Wearable Devices in Scoliosis Treatment: A Scoping Review of Innovations and Challenges
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Search Strategy
2.3. Study Selection
3. Results
3.1. Sensor-Integrated Wearable and Orthotic Technologies
- Pressure sensors:
- IMUs:
- Surface Electromyography (sEMG) Sensors:
- Temperature sensors:
- Textile-based or flexible sensors:
- Capacitive and dielectric sensors:
Citation | Objective | Methodology | Key Findings and Conclusions |
---|---|---|---|
3D-printed braces for individualized treatment | |||
Redaelli, Alexander Storm (2020) [12] | Feasibility and cost-effectiveness of 3D-printed vs. thermoformed scoliosis braces. | Comparative study (N = 1) | FDM 3D printing with PETG offers a cost-effective, customizable alternative to thermoforming for scoliosis braces, with superior stiffness, comfort, and short-term durability. |
Storm, Redaelli et al. (2022) [13] | Stability comparison of FDM, conventional, and unbraced conditions using sensors. | Pilot study evaluating the production process Clinical comparison (N = 10) | 3D-printed PETG scoliosis braces proved cost-effective and customizable, offering comparable stability to conventional braces and eliminating the need for plaster casting. |
Costantini, Redaelli et al. (2025) [14] | To assess whether 3D-printed braces offer advantages or disadvantages over conventional braces. | Clinical pilot study (N = 10) | 3D-printed braces, providing customizable support through additive manufacturing without negatively affecting gait dynamics, showed no significant differences in mobility compared to conventional braces, with both similarly limiting trunk motion and reducing AP acceleration while preserving other gait metrics. |
Li, Yang et al. (2022) [15] | 3D-printed patient-specific brace with asymmetric stiffness for targeted corrective force. | Design and simulation, clinical application (N = 1) | The brace featured asymmetric stiffness (concave: 145.88 N/mm, convex: 35.96 N/mm) with higher corrective force on the convex side (33.53 N vs. 3.27 N). Cobb angle reduced from 49° to 42.4° after 6 months. |
Martin, Gugel et al. (2024) [16] | To develop a flexible, printed dielectric sensor grid for real-time pressure monitoring inside scoliosis braces. | Material and sensor development Proof-of-concept testing (N = 0) | A 34 wt.% graphite–silicone mix achieved optimal conductivity (0.32 kΩ) with stable resistance under 50% strain. Square-electrode capacitance grids enhanced sensitivity 10×. Pressure monitoring in scoliosis braces improves but still requires further calibration and testing due to uneven and lateral pressure issues. |
Smart bracing systems | |||
Fregna, Raccagni et al. (2024) [1] | Influence of personal and clinical factors on brace adherence in AIS patients. | Cross-sectional study (N = 638) | Brace adherence in AIS was highest among younger, less skeletally mature females, with optimal compliance at 19–22 h/day, supporting the role of psychosocial factors and sensor-based monitoring. |
Erzurumluoglu, Ozlem et al. (2024) [4] | To examine the pressure applied to the brace by integrating a textile-based pressure sensor array. | Laboratory-based feasibility study | The textile-based capacitive sensor system showed high accuracy, low error, and stable pressure mapping, proving suitable for real-time monitoring in scoliosis braces. |
Tymins, Zaborowska-Sapeta et al. (2022) [5] | Presents a prototype of the intelligent brace | Prototype development and clinical testing (N = 1) | The smart brace prototype, using graphene-based sensors, enabled real-time tracking of corrective forces (~150 N) and patient compliance, effectively detecting irregular usage and supporting mobile-based monitoring. |
Guy, Labelle et al. (2021) [6] | To assess the effectiveness of CAD/CAM brace design, with and without simulations. | RCT CAD/CAM: N = 61, CAD-FEM: N = 59 | CAD-FEM and CAD-only braces showed similar clinical outcomes, with finite element method (FEM) improving design efficiency but offering no significant advantage in correction, adherence, or quality of life. |
Yahyaiee Bavil and Rouhi (2020) [8] | To evaluate night-time Providence brace’s effectiveness in reducing the Cobb angle. | Combined experimental and computational study. (N = 1) | The Providence brace significantly reduced Cobb angle via FE modeling and clinical results, with strong predictive accuracy (4.4% error), highlighting its effectiveness in preventing scoliosis progression. |
Fuss, Ahmad et al. (2021) [17] | To develop a cost-effective but accurate pressure sensor system for TLSOs. | Development, material testing, and experimental testing (N = 2) | The developed low-cost sensor system demonstrated viability for long-term pressure monitoring in scoliosis braces, showing minor hysteresis from foam liners while maintaining ~12% RMSE accuracy, with peak pressures (up to 0.135 MPa) during deep inspiration, primarily in thoracolumbar regions. |
Gesbert, Colobert et al. (2021) [18] | Reliability analysis of a textile sensor system for the measurement of brace pressure. | Prospective pilot study, Calibration tests, and clinical validation (N = 4) | The (Smart T-Shirt, STS) prototype showed high accuracy (r2 = 0.99) and reproducibility (r2 > 0.9), effectively detecting posture-based pressure changes, proving reliable for real-time brace pressure monitoring and design optimization. |
