scholarly journals Photoplethysmographic Time-Domain Heart Rate Measurement Algorithm for Resource-Constrained Wearable Devices and its Implementation

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1783 ◽  
Author(s):  
Marek Wójcikowski ◽  
Bogdan Pankiewicz
Keyword(s):  
Heart Rate ◽  
Time Domain ◽  
Body Movement ◽  
Real Life ◽  
Ground Truth ◽  
Skin Surface ◽  
Detection Algorithm ◽  
Resource Constrained ◽  
Peak Detection Algorithm

This paper presents an algorithm for the measurement of the human heart rate, using photoplethysmography (PPG), i.e., the detection of the light at the skin surface. The signal from the PPG sensor is processed in time-domain; the peaks in the preprocessed and conditioned PPG waveform are detected by using a peak detection algorithm to find the heart rate in real time. Apart from the PPG sensor, the accelerometer is also used to detect body movement and to indicate the moments in time, for which the PPG waveform can be unreliable. This paper describes in detail the signal conditioning path and the modified algorithm, and it also gives an example of implementation in a resource-constrained wrist-wearable device. The algorithm was evaluated by using the publicly available PPG-DaLia dataset containing samples collected during real-life activities with a PPG sensor and accelerometer and with an ECG signal as ground truth. The quality of the results is comparable to the other algorithms from the literature, while the required hardware resources are lower, which can be significant for wearable applications.

Abstract 15830: Elevated Resting Heart Rate is Associated With Impaired Quality of Life and Worse NYHA Functional Capacity in Patients With Chronic Heart Failure: Results From REALITY HF Study

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Yuksel Cavusoglu ◽  
Omer Kozan ◽  
Ahmet Temizhan ◽  
Serdar Kucukoglu
Keyword(s):  
Quality Of Life ◽  
Heart Failure ◽  
Heart Rate ◽  
Functional Capacity ◽  
Real Life ◽  
Left Ventricular ◽  
Summary Score ◽  
Treatment Modalities ◽  
Resting Heart Rate

Purpose: Resting heart rate (HR), health related quality of life (HQoL) and NYHA functional capacity are referred as important determinants of prognosis and targets of therapy in heart failure (HF). REALITY HF (Resting Heart Rate and Real Life Treatment Modality in Outpatients with Left Ventricular Systolic Dysfunction) study data were analyzed for the evaluation of any relationship of resting HR with HQoL assessed by Kansas City Cardiomyopathy Questionnaire (KCCQ) and NYHA functional class. Methods: REALITY HF was a multicenter, prospective registry designed to evaluate HF patients’ characteristics and effects of treatment modalities on resting HR and enrolled 1057 patients (age 61±12 years) with LVEF <40%. 781 (74%) patients in sinus rhythm were included in this analysis. Patients were classified into 4 groups according to the quartiles of HR: Q1:<68 bpm (n=234), Q2:69-75 bpm (n=189), Q3:76-87 bpm (n=194) and Q4:>87 bpm (n=164). KCCQ was completed in a random sample of 320 (Q1:n=27, Q2:n=99, Q3:n=125, Q4:n=69) patients, in which higher scores show better patient’s health status. Results: During enrollment, 82% of patients were receiving ≥2 drugs including ACE[[Unable to Display Character: &#304;]]/ARB, beta blocker, aldosterone blocker, diuretic or digoxin. Resting HR was 76±14 bpm and 68% of patients had a resting HR ≥70 bpm. KCCQ overall summary score (OSC) was found to be 75.7±13.2 in those in Q1, 65.5±20.8 in Q2, 64.4±20.6 in Q3 and 58.3±21.2 in Q4 (p=0.004) and KCCQ clinical summary score (CSS) was 80.4±15.7 in those in Q1, 70.0±22.4 in Q2, 69.9±21.9 in Q3 and 63.8±23.3 in Q4 (p=0.016). Also, there was a significant negative correlation between resting HR and OSC (p=0.008) or CSS (p=0.031). The distribution of NYHA-I patients for Q1, Q2, Q3 and Q4 were 40.7%, 22.8%, 23.8% and 12.7%, NYHA-II patients-30.8%, 23.1%, 27.2% and 18.9%, NYHA-III patients-21.2%, 23.9%, 24.3% and 30.6% and NYHA-IV patients-22.7%, 34.1%, 22.7% and 20.5%, respectively (p<0.001). Also, resting HR were found to gradually and significantly increase across NYHA categories (72.8±12 bpm in NYHA-I, 76.1±13 bpm in NYHA-II, 80.2±15 bpm in NYHA-III and 78.9±16 bpm in NYHA-IV, p<0.001). Conclusions: These results suggest that elevated resting HR in HF patients is associated with impaired HQoL and worse NYHA functional capacity.

