ArticleIEEE sensors journal2018
Universal Pre-Ejection Period Estimation Using Seismocardiography: Quantifying the Effects of Sensor Placement and Regression Algorithms.
Article in IEEE sensors journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 30 citations in OpenAlex.
- Pragmatic Models for Detection of Hypertension Using Ballistocardiograph Signals and Machine Learning.Bioengineering (Basel, Switzerland) · 2025Article
- From video to vital signs: a new method for contactless multichannel seismocardiography.NPJ cardiovascular health · 2025Article
- Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions.Sensors (Basel, Switzerland) · 2024Article
- A Wavelet-Based Approach for Motion Artifact Reduction in Ambulatory Seismocardiography.IEEE journal of translational engineering in health and medicine · 2024Article
- Synthetic seismocardiogram generation using a transformer-based neural network.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Monitoring of Cardiorespiratory Parameters during Sleep Using a Special Holder for the Accelerometer Sensor.Sensors (Basel, Switzerland) · 2023Article
- Wearable Cuff-Less Blood Pressure Estimation at Home via Pulse Transit Time.IEEE journal of biomedical and health informatics · 2021Article
- Non-Invasive Wearable Patch Utilizing Seismocardiography for Peri-Operative Use in Surgical Patients.IEEE journal of biomedical and health informatics · 2021Article
- Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor.IEEE journal of biomedical and health informatics · 2021Article
- Analysis of Cardiac Vibration Signals Acquired From a Novel Implant Placed on the Gastric Fundus.Frontiers in physiology · 2021Article
- Cardiovascular adaptation to simulated microgravity and countermeasure efficacy assessed by ballistocardiography and seismocardiography.Scientific reports · 2020Article
- Modeling Consistent Dynamics of Cardiogenic Vibrations in Low-Dimensional Subspace.IEEE journal of biomedical and health informatics · 2020Article
- Ballistocardiogram signal processing: a review.Health information science and systems · 2019Review
- Recent Advances in Seismocardiography.Vibration · 2019Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Seismocardiography (SCG), the measurement of local chest vibrations due to the heart and blood movement, is a non-invasive technique to assess cardiac contractility via systolic time intervals such as the pre-ejection period (PEP). Recent studies show that SCG signals measured before and after exercise can effectively classify compensated and decompensated heart failure (HF) patients through PEP estimation. However, the morphology of the SCG signal varies from person to person and sensor placement making it difficult to automatically estimate PEP from SCG and electrocardiogram signals using a global model. In this proof-of-concept study, we address this problem by extracting a set of timing features from SCG signals measured from multiple positions on the upper body. We then test global regression models that combine all the detected features to identify the most accurate model for PEP estimation obtained from the best performing regressor and the best sensor location or combination of locations. Our results show that ensemble regression using XGBoost with a combination of sensors placed on the sternum and below the left clavicle provide the best RMSE = 11.6 ± 0.4 ms across all subjects. We also show that placing the sensor below the left or right clavicle rather than the conventional placement on the sternum results in more accurate PEP estimates.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.