Zou, Zhou et al. (2025) [19] | To evaluate the feasibility of an integrated force-temperature for monitoring AIS brace compliance. | Prospective pilot study (N = 12) | Patients overestimated brace wear time, but a dual-sensor system (force + temperature) achieved 92.3% accuracy in detecting true wear, enabling early detection of non-compliance for timely interventions. |
Catalina, Robert, and Calin (2020) [10] | To design a smart orthosis that can detect postural changes in the variation of spine curvature. | Design and evaluation research (N = 0) | The study presents a smart orthosis integrating inertial and flex sensors that enhances posture awareness and rehab outcomes via real-time mobile feedback. |
Gaume, Pietton et al. (2020) [20] | To assess the mean walking distance per day in AIS patients using smartphone-based pedometers. | Prospective observational study. Control group: N = 25, AIS: N = 19 | Braced AIS patients walked significantly more than untreated peers and controls, with no link between Cobb angle and activity, showing AIS does not limit activity; smartphone pedometers offer a low-cost monitoring solution. |
Lin, Lou et al. (2020) [21] | To compare the effectiveness of the automated pressure-adjustable orthosis (PO) and conventional orthosis (CO) for the treatment of AIS. | RCT PO group: N = 11 CO group: N = 12 | The pressure-optimized orthosis outperformed conventional braces with greater correction, no curve progression at 1-year follow-up, and significantly improved compliance and wear time, enhancing scoliosis management without affecting quality of life. |
Ray, Nouaille et al. (2023) [22] | Proposes a robotic solution that provides greater mobility and adapts the procedure to the patient. | Validating tests and feasibility (N = 1) | A 2.5 kg modular robotic brace using Stewart-Gough platforms showed precise trajectory tracking and adaptive motion, offering improved comfort and motion accuracy over traditional rigid braces for scoliosis correction. |
Lim, Mak et al. (2024) [23] | To assess the efficacy of a 3D customized over-corrective brace, “ScoliBrace,” an orthosis treatment for AIS | Prospective pilot study (N = 30) | ScoliBrace wear showed dose-dependent efficacy, reducing Cobb angle by 0.794° per extra hour worn, with optimal adherence at 15–18 h/day, effectively halting progression and avoiding surgery in most cases. |
Marchese, Du Plessis et al. (2024) [24] | To evaluate short- and medium-term trunk extensor and abdominal endurance in AIS patients using ScoliBrace® and ScoliBalance® treatment. | Retrospective study (N = 33) | The combined Scoli-Brace® and ScoliBalance® treatment significantly enhanced trunk and abdominal endurance in AIS patients over time, with many achieving the 180 s maximum hold duration by follow-up. The approach particularly strengthened trunk extensors without causing muscle weakening. |
Ali, Fontanari et al. (2022) [25] | Presents finite element analysis (FEA) of an active soft brace | Computational modeling and simulation (N = 0) | The validated FE model showed that the active soft brace reduces Cobb angle and pressure, providing a comfortable, corrective alternative to rigid braces. |
Cakmak, Cegindir et al. (2022) [26] | A posture-supporting garment for scoliosis, developed using pattern engineering and textile structures. | Develop and test a prototype (N = 1) | Prototype A, a soft exosuit brace, matched rigid orthoses in Cobb angle correction (up to 10.7%) while providing superior comfort, increased wear time, and high satisfaction through optimized design and materials. |
Farhadiyadkuri and Zhang (2023) [27] | A Multi-Body-FE Simscape model and an analytical model of the AIS bracing treatment are created. | Computational Modeling and Simulation (N = 0) | This study introduced the first MB-FE Simscape model with NPIC control for AIS bracing, achieving <6.5% stiffness error and superior tracking precision (<1% stiffness/damping error, 0.88–3.28% pose error) over traditional methods. |
Zapata, Virostek et al. (2024) [28] | To measure night-time brace adherence using temperature sensors and its impact on curve progression. | Prospective case series (N = 122) | Night-time use of the Providence brace effectively prevented AIS progression, especially in patients with single or smaller curves and high adherence, with only 6% requiring surgery, lower than rates seen in full-time bracing. |
Redchen, Vissarionov et al. (2021) [48] | Evaluated yearly outcomes of trunk orthoses post-surgery in children with congenital spinal deformities. | Prospective clinical study (N = 25) | Functional-corrective orthoses provided up to 60% curve correction post-surgery, with thoracic improvements partly sustained and lumbar curves regressing, supporting extended lumbar orthosis use until skeletal maturity. |
Ali, Fontanari et al. (2022) [49] | Presents an active soft brace that maintains spinal mobility while applying corrective elastic forces. | Modeling and validation experiments (N = 0) | The TSA-powered brace delivered safe, effective corrective forces (0–6 kPa) with accurate control (RMSE: 1.74 mm), preserving mobility and enabling prolonged, low-power scoliosis treatment comparable to rigid braces. |
West et al. (2022) [50] | To assess the accuracy of the Scolioscreen (smartphone with an application) compared to the Scoliometer. | Diagnostic Accuracy Study (N = 50) | Scolioscreen showed high accuracy and inter-rater reliability (ICC ≥ 0.93) for ATR measurement, offering a low-cost, user-friendly tool for reliable at-home scoliosis screening, even by untrained parents. |
