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Chang et al. Soft Sci. 2026, 6, 29 Page 7 of 26

As for the dynamic variations of muscle stiffness, it drastically soars to a peak value when fatigue or injury
takes place . This can be explained by the abnormal internal structures, where either muscle fiber damage
[63]
or inflammation-induced tissue swelling (accumulated with interstitial fluids and inflammatory mediators)
stiffens the muscle with reduced elasticity . After the inflammation subsides, the swelling of muscle tissue
[58]
gradually relieves by the synergy of transporting, processed and neutralizing the excessive interstitial fluid
and inflammatory mediators with body’s drainage and immune systems. In this way, the mechanical
property of muscle restores, presenting as a soft and elastic tissue [64,65] .

Multimodal interpretation of transitions between muscle states across temporal scales
Muscle fatigue, injury and recovery represent a continuous physiological spectrum rather than strictly
separated phases . Currently, there exist no universally accepted quantitative thresholds that allow any
[24]
indicators alone to definitively classify these processes. Instead, differentiation relies on the interpretation of
multimodal physiological patterns, temporal evolution, and the reversibility of functional changes.

Muscle fatigue is primarily characterized as a functional and reversible decline in performance capacity
without substantial structural disruption . Reported indicators typically demonstrate transient alterations,
[66]
such as decreased MF and increased RMS in sEMG, elevated metabolic load reflected by increased lactate
levels, and minor short-term changes in muscle stiffness. These signals generally return toward baseline
following adequate rest . By integrating neuromuscular, metabolic, and mechanical indicators over short
[67]
time scales and assessing their rapid reversibility relative to individualized baselines, wearable systems can
infer fatigue as a transient functional deviation rather than structural impairment.

Muscle injury involves structural disruption at the myofiber or extracellular matrix level . In contrast to
[59]
fatigue, injury is often associated with persistent strength loss, increased muscle stiffness, prolonged
inflammation, and elevations in biochemical markers (such as CK) that indicate muscle membrane
damage . Existing biomarkers may reveal indirect manifestations of injury through abnormal motor unit
[68]
recruitment patterns, sustained asymmetry in movement biomechanics, reduced contractile efficiency, and
prolonged deviations from baseline functional metrics . When multimodal signals demonstrate
[69]
cross-domain abnormalities that persist across extended time scales and fail to recover following rest, it may
suggest transition from functional fatigue to structural injury.

Muscle recovery or healing reflects a dynamic remodeling process characterized by progressive
normalization of bioelectrical, biochemical, and biomechanical parameters. Monitoring these markers during
healing may reveal gradual restoration of neuromuscular coordination, reduction of inflammatory signals,
recovery of muscle oxygen utilization efficiency, and stabilization of mechanical properties such as stiffness
and strength . Longitudinal multimodal tracking enables quantification of recovery trajectories, where
[70]
coordinated normalization across neuromuscular, mechanical, and metabolic domains over intermediate
time scales indicates progression from injury toward functional recovery.

Therefore, rather than relying on single-parameter thresholds, current evidence supports a potentially
feasible, pattern-based interpretation framework combining bioelectrical, biochemical, mechanical, and
temporal features to infer transitions among fatigue, injury, and healing states [71-73] [Table 1].

WEARABLE SENSORS FOR MUSCLE HEALTH MONITORING
Wearable sensors have become a promising route for realizing continuous, real-time and non-invasive
monitoring of muscle functional status in the field of sports and rehabilitation [56,57] [Table 2]. To enable
meaningful interpretation of wearable-derived signals in muscle health monitoring, it is essential to