The DIAQNOS project, short for DIAmond-based Quantum Sensing for NeurOSurgery, is funded by the German Federal Ministry of Research, Technology, and Space and coordinated in Mainz by Dr. Arne Wickenbrock. The research was carried out in the group of Prof. Dr. Dmitry Budker, a member of the PRISMA++ Cluster of Excellence and the Helmholtz Institute Mainz. The coordinating author of the new paper, doctoral student Muhib Omar, developed the quantum sensor during his doctoral research. According to Wickenbrock, the results are the product of more than ten years of development work, and the team works closely with neurosurgeons to ensure that the technologies do not remain confined to the laboratory but find clear practical applications. The primary goal, he explained, is to build highly sensitive sensors that function outside the laboratory and can fulfill important societal needs.

The heart of the technology lies in a remarkable defect of the diamond crystal lattice. A nitrogen vacancy center forms when a vacancy sits directly next to a nitrogen atom that has been incorporated into the diamond in place of a carbon atom. These atomic-scale defects possess energy levels that respond to their surroundings, and by interrogating them optically and with microwaves, researchers can measure magnetic fields, electric fields, temperature, and mechanical stress with extraordinary precision. Because the diamond host is chemically inert and biocompatible, and because the quantum states of NV centers can be read out at ambient conditions, the platform has long been viewed as a candidate for bringing quantum sensing out of shielded laboratory basements and into hospitals.

To prove that the concept could withstand the rigors of real biomagnetic measurement, the DIAQNOS consortium deployed three magnetometer systems developed independently by its partners: Johannes Gutenberg University Mainz, the Universities of Stuttgart and Freiburg, and the startup Q.ANT GmbH. Each system was used to measure the heart’s magnetic field, and the fact that three independently engineered instruments converged on the same physiological signals demonstrated that quantum technologies in Germany are ready to take the important step toward medical applications. The exercise also identified the improvements still needed before clinical deployment. The fiber-based NV-diamond magnetometer built by the Mainz group was designed as a portable endoscope and operates without a magnetic bias field, in contrast to the other two systems, which use such fields to filter out magnetic interference from the environment.

Understanding why this matters requires a look at how heart activity is measured today. The two common methods are electrocardiography and magnetocardiography. Electrocardiography, the ubiquitous ECG, uses electrode patches applied to the patient’s skin to detect the electrical activity within the heart. It is inexpensive and widely used, but it is susceptible to the differing conductivity of body tissues, and certain medical scenarios, such as burn wounds, can make it impossible to place electrodes on the skin at all. Magnetocardiography, by contrast, detects the magnetic fields produced by the heart’s electrical currents. It requires no contact with the skin and is only minimally influenced by tissue conductivity, but because the signals are vanishingly weak, the method has historically depended on costly and complex instruments such as superconducting quantum interference devices, known as SQUIDs, and optically pumped magnetometers, or OPMs.

The diamond-based system offers an alternative with several significant advantages over existing magnetocardiographic approaches. The most striking is size: the Mainz sensor is a truncated diamond pyramid with a volume of less than 0.5 cubic millimeters, small enough to be easily transported and positioned. Unlike SQUID-based systems, which require liquid-helium cooling, and unlike many OPMs, which rely on heated vapor cells, NV magnetometers operate at room temperature. That means they can be placed directly on the patient’s skin at any desired location, which opens the possibility of more precise mapping of biomagnetic signals. Potential applications include three-dimensional reconstruction of the heart’s electrical conduction system and the measurement of fetal heart activity, a task that is notoriously difficult with conventional electrodes because the fetal signal is buried within the maternal one. Wickenbrock summarized the appeal succinctly: NV magnetometers are characterized by fast initialization, excellent biocompatibility, and stable operation over a wide temperature range, making them particularly attractive for biomedical applications.