Zapata, McIntosh et al. (2023) [51] | To evaluate the effects of adding physiotherapeutic scoliosis-specific exercises (PSSE) to night-time bracing. | Prospective comparative study (N = 115) | PSSE combined with night-time bracing outperformed bracing alone in managing thoracolumbar/lumbar curves < 35°, reducing curve progression, improving Cobb angle stability, and lowering full-time bracing need in AIS patients. |
Smart clothing embedded with sensors | |||
Caviedes, Jammula et al. (2020) [3] | Wearable sensor system for home therapy providing real-time feedback to improve exercise accuracy. | Design and simulation, clinical application. Sensor array with mobile app integration | The wearable sensor system, using custom garments and harnesses, demonstrated 70–100% sensitivity and perfect specificity in detecting exercises, enabling real-time feedback for posture correction and therapy adherence. |
Anwary, Cetinkaya et al. (2021) [38] | To develop the Smart-Cover for real-time sitting posture and asymmetry monitoring using pressure sensors. | Laboratory-based feasibility study (N = 10) | Smart-Cover detected sitting asymmetry with ±4% accuracy over a 4.2–8.4 kg pressure range, provided real-time mobile-app feedback, offering a cost-effective solution to promote ergonomics and prevent posture-related disorders. |
Simegnaw, Teyeme et al. (2022) [40] | To develop a smart shirt with motion sensors for real-time monitoring of trunk posture and bending angles during cycling. | Validating tests and feasibility (N = 1) | The smart shirt accurately measured trunk bending angles (8–35°), with 99% of postures within ergonomic limits. Its CA-74 threads remained reliable after 17 washes, enabling precise, real-time posture monitoring to support cycling performance, injury prevention, and broader ergonomic applications. |
Yağcı, Turgut, and Yakut (2020) [41] | Scapular taping effects on 3D shoulder and thoracic motion in AIS daily activities. | Prospective intervention study with pre-post testing (N = 24) | Elastic scapular taping improved scapular orientation (external and upward rotation), as well as humeral and trunk kinematics during functional tasks, supporting dynamic stability and upper limb function in adolescents with scoliosis. |
Lee, Yip et al. (2023) [39] | To develop a smart textile with silicone-embedded fiber Bragg grating (FBG) sensors for real-time bracing pressure monitoring in AIS patients. | A PIMA cotton undergarment with embedded FBG sensors was developed and validated. | Silicone-embedded FBG sensors provided reliable and sensitive force measurements (up to 10 N, R2 > 0.90, ICC = 0.97), improving brace pressure monitoring in AIS through better stability, skin compatibility, and enhanced fit and comfort for improved clinical outcomes. |
Lee, Wang et al. (2025) [42] | To develop body pressure mapping knitwear (BPMK) with FBG sensors for force monitoring. | Sensor-embedded textile testing, Force measurement + FEA simulation | The FBG-equipped BPMK system provided accurate real-time force monitoring with strong agreement to FEA and X-ray data, enhancing comfort, adaptability, and MRI compatibility, safety, compliance, and scoliosis treatment outcomes. |
Mosleh, Abtew et al. (2021) [43] | To create adaptive clothing for women with scoliosis that adjusts to spinal deformity progression. | Validating tests and feasibility (N = 1) | The 3D geometrical model enables automated, adaptive garment design for AIS patients using skeleton-based referencing and ease allowances, enhancing fit and comfort while minimizing scanning and manual adjustments. |
Liu, Zhang et al. (2025) [44] | To investigate soft brace effects on balance, proprioception, and textile design in AIS. | Pilot study, experimental trial, (N = 10), 3D scanning, EOS, motion capture | The PCG soft brace improved postural alignment and proprioception—especially in thoracic/lumbar regions—highlighting its potential for managing mild scoliosis, though personalization and long-term evaluation remain essential. |
Xuan, Lei et al. (2024) [52] | To develop a smart wearable system for real-time brace monitoring and comfort assessment. | Experimental Sensor-integrated 3D-printed orthosis | The intelligent system offers reliable, real-time monitoring of orthopedic pressure and comfort with <2 s latency and <2% error, enhancing adherence, personalization, and clinical decision-making in scoliosis bracing. |
Inertial Measurement Unit (IMU)-based wearables | |||
Dehzangi, Bache et al. (2021) [29] | To develop a smart scoliosis brace system for unsupervised monitoring of wear time, tightness, and activity. | Prospective, single-center, observational study, Boston-type TLSO with wearable sensors | The system enables accurate, remote, context-aware monitoring for scoliosis bracing, achieving >99% activity classification accuracy, improving compliance from 7% to 90%, and detecting a 33% force drop, supporting early identification of poor fit and timely personalized re-fitting. |
Kim, Hwang et al. (2024) [30] | To develop a wearable system (WLSCMS) for real-time monitoring of spine curvature using IMU sensors combined with ML. | Design and simulation (N = 20), Smart waistband, ML used to classify spinal curvature | The WLSCMS system offers a user-friendly, accurate wearable for lumbar monitoring, achieving >99% classification accuracy without individual calibration and outperforming single-sensor setups, with strong clinical potential pending further validation. |
