Flexible electromyography sensor with in situ gelation hydrogel for early diagnosis of lumbar spine diseases

Mingxuan Zhang , Mingming Hao , Guoqiang Ren , Yinchao Zhao , Chujie Lv , Yizhang Xia , Wei Wang , Wei Chen , Yi Chen , Lianhui Li , Qifeng Lu , Ting Zhang

InfoMat ›› 2025, Vol. 7 ›› Issue (12) : e70066

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InfoMat ›› 2025, Vol. 7 ›› Issue (12) :e70066 DOI: 10.1002/inf2.70066
RESEARCH ARTICLE
Flexible electromyography sensor with in situ gelation hydrogel for early diagnosis of lumbar spine diseases
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Abstract

Prolonged sitting is a major risk factor for lumbar spine disorders, significantly affecting both physical and mental health. However, conventional clinical diagnosis primarily relies on imaging evaluations conducted after symptom onset, often missing opportunities for early intervention and allowing for disease progression. To address this, this paper presents a diagnostic method based on electromyography (EMG) using an adaptive flexible electromyography sensor (FES). The FES consists of a thermo-responsive in situ gelation hydrogel and flexible mesh electrode patch. The hydrogel undergoes a sol–gel transition at body temperature, enabling conformal skin contact and strong adhesion. As a result, the adhesion of the FES is 15 times stronger than that of conventional EMG electrodes. Consequently, the contact impedance is significantly reduced to 40 kΩ/cm2 at 10 Hz, and a high signal-to-noise ratio of 23.28 dB is achieved, allowing for the effective monitoring of subtle electrophysiological signals during prolonged sitting. Overall, this research provides a foundation for the early-stage diagnosis of lumbar disorders, facilitating the transition of lumbar disease management from reactive treatment to proactive prevention.

Keywords

early diagnosis / EMG signals / flexible electromyography sensors / in-situ gelation hydrogel / prolonged sitting

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Mingxuan Zhang, Mingming Hao, Guoqiang Ren, Yinchao Zhao, Chujie Lv, Yizhang Xia, Wei Wang, Wei Chen, Yi Chen, Lianhui Li, Qifeng Lu, Ting Zhang. Flexible electromyography sensor with in situ gelation hydrogel for early diagnosis of lumbar spine diseases. InfoMat, 2025, 7(12): e70066 DOI:10.1002/inf2.70066

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References

[1]

Christensen SWMP, Palsson TS, Krebs HJ, Graven-Nielsen T, Hirata RP. Prolonged slumped sitting causes neck pain and increased variocoupler muscle activity during a computer task in healthy participants-a randomized crossover study. Appl Ergon. 2023;110:104020.

[2]

De Carvalho DE, de Luca K, Funabashi M, et al. Association of exposures to seated postures with immediate increases in back pain: a systematic review of studies with objectively measured sitting time. J Manipulative Physiol Ther. 2020;43(1):1-12.

[3]

Boukabache A, Preece SJ, Brookes N. Prolonged sitting and physical inactivity are associated with limited hip extension: a cross-sectional study. Musculoskelet Sci Pract. 2021;51:e102282.

[4]

Lis AM, Black KM, Korn H, Nordin M. Association between sitting and occupational LBP. Eur Spine J. 2007;16(2):283-298.

[5]

Park JH, Srinivasan D. The effects of prolonged sitting, standing, and an alternating sit-stand pattern on trunk mechanical stiffness, trunk muscle activation and low back discomfort. Ergonomics. 2021;64(8):983-994.

[6]

Sasiadek M, Jackow-Nowicka J. Degenerative disease of the spine: how to relate clinical symptoms to radiological findings. Adv Clin Exp Med. 2024;33(1):91-98.

[7]

Deer T, Sayed D, Michels J, Josephson Y, Li S, Calodney AK. A review of lumbar spinal stenosis with intermittent neurogenic claudication: disease and diagnosis. Pain Med. 2019;20-(Supplement_2):S32-S44.

[8]

Szpalski M, Gunzburg R. Lumbar spinal stenosis in the elderly: an overview. Eur Spine J. 2003;12(Supplement_2):S170-S1775.

[9]

Wei B, Wu H. Study of the distribution of lumbar modic changes in patients with low back pain and correlation with lumbar degeneration diseases. J Pain Res. 2023;16(2023):3725-3733.

[10]

Chen C, Xiao B, He X, Wu J, Li W, Yan M. Prevalence of low back pain in professional drivers: a meta-analysis. Public Health. 2024;231(Supplement_1):23-30.

[11]

Ferreira ML, De Luca K, Haile LM. Global, regional, and national burden of low back pain, 1990-2020, its attributable risk factors, and projections to 2050: a systematic analysis of the global burden of disease study 2021. Lancet Rheumatol. 2023;5(6):e316-e329.

[12]

Eldabe S, Nevitt S, Bentley A, et al. Network meta-analysis and economic evaluation of neurostimulation interventions for chronic nonsurgical refractory back pain. Clin J Pain. 2024;40(9):507-517.

[13]

Channak S, Spekle EM, van der Beek AJ, Janwantanakul P. The effectiveness of a dynamic seat cushion in preventing neck and low-back pain among high-risk office workers: a 6-month cluster-randomized controlled trial. Scand J Work Environ Health. 2024;50(7):55-566.

[14]

Merlo JK, da Silva AV, Casonatto J, et al. Effects of a mat pilates exercise program associated with photobiomodulation therapy in patients with chronic nonspecific low back pain: a randomized, double-blind, sham-controlled trial. Healthcare (Basel). 2024;12(14):16.

[15]

Hoffeld K, Lenz M, Egenolf P, et al. Patient-related risk factors and lifestyle factors for lumbar degenerative disc disease: a systematic review. Neurochirurgie. 2023;9:01482.

