ArticleScience advances2026
A hemispherical latitude-gradient sensor for closed-loop monitoring and management of scoliosis correction.
Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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13 authors.
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Abstract
Conservative treatment of scoliosis relies on physiotherapy and bracing, yet both approaches lack tools for quantitative, real-time monitoring of corrective forces. Here, we introduce a hemispherical latitude-gradient (HS-LG) sensor as a previously unknown sensing paradigm for soft, curved-body interfaces, using scoliosis as a clinical exemplar. Leveraging a nonzero Gaussian curvature ([Formula: see text]) geometry, the device acts as a spatiotemporal mechanical filter, converting normal pressure into in-plane tensile forces to overcome shear and stress artifacts limiting conventional sensors. Integrated into a wireless platform, the HS-LG sensor enables immediate visualization of spatiotemporal pressure dynamics during therapy. In physiotherapy, bilateral deployment established the first quantitative, closed-loop Schroth regimen. Real-time visual feedback amplified targeted asymmetric breathing by ∼40% and decoupled nontargeted regional effort, transforming subjective instruction into data-driven neuromuscular internalization. In bracing, embedded sensors mapped pressures during daily activities, uncovering highly dynamic, posture-specific force redistributions, including transient pressure gradient reversals during ambulation, that challenge conventional static orthotic paradigms. Furthermore, age ([Formula: see text]) and body mass index (BMI; [Formula: see text]) emerged as strong predictors of daily wear compliance in the lumbar cohort, while BMI consistently drove interfacial mechanical loading across both spinal regions (lumbar [Formula: see text]; thoracic [Formula: see text]). Together, these results establish the HS-LG sensor design as a versatile, patient-ready platform that links geometry-driven sensing design to personalized, data-informed scoliosis management, while broadly advancing the development of wearable mechanosensing technologies for soft, curved biological surfaces.
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