatively light initialization, the information filter can estimate unknown variables based on a series of measurements containing noise and other inaccuracies. Therefore, this filter is suitable for application in an embedded device. For faster calculation time in the implementation, the FFT analysis was calculated only for a major peak in frequency domain. Test and measurement of respiration rate was conducted based on the device algorithm and spirometer. Heartbeat measurements were also evaluated by comparing the heartbeat data of the PPG sensor and pulse-oximeter. Based on the test, the implemented algorithm can measure the respiration rate with approximately 80% accuracy compared with the spirometer.

Design and Implementation of the Control System for Two-Wheeled Self-Balancing Vehicles

2012 ◽  
Vol 588-589 ◽  
pp. 1606-1610 ◽  
Author(s):  
Min Dai ◽  
Jian Wang ◽  
Xiao Gang Sun ◽  
Shuang Hu ◽  
Jun Xiang Jia
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Closed Loop ◽  
Low Cost ◽  
Control System Design ◽  
Hardware Platform ◽  
Accelerometer Sensor ◽  
Design And Implementation ◽  
Avr Mcu ◽  
Gyroscope Sensor

A control-system design for a two-wheeled self-balancing vehicle is discussed in this paper. We have developed a low-cost hardware platform based on AVR MCU, accelerometer sensor and gyroscope sensor, for which the critical circuits, such as sensors and motor driver, are introduced. The control strategy operates by two steps: a) securing the real-time vehicle posture by integrating the data from accelerometer and gyroscope sensors; b) using a closed-loop PID controller to keep the vehicle balanced. This control system is applied to a prototype two-wheeled self-balancing vehicle, whose performance has turned out to be a satisfaction.

Collaborative use of RGB and thermal imaging for remote breathing rate measurement under realistic conditions

2020 ◽  
Vol 111 ◽  
pp. 103504
Author(s):  
Lushuang Chen ◽  
Menghan Hu ◽  
Ning Liu ◽  
Guangtao Zhai ◽  
Simon X. Yang
Keyword(s):  
Thermal Imaging ◽  
Breathing Rate ◽  
Rate Measurement
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