Application of Biomedical Signal Acquisition Equipment in Human Sport Heart Rate Monitoring

Aiming at exploring biomedical signal acquisition equipment used in human motion heart rate monitoring, the research on the related hardware design and signal processing method was carried out. A biomedical signal acquisition device based on photoplethysmography (PPG) is designed, and the equipment was applied to acquire PPG signals and acceleration sensor signals under different motion states. The analysis of the experimental data showed that, the fusion method of the acceleration sensing information in the motion artifact removal method is perfected. The effectiveness of the baseline drift removal algorithm, motion artifact removal algorithm and dynamic heart rate monitoring algorithm was verified by reconstructing the signal quality evaluation index. To sum up, taking MINDRAY VS-800 as a reference device, it is compared with the adaptive filtering technology in terms of signal quality, BPM detection results and algorithm complexity, and better results are finally obtained.

Download Full-text

Intrapartum signal quality with external fetal heart rate monitoring – A two way trial of external Doppler CTG ultrasound and the abdominal fetal electrocardiogram

Zeitschrift für Geburtshilfe und Neonatologie ◽

10.1055/s-0031-1293272 ◽

2011 ◽

Vol 215 (S 01) ◽

Author(s):

J Reinhard ◽

BR Hayes-Gill ◽

S Schiermeier ◽

W Hatzmann ◽

TM Heinrich ◽

...

Keyword(s):

Heart Rate ◽

Fetal Heart Rate ◽

Fetal Heart ◽

Signal Quality ◽

Heart Rate Monitoring ◽

Fetal Electrocardiogram ◽

Fetal Heart Rate Monitoring

Download Full-text

Design of a New Long-Time Continuous Photoplethysmography Signal Acquisition System to Obtain Accurate Measurement of Heart Rate

ASME 2020 29th Conference on Information Storage and Processing Systems ◽

10.1115/isps2020-1916 ◽

2020 ◽

Author(s):

Rajeev Kumar Pandey ◽

Jerry Lin ◽

Paul C.-P. Chao

Keyword(s):

Heart Rate ◽

Signal To Noise Ratio ◽

Moving Average ◽

Motion Artifact ◽

Acquisition System ◽

Experimental Result ◽

Signal Acquisition ◽

Readout System ◽

Long Time ◽

Filter Signal

Abstract This study presents a time-interleave and low DC drift long-time continuous photoplethysmography (PPG) signal acquisition system to obtain accurate measurement of heart rate (HR) in real-time. Time-interleave functionality is used herein to minimize the mispositioning issue. Intensity tuning and transimpedance amplifier gain tuning is used herein to acquire a high-quality PPG signal. The front-end analog readout circuit is designed and implemented by using T18 process. The experimental result shows that the design readout system has the DC settling time of 1 second after the motion artifact. The measured current sensing range is 30nA–10uA. The estimated signal to noise ratio is 68dB@1Hz. The backend pre-signal processing incorporates a new convolution-based moving average filter, signal quality index estimator, and a peak-through detector. The non-invasive PPG sensor is applied to the wrist artery of the 40 healthy subjects for sensing the pulsation of the blood vessel. During the measurement, the subject did not drink (alcohol), eat, smoke or workout. The Measurement results shows that the heart rate accuracy and standard error are 95%, and 0.37±1.96bpm, respectively.

Download Full-text

Motion Artifact Removal in Ambulatory ECG Signal for Heart Rate Variability Analysis

IEEE Sensors Journal ◽

10.1109/jsen.2019.2939391 ◽

2019 ◽

Vol 19 (24) ◽

pp. 12432-12442 ◽

Cited By ~ 4

Author(s):

Deepak Berwal ◽

Vandana C.R. ◽

Sourya Dewan ◽

Jiji C.V. ◽

Maryam Shojaei Baghini

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Motion Artifact ◽

Heart Rate Variability Analysis ◽

Ecg Signal ◽

Artifact Removal ◽

Variability Analysis ◽

Ambulatory Ecg

Download Full-text

Heart Rate Monitoring During Intense Physical Activities Using a Motion Artifact Corrupted Signal Reconstruction Algorithm in Wearable Electrocardiogram Sensor

