SMARTSENS has led to breakthroughs in neuromechanical sensing, modeling, and human-machine interfacing.
1) Novel HD-EMG Decomposition for Dynamic Movements:
Prior to SMARTSENS, fully validated decomposition algorithms existed only for isometric (static) contractions, significantly limiting their applicability to real-world human movement. SMARTSENS is the first to validate that individual motor unit discharges—previously measurable only in tightly controlled conditions—can now be extracted during functional, whole-body activities like locomotion. This is a fundamental step forward in human neurophysiology, as it enables, for the first time, the study of how populations of motor neurons coordinate muscle contractions in the context of natural tasks such as walking, running, or stair climbing. This capability is essential for understanding movement disorders, optimizing rehabilitation strategies, and designing assistive technologies that respond intelligently to the user’s neural intent.
2) New Spinal Motor Neuron and Reflex Models for Torque Estimation:
SMARTSENS introduced sensor-driven models of spinal motor neuron pools, capable of simulating how thousands of spinal neurons collectively generate musculoskeletal force. These models integrate information from HD-EMG signals to estimate the activity of individual neurons, including their recruitment thresholds, firing behavior, and reflex contributions. Importantly, this improves the accuracy of reconstructing ankle torque during movement. This is crucial for understanding how the nervous system translates cellular-level activity into joint-level function.
3) Non-Invasive Neural Control of Assistive Robots
SMARTSENS validated these models within fully wearable systems, including soft exosuits, powered orthoses, and bionic leg prostheses. By embedding EMG sensors and neuromuscular models into wearable robots, the project demonstrated real-time, volitional control of assistive devices. This establishes a new class of non-invasive, neural human-machine interfaces (HMIs), capable of decoding intent from spinal neurons and converting it into movement assistance in real-world settings. This development is especially relevant for people with limb loss, neuromuscular diseases, or age-related mobility decline, offering them the possibility of enhanced autonomy and function through wearable neuroprostheses.
