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Enhancing Orthotic Treatment for Scoliosis: Development of Body Pressure Mapping Knitwear with Integrated FBG Sensors

Sensors 2025, 25(5), 1284; https://doi.org/10.3390/s25051284

by Ka-Po Lee^1,†

, Zhijun Wang^2,†, Lin Zheng¹

, Ruixin Liang¹, Queenie Fok¹, Chao Lu³, Linyue Lu³

, Jason Pui-Yin Cheung⁴

, Kit-Lun Yick¹ and Joanne Yip^1,*

Reviewer 1: Anonymous

Reviewer 2: Anonymous

Sensors 2025, 25(5), 1284; https://doi.org/10.3390/s25051284

Submission received: 26 January 2025 / Revised: 16 February 2025 / Accepted: 18 February 2025 / Published: 20 February 2025

(This article belongs to the Special Issue Advances in Optical Fiber-Based Sensors)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Enhancing Orthotic Treatment for Scoliosis: Development of Body Pressure Mapping Knitwear with Integrated FBG Sensors

This article is devoted to the study of the effect of corrective corsets on the Cobb angle and spinal curvature. The study is based on the FE model developed in the Fok program.

The authors of the work are engaged in the design and creation of a knitted product - a corset with a pressure sensor system (BPMK). 14 FBG sensors located on the surface of the corset allow measuring both the general and local pressure exerted by the fixing elements.

To test the effectiveness of the developed corset, it was tested on a soft mannequin simulating a patient with adolescent idiopathic scoliosis (AIS). The results obtained will help to evaluate the effect of the corset on the correction of spinal deformity. The article is well structured, one there are a number of remarks.

- In the abstract, "FBG" should be spelled out in full at its first mention to ensure clarity for readers unfamiliar with the term.

- the main text, abbreviations such as "FE" (likely referring to "Finite Element") and "BMI" (Body Mass Index) should be explicitly defined at their first occurrence to enhance readability and prevent ambiguity.

-In Table 3, a period should be inserted in the line: "Skeletal structure Vertebrae, rib cage, pelvis 10,000" to maintain proper formatting and readability.

-In line 270, "the T1 vertebra" is mentioned. To improve clarity, it would be beneficial to include an indication or label in the corresponding figure to clearly show the location of the T1 vertebra.

-The quality of Figure 8 should be improved to ensure better visibility and readability of key details. Higher resolution or enhanced contrast might help in making the figure more informative.

-Consider adding numerical values of the obtained results to the figure annotations where applicable. This will provide readers with clearer, data-driven insights without requiring them to refer back to the text.

-In line 271, insert "the" before "bottom" to correct the grammatical structure.

- While the use of a validated soft AIS mannequin is a strength, it would be beneficial to provide more details on how its mechanical properties compare to actual human tissue, particularly regarding stiffness and deformation under load.

- Further testing on human subjects or a more detailed discussion on the feasibility of human trials would enhance the practical applicability of the findings.

- The prediction equations for FBG sensors should be explained more clearly, with additional validation against real-world clinical data, if possible.

Author Response

Comment 1: In the abstract, "FBG" should be spelled out in full at its first mention to ensure clarity for readers unfamiliar with the term.

Response 1: Thank you for your reminder. 'FBG' has been clarified to 'fiber Bragg grating (FBG)' in the abstract.

Comment 2. the main text, abbreviations such as "FE" (likely referring to "Finite Element") and "BMI" (Body Mass Index) should be explicitly defined at their first occurrence to enhance readability and prevent ambiguity.

Response 2: Thank you for your reminder. 'FE' has been clarified to 'finite element (FE)', and 'BMI' has been clarified to 'body mass index (BMI)'.

Comment 3. In Table 3, a period should be inserted in the line: "Skeletal structure Vertebrae, rib cage, pelvis 10,000" to maintain proper formatting and readability.

Response 3: Thank you for your suggestion, Table 3 has been updated.

Comment 4. In line 270, "the T1 vertebra" is mentioned. To improve clarity, it would be beneficial to include an indication or label in the corresponding figure to clearly show the location of the T1 vertebra.

Response 4: Thank you for your suggestion, 'T1' has been added in Figure 6 to indicate the location of the T1 vertebra.

Comment 5. The quality of Figure 8 should be improved to ensure better visibility and readability of key details. Higher resolution or enhanced contrast might help in making the figure more informative.

Response 5: Figure 8 has been updated to ensure better visibility and readability of key details.

Comment 6. Consider adding numerical values of the obtained results to the figure annotations where applicable. This will provide readers with clearer, data-driven insights without requiring them to refer back to the text.

Response 6: Thank you for your suggestion. All equations have been included in Figure 8 for easier reading.

Comment 7. In line 271, insert "the" before "bottom" to correct the grammatical structure.

Response 7: Thank you for your suggestion, "the" has been added before "bottom".

