Evaluation of fatigue progression during overhead tasks and the effects of exoskeleton assistance

Abstract

Upper-limb occupational exoskeletons reduce injuries during overhead work. Previous studies focused on muscle activation with and without exoskeletons, but their impact on shoulder fatigue remains unclear. Additionally, no studies have explored how exoskeleton support levels affect fatigue. This study investigates the effects of assistive profiles on muscular and cardiovascular fatigue. Electromyographic (EMG) and electrocardiographic signals were collected to compute EMG median frequency (MDF), heart rate (HR), and heart rate variability (HRV). Fatigue was assessed using three MDF and HR metrics: relative change (,), slope (,), and intercept (,) of the linear regression. Results showed decreased 64% (p = 0.0020) with higher assistance compared to no exoskeleton; decreased 40% (p < 0.0273) with lower assistance, decreased up to 67% (p = 0.0039) and by 43% (p < 0.0098) with higher and medium assistance. HRV metrics included root mean square of successive differences (RMSSD) and low-frequency to high-frequency power ratio (LF/HF). RMSSD indicated parasympathetic dominance, while rising LF/HF ratio suggested physiological strain. Findings support occupational exoskeletons as ergonomic tools for reducing fatigue.

Keywords: biomechanics; exoskeletons; human-robot interaction.

Figure 1.

Experimental setup and protocol. (a) The participant wearing the exoskeleton during the experiment. (b) Overview of experimental protocol. (c) Representation of sensor placement. (d) Raw physiological signals.

Figure 2.

Schematic representation of data processing. (a) Generalized flowchart for processing physiological signals, applicable to both electromyographic (EMG) and electrocardiographic (ECG) data. (b) A graphical representation showing the signal processing steps, with EMG data used as an example: (a) Filtering the EMG signal to remove noise. (b) Dividing the filtered data into windows and calculating EMG parameters from each window. (c) Removing outliers and applying smoothing to the EMG parameters. (d) Performing linear regression and comparing the initial and final data points of the EMG parameters. (e) Computing evaluation metrics. The same steps were applied to the ECG data, but evaluation metrics were computed only from heart rate.

Figure 3.

Normalized median frequency (MDF) profiles averaged across all participants during the overhead screwing experiment, shown for the left and right anterior deltoid (AD) and the left and right posterior deltoid (PD) muscles. Shaded area represents standard deviation, while the lines indicate the moving average applied to the MDF values.

Figure 4.

Relative change in median frequency (MDF). Results are shown for left and right anterior deltoid (AD) and left and right posterior deltoid (PD) muscles. Anti-gravitational support values provided by the exoskeleton are reported as median values across all participants. Plus marks represent the outlier in the data. Bars represent the change across conditions, and asterisks mark statistically significant differences between conditions. Percentage differences are reported compared to the no exoskeleton (NO EXO) condition.

Figure 5.

Median frequency slope values for all tested conditions (NO EXO, EXO L, EXO M, EXO H) for left and right anterior deltoid (AD) and left and right posterior deltoid (PD) muscles. Anti-gravitational support values provided by the exoskeleton are reported as median values across all participants. Bars represent the change across conditions, and asterisks mark statistically significant differences between conditions. Percentage differences are reported compared to the no-exoskeleton condition.

Figure 6.

Median frequency intercept values for all tested conditions (NO EXO, EXO L, EXO M, EXO H) for left and right anterior deltoid (AD) and left and right posterior deltoid (PD) muscles. Anti-gravitational support values provided by the exoskeleton are reported as median values across all participants. Bars represent the change across conditions, and asterisks mark statistically significant differences between conditions. Percentage differences are reported compared to the NO EXO condition.

Figure 7.

Analysis of cardiovascular fatigue under no exoskeleton (NO EXO) and exoskeleton conditions (EXO L, EXO M, and EXO H). (a) Normalized heart rate (HR) profiles (as %) averaged across all participants during the overhead screwing experiment for all tested conditions. Shaded area represents the standard deviation, while the lines indicate the moving average applied to the HR data. Evaluation metrics of HR under varying levels of anti-gravitational support are shown aggregated across all subjects: (b) relative change in HR, (c) slope of the linear fit on HR, and (d) intercept of the linear fit on HR. Anti-gravitational support values provided by the exoskeleton are reported as median values (both sides). Bars represent the change across conditions and asterisks mark statistically significant differences between conditions. Percentage differences are reported compared to the NO EXO condition.

Figure 8.

Representation of heart rate variability. The figure shows normalized root mean square of successive differences (RMSSD) and low-frequency to high-frequency power ratio (LF/HF) profiles (as %) averaged across all participants (a–b). The shaded area represents the standard deviation, while the lines indicate the moving average applied to the data.