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Background: Heart failure (HF) is the leading cause of hospitalization in individuals over 65 years of age. Identifying noninvasive methods to detect HF may address the epidemic of HF. Seismocardiography which measures cardiac vibrations transmitted to the chest wall has recently emerged as a promising technology to detect HF., Objectives: In this multicenter study, the authors examined whether seismocardiography using commercially available smartphones can differentiate control subjects from patients with stage C HF., Methods: Both inpatients and outpatients with HF were enrolled from Finland and the United States. Inpatients with HF were assessed within 2 days of admission, and outpatients were assessed in the ambulatory setting. In a prespecified pooled data analysis, algorithms were derived using logistic regression and then validated using a bootstrap aggregation method., Results: A total of 217 participants with HF (174 inpatients and 172 outpatients) and 786 control subjects from cardiovascular clinics were enrolled. The mean age of participants with acute HF was 64 ± 13 years, 64.9% were male, left ventricular ejection fraction was 39% ± 15%, and median N-terminal pro-B-type natriuretic peptide was 5,778 ng/L (Q1-Q3: 1,933-6,703). The majority (74%) of participants with HF had reduced EF, and 38% had atrial fibrillation. Across both HF cohorts, the algorithms had an area under the receiver operating characteristic curve of 0.95 with a sensitivity of 85%, specificity of 90%, and accuracy of 89% for the detection of HF, with a decision threshold of 0.5. The positive and negative likelihood ratios were 8.50 and 0.17, respectively. The accuracy of the algorithms was not significantly different in subgroups based on age, sex, body mass index, and atrial fibrillation., Conclusions: Smartphone-based assessment of cardiac function using seismocardiography is feasible and differentiates patients with HF from control subjects with high diagnostic accuracy. (Recognition of Heart Failure With Micro Electro-mechanical Sensors FI; NCT04444583; Recognition of Heart Failure With Micro Electro-mechanical Sensors [NCT04378179]; Detection of Coronary Artery Disease With Micro Electro-mechanical Sensors; NCT04290091)., Competing Interests: Funding Support and Author Disclosures This work was funded by a grant from the European Innovation Council (phase 2 funding 954566), Novartis Pharma, and Cardiosignal. Drs Santalahti, Pänkäälä, Kaisti, Dehkordi, Koivisto, and Blomster are employed by CardioSignal. Dr Haddad has received research grants from CardioSignal (REFLECS study), Janssen (computational approaches in pulmonary hypertension), Verily (Project Baseline Health Study), and the National Institutes of Health. Dr Saraste has received grants from the Finnish Foundation for Cardiovascular Research, the Academy of Finland, and Turku University Hospital, and consultancy or speaker fees from Abbott, AstraZeneca, Bayer, Novartis, and Pfizer, all outside of the submitted work. Dr Knuuti has received a personal research grant from the Finnish Foundation for Cardiovascular Research, a research grant from the Finnish State Research Funding, consultancy fees from GE Healthcare and Synektik, and speaker fees from GE Healthcare, Bayer, Lundbeck, Boehringer Ingelheim, Pfizer, Siemens, and Merck, outside of the submitted work. Dr Mahaffey has received research grants or contracts from AHA, Apple, Bayer, California Institute Regenerative Medicine, CSL Behring, Eidos, Ferring, Gilead, Google (Verily), Idorsia, Johnson & Johnson, Luitpold, Novartis, PAC-12, Precordior, and Sanifit; has received consulting or other income from Applied Therapuetics, Bayer, BMS, BridgeBio, CSL Behring, Elsevier, Fosun Pharma, Human, Johnson & Johnson, Moderna, Myokardia, Novartis, Novo Nordisk, Otsuka, Phasebio, Portola, Quidel, and Theravance; and has equity in Human, Medeloop, Precordior, and Regencor. Dr Blomster has received honoraria from Novo Nordisk and Boehringer Ingelheim. Drs Blomster, Koivisto, Pänkäälä, and Santalahti have equity in Precordior/CardioSignal., (Copyright © 2024. Published by Elsevier Inc.)

The right internal jugular vein is connected to the right atrium of the heart via the superior vena cava, and consequently its pressure, known as the jugular venous pressure or the jugular venous pulse (JVP), is an important indicator of cardiac function. The JVP can be estimated visually from the neck but it is rather difficult and imprecise. In this article we propose a method to measure the JVP using a motion sensor patch attached to the neck. The JVP signal was extracted from the sensor's 3-axes gyroscope signal and aligned with simultaneously measured ECG and seismocardiogram signals.The method was tested on 20 healthy subjects. The timings of the characteristic JVP waves were compared with the ECG R peaks and seismocardiogram heart sounds S1 and S2. The JVP was reliably measured from 18 subjects with all three waves identified. The timings of the waves were also physiologically plausible when compared to the ECG R peak and the heart sounds. Importantly, the JVP was also found to modulate with respiration, further indicating that the measured signal was indeed the JVP and not the carotid pulse.The results show that the JVP can be measured with a wearable patch-like device registering the delicate motions of the right internal jugular vein. The method has potential to be developed into a clinical tool to measure cardiac health in diseases such as heart failure and chronic obstructive pulmonary disease (COPD).Clinical relevance-The developed method could enable an affordable measurement of clinically important cardiac parameter, jugular venous pulse, as a part of a routine examination.