[16]

Wu A, March L, Zheng X, et al. Global low back pain prevalence and years lived with disability from 1990 to 2017: estimates from the global burden of disease study 2017. Ann Transl Med. 2020;8(6):99.

[17]

Ren G, Zhang M, Zhuang L, et al. MRI and CT compatible asymmetric bilayer hydrogel electrodes for EEG-based brain activity monitoring. Microsyst Nanoeng. 2024;10(1):56.

[18]

Weishaupt D, Zanetti M, Boos N, Hodler J. MR imaging and CT in osteoarthritis of the lumbar facet joints. Skeletal Radiol. 1999;28(4):215-219.

[19]

Röhrle O, Yavuz , Klotz T, Negro F, Heidlauf T. Multiscale modeling of the neuromuscular system: coupling neurophysiology and skeletal muscle mechanics. Wiley Interdiscip Rev Syst Biol Med. 2019;11(6):1457.

[20]

Meriggioli MN, Sanders DB. Autoimmune myasthenia gravis: emerging clinical and biological heterogeneity. Lancet Neurol. 2009;8(5):475-490.

[21]

Zhao L, Li H, Meng J, Li Z. The recent advances in self-powered medical information sensors. InfoMat. 2020;2(1):212-234.

[22]

Zhang M, Hao M, Liu B, et al. Recent progress of hydrogels in brain-machine interface. Soft Sci. 2024;4(4):4.

[23]

Gao J, Hu M, Sun H, et al. Disposable and flexible smart electronic tapes for long-term biopotential monitoring. NPJ Flex Electron. 2025;9(1):6.

[24]

Zhang B, Li J, Zhou J, et al. A three-dimensional liquid diode for soft, integrated permeable electronics. Nature. 2024;628(8006):84-92.

[25]

Li X, Wang ZL, Wei D. Scavenging energy and information through dynamically regulating the electrical double layer. Adv Funct Mater. 2024;4:2405520.

[26]

Wu J. Understanding the electric double-layer structure, capacitance, and charging dynamics. Chem Rev. 2022;22:10821-10859.

[27]

Wang H, Ding Q, Luo Y, et al. High-performance hydrogel sensors enabled multimodal and accurate human-machine interaction system for active rehabilitation. Adv Mater. 2024;36(11):2309868.

[28]

Oh B, Lim YS, Ko KW, et al. Ultra-soft and highly stretchable tissue-adhesive hydrogel based multifunctional implantable sensor for monitoring of overactive bladder. Biosens Bioelectron. 2023;225:115060.

[29]

Li X, Lin H, Yu Y, et al. In situ rapid-formation sprayable hydrogels for challenging tissue injury management. Adv Mater. 2024;6(19):2400310.

[30]

Coulter SM, Pentlavalli S, An Y, et al. In situ forming, enzyme-responsive peptoid-peptide hydrogels: an advanced long-acting injectable drug delivery system. J Am Chem Soc. 2024;146(31):21401-21416.

[31]

Chen S, Luo Y, He Y, et al. In-situ-sprayed therapeutic hydrogel for oxygen-actuated Janus regulation of postsurgical tumor recurrence/metastasis and wound healing. Nat Commun. 2024;5(1):814.

[32]

Liu GW, Pickett MJ, Kuosmanen JLP, et al. Drinkable in situ-forming tough hydrogels for gastrointestinal therapeutics. Nat Mater. 2024;23(9):292-1299.

[33]

Li L, Ye X, Ji Z, et al. Paintable, fast gelation, highly adhesive hydrogels for high-fidelity electrophysiological monitoring wirelessly. Small. 2025;21(8):2407996.

[34]

Lan L, Ping J, Li H, et al. Skin-inspired all-natural biogel for bioadhesive interface. Adv Mater. 2024;36(25):401151.

[35]

Kumar A, Sharma G, Naushad M, et al. Bio-inspired and biomaterials-based hybrid photocatalysts for environmental detoxification: a review. Chem Eng J. 2020;82:122937.

[36]

Yang S, Cheng J, Shang J, et al. Stretchable surface electromyography electrode array patch for tendon location and muscle injury prevention. Nat Commun. 2023;4(1):6494.

[37]

Gonzalez-Izal M, Malanda A, Gorostiaga E, Izquierdo M. Electromyographic models to assess muscle fatigue. J Electromyogr Kinesiol. 2012;2(4):501-512.

[38]

Graham RB, Wachowiak MP, Gurd BJ. The assessment of muscular effort, fatigue, and physiological adaptation using EMG and wavelet analysis. PLoS One. 2015;10(8):0135069.

[39]

Ament W, Verkerke GJ. Exercise and fatigue. Sports Med. 2009;39(5):389-422.

[40]

Yi X, Jia J, Deng S, Shen SG, Xie Q, Wang G. A blink restoration system with contralateral EMG triggered stimulation and real-time artifact blanking. IEEE Trans Biomed Circuits Syst. 2013;7(2):140-148.

[41]

Gao H, Sun M, Li M, et al. Force decoding of caudal forelimb area and rostral forelimb area in chronic stroke rats. IEEE Trans Biomed Eng. 2021;68(10):3078-3086.

[42]

Wei W, Dai Q, Wong Y, Hu Y, Kankanhalli M, Geng W. Surface-electromyography-based gesture recognition by multi-view deep learning. IEEE Trans Biomed. 2019;66(10):2964-2975.

[43]

Duan S, Wu L, Xue B, Liu A, Qian R, Chen X. A hybrid multimodal fusion framework for sEMG-ACC-based hand gesture recognition. IEEE Sens J. 2023;23(3):2773-2784.

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