Selthafner, Liu et al. (2021) [9] | To evaluate the effectiveness of PSSE on postural balance in AIS patients by measuring the center of pressure (COP) metrics. | Prospective, intervention study, N = 6 (AIS patients), 12-week PSSE program, pre- and post-imaging DIERS 4D | After PSSE, measurable postural improvements were observed through COP and forefoot pressure changes—15% increase in anterior-posterior COP, 25% decrease in medial-lateral COP, and improved symmetry, supporting dynamic pressure analysis as a valuable tool for evaluating AIS therapy outcomes. |
Fercho, Krakowiak et al. (2022) [31] | To evaluate three spinal braces’ effectiveness in restricting spinal motion using IMUs during daily tasks. | Comparative study (N = 10, healthy adults), IMU-based motion analysis | Spinal orthoses restrict motion task-specifically; TLSO excels in sitting/walking, Hohmann in lifting, with IMUs revealing significant performance differences. |
Mak, Liang et al. (2023) [32] | To develop and evaluate a neural network using IMUs for 3D spinal curvature estimation. | Design and simulation, clinical application (N = 15, healthy participants) | The IMU-based neural network accurately estimated spinal curvature (0.26 cm error) and Cobb angles, offering a cost-effective, real-time alternative to X-rays for scoliosis monitoring, with potential for clinical, home, and biofeedback use. |
Farella, Vanzini et al. (2022) [45] | Investigation of motor control alterations in children with idiopathic scoliosis using clinical assessments and IMU-based metrics. | Motor and gait analysis in 34 scoliosis children using ABC-2 and IMUs vs. healthy controls. | Children with idiopathic scoliosis show impaired motor control, slower and more variable gait, and reduced stability; IMU-based non-linear metrics enable early detection and support intervention planning. |
Gan, Liu et al. (2024) [46] | Evaluating gait symmetry, regularity, and head balance control in AIS patients using wearable accelerometers. | Comparative study (N = 34; 17 scoliosis patients, 17 healthy controls) | AIS patients exhibit reduced head and lumbar vertical motion and lower head regularity, indicating impaired walking balance; wearable accelerometers offer effective, non-invasive tools for real-world gait assessment and monitoring. |
Hong, Wang et al. (2022) [47] | To develop a flexible, non-invasive sensor tape with integrated accelerometers for real-time spinal curvature assessment. | Design and validation study (N = 15) Flexible sensor tape with 30 MEMS accelerometers | The novel sensor tape demonstrated 99% accuracy and strong correlation with Vicon in spinal angle measurements, offering a reliable, low-cost, and reusable tool for accurate, non-radiative spinal monitoring with strong clinical and ergonomic potential. |
Wardell, Jayasuriya et al. (2022) [37] | To determine the best sensor placement and temperature threshold for accurately measuring scoliosis brace wear time. | Comparative study Seven Orthotimer and five iButton sensors are embedded in the spinal brace. | Optimal brace wear detection was achieved using abdomen and axilla sensors, with iButton preferred clinically and highest accuracy from uninsulated placement on the anterior abdominal wall using a 26 °C threshold. |
Żurawski, Śliwiński et al. (2023) [53] | To present a 3D photogrammetric model for monitoring spinal curvature changes in children with postural disorders. | Clinical pilot study (N = 211, spinal deformity patients; 101 controls) | Photogrammetric systems enable sensitive, non-invasive monitoring of pediatric postural rehabilitation, revealing significant improvements in trunk imbalance, pelvic tilt, and spinal curvature, while highlighting the need for individualized, dynamic therapy assessment. |
Asano, Inami et al. (2024) [54] | To study dynamic spinal and lower limb alignment during gait in adult spinal deformity (ASD) patients compared to static posture using IMUs. | Comparative study (N = 34, ASD patients), IMUs used to track gait-phase spinal and joint changes | IMU data show that in ASD patients, forward trunk tilt during gait results from lumbar flexion and pelvic anteversion, with worsened posture compared to standing, emphasizing the importance of dynamic assessment. |
Truong, Matsumoto et al. (2024) [55] | To establish guidelines for safely managing pediatric scoliosis with implanted programmable devices (IPD). | Modified Delphi consensus study (N = 25 experts) | Experts reached over 94% consensus on safe use of neuromonitoring and MCGRs in IPD patients, supporting device deactivation during surgery and confirming that, with precautions, standard tools are safe for scoliosis care. |
3.2. EMG-Based Wearables
Citation | Objective | Methodology | Key Findings and Conclusions |
---|---|---|---|
Garg, Gupta et al. (2021) [33] | To compare gait patterns among AIS, congenital scoliosis, and healthy controls to identify differences in gait parameters. | Prospective Cohort Study with EMG and radiographic analysis. 79 AIS Patients | Lumbar and thoracolumbar scoliosis exhibit convex-side EMG asymmetry and coronal imbalance, with asymmetry strongly correlated with the lumbar Cobb angle—most notably at L3—whereas thoracic scoliosis shows no significant muscle activity asymmetry. |