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 Camera-based heart rate estimation for hospitalized newborns in the presence of motion artifacts

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Qiong Chen ◽  
Yalin Wang ◽  
Xiangyu Liu ◽  
Xi Long ◽  
Bin Yin ◽  
...  
Keyword(s):  
Heart Rate ◽  
Body Movement ◽  
Region Of Interest ◽  
Ground Truth ◽  
Absolute Error ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Majority Voting ◽  
Thermal Cameras ◽  
Electrocardiogram Ecg

Abstract Background Heart rate (HR) is an important vital sign for evaluating the physiological condition of a newborn infant. Recently, for measuring HR, novel RGB camera-based non-contact techniques have demonstrated their specific superiority compared with other techniques, such as dopplers and thermal cameras. However, they still suffered poor robustness in infants’ HR measurements due to frequent body movement. Methods This paper introduces a framework to improve the robustness of infants’ HR measurements by solving motion artifact problems. Our solution is based on the following steps: morphology-based filtering, region-of-interest (ROI) dividing, Eulerian video magnification and majority voting. In particular, ROI dividing improves ROI information utilization. The majority voting scheme improves the statistical robustness by choosing the HR with the highest probability. Additionally, we determined the dividing parameter that leads to the most accurate HR measurements. In order to examine the performance of the proposed method, we collected 4 hours of videos and recorded the corresponding electrocardiogram (ECG) of 9 hospitalized neonates under two different conditions—rest still and visible movements. Results Experimental results indicate a promising performance: the mean absolute error during rest still and visible movements are 3.39 beats per minute (BPM) and 4.34 BPM, respectively, which improves at least 2.00 and 1.88 BPM compared with previous works. The Bland-Altman plots also show the remarkable consistency of our results and the HR derived from the ground-truth ECG. Conclusions To the best of our knowledge, this is the first study aimed at improving the robustness of neonatal HR measurement under motion artifacts using an RGB camera. The preliminary results have shown the promising prospects of the proposed method, which hopefully reduce neonatal mortality in hospitals.

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.

scholarly journals Study on the Effect of the Ambient Temperature toward the Quality of Sleep

2017 ◽  
Vol 7 (6) ◽  
pp. 2986
Author(s):  
Wira Hidayat bin Mohd Saad ◽  
Khoo Chin Wuen ◽  
Masrullizam bin Mat Ibrahim ◽  
Nor Hashimah Binti Mohd Saad ◽  
Syafeeza Binti Ahmad Radz ◽  
...  
Keyword(s):  
Heart Rate ◽  
Body Temperature ◽  
Ambient Temperature ◽  
Body Condition ◽  
Body Movement ◽  
The Body ◽  
Quality Of Sleep ◽  
Ambient Temperatures ◽  
The Right

Getting enough sleep at the right times can help in improving quality of life and protect mental and physical health. This study proposes a portable sleep monitoring device to determine the relationship between the ambient temperature and quality of sleep. Body condition parameter such as heart rate, body temperature and body movement was used to determine quality of sleep. All readings will be log into database so that users can review back and hence analyze quality of sleep. The functionality of the overall system is designed for a better experience with a very minimal intervention to the user. The simple test on the body condition (body temperature and heart rate) while asleep with several different ambient temperatures are varied and the result shows that someone has a better sleep for the temperature range of 23 to 28 degree Celsius. This can prove by lower body temperature and lower heart rate.

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