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Page 10 of 26 Chang et al. Soft Sci. 2026, 6, 29

Ultra-sensitivity;
~ 0.08 Lab validation
Optical immunoassay 20 min 0-10 pg/mL 100 pg/mL Low Intracellular detection; NA [82]
8
nm/decade only
Real-time
Design
Biomechanical Muscle strength Bioelectrical signal ~ 0.0061 2 s 0-20 kg 2.5 kg Medium Low impedance; complexity; Lab High [84]
sensors acquisition mV/kg Wireless
validation only
Ultra-compliance; High Lab validation
Piezoelectricity (Strain) ~ 0.066 V/% NA -30%-30% NA Medium High [85]
repeatability only
Micro electro mechanical Ease to use; Clinical Design
Tissue stiffness ~ 0.04 μV/kPa 1 min 0-1600 kPa 25 kPa Medium Medium [86]
systems validation complexity
Small-lesion;
~ 0.125 Fabrication
Piezoelectricity 1 min 0-160 kPa 8 kPa Medium Real-time; Clinical Low [87]
μV/kPa complexity
validation
~ 0.085 Depth-sensitivity; Lab validation
Elastography 0.6 ms 0-1532 kPa 88 kPa Medium High [88]
/(m·kPa) Motion-tolerance only
Fabrication
Near-infrared spectroscopy ~ 0.35 Hz/kPa 0.3 s 0-800 kPa 20 kPa Medium High spatial resolution complexity; Lab High [89]
validation only
Note: Technological maturity is evaluated as high (product available), medium (human validation available), and low (prototype only). Comfort is classified is evaluated as high, medium, and low based on the skin conformability
of the device (influenced by size, weight, substrate stiffness and mechanical structure design). sEMG: Surface electromyography; Mb: myoglobin; CK: creatine kinase; IL-6: Interleukin-6; TGF-β: transforming growth factor-β; NA:
not available.

Nevertheless, sEMG and ECG signals are susceptible to electrode placement variability, cross-talk, and motion artifacts, which may affect reproducibility and
quantitative consistency across individuals and during dynamic activities. Thus, current bioelectrical wearables are better suited for relative, qualitative monitoring
rather than absolute, quantitative measurement.

Wearable biochemical sensors
The balance between energy substrate consumption and synthesis, along with the level of inflammatory response, constitutes a key dimension for assessing the extent of
muscle fatigue, damage, and repair efficiency [105] . Core biomarkers reflecting this balance encompass reserved glycogen, lactate, LDH, UN, Mb, CK and IL-6. These
biomarkers are present in blood, sweat, and interstitial fluid, with their concentration dynamics exhibiting significant cross-correlations [106,107] . Therefore, measurements
obtained from sweat or interstitial fluid can be utilized to estimate their corresponding levels in blood, thereby providing a non‑invasive or minimally invasive
analytical approach for evaluating muscle metabolic status.