Zhang, Bao et al. (2024) [34] | To evaluate the clinical effectiveness of sEMG combined with a spine 3D data system. | Original research Participants: 10 AIS patients (6 thoracic, 4 lumbar curves) | sEMG combined with 3D motion data enables accurate, non-invasive assessment of muscle asymmetry and Cobb angle, especially in lumbar scoliosis, with strong correlation to EOS imaging (r = 0.971), supporting dynamic scoliosis monitoring. |
Wong, Shayestehpour et al. (2024) [35] | To investigate spinal muscle roles in AIS—stabilization vs. progression—using TES, radiography, and EMG. | Cross-sectional study, 45 AIS (subgroups: TES = 5, EMG = 6). | In small-curve AIS, spinal muscles contribute to stability, while in larger curves (>20°), thoracic erector spinae (TES) activation may worsen deformity. Higher summed EMG ratios indicate corrective muscle function, whereas lower ratios are associated with progression risk. |
Wilczynski and Karolak. (2021) [36] | To explore the relationship between the sEMG frequency of erector spinae and scoliosis curve characteristics in children. | Observational Participants: 244 children, 103 with scoliosis, 141 with scoliotic posture. | sEMG patterns in AIS reveal gender-specific differences and abnormal erector spinae activity, suggesting CNS dysfunction, with potential for standardized sEMG profiles in early detection and prevention |
Park, Ko et al. (2021) [56] | Study muscle imbalance (EMG), leg length difference, and scoliosis curve types in AIS patients. | Prospective Comparative Study, groups: AIS (n = 20), congenital scoliosis (n = 20), healthy controls (n = 20). | AIS and congenital scoliosis patients exhibit similar gait abnormalities driven by spinal deformity, with convex-side muscle dominance highlighting the need for concave-side strengthening and leg length assessment. |
Wang, Jiang et al. (2022) [57] | To investigate neuromuscular synergy patterns in the back muscles of AIS patients using high-density EMG. | Prospective comparative study with 10 AIS patients and 10 healthy controls | AIS patients demonstrate asymmetric muscle activation during dynamic tasks, particularly with Cobb angles >20°, including increased convex-side activity and reduced dominant-side control. High-density EMG and synergy analysis effectively reveal these neuromuscular adaptations, supporting their use in guiding targeted therapies. |
Haksever, Soylu et al. 2024) [58] | To analyze spinae muscle activation during three types of 3D scoliosis-specific elongation exercises. | Prospective cohort study, 24 adolescents with AIS | TheraBand resistance elicits strong paraspinal activation in AIS patients, with LES showing greater side differences, supporting its use in 3D-targeted exercises for bilateral muscle rebalancing. |
Vongsirinavarat, Kao-ngampanich et al. (2023) [59] | Comparing the paraspinal muscle activity during three self-corrective positions and the habitual standing in AIS. | Cross-sectional observational study 33 adolescents with AIS | Corrective positions enhance EMG ratios compared to habitual standing, with the O1 position most effective for thoracic curves and symmetrical correction optimal for lumbar curves. These self-corrective exercises improve muscle activation across all PUMC curve subtypes. |
Liang, Yip et al. (2022) [60] | To analyze the relationship between physical features and EMG signals in scoliosis patients using ML. | Cross-sectional study with 106 participants (73 scoliosis patients, 33 controls) | Lumbar EMG asymmetry and paraspinal imbalance in AIS patients support sEMG biofeedback and ML-based early detection, with SVM achieving 85% prediction accuracy using ATR, height, and EMG ratio as key features. |
Wilczynski and Karolak. (2021) [61] | To analyze the relationship between scoliosis features and sEMG amplitude of the erector spinae in young school children. | Cross-sectional study, N = 251 children, 41%: scoliosis, 56%: scoliotic posture, 3%: normal posture | Thoracic curvatures and sex-related curve direction differences were most common, with elevated erector spinae sEMG amplitudes correlating with curve characteristics, supporting sEMG as a non-invasive tool for early scoliosis detection and monitoring. |
Banno, Yamoto et al. (2022) [62] | To compare muscle activity in ASD patients and age-matched controls using surface EMG. | Prospective case series study. ASD Group: 14 Control Group: 8 | Improved post-op muscle activity in ASD patients suggests pre-op sEMG abnormalities may reflect CNS dysfunction contributing to scoliosis onset, supporting standardized sEMG profiles for early detection and prevention. |
Asada, Miura et al. (2023) [63] | Examined time-based changes in spinal alignment and muscle activity during walking in ASD patients. | Retrospective study 26 ASD patients | In ASD patients, walking worsens spinal alignment with increased SpSVA and compensatory cervical PVM and Gmax activity; degeneration limits thoracic/lumbar PVM response, and quadriceps fatigue may reduce walking endurance. |
Fan, To et al. (2023) [64] | To analyze EMG differences in paravertebral muscles and compare EMG patterns between AIS patients and healthy individuals. | Prospective cohort study with 6-month follow-up. 534 girls (267 AIS, 267 age-matched controls). | AIS patients showed significant EMG asymmetry, with rms-EMG ratios strongly predicting curve progression (AUC: 96% thoracic, 90% lumbar), making asymmetry at AV during back extension a powerful early indicator of scoliosis progression. |
