scholarly journals Peak Detection Algorithm for Vital Sign Detection Using Doppler Radar Sensors

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1575 ◽  
Author(s):  
Ju-Yeon Kim ◽  
Jae-Hyun Park ◽  
Se-Young Jang ◽  
Jong-Ryul Yang
Keyword(s):  
Heart Rate ◽  
Doppler Radar ◽  
Vital Signs ◽  
Accurate Method ◽  
Detection Algorithm ◽  
Peak Detection ◽  
Operating Characteristics ◽  
Radar Sensor ◽  
Peak Detection Algorithm ◽  
Hrv Analysis

An accurate method for detecting vital signs obtained from a Doppler radar sensor is proposed. A Doppler radar sensor can remotely obtain vital signs such as heartbeat and respiration rate, but the vital signs obtained by using the sensor do not show clear peaks like in electrocardiography (ECG) because of the operating characteristics of the radar. The proposed peak detection algorithm extracts the vital signs from the raw data. The algorithm shows the mean accuracy of 96.78% compared to the peak count from the reference ECG sensor and a processing time approximately two times faster than the gradient-based algorithm. To verify whether heart rate variability (HRV) analysis similar to that with an ECG sensor is possible for a radar sensor when applying the proposed method, the continuous parameter variations of the HRV in the time domain are analyzed using data processed with the proposed peak detection algorithm. Experimental results with six subjects show that the proposed method can obtain the heart rate with high accuracy but cannot obtain the information for an HRV analysis because the proposed method cannot overcome the characteristics of the radar sensor itself.

Combined Time-Frequency Calculation of pNN50 Metric From Noisy Heart Rate Measurements

2014 ◽  
Author(s):  
Payam Parsinejad ◽  
Yolanda Rodriguez-Vaqueiro ◽  
Jose Angel Martinez-Lorenzo ◽  
Rifat Sipahi
Keyword(s):  
Heart Rate ◽  
Mental Workload ◽  
Human Subjects ◽  
Detection Algorithm ◽  
Frequency Domain Analysis ◽  
Peak Detection ◽  
Time Frequency ◽  
Peak Detection Algorithm ◽  
Frequency Calculation ◽  
Noticeable Improvement

pNN50 is a metric derived from heart rate (HR) measurements, and it is known to correlate with mental-workload changes in human subjects. Conventionally, this metric is calculated based on the variability of successive time periods in peak-to-peak occurrences in HR data. In the case of noisy measurements of HR, however, peak-to-peak detection may not be reliable. Here, we present a combined time-frequency domain analysis, benefiting from Short Time Fourier Transform, by which we can more accurately extract pNN50 metric from noisy HR data. An experimental measurement with added noise is used as a benchmark problem to demonstrate the effectiveness of the approach with noticeable improvement over the conventional time domain peak-to-peak detection algorithm.

scholarly journals 915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 561 ◽  
Author(s):  
Jae-Hyun Park ◽  
Yeo-Jin Jeong ◽  
Ga-Eun Lee ◽  
Jun-Taek Oh ◽  
Jong-Ryul Yang
Keyword(s):  
Heart Rate ◽  
Continuous Wave ◽  
Doppler Radar ◽  
Vital Signs ◽  
Path Loss ◽  
Low Noise ◽  
Radar Sensor ◽  
Continuous Wave Doppler ◽  
Front End ◽  
Front End Module

A miniaturized continuous-wave Doppler radar sensor operating at 915 MHz to remotely detect both respiration and heart rate (beats per minute) is presented. The proposed radar sensor comprises a front-end module including an implemented complementary metal-oxide semiconductor low-noise amplifier (LNA) and fractal-slot patch antennas, whose area was reduced by 15.2%. The two-stage inverter-based LNA was designed with an interstage capacitor and a feedback resistor to acquire ultrawide bandwidth. Two operating frequencies, 915 MHz and 2.45 GHz, were analyzed with regard to path loss for efficient operation because frequency affects detection sensitivity, reflected signal power from the human body, and measurement distance in a far-field condition. Path-loss calculation based on the simplified layer model indicates that the reflected power of the 915 MHz radar could be higher than that of the 2.45 GHz radar. The implemented radar front-end module excluding the LNA occupies 35 × 55 mm2. Vital signs were obtained via a fast Fourier transform and digital filtering using raw signals. In an experiment with six subjects, the respiration and heart rate obtained at 0.8 m using the proposed radar sensor exhibited mean accuracies of 99.4% and 97.6% with respect to commercialized reference sensors, respectively.

scholarly journals Heart Rate Monitoring using Peak Detection in Photoplethysmography Signals of Fingertip Images Captured using Smartphone

2019 ◽  
Vol 8 (2) ◽  
pp. 3131-3137
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Health Care Services ◽  
Vital Signs ◽  
Preventive Health Care ◽  
Detection Algorithm ◽  
Peak Detection ◽  
Blood Pressure Monitor ◽  
Pressure Monitor ◽  
Care Services

Smartphone plays a major role in contributing towards preventive health care services, as they enable users to track by themselves, their diet and fitness regime. Monitoring vital signs particularly, heart rate regularly helps in early detection of heart related ailments. Given the present context, a smartphone is readily available with most of the population; hence it is much easy to monitor heart rate using the same. In this paper, a smartphone based application is presented which calculates the heart rate from the photoplethysmography (PPG) signals obtained from the fingertip images captured through the camera. Heart rate is calculated by counting the peaks that occur in the PPG signals in a particular duration. In order to detect the peaks, a peak detection algorithm proposed in [1] is used, as the algorithm helps in detecting peaks accurately without any pre-processing. The proposed technique is very simple as it calculates heart rate directly from time series PPG data without the need of converting to frequency domain data and can be employed in any smartphone to measure heart rate. In order to validate the proposed method, experiment was performed to calculate the heart rate of forty nine individuals and the obtained results were compared with heart rate readings measured using digital blood pressure (BP) monitor for those individuals. The heart rate obtained from proposed method is close to one that is obtained from digital blood pressure monitor with three percent discrepancy

scholarly journals Correction: Park, J.-H. et al. 915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs. Electronics 2019, 8, 561

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 855 ◽  
Author(s):  
Park ◽  
Jeong ◽  
Lee ◽  
Oh ◽  
Yang
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Vital Signs ◽  
Radar Sensor ◽  
Continuous Wave Doppler ◽  
Published Paper

The authors wish to make the following corrections to the published paper [...]

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