Contactless heart rate variability measurement by IR and 3D depth sensors with respiratory sinus arrhythmia

Bakhtiyari, Kaveh; Beckmann, Nils; Ziegler, Jürgen

doi:10.1016/j.procs.2017.05.319

Cited by 16 publications

(7 citation statements)

References 9 publications

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“…Nevertheless, HRV seemed to be forgotten in the next decade, as it was not adopted for risk stratification by any guidelines on STEMI, non-ST segment elevation myocardial infarction (NSTEMI), or chronic coronary syndromes [25][26][27][28][29]. The enthusiasm for HRV evaluation was raised once more advanced technology became available, including different sensors and wearable devices, allowing a more straightforward measurement of various HRV parameters, even in a contactless way [30][31][32].…”

Section: Discussionmentioning

confidence: 99%

Measuring Heart Rate Variability in Patients Admitted with ST-Elevation Myocardial Infarction for the Prediction of Subsequent Cardiovascular Events: A Systematic Review

et al. 2021

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Ischemic heart disease represents the leading cause of death, emphasizing risk stratification and early therapeutic intervention. Heart rate variability (HRV), an indirect marker of autonomic nervous system activity, was investigated extensively as a risk factor for adverse cardiovascular events following acute myocardial infarction. Thus, we systematically reviewed the literature to investigate the association of HRV parameters with mortality and adverse cardiovascular events in patients presenting with ST-elevation myocardial infarction (STEMI). Following the search process in the MEDLINE (PubMed), Embase, and Cochrane databases, nine studies were included in the final analysis. Lower time-domain HRV parameters and a higher ratio between power in the low-frequency (LF) band and power in the high-frequency (HF) band (LF/HF) were associated with higher all-cause mortality during follow-up, even in patients treated mainly with percutaneous coronary interventions (PCI). Although most studies measured HRV on 24 h ECG recordings, short- and ultra-short-term measures (1 min and 10 s, respectively) were also associated with an increased risk of all-cause mortality. Although data were discrepant, some studies found an association between HRV and cardiac mortality, reinfarction, and other major adverse cardiovascular events. In conclusion, HRV measurement in patients with STEMI could bring crucial prognostic information, as it was associated with an increased risk of all-cause mortality documented in clinical studies. More and larger clinical trials are required to validate these findings in contemporary patients with STEMI in the context of the new generation of drug-eluting stents and current antithrombotic and risk-modifying therapies.

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Section: Discussionmentioning

confidence: 99%

Measuring Heart Rate Variability in Patients Admitted with ST-Elevation Myocardial Infarction for the Prediction of Subsequent Cardiovascular Events: A Systematic Review

et al. 2021

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“…However, the KLT feature tracking algorithm was used to track the feature points, and tracking was not performed using depth information. Bakhtiyari et al [3] also proposed a method for improving the HR measurement accuracy by measuring respiratory signals using an MS Kinect2. In this method, HR was measured using both RGB and depth image sequences.…”

Section: Related Workmentioning

confidence: 99%

PPG3D: Does 3D head tracking improve camera-based PPG estimation?

Nagamatsu

Nowara

Pai

et al. 2020

2020 42nd Annual International Conference of the IEEE Engineering in Medicine &Amp; Biology Society (EMBC)

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Over the last few years, camera-based estimation of vital signs referred to as imaging photoplethysmography (iPPG) has garnered significant attention due to the relative simplicity, ease, unobtrusiveness and flexibility offered by such measurements. It is expected that iPPG may be integrated into a host of emerging applications in areas as diverse as autonomous cars, neonatal monitoring, and telemedicine. In spite of this potential, the primary challenge of non-contact camera-based measurements is the relative motion between the camera and the subjects. Current techniques employ 2D feature tracking to reduce the effect of subject and camera motion but they are limited to handling translational and in-plane motion. In this paper, we study, for the first-time, the utility of 3D face tracking to allow iPPG to retain robust performance even in presence of out-of-plane and large relative motions. We use a RGB-D camera to obtain 3D information from the subjects and use the spatial and depth information to fit a 3D face model and track the model over the video frames. This allows us to estimate correspondence over the entire video with pixel-level accuracy, even in the presence of out-of-plane or large motions. We then estimate iPPG from the warped video data that ensures per-pixel correspondence over the entire window-length used for estimation. Our experiments demonstrate improvement in robustness when head motion is large.

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“…Three-dimensional optical systems have found popularity in numerous fields of application spanning from robotics [1], automotive [2], industrial [3], mechanical engineering and cultural heritage [4,5], to the biomedical field [6,7,8]. Their success is mainly due to recent developments, which have allowed the creation of devices that are less expensive, yet accurate and compact.…”

Section: Introductionmentioning

confidence: 99%

Metrological and Critical Characterization of the Intel D415 Stereo Depth Camera

Carfagni

Furferi

Governi

et al. 2019

Sensors

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Low-cost RGB-D cameras are increasingly being used in several research fields, including human–machine interaction, safety, robotics, biomedical engineering and even reverse engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras have proven to be among the most suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e., ~160–10,000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations for the RealSense D415. In particular, tests are carried out to assess the device performance in the near range (i.e., 100–1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e., the German VDI/VDE 2634 Part 2) with a number of literature-based strategies. Performance analysis is finally compared against the latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in reverse engineering applications.

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Contactless heart rate variability measurement by IR and 3D depth sensors with respiratory sinus arrhythmia

Cited by 16 publications

References 9 publications

Measuring Heart Rate Variability in Patients Admitted with ST-Elevation Myocardial Infarction for the Prediction of Subsequent Cardiovascular Events: A Systematic Review

Measuring Heart Rate Variability in Patients Admitted with ST-Elevation Myocardial Infarction for the Prediction of Subsequent Cardiovascular Events: A Systematic Review

PPG3D: Does 3D head tracking improve camera-based PPG estimation?

Metrological and Critical Characterization of the Intel D415 Stereo Depth Camera

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