Fan, Wang et al. (2024) [65] | To develop a pressure and sEMG sensor array into a scoliosis brace to enhance treatment efficiency. | Proof-of-concept study integrating wearable sensors with ML. | The MXene-based sensor array enabled real-time scoliosis monitoring with high durability, accurate sEMG and pressure sensing, and 100% motion classification, supporting brace optimization and curve progression prediction. |
Ng, Duncombe et al. (2024) [66] | Compared activation in resisted vs. unresisted trunk extension in adolescents with and without scoliosis. | Cross-sectional study Participants: 44 females (AIS = 24, controls = 20). | No group-level difference in peak activation between unresisted and resisted tasks, but high individual variability suggests both are needed to accurately assess paraspinal MVC in adolescents. |
Wang, Xia et al. (2024) [67] | Analyzed activation to assess neuromuscular characteristics of scapular stabilizers in AIS patients. | Cross-sectional study, observational study. Participants: 17 AIS, 19 controls | AIS patients exhibited impaired scapular neuromuscular control with reduced concave-side AMAs and altered muscle timing, suggesting a need for targeted rehab to enhance stability and motor control. |
Muraoka, Hasegawa et al. (2025) [68] | To determine whether spinal correction surgery in ASD patients reduces muscle activity and fatigue. | Prospective cohort study, Participants: 16 ASD patients, 16 healthy controls | Preoperative ASD patients had elevated muscle activity that decreased post-surgery, reflecting reduced fatigue and improved alignment, HRQOL, and pain, with I-EMG confirming enhanced postoperative muscle efficiency. |
Wang, Wang et al. (2025) [69] | Paraspinal muscle activity comparison in AIS vs. healthy individuals for rehab optimization. | Case-control study Participants: 12 AIS patients. 10 healthy controls (age-matched). | AIS patients showed greater muscle asymmetry and reduced sitting activity; targeted Schroth exercises improved paraspinal activation, while erect sitting may worsen S-curve asymmetry. |
3.3. Digital and Remote Therapeutic Platforms
Citation | Objective | Methodology | Key Findings |
---|---|---|---|
Günther, Schober et al. (2023) [70] | Explored motivational barriers and tools to improve home-based scoliosis therapy. | Cross-sectional survey study (Patients: N = 72, Therapists: N = 30) | Most scoliosis patients under-exercised, but motivation—especially in older adults—improved with peer support, assistive devices, and digital tools, highlighting the value of tech-integrated strategies for effective home-based therapy. |
Culpepper, Murphy et al. (2024) [11] | To assess how telehealth use evolved in early-onset scoliosis (EOS) care during and after the COVID-19 pandemic. | Web-based survey (N = 191, Pediatric Spine Study Group members) | Telehealth use for early-onset scoliosis surged during the pandemic, with bracing and curve monitoring most compatible; common virtual exam methods included back inspection and gait observation, while legal and reimbursement issues continue to limit broader adoption. Telehealth is a lasting, valuable complement to in-person EOS care, especially for follow-ups. |
Moreira, Teles et al. (2020) [71] | To the use of smart mobile apps with ML for measuring human posture and ROM. | Design and simulation Mobile app prototype using TensorFlow and PoseNet | AI-powered smartphone apps accurately measured posture and ROM by identifying key landmarks, offering a low-cost, accessible tool for musculoskeletal monitoring in clinical and home settings. |
Martínez-Borba, Suso-Ribera et al. (2021) [72] | To test the feasibility of a mobile app to monitor brace adherence and wellbeing in AIS. | Clinical pilot study (N = 40 adolescents) 90-day trial using a mobile app | Since this is a study protocol, outcome data are not available. The anticipated outcomes include high adherence and usability rates, effective detection of brace-related issues, and increased treatment safety through early interventions based on app-generated alerts. |
Xia, Hou et al. (2021) [73] | To develop a spinal orthopedic system using BLE and IoT for remote control and monitoring of spinal deformity treatment. | Design and simulation, BLE-enabled growing rod system integrated with mobile app and cloud server | The mobile app-enabled system accurately monitored spinal elongation and adherence with real-time cloud connectivity, offering a personalized, low-power solution to enhance AIS care and reduce clinical workload. |
Bottino, Settino et al. (2023) [74] | To evaluate digital tools for scoliosis management and propose a framework to assess their features and usability. | Comparative analysis study (N = 7 tools) | Most scoliosis apps measure ATR via motion sensors; only one estimates Cobb angle. Functions vary, and a selection guideline was proposed based on OS, features, and user skill. Digital scoliosis tools enhance monitoring and engagement. The evaluation framework supports clinicians and patients in selecting the right app, encouraging smarter scoliosis care. |
Akazawa, Torii et al. (2021) [76] | To create an accessible, low-cost mobile app with a standard 2D camera for screening scoliosis. | Design and simulation, clinical application, Trunk asymmetry detection, | A 2D camera-based mobile app reliably detects trunk asymmetry for scoliosis screening using image analysis, offering a scalable solution for resource-limited settings. |
