JMIR Publications

ABSTRACT

Background:

Passive exoskeletons are implemented in occupational settings to reduce physical strain and muscle activity during demanding tasks. Surface electromyography (sEMG) is commonly used to quantify these effects, but sEMG signal acquisition in exoskeleton applications is often compromised by mechanical artifacts from exoskeleton–sensor interaction. Existing standards for sEMG electrode placement and data processing rarely address these challenges. Additionally, extensive signal filtering can remove relevant muscle activity information.

Objective:

This experimental study aimed to evaluate custom 3D-printed covers (‘boxes’) for dry sEMG electrodes, designed to protect sensors from simulated exoskeleton related perturbations. We hypothesized that these covers would reduce motion artifacts and improve signal integrity without affecting skin physiology.

Methods:

Twenty-three healthy adults participated. Dry sEMG electrodes (Delsys Trigno Mini/ Avanti) were attached to the right and left vastus medialis muscles. A 3D printed cover (‘small Box or large Box’ depending on sensor size) was attached to the skin over the sensors. Each participant performed knee extension tasks under six conditions, combining two cover states (NoBox, Box) and three types of mechanical perturbation (none, vertical load, lateral load). Loads of 3.35 kg simulated typical exoskeleton-induced disturbances. sEMG data were rectified and normalized to maximal voluntary contraction (%MVC). Signal quality was evaluated using RMS amplitude in %MVC, standard deviation, frequency-domain SNR via fast Fourier transformation (FFT), and time synchronization using dynamic time warping (DTW). Skin temperature and electrical resistance due to skin moisture were monitored. Linear mixed-effects models and paired t-tests were used for analysis.

Results:

Application of the boxes resulted in reduced mean muscle activation during mechanical perturbations (vertical: –3.61% MVC, lateral: –2.17% MVC; both P <.001), lower within-trial variability (e.g., lateral perturbation ΔSD: –5.86, P <.001), and higher SNR compared to uncovered conditions (ΔSNR up to +1.10, P <.001). Skin temperature, resistance, and baseline noise were not influenced by the box (all P  >.05). The large cover yielded inconsistent results, with some reduction in variability during perturbation (lateral ΔSD: –2.86, P <.001), but lower SNR and more variability in unperturbed trials compared to NoBox.

Conclusions:

The small 3D-printed box stabilizes the sEMG signal by mechanically shielding the sensor from external disturbances and reducing motion artifacts. Consistency and reliability of sEMG recordings are enhanced without negatively affecting local skin temperature and resistance. The medical adhesive, used to attach the box to the skin, further improves signal quality by limiting lateral dissipation and providing a localized measurement area beneath the box. In contrast, inadequate anatomical fit of the large box may introduce additional variability rather than reduce disturbances. Our study demonstrates that a small, anatomically designed protective cover can effectively reduce motion artifacts and improve sEMG signal quality during mechanical perturbations, without interfering with physiological skin parameters. This approach represents a promising method for enhancing the reliability of sEMG measurements in exoskeleton studies. Clinical Trial: German Clinical Trials Register (Germany), DRKS00035777; https://drks.de/search/en/trial/DRKS00035777