The study is candid about the remaining hurdles. NV diamond magnetometers still trail SQUIDs and OPMs in raw sensitivity and signal-to-noise ratio, a performance gap that must be closed before they can match the diagnostic quality of established instruments. Yet the researchers argue that the gap is bridgeable, and their strategy rests on a unique combination of wide dynamic range, noise suppression, and scalable geometry. Because the detectors are so compact, they can be combined with signal-enhancement mechanisms that could lift their performance to ECG-like quality. The most prominent of these are flux concentrators: engineered magnetic structures that gather and concentrate magnetic flux within the diamond, thereby amplifying the signals the NV centers detect. Thanks to the small sensor volume, amplifications of more than a factor of 100 can be achieved, and the development of flux concentrators that function at room temperature is one of Omar’s main research focuses. Adapting magnetic structures to optimally concentrate the field lines from a source within the diamond, he noted, is the path to bringing these quantum technologies into practical use.

The same compactness enables a second powerful trick: gradiometry. By pairing two spatially separated sensors and measuring the difference between their readings, a gradiometer rejects distant, spatially uniform interference while remaining sensitive to nearby sources such as the heart. This differential scheme supports intraoperative nerve monitoring in unshielded environments, a capability of direct interest to surgical teams. It also facilitates the noninvasive separation of maternal and fetal heart signals for prenatal monitoring, since the two sources occupy different positions and therefore produce different field gradients at the sensors. In surgical oncology as well, gradiometric readout offers a route to detecting subtle biomagnetic contrasts without the shielding infrastructure that conventional magnetometry demands.

Perhaps the most ambitious horizon lies in the brain. Magnetoencephalography, the magnetic analogue of measuring brain activity, currently requires either cryogenic SQUID arrays fixed in helmet-like dewars or, more recently, OPM arrays that still demand careful magnetic shielding. NV gradiometers could enable portable magnetoencephalography systems that operate at room temperature, which would open new possibilities for neurological diagnostics and for next-generation brain-computer interfaces. A wearable, unshielded brain imager would transform the study and treatment of conditions ranging from epilepsy, which the Mainz team explicitly cites as a target, to a broad spectrum of cognitive and movement disorders. The DIAQNOS project’s name reflects this ambition: the collaboration was conceived from the outset with neurosurgery in mind, and the cardiac measurements reported in Science Advances serve as a rigorous demonstration that the sensors can resolve genuine biomagnetic signals in practice, not merely in principle.

The study, titled Human Cardiac Measurements with Diamond Magnetometers and published on 16 September 2026, arrives at a moment when quantum sensing is moving rapidly from laboratory curiosity toward commercial and clinical reality. The convergence of three independently built instruments on the same cardiac signals suggests that the underlying physics is robust and the engineering reproducible. Challenges certainly remain: sensitivity must improve, flux concentrators must be perfected, and regulatory pathways for clinical use must be navigated. But the trajectory is clear. A sensor smaller than a grain of sand, needing no cooling, no shielding, and no skin contact, that can listen to the magnetic signature of a beating heart represents exactly the kind of quiet revolution that quantum technology has promised. If the Mainz group and its partners can close the remaining performance gap, the faint magnetic echo of every heartbeat may soon become as routine a diagnostic signal as the electrical spike that has dominated cardiology for a century.

Subject of Research: Nitrogen vacancy diamond quantum magnetometers for measuring human cardiac biomagnetic signals

Article Title: Diamond magnetometers can open a new window into heart activity

Article References: Diamond magnetometers can open a new window into heart activity. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: diamond magnetometers, nitrogen vacancy centers, quantum sensing, magnetocardiography, biomagnetic signals, heart activity, DIAQNOS, Science Advances, flux concentrators, gradiometry, medical diagnostics, brain-computer interfaces

Magnetocardiography, or MCG, is the magnetic sibling of the electrocardiogram. Where ECG electrodes record the voltages cardiac cells impress on the skin, MCG magnetometers record the magnetic fields generated by the same ionic currents. Because magnetic fields traverse biological tissue largely indifferent to the wildly different conductivities of muscle, fat, lung, and blood, MCG can carry information complementary to the ECG about how activation waves sweep through the heart. The catch is magnitude. Superconducting quantum interference devices — SQUIDs — the workhorses of MCG for half a century, achieve sensitivities of roughly one femtotesla per root hertz, but only at the price of cryogenic cooling. The insulated Dewar vessels holding their cryogens must stand between sensors and body, pushing the detectors centimeters from the heart and forcing engineers to arrange them in a flat plane facing the chest. That planar geometry was never really chosen; it was inherited from the physics of keeping superconductors cold. And it came at a cost: sources far from that plane — above all the heart’s posterior wall — are the ones a flat array struggles to localize.