Yates, Rehman et al. (2021) [77] | Demonstration of wearable-based Human digital twin (HDT) for remote post-op scoliosis recovery monitoring. | Case study (N = 1) | Recovery times varied across physiological metrics (e.g., 3 weeks for sleep, 19 weeks for resting HR). By 5 months post-op, the patient exceeded baseline step count by over 800 steps/day, indicating improved mobility and activity. |
Yuan, Shi et al. (2025) [78] | To compare digital scoliosis-specific exercise therapy using the Healbone system with traditional in-person care for AIS. | RCT, (N = 128 patients), Digital care (HIRS-supported home therapy) vs. usual care | The digital care group showed significantly greater Cobb angle improvement and pelvic tilt correction, along with higher engagement and daily exercise adherence compared to usual care. Home-based PSSE via the HIRS system offers an effective and accessible alternative for managing AIS. |
Taslimipour, Rojhani-Shirazi et al. (2021) [75] | Evaluation of a VR dance training program’s effect on thoracic kyphosis angle and respiratory function (FVC, FEV1). | Randomized controlled trial (32 women). Compare traditional therapy vs. therapy + Xbox Kinect-based VR dance training. | Both groups showed improvements in kyphosis angle and FVC. The VRRT group demonstrated greater improvements than the RT group in all outcomes: Kyphosis angle: −13.23° vs. −7.33°, FEV1 increase: +8.06% vs. +1.81%, FVC increase: +7.93% vs. +3.31%. VRRT had larger effect sizes and statistical power. VR enhances engagement, motor control, and proprioception. |
Kandasamy, Bettany-Saltikov et al. (2021) [79] | Evaluation of a VBAR app’s impact on physiotherapy students’ learning of spinal anatomy and deformities. | A crossover study (N = 74 students) comparing traditional learning to VBAR | VBAR significantly improved students’ understanding of spinal anatomy, increased engagement, and clarified misconceptions compared to traditional methods, with high usability and strong support for collaborative and self-directed learning. |
Moraes, Cardoso et al. (2022) [80] | To evaluate whether immersive virtual reality (IVR) enhances the effectiveness of postural therapy for scoliosis treatment. | Randomized controlled trial (N = 22 children) Comparison of VR-assisted therapy vs. traditional therapy | The VR training group showed significantly greater improvements in postural stability, tolerance time, and proprioceptive control than the control group, with enhanced engagement contributing to better consistency and endurance. Immersive VR showed promise as a physiotherapy adjunct, though sustained motivation and long-term effects require further study. |
Misterska, Górski et al. (2023) [81] | To develop a VR system using biometric avatars to assess body image perception in adolescent girls with AIS | Design and simulation, comparative study, Use of “Avatar Scoliosis 3D” VR app with 3D body scans | AIS patients often overestimated their deformity, with avatar-based VR revealing individual body image distortions correlated with Cobb angle, offering objective insight into body perception issues and even post-surgery. The VR-based tool provided a promising method for both clinical assessment and psychological support. |
Nam, Park et al. (2023) [82] | To evaluate the Smart-Bar Device (SBD) with AR for improving posture accuracy in scoliosis exercises. | Clinical pilot study (N = 10 healthy adults + AIS patients) | The SBD demonstrated high validity (r = 0.836–0.988) and significantly improved posture accuracy in scoliosis patients using AR guidance, with real-time visual and auditory feedback enhancing movement precision. AR-based feedback improves the accuracy of stretching exercises and may benefit home-based rehabilitation for scoliosis patients. |
Moraes, Palmeira et al. (2024) [83] | To assess the effectiveness of VR-supported postural therapy versus traditional methods using baropodometric analysis. | RCT, (N = 22) Comparison of VR-assisted therapy vs. traditional therapy | While both groups improved posturally, the VR-assisted group showed greater gains in balance and foot pressure metrics, with significant reductions in asymmetries, attributed to enhanced visual feedback and interactive engagement in the VR environment. |
Wan, Mak et al. (2024) [84] | To evaluate the effectiveness of a motion-sensing video game in improving posture and alignment in adults with adult degenerative scoliosis (ADS). | Clinical pilot study (N = 10 older women with ADS) 6-week training program using a posture-controlled video game | Participants improved sagittal alignment (notably head and C7 position). While spine length slightly decreased, shoulder and pelvis symmetry improved over the 6 weeks. Muscle activity remained imbalanced, indicating habitual movement patterns. Although some effects diminished over time, video games promoted engagement and could support long-term posture correction when used frequently or in conjunction with home-based systems. |
3.4. Integration of AI and Machine Learning for Personalized Rehabilitation
Citation | Objective | Methodology | Key Findings and Conclusions |
---|---|---|---|
