Eliminates Motion Artifacts, Enabling 5-Day sEMG Fatigue Tracking During Dynamic Movement
This technology uses a flexible, skin-like e-tattoo sensor and advanced signal processing to accurately monitor muscle fatigue during exercise, filtering out noise for reliable, multi-day tracking useful in sports, rehabilitation, and wearable robotics.
Background
Surface electromyography (sEMG) is a critical tool used to monitor muscle activation and estimate fatigue across various domains, including athletic training, physical rehabilitation, and the control of wearable robotic exoskeletons. Continuous, multi-day tracking of muscle fatigue is essential for optimizing physical performance, preventing injury, and guiding recovery protocols. To achieve this in real-world settings, there is a pressing need for wearable monitoring systems that can reliably capture physiological signals during dynamic exercises over extended periods. Such continuous monitoring requires sensors that can seamlessly integrate with the user's daily life without requiring constant recalibration or interrupting routine activities.
Despite the clear demand, current sEMG approaches face significant limitations that hinder accurate fatigue assessment. Traditional Ag/AgCl gel electrodes are prone to sensor instability and high contact impedance over time, often causing skin irritation and signal degradation during multi-day wear or exposure to moisture. Furthermore, dynamic movements introduce severe motion artifacts driven by sensor inertia and shifts at the skin-electrode interface. These mechanical disturbances, combined with impulsive noise like electrostatic bursts, result in highly nonstationary signals. This nonstationarity obscures the underlying physiological data, making it exceedingly difficult to extract stable spectral features and accurately predict fatigue levels.
Technology Description
This advanced muscle fatigue estimation solution integrates an ultrathin, skin-conformal e-tattoo sensor with a sophisticated multi-stage signal processing pipeline. The wearable hardware features a 50-µm-thick, stretchable, serpentine-patterned conductive graphite polyurethane film that adheres directly to the skin. It is paired with a compact data acquisition module that continuously samples electromyography signals. The core software component is the BH-IEEMD pipeline, which sequentially applies digital bandpass filtering, Hampel filtering for outlier suppression, and a two-pass iterative ensemble empirical mode decomposition. This architecture extracts stable physiological features, feeding them into machine learning regression models to predict fatigue levels.
This technology is highly differentiated by its ability to provide reliable, continuous multi-day monitoring during dynamic exercises without daily recalibration. Unlike traditional gel electrodes, the biocompatible e-tattoo maintains lower contact impedance over five days of continuous wear, allowing users to shower or swim without signal degradation. Furthermore, the specialized BH-IEEMD pipeline uniquely overcomes the nonstationarity and mechanical artifacts inherent in dynamic movements. By isolating true physiological muscle activation from motion-induced noise, the system significantly improves signal stationarity, resulting in highly accurate fatigue tracking for athletic training and rehabilitation.
Technologies
Benefits
- Enables continuous, multi-day wear (up to five days) without skin irritation, allowing users to comfortably perform daily activities such as showering and swimming.
- Significantly reduces motion-induced artifacts and maintains stable, low contact impedance through an ultrathin, stretchable, and skin-conformal e-tattoo design.
- Effectively isolates true physiological muscle signals from mechanical noise, impulsive spikes, and nonstationary interference during dynamic exercises using an advanced multi-stage signal processing pipeline.
- Delivers highly accurate and reliable muscle fatigue tracking with high model certainty and superior sensitivity to physiological fatigue trends.
- Elimates the need for daily sensor recalibration, providing a robust and low-maintenance solution for longitudinal monitoring.
- Offers versatile, real-world applications across athletic training, physical rehabilitation, and the control of wearable robotic exoskeletons.
Commercial Applications
- Athletic training fatigue monitoring
- Physical therapy and rehabilitation
- Wearable robotic exoskeleton control
- Industrial worker fatigue monitoring
- Military personnel fatigue tracking
Opportunity
This patent is available for exclusive licensing.
This system integrates a 50-µm-thick, serpentine-patterned graphite polyurethane e-tattoo with a BH-IEEMD signal processing pipeline. The sensor maintains stable skin-conformal contact, minimizing motion artifacts during dynamic exercise. The multi-stage architecture employs digital bandpass filtering, Hampel outlier suppression, and two-pass ensemble empirical mode decomposition with adaptive median filtering. This isolates physiological electromyography signals from nonstationary noise, enabling accurate muscle fatigue estimation via regression-based feature analysis.
Provisional patent 64/054,891 filed 04/01/26