Comment 8. While the use of a validated soft AIS mannequin is a strength, it would be beneficial to provide more details on how its mechanical properties compare to actual human tissue, particularly regarding stiffness and deformation under load.

Response 8: Thank you for your insightful question. We recognize the importance of comparing the mechanical properties of the validated soft AIS mannequin to those of actual human tissue, particularly regarding stiffness and deformation under load. However, direct comparisons can be challenging due to the different measurement systems used. For instance, the hardness of silicone is typically measured using Shore hardness developed by Albert F. Shore, while human skin is often assessed using Young's modulus, which is approximately 0.05 MPa.

Silicone rubber has been demonstrated to effectively simulate human skin properties. For example, Yu et al. [1] developed a soft mannequin for garment pressure testing using silicone rubber, along with glass fibers and PU foam, to replicate human anatomical features. Similarly, Chan [2] created a soft mannequin for adolescent idiopathic scoliosis (AIS) using Ecoflex™ 0010 silicone for both muscle tissues and skin. These studies highlight the suitability of silicone materials in accurately mimicking human skin. The soft mannequin we used is using a combination of materials to optimize softness. The skin was made from Dragon Skin™ 10 Very Fast Platinum Silicone (Shore hardness of 10A) [3], and Ecoflex™ 0010 Platinum Silicone (Shore hardness of 00-10) [4].

Reference:

1. Yu W, Fan JT, Qian XM. A soft mannequin for the evaluation of pressure garments on human body. Sen'i Gakkaishi. 2004;60(2):57-64.

2. Chan, W. Y. (2019). Evaluation and enhancement of thermal and mechanical performance of posture correction girdle for adolescent idiopathic scoliosis (AIS). [Doctoral dissertation, The Hong Kong Polytechnic University]. 2019. https://theses.lib.polyu.edu.hk/handle/200/10231

3. Smooth-On I. Dragon Skin™ 10 VERY FAST, https://www.smooth-on.com/products/dragon-skin-10-very-fast/ (2025, accessed 10 Feb 2025).

4. Ecoflex™ 00-10, https://www.smooth-on.com/products/ecoflex-00-10/ (2025, accessed 10 Feb 2025).

Comment 9. Further testing on human subjects or a more detailed discussion on the feasibility of human trials would enhance the practical applicability of the findings.

Response 9: Thank you for your insightful comments. We acknowledge that while our study demonstrates promising results using a validated soft AIS mannequin, conducting trials with actual human participants is essential.

We believe that human trials are feasible, and this paper represents an initial step toward that goal. However, improvements are necessary. We identified key limitations, such as the wearability of the device; for instance, the large interrogator can hinder the subject's movement during experiments. Additionally, the fragility of the silica optical fiber and the design of the undergarment need enhancement to reduce breakage risk. To address these challenges, we propose using a miniature interrogator, polymer optical fibers, and a design with front openings in the undergarment.

To highlight the importance of the feasibility of human trials, the limitations and proposed solutions are detailed in the 'Limitations of Experiments and Future Work' section.

Comment 10. The prediction equations for FBG sensors should be explained more clearly, with additional validation against real-world clinical data, if possible.

Response 10: Thank you for your valuable feedback. Additional discussion has been added in Section 3.1 to further explain the prediction equations for the FBG sensors, and in Section 3.2 to compare the collected data with the clinical data.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

(1) In the study, the authors developed a volumetric pressure mapping knitted fabric integrated with fourteen silicone embedded fiber Bragg grating sensors to monitor real-time and overall force changes during brace treatment. However, the abstract only presents qualitative results or conclusions, lacking clear explanations of quantitative results. For example, research results indicate that the measured force is highly consistent with the force obtained from clinical studies. What are the measurement results and clinical outcomes?
(2) The manuscript mentions that the methods used for continuous monitoring of applied pressure have limitations and may cause discomfort due to limited wearability. So, how has the comfort of the methods or solutions proposed in this study been overcome? And how is its comfort evaluated? What parameters are used to obtain the quantitative evaluation? Can similar comfort and accuracy evaluation results be obtained through experiments and clinical trials using dummies?
(3) In Table 3, we can see that almost all material authors in the model assumed it to be an elastic material. This is because in Figure 3, the author only provided the elastic modulus and Poisson's ratio of the relevant materials as two mechanical parameters. But in reality, all kinds of materials in nature are elastic-plastic. Is this assumption reasonable and accurate?
(4) What tools or methods were used in the research? Business software or self programming? If it is self transformation, the reviewer believes that specific relevant theories and solution methodologies need to be provided in the manuscript. If it is commercial software (such as ABAQUS or COMSOL), relevant information about the software or program needs to be provided.
(5) Figure 9 needs to provide relevant legends to display the specific physical meanings represented by different color blocks.
(6) From Figure 10, it can be seen that the deformation of bones is at the millimeter level. Such small results are easy and accurate to obtain for numerical simulations. However, for clinