Fig. 1: Overview of the MAP for fatigue profiling. | Nature Sensors

Fig. 1: Overview of the MAP for fatigue profiling.

From: Meta-topological hydrogel enables multisource and frequency-tailored artefact mitigation for bioelectronics

Fig. 1: Overview of the MAP for fatigue profiling.The alternative text for this image may have been generated using AI.

a, Impact of fatigue including economic loss, health issues and safety accidents, where the area associated with each factor represents its relative magnitude of impact. b, Illustration of the metahydrogel platform that collects electrophysiological and haemodynamic information and performs machine learning powered fatigue evaluation. c, Working mechanism of metahydrogel for collecting targeted signals and attenuating concomitant artefacts. Left: mechanical interference is blocked and dissipated by local resonance. Right: biopotential artefacts are filtered through frequency-selective ionic mobility, as solvation reconstruction dynamics do not respond at EMG frequencies. Schematics in b created in BioRender: brain, Tian, G. https://biorender.com/odm98mm (2026); spinal cord, Tian, G. https://biorender.com/ckttg2c (2026); heart, Tian, G. https://biorender.com/2540e4r (2026); vessel, Tian, G. https://biorender.com/hl83bbg (2026).

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