Yahara, Tamura et al. (2022) [2] | To develop and evaluate a deep convolutional neural network (DCNN) model for predicting curve progression in AIS patients. | Pilot study (N = 58) | The DCNN model outperformed surgeons in predicting scoliosis progression (69% accuracy, AUC 0.70), with improved performance via transfer learning and focus on spinal regions per Grad-CAM, enabling early, objective, and personalized treatment planning for mild, immature cases. |
Kaczmarek, Pulik et al. (2023) [7] | Evaluation of lumbar torsional mobility via real-time DSC for physiotherapy planning. | Clinical pilot study, (N = 55 healthy adults) | Mean rotation to the right: 4.78° ± 2.24°; to the left: 2.99° ± 1.44° (p < 0.0001). Max rotation: right 11.35° ± 3.33°, left 7.42° ± 1.97°. No significant sex-based differences. The DSC device offers real-time spinal mobility assessment, supports low back pain therapy planning, and shows reliable performance for future clinical use. |
Rothstock, Weiss et al. (2020) [85] | To develop a semi-automatic ML method using 3D surface topography for scoliosis severity and treatment group classification. | Design and simulation, clinical application (N = 50 AIS patients), neural network trained | The model achieved 90% accuracy (80% sensitivity, 100% specificity) in classifying scoliosis severity and up to 75% accuracy in simplified ALS group classification, with reduced performance when distinguishing similar curve patterns. |
Petrosyan, Makaryan et al. (2024) [86] | To propose and validate a targeted safe model using MoCap and ultrasound for continuous IS therapy monitoring. | Clinical pilot study (N = 6 AIS patients) 6-month PSSE and Boston brace rehabilitation program | Reductions in Cobb angle (X-ray: from 36.2° to 23.6°, p < 0.001; MoCap: from 34.6° to 21.4°, p = 0.0014). SRS-22 score improved from 2.6 to 3.9 (p = 0.002). Strong negative correlation between muscle thickness/mass and Cobb angle (SMM: R = –0.96). L3–L4 muscle gains were linked to curve reduction, supporting personalized, segment-targeted PSSE and bracing. |
Farhadiyadkuri, Popal et al. (2022) [87] | To develop and validate a patient-specific robotic spine exoskeleton with adaptive control to overcome limitations of traditional AIS bracing. | Designed a robotic exoskeleton using 3 Stewart-Gough platforms with 18 actuators, employing inverse dynamics and adaptive impedance control. | MRAIC provided superior position tracking and smoother, safer interaction than conventional control, enabling the exoskeleton to deliver precise corrective forces at T4, T7, and T11 while maintaining performance under uncertainty and sensor noise. The robotic exoskeleton with MRAIC enables safer, adaptive, closed-loop scoliosis treatment. |
Li, Qian et al. (2024) [88] | To assess an AI app for Cobb angle measurement, validating its accuracy against manual picture archiving and communication system (PACS) methods. | Design and simulation, clinical application (N = 601 scoliosis patients) Mobile app for Cobb angle estimation. | The app demonstrated excellent consistency with PACS (ICC > 0.97), low mean absolute error (~2°), and high accuracy across scoliosis severities, outperforming PACS in repeatability for Cobb angle measurements. The AI app offered a fully automated, portable solution for clinical and remote scoliosis follow-up. |
4. Discussion
4.1. Key Findings
4.2. Limitations of Existing Evidence
4.3. Future Directions
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
Abbreviations
AIS | Adolescent idiopathic scoliosis |
ASD | Adult spinal deformity |
AI | Artificial intelligence |
ATR | Axial trunk rotation |
BPMK | Body pressure mapping knitwear |
CO | Conventional orthosis |
DSC | Dynamic segmental calibration |
EMG | Electromyography |
EOS | Early-onset scoliosis |
FBG | Fiber Bragg grating |
FEM | Finite element method |
FEA | Finite element analysis |
HDT | Human digital twin |
IPDs | Implanted programmable devices |
IVR | Immersive virtual reality |
IMU | Inertial measurement unit |
ML | Machine learning |
MCGRs | Magnetically controlled growing rods |
MB-FE | Multi-body finite element |
PETG | Polyethylene terephthalate glycol-modified |
PSSE | Physiotherapeutic scoliosis-specific exercises |
PACS | Picture archiving and communication system |
PCG | Posture correction girdle |
PO | Pressure-adjustable orthosis |
RMSE | Root mean square error |
ROM | Range of motion |
SVM | Support vector machine |
TLSO | Thoracolumbosacral orthoses |
VR | Virtual reality |
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Fazeli Veisari, S.; Bidari, S.; Barati, K.; Atlasi, R.; Komeili, A. Wearable Devices in Scoliosis Treatment: A Scoping Review of Innovations and Challenges. Bioengineering 2025, 12, 696. https://doi.org/10.3390/bioengineering12070696
Fazeli Veisari S, Bidari S, Barati K, Atlasi R, Komeili A. Wearable Devices in Scoliosis Treatment: A Scoping Review of Innovations and Challenges. Bioengineering. 2025; 12(7):696. https://doi.org/10.3390/bioengineering12070696
Chicago/Turabian StyleFazeli Veisari, Samira, Shahrbanoo Bidari, Kourosh Barati, Rasha Atlasi, and Amin Komeili. 2025. "Wearable Devices in Scoliosis Treatment: A Scoping Review of Innovations and Challenges" Bioengineering 12, no. 7: 696. https://doi.org/10.3390/bioengineering12070696
APA StyleFazeli Veisari, S., Bidari, S., Barati, K., Atlasi, R., & Komeili, A. (2025). Wearable Devices in Scoliosis Treatment: A Scoping Review of Innovations and Challenges. Bioengineering, 12(7), 696. https://doi.org/10.3390/bioengineering12070696