2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) ◽

10.1109/chase.2016.8 ◽

2016 ◽

Cited By ~ 2

Author(s):

S. M. A. Salehizadeh ◽

Y. Noh ◽

K. H. Chon

Keyword(s):

Heart Rate ◽

Signal Reconstruction ◽

Reconstruction Algorithm ◽

Motion Artifact ◽

Physical Activities ◽

Heart Rate Monitoring

Download Full-text

Experimental Study on Biomedical Signal Acquisition of Sports Fatigue

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2020.2949 ◽

2020 ◽

Vol 10 (4) ◽

pp. 884-889

Author(s):

Mingli Chi

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Maximal Exercise ◽

Processing System ◽

Future Application ◽

Signal Acquisition ◽

Biomedical Signal ◽

Fatigue Exercise ◽

Exercise Induced ◽

Exercise Fatigue

To explore the biomedical signal acquisition of sports fatigue, the Pclab-UE biomedical signal acquisition and processing system is used to collect and process heart rate variability (HRV) automatically after quiet and fatigue exercise. In the meanwhile, the experimental data are analyzed. The heart rate variability of the subjects is recorded, aiming to provide experimental evidence for the future application of HRV in the diagnosis of exercise fatigue. Moreover, it also provides a noninvasive diagnostic index for exercise fatigue and exercise training practice. The research results showed that, the HRV values in the sub-maximal exercise caused fatigue. The maximal exercise induced fatigue is significantly decreased and there are significant differences. As a result, it is summed up that we can use HRV as a quantitative analysis index for the diagnosis of sports fatigue.

Download Full-text

Heart Rate Monitoring Using Motion Artifact Modeling with MISO Filters

Journal of the Institute of Electronics and Information Engineers ◽

10.5573/ieie.2015.52.8.018 ◽

2015 ◽

Vol 52 (8) ◽

pp. 18-26 ◽

Cited By ~ 1

Author(s):

Sunho Kim ◽

Jungsub Lee ◽

Hyunil Kang ◽

Baeksan Ohn ◽

Gyehyun Baek ◽

...

Keyword(s):

Heart Rate ◽

Motion Artifact ◽

Heart Rate Monitoring

Download Full-text

A Novel Adaptive Recursive Least Squares Filter to Remove the Motion Artifact in Seismocardiography

Sensors ◽

10.3390/s20061596 ◽

2020 ◽

Vol 20 (6) ◽

pp. 1596 ◽

Cited By ~ 1

Author(s):

Shuai Yu ◽

Sheng Liu

Keyword(s):

Heart Rate ◽

Least Squares ◽

Motion Artifact ◽

Recursive Least Squares ◽

Detection Accuracy ◽

Artifact Removal ◽

Ecg Signals ◽

The Right ◽

Electrocardiogram Ecg ◽

Recursive Least Squares Filter

This paper presents a novel adaptive recursive least squares filter (ARLSF) for motion artifact removal in the field of seismocardiography (SCG). This algorithm was tested with a consumer-grade accelerometer. This accelerometer was placed on the chest wall of 16 subjects whose ages ranged from 24 to 35 years. We recorded the SCG signal and the standard electrocardiogram (ECG) lead I signal by placing one electrode on the right arm (RA) and another on the left arm (LA) of the subjects. These subjects were asked to perform standing and walking movements on a treadmill. ARLSF was developed in MATLAB to process the collected SCG and ECG signals simultaneously. The SCG peaks and heart rate signals were extracted from the output of ARLSF. The results indicate a heartbeat detection accuracy of up to 98%. The heart rates estimated from SCG and ECG are similar under both standing and walking conditions. This observation shows that the proposed ARLSF could be an effective method to remove motion artifact from recorded SCG signals.

Download Full-text