The mathematical obstacle is the inverse problem: reconstructing the three-dimensional distribution of current sources inside the heart from magnetic measurements made outside the body. The problem is famously ill-posed, admitting no unique solution and amplifying noise and modeling errors without mercy. Recent advances in quantum sensing have loosened the hardware’s grip on geometry. Optically pumped magnetometers, which read magnetic fields through the spin states of atoms in a vapor cell, and nitrogen-vacancy diamond magnetometers both operate without cryogenic cooling, permitting sensors to be placed closer to the body and at positions and angles a SQUID Dewar forbids. Earlier theoretical studies had hinted that posterior or multiplane measurements might improve reconstruction, but experimental validation remained scarce, because array geometry was hard to vary in a real system. The Tokyo team hypothesized that a cylindrical array enclosing the torso would sample the cardiac magnetic field more informatively than a planar one, particularly for deep or posterior activity, and set out to test the idea at three levels of realism: simulation, a tissue-mimicking phantom, and living animals.

The foundation was a numerical model built from magnetic resonance imaging of a ten-week-old male rat. Using 3D Slicer, the researchers segmented the heart, lungs, and torso into boundary surfaces and assigned conductivities of 0.239, 0.067, and 0.033 siemens per meter respectively. They then solved the MCG forward problem with the boundary element method, using the Helsinki BEM Framework to compute the external field via the Geselowitz quasistatic formulation, in which the measured field is a superposition of the primary current generated by cellular electrical activity and secondary return currents that accumulate on tissue boundaries of differing conductivity. Against this model they pitted two geometries with matched projected areas: a planar array of 49 points on a 30-by-60-millimeter rectangle, and a cylindrical array of 48 points on a cylinder 30 millimeters long with a 30-millimeter radius. Five families of test dipoles — vertical, tangential, horizontal, radial, and randomly oriented — each comprising 100 sources of 1000 nanoampere-meters distributed through the heart region, were split into front-side and back-side groups relative to the cardiac midline, and Gaussian noise of 3 and 10 picotesla was injected to probe two signal-to-noise regimes.

The simulations delivered a consistent verdict. Signal-to-noise ratios fell with distance for both arrays, and radial dipoles, which generate little or no external magnetic field, were consistently the hardest to detect. For sources on the front of the heart, the planar array held a modest SNR edge; for back-side sources, the cylinder won. Crucially, the cylindrical array produced smaller average localization errors than the planar array across every tested distance and orientation, with the gap widening for back-side and deeper sources and for vertically oriented dipoles in particular, while radial dipoles grew markedly more error-prone under high noise. The most counterintuitive finding concerned goodness of fit, the standard measure of how well a reconstructed source explains the data. The planar array often posted slightly higher GOF values than the cylinder — even for back-side sources the cylinder localized far better. The authors’ explanation is subtle: a planar array by itself cannot fully distinguish the magnetic field patterns of dipoles at different locations, so a fit can look deceptively good while pointing to the wrong place. A high goodness of fit, in short, is not the same as a correct answer.

To confirm the effect in physical reality, the team built a rat-sized wet phantom: a cylindrical container filled with 0.9 percent saline of conductivity 0.21 siemens per meter, housing a physical single-dipole source — a small coil with exposed contacts roughly four millimeters apart, driven by a 20-hertz, five-volt sinusoidal voltage producing a dipole moment of approximately 860 nanoampere-meters, near the simulated value. Measurements were made inside a four-layer permalloy magnetically shielded room using four Quspin Gen-3 dual-axis optically pumped magnetometers. Because only four sensors existed, the researchers engineered a custom non-magnetic scanning apparatus — motors mounted outside the shielded room, motion transmitted mechanically — that rotated the subject for cylindrical sampling and translated it for planar mapping, reconstructing dense arrays from sequential positions. After averaging 500 cycles at each point, the cylindrical configuration localized the phantom’s source to within about 1.9 millimeters, versus roughly 13.0 millimeters for the planar array — even though the planar fit was nominally slightly better, with goodness-of-fit values of 0.94 against 0.91. Strikingly, the cylinder’s error was smaller than in simulation, while the planar array performed comparably to its simulated results.

