Quantifying upper-limb muscle fatigue using wearable sEMG: A systematic review and direction-of-effect analysis

Muscle fatigue experienced in the upper limb immensely influences the effectiveness of rehabilitation, workplace ergonomics, and the efficiency of human-machine interactions. However, it remains inadequately monitored in practical contexts due to the absence of a thorough, continuous, and unbiased assessment tool. Wearable surface Electromyography (sEMG) is valuable for evaluating muscle fatigue in real-time, yet inconsistent research undermines result reliability and comparability. This systematic review addresses this gap by critically synthesising experimental studies on wearable sEMG-based upper-limb muscle fatigue assessment and evaluating the consistency of reported fatigue-related signal changes. Following the PRISMA 2020 framework, 15 studies were included after screening 912 studies published from 2016 to 2026. Extracted data encompassed feature domains, task protocols, definitions of fatigue, and methodologies for validation. Due to heterogeneity and incomplete statistical reporting, a pooled meta-analysis was not feasible; instead, a direction-of-effect synthesis was performed on studies reporting explicit feature-level changes. Across the examined studies, Time-domain metrics were reported the most (13/15), then frequency-domain metrics (8/15), and finally temporal/non-linear metrics (4/15). Amplitude-based features increased in 80% (8/10), while frequency-domain features decreased in around 86% (6/7). Temporal and non-linear features exhibited variable behaviour across tasks, with studies primarily in healthy populations and lacking clinical validation. sEMG-derived features correlate with muscle fatigue, yet the evidence strength is limited by small sample sizes, methodological variability, and unweighted vote-counting synthesis. Findings remain descriptive and cautiously interpreted. This review underscores constraints, inconsistencies in standardization, and investigation of sensing technologies, underscoring the necessity for uniform protocols and validation within clinical cohorts.