Human Cardiac Measurements with Diamond Magnetometers

TL;DR

This work demonstrates direct, non-invasive detection of human cardiac magnetic signals using nitrogen-vacancy centers in diamond across three independent NV-magnetometer platforms in shielded, partially shielded, and unshielded environments. By averaging over hundreds to thousands of heartbeats, the authors achieve MCG traces with sensitivities in the $6-26~\mathrm{pT}/\sqrt{\mathrm{Hz}}$ range and active sensing volumes below $0.5~\mathrm{mm}^3$, outlining a pathway toward single-shot MCG sensing. NV-based gradiometry provides efficient common-mode noise rejection, enabling operation in realistic, noisy settings and cross-validation with OPM references. The study discusses sensitivity improvements and quantum-enhanced strategies, and highlights potential extensions to MEG and non-invasive biomagnetic source localization, framing a clear route toward clinical translation and broader adoption of diamond-based biomagnetic sensing.

Abstract

We demonstrate direct, non-invasive and non-contact detection of human cardiac magnetic signals using quantum sensors based on nitrogen-vacancy (NV) centers in diamond. Three configurations were employed recording magnetocardiography (MCG) signals in various shielded and unshielded environments. The signals were averaged over a few hundreds up to several thousands of heart beats to detect the MCG traces. The compact room-temperature NV sensors exhibit sensitivities of 6-26 pT/Hz^(1/2) with active sensing volumes below 0.5 mm^3, defining the performance level of the demonstrated MCG measurements. While the present signals are obtained by averaging, this performance already indicates a clear path toward single-shot MCG sensing. To move beyond shielded environments toward practical clinical use, strong noise suppression is required. To this end, we implement NV-based gradiometry and achieve efficient common-mode noise rejection, enabled by the intrinsically small sensing volume of NV sensors. Together, these multi-platform results obtained across diverse magnetic environments provide a solid foundation for translating quantum sensors into human medical diagnostics such as MCG and magnetoencephalography (MEG).

Figures (4)

• Figure 1: Column (a) JGU: a.1): Diamond sensor head dimensions. a.2): Amplitude spectral density with a baseline of 13 pT/$\sqrt{\mathrm{Hz}}$, measured inside the shielded room of the Helmholtz Institute Mainz (JGU). a.3): ECG trace and diamond MCG signal (12000 averages) with indications of the main components of the ECG, P wave, QRS complex and T wave. Column (b) ZAQuant: b.1): Sensor schematic. b.2): Measured amplitude spectral densities inside the partially shielded environment, showing a noise baseline of 7 pT/$\sqrt{\mathrm{Hz}}$. b.3): ECG trace and averaged diamond MCG signal (300 averages). Column (c) Q.ANT: a.1): Sensor design. a.2): Amplitude spectral density with a baseline of 26 pT/$\sqrt{\mathrm{Hz}}$; filters were applied during acquisition. .3): ECG trace and diamond MCG signal (2000 averages).
• Figure 2: a) OPM array with sensor labeling and its position on the subject's chest. The position of the diamond sensor measurements are indicated as the white dots on the torso. b) The 47 different OPM MCG signals after band-pass filtering and averaging 100 times. The color overlay indicates the amplitude of the QRS complex. A and B mark the positions of the diamond sensor measurements. c) Schematic of the JGU sensor [photographs shown in Fig.\ref{['fig:1']} a)] with indication of the main components. Working principle and more details can be found in zulfpaper. PBS: Polarizing beam splitter. d) The resulting OPM, ECG, and diamond signal traces for MCG signal detection at the positions of A and B with respect to the OPM array.
• Figure 3: a) Time-domain traces from the two diamond sensors of ZAQuant used to characterize gradiometry performance, (“right” sensor in blue, “left” sensor in orange) together with their differential signal (green), recorded under different background-coil magnetic fields. Inset: Schematic illustrating the two diamond sensors, used to assess the gradiometric performance. b) Zoomed in differential signal time trace. c) Amplitude spectral density corresponding to the three magnetic traces shown in panel (a).
• Figure 4: Comparison of sensors used for MCG detection, including the present work, characterized by their sensitivity and a representative linear dimension of the sensing volume. Green: JGU, purple: ZAQuant, brown: Q.ANT, SQUID Matlashov2011, OPM Alem2023OPMMEG