The decisive test came in living animals. The team recorded MCG from five healthy, ten-week-old male rats, anesthetized with 1.5 to 2 percent isoflurane, hearts beating at six to seven hertz, positioned prone at the phantom’s distances: planar at 28 millimeters, cylinder at 32-millimeter radius. Each point was recorded for about two minutes, the electrocardiogram’s R-peak serving as a timing trigger to average 500 heartbeats per position — a strategy that sacrificed simultaneity for signal-to-noise. Magnetometers were recalibrated before every point, and anesthesia was managed to keep physiology stable. When the researchers applied single-dipole fitting to the R-wave of the averaged signals, both arrays placed the source broadly in the lower ventricular free wall and apex of the rat heart, consistent with known R-wave activation. But the cylinder’s simulated advantage did not clearly materialize: some cylindrical estimates landed outside the heart model altogether, and the cylindrical array showed lower goodness-of-fit values in every measurement, sometimes below 0.7 while the planar array stayed above 0.9. The reason, the authors argue, lies in the source model rather than the sensor geometry. Normal ventricular activation is spatially distributed — a coordinated depolarization wave sweeping across the myocardium — and cannot be honestly compressed into a single point.

The team therefore turned to a distributed model better matched to the biology. They placed 500 fixed source locations one millimeter beneath the heart model’s surface, each modeled as a freely oriented current dipole, and estimated their moments with minimum norm estimation — an L2-norm inverse solution stabilized by zero-order Tikhonov regularization, with the regularization parameter scaled to the lead-field matrix’s singular values. Reconstructed maps from both arrays concentrated around the lower ventricular and apical regions, matching previously reported rat activation patterns. Yet the two geometries told different stories. The cylindrical array consistently assigned more reconstructed amplitude to the posterior heart, pushing the source-weighted center — the amplitude-weighted centroid of the map — deeper along the anterior-posterior axis than the planar array did. Data fits were high for both, mostly above 0.95, and source entropy, a Shannon-entropy gauge of spatial concentration, differed only slightly between them. Repeatability separated the arrays most sharply: across five repeated measurements per animal, the cylindrical array’s source maps correlated with one another at values generally above 0.8, exceeding the planar array’s consistency in four of five rats. The cylinder, in short, produced a more stable picture of activity the flat array could barely resolve.

The researchers also confronted a blind spot in their own hardware. An optically pumped magnetometer’s vapor cell is physically large compared with a rat’s heart, so treating each sensor as an ideal point measurement could distort the comparison. Modeling each channel instead as eight integration points spread across the sensor’s actual volume increased absolute errors for both arrays, but the ratio of cylindrical to planar median error shifted only from about 0.46 to 0.48. The geometry effect was no artifact of idealized point sensors.

The implications extend beyond rats. For decades, SQUID-based MCG systems have sampled the chest from the front and little else, and few studies have asked what posterior coverage might add. By binding simulation, phantom validation, and in vivo measurement into one matched framework, the Tokyo group has created an experimental platform for vetting array designs before committing them to hardware. The authors caution that their cylindrical configuration cannot simply be scaled to humans, whose torso geometry, feasible array radii, and sensor-source distances differ substantially, and they are candid about its simplifications: a heart model without chamber-level segmentation, a torso truncated above and below the cardiac region, a single-layer phantom, sequential rather than simultaneous sampling, biaxial rather than triaxial sensor data, and healthy animals in normal rhythm — the least favorable condition for focal source localization. Localized activation patterns such as premature ventricular contractions, or controlled disease models, would offer cleaner tests. Yet the central message stands: when it comes to reading the heart’s magnetic secrets, wrapping around the problem sees more than staring at it from one side.