Periodic Reporting for period 1 - qMOTION (Simulation-enhanced High-density Magnetomyographic Quantum Sensor Systems for Decoding Neuromuscular Control During Motion)
Reporting period: 2022-09-01 to 2025-02-28
Being able to decode neural signals that control skeletal muscles with high accuracy will enable scientific breakthroughs in diagnostics and treatment, including early detection of neurodegenerative diseases, optimising personalised treatment or gene therapy, and assistive technologies like neuroprostheses. This breakthrough will require technology that is able to record signals from skeletal muscles in sufficient detail to allow the morpho-functional state of the neuromuscular system to be extracted. No existing technology can do this. Measuring the magnetic field induced by the flow of electrical charges in skeletal muscles, known as Magnetomyography (MMG), is expected to be a game-changing technology because magnetic fields are not attenuated by biological tissue. However, the extremely small magnetic fields involved require extremely sensitive magnetometers. The only promising option is novel quantum sensors, such as optically pumped magnetometers (OPMs), because they are small and modular. Our vision is to use this technology and our expertise in computational neuromechanics to decode, for the first time, neuromuscular control of skeletal muscles based on in vivo, high-density MMG data. For this purpose, we will design the first high-density MMG prototype and develop custom calibration techniques. We will record magnetic fields induced by skeletal muscles and combine them with the advanced computational musculoskeletal system models, which will allow us to derive robust and reliable source localisation and separation algorithms.
Benchmarking experiments: MMG and EMG are complementary modalities for recording the electrical activity of muscles. In contrast to EMG, however, MMG has not been well explored. With the qMOTION project, we investigate whether MMG can provide new insights into neuromuscular physiology that are not accessible by EMG. For this purpose, it is essential to measure MMG and EMG simultaneously at the highest resolution and quality currently possible. This includes special non-magnetic EMG electrodes. Ultimately, we want to record benchmark data sets that compare the performance of MMG and EMG for decoding human motion.
Modelling and simulation: Simulations provide insights into MMG signals that would not be easily possible experimentally. Most importantly, simulations can precisely define muscular activation, tissue properties, and measurement accuracy. These factors usually lead to significant uncertainties in experimental data. In addition, labelled data sets can be generated to test and benchmark signal processing algorithms, such as motor unit decomposition or inverse modelling-based imaging.
Phantom fibre measurements: OPM-MMG is a novel methodology, and its limitations are not well explored. The quantification of data uncertainty during benchmark experiments and well-calibrated sensors is essential for the accuracy of MMG-based biomedical applications. To address this, a device called the "Phantom Fiber" is being developed to simulate the magnetic field of a muscle fiber during contraction to calibrate and verify sensor setups containing multiple OPMs.
Benchmarking experiments: MMG and EMG are complementary modalities for recording the electrical activity of muscles. In contrast to EMG, however, MMG has not been well explored. With the qMOTION project, we investigate whether MMG can provide new insights into neuromuscular physiology that are not accessible by EMG. For this purpose, it is essential to measure MMG and EMG simultaneously at the highest resolution and quality currently possible. This includes special non-magnetic EMG electrodes. Ultimately, we want to record benchmark data sets that compare the performance of MMG and EMG for decoding human motion.
Modelling and simulation: Simulations provide insights into MMG signals that would not be easily possible experimentally. Most importantly, simulations can precisely define muscular activation, tissue properties, and measurement accuracy. These factors usually lead to significant uncertainties in experimental data. In addition, labelled data sets can be generated to test and benchmark signal processing algorithms, such as motor unit decomposition or inverse modelling-based imaging.
Phantom fibre measurements: OPM-MMG is a novel methodology, and its limitations are not well explored. The quantification of data uncertainty during benchmark experiments and well-calibrated sensors is essential for the accuracy of MMG-based biomedical applications. To address this, a device called the "Phantom Fiber" is being developed to simulate the magnetic field of a muscle fiber during contraction to calibrate and verify sensor setups containing multiple OPMs.
The primary technical activity of the qMOTION project is the development of a novel measurement system prototype to overcome the fundamental physical limitations of electromyography (EMG). Traditional EMG signals are distorted and smeared as they pass through biological tissue, making it difficult to accurately identify individual neural commands. The project’s core scientific approach is a "simulation-enhanced" strategy that tightly integrates advanced computational modeling with new hardware based on high-sensitivity quantum sensors, such as optically pumped magnetometers (OPMs).
