A hemispherical latitude-gradient sensor for closed-loop monitoring and management of scoliosis correction
- Hehua Zhang
- Yuyu Gao
- Xinxin He
- Haoyu Wang
- Jianpeng Zhang
- Weibin Zhu
- Yuan Guo
- Zhenlin Chen
- Binbin Zhang
- Shengxin Jia
- Kuanming Yao
- Yiming Liu
- Xinge Yu
2026-07-31
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 ( K G ≠ 0 ) 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 ( r = 0.738 ) and body mass index (BMI; r = 0.733 ) emerged as strong predictors of daily wear compliance in the lumbar cohort, while BMI consistently drove interfacial mechanical loading across both spinal regions (lumbar r = 0.61 ; thoracic r = 0.77 ). 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.