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Page 12 of 26 Chang et al. Soft Sci. 2026, 6, 29

load progressive/ return-to-activity protocols [121] .At present, detection relies primarily on spot testing of
serum or fingertip/urine samples; non-invasive, continuous wearable monitoring remains immature. A more
realistic approach involves using microneedle patches to collect interstitial fluid, combined with
immunoelectrochemical or coupled enzyme activity colorimetry, as a phased retesting tool during
post-match and recovery periods. Within the continuous training-competition-recovery [122] , Mb for early
screening within hours and CK for progression assessment within 24-72 hours are recommended,
[47]
alongside joint interpretation with continuous signals like sEMG [123] . Decisions on load adjustment and
return to exercise should be based on individual baselines and relative changes. Limitations such as minimal
invasiveness, time lag and individual differences require attention. Overall, this approach is best positioned
as research/quasi-implementation, serving as a structural supplement to continuous signals .
[124]

For inflammatory regulation monitoring
During the entire cycle of muscle fatigue injury and repair, inflammation-related factors, such as
Interleukin-6 (IL-6), and transforming growth factor-β (TGF-β), exhibit phased dynamic changes along the
temporal axis of “injury initiation-inflammatory response-tissue remodeling”. These temporal patterns
provide critical biological insights for evaluating muscle inflammatory states and determining repair
processes at the molecular level . Among them, IL-6, a prototypical pro-inflammatory cytokine, serves as
[125]
an indicator of early post-injury inflammatory activation, while TGF-β modulates tissue remodeling during
the middle stage phase. Together, these cytokines form key molecular targets for monitoring the
inflammation-repair process. Current wearable technologies for detecting inflammatory factors utilize ISF as
the primary sample [118,126] .Through electrochemical (e.g., amperometric, potentiometric) or optical (e.g.,
fluorescence quenching, colorimetric) techniques, these devices convert biomolecular binding events -
between inflammatory factors and their recognition elements - into quantifiable electrical or optical signals.
This approach enables highly selective capture of inflammatory factors such as IL-6 and TGF-β, minimizing
interference from other body fluids constituents .
[127]
Wearable monitoring of inflammatory factors remains in the stage of application expansion and
experimental verification, yet to reach practical implementation. Overcoming technical bottlenecks would
enable it to complement existing metabolic dimension (e.g., sweat lactic acid) and mechanical (e.g., muscle
strength and stiffness) indicators already in preliminary use, addressing the gap in molecular-level
monitoring of muscle inflammatory states [128] . This advancement would further strengthen the evidence
chain for comprehensive assessment of muscle fatigue, injury, and repair cycles, offering a more robust
molecular foundation for precise interventions - such as optimizing anti-inflammatory timing and refining
rehabilitation protocols.

Despite the progress achieved so far, wearable biochemical sensing still faces inherent challenges. Analyte
levels in sweat or interstitial fluid may not directly reflect blood concentrations due to compartmental
differences and temporal delays, while low biomarker abundance increases susceptibility to noise and
cross-reactivity. Signal stability can also be affected by sweat variability, biofouling, and calibration drift,
particularly during dynamic exercise. Therefore, current wearable biochemical sensors are better suited for
trend monitoring rather than definitive diagnostic use.

Wearable biomechanical sensors
For muscle strength and dynamic kinematics assessment
The direct measurement of narrow “muscle strength” - such as isokinetic and isometric contraction force -
relies on gold standards instruments including isokinetic force gauges, isometric force gauges and handgrip
force gauges [129,130] . These tools offer high objectivity and repeatability while providing core metrics like peak
muscles contraction force . For dynamic tasks involving complex movements (e.g., running, jumping and
[131]