A Unique Window into the Central Nervous System
Motion is planned and initiated in the central nervous system. However, interpreting brain signals is exceptionally challenging. The activity of spinal motor neurons can be reconstructed by decomposing signals from muscles. Hence, studying muscles is a unique window into the central nervous system.
3D Ultrasound imaging
Fully automated 3D ultrasound allows a reliable reconstruction of the muscle geometry and architecture.
Biofeedback, Rehabilitation therapies as well as the adaption of active prostheses and orthoses demand a sophisticated interpretation of muscle signals. Thereby, the attachment of sensors, i.e. electrodes, comes along dealing with different impacts. Our aim is to improve the understanding of muscular activity, its conditional behavior and the source of its generation, using high-sensity electromyography (EMG). Moreover, the whole functional scope is going to be addressed by the investigation: from surface expressions to the characteristics in the central nervous system.
The EMG is a diagnostic technique to record electrical potentials from the skeletal muscle. The electromyographic signal consists of motor unit action potentials innervating the muscle fibers contributing to a comprehensive contraction using specific strategies in motor control, depending on multiple factors, as load and intention, for example. The decomposition of the signal reveals the contribution of different neural influences, like afferent sensory input, spinal and cortical shares eventually leading to a movement. Proper acquisition in experiments and reliable processing are the fundamentals of this analysis.
In biomechanical modeling of muscles, knowledge of the mechanical properties of the muscle, such as the geometry, is necessary. One widely used technique with a short acquisition time is ultrasonic imaging of the muscles. Most often, muscles are imaged with ultrasound in a two-dimensional view. There are also concepts for the three-dimensional ultrasound measurement of muscle tissue to acquire the whole muscle geometry. Here, the transducer moves along the muscle’s longitudinal axis, obtaining several transversal images that can be reconstructed into a 3D image. Although these methods show reasonable results, they are subject to various limitations, such as the need for an expensive optical motion capture system in order to know the translation and rotation between two images.
Therefore, in this project, a rig that holds the ultrasound transducer and automatically moves it to scan one whole muscle has been developed. Using encoders to track positions enables 3D ultrasound imaging without the necessity of an expensive motion capture system and other settings bound to a lab environment. This allows a controlled and reproducible ultrasound data acquisition.
Moreover, within this project, an image processing algorithm is developed and employed to compute the fascicle direction for each volume element derived from ultrasound images of the tibialis anterior muscle. This methodology enables the determination of the pennation angle in three dimensions and allows for the examination of architectural characteristics of the muscle in high contraction levels.
Furthermore, a methodology for the acquisition of volumetric ultrasound data of the tibialis anterior muscle during dynamic movement and an algorithm for 3D reconstruction of the collected dynamic images are developed. This methodology enables the investigation of shape changes of the tibialis anterior during dynamic movement.
The methods developed in this project provide a novel way to investigate muscle architecture and contraction behavior, yielding valuable additional information about muscle functionality.
Sahrmann A, Röhrle O, Handsfield G, Besier T. Ultraschallsystem, Verfahren zum Aufnehmen eines 3D- und/oder 4D-Ultraschallbilds, und Computerprogrammprodukt. Deutsches Patent- und Markenamt; 2022. DE102022206137A1.
This Terra Incognita project, funded by the University of Stuttgart, aims to investigate muscle fatigue comprehensively, integrating both central (the neural control of muscles) and peripheral (muscle energetics) aspects. The aim is to measure for the first time simultaneously:
- The neural control of muscles by decomposing high-density invasive electromyography (EMG).
- Muscle mechanics by recording joint torques.
- Muscle energetics through phosphorus magnetic resonance spectroscopy (P-MRS).
The measurements will be conducted with our collaborator, Jeroen Jeneson. Particularly challenging is the development of MR-compatible high-density EMG electrodes. Such electrodes do not exist yet. If successful, this project will improve our understanding of muscle fatigue, which is essential for the diagnosis and treatment of diseases with exercise intolerance (e.g., long covid).