The project's main achievement to date is the foundational in silico validation of its central hypothesis. A key simulation study (published) provided the first quantitative, theoretical proof that high-density magnetomyography (HD-MMG) is superior to high-density EMG for the critical task of motor unit decomposition. By modeling the propagation of both electric and magnetic fields, the study demonstrated that the magnetic signal remains largely unperturbed by tissue, enabling a significantly more accurate reconstruction of the underlying neural commands. This crucial result, published with its full replication data, de-risked the project's core premise before significant investment in hardware development.
In parallel, the project has pursued two other key technical streams. Firstly, it has contributed to advancing the enabling hardware by investigating the optimization of quantum sensors for the unique demands of biomagnetic measurements. Secondly, it has strengthened its computational framework by refining the underlying biological models. This includes a simulation study that elucidated complex neuronal behaviors, thereby increasing the fidelity and predictive power of the project's simulations.
Moving from theory to practice, the project has achieved several major technical milestones. A key development has been the construction of a physical "phantom fiber" device, a novel tool designed specifically for the calibration and benchmarking of OPM arrays for MMG. Building on this, we conducted the first multi-OPM measurements on muscles within the world-class magnetically shielded room at the PTB in Berlin, marking a critical step toward experimental validation. The most significant hardware achievement is the construction and testing of the first high-density OPM-MMG prototype device, incorporating more than 80 OPMs.
The project's main achievement to date is the foundational in silico validation of its central hypothesis. A key simulation study (published) provided the first quantitative, theoretical proof that high-density magnetomyography (HD-MMG) is superior to high-density EMG for the critical task of motor unit decomposition. By modeling the propagation of both electric and magnetic fields, the study demonstrated that the magnetic signal remains largely unperturbed by tissue, enabling a significantly more accurate reconstruction of the underlying neural commands. This crucial result, published with its full replication data, de-risked the project's core premise before significant investment in hardware development.
In parallel, the project has pursued two other key technical streams. Firstly, it has contributed to advancing the enabling hardware by investigating the optimization of quantum sensors for the unique demands of biomagnetic measurements. Secondly, it has strengthened its computational framework by refining the underlying biological models. This includes a simulation study that elucidated complex neuronal behaviors, thereby increasing the fidelity and predictive power of the project's simulations.
Moving from theory to practice, the project has achieved several major technical milestones. A key development has been the construction of a physical "phantom fiber" device, a novel tool designed specifically for the calibration and benchmarking of OPM arrays for MMG. Building on this, we conducted the first multi-OPM measurements on muscles within the world-class magnetically shielded room at the PTB in Berlin, marking a critical step toward experimental validation. The most significant hardware achievement is the construction and testing of the first high-density OPM-MMG prototype device, incorporating more than 80 OPMs.
The results from the qMOTION project promise transformative impacts across science, medicine, and technology. By enabling the high-fidelity, non-invasive decoding of neural signals, the technology could spark scientific breakthroughs in understanding motor control and neuromuscular diseases. In clinical medicine, its potential is profound, offering a path to sensitive biomarkers for the early detection of neurodegenerative conditions like ALS and a tool for objectively personalizing treatments. Furthermore, it could revolutionize assistive technologies, potentially paving the way for a new generation of intuitive, high-dexterity neuroprostheses controlled by clean neural signals.
To ensure this potential is realized, several key needs must be addressed. The methodology is still brand new and on a basic science level, but with the potential to become a disruptive technology. For this, however, much further (basic) research is critical, specifically the transition from simulation to in vivo human trials and demonstration through benchmarking experiments. The development of standardized calibration tools, like the project's "phantom fiber" device, is essential for ensuring reliability and forming a basis for a future standardization framework. For long-term clinical uptake, the project will require pathways for commercialization, IPR support, and navigation of regulatory approvals. The project's main outcome is the creation of a validated, new technological platform for neuromuscular analysis.
To ensure this potential is realized, several key needs must be addressed. The methodology is still brand new and on a basic science level, but with the potential to become a disruptive technology. For this, however, much further (basic) research is critical, specifically the transition from simulation to in vivo human trials and demonstration through benchmarking experiments. The development of standardized calibration tools, like the project's "phantom fiber" device, is essential for ensuring reliability and forming a basis for a future standardization framework. For long-term clinical uptake, the project will require pathways for commercialization, IPR support, and navigation of regulatory approvals. The project's main outcome is the creation of a validated, new technological platform for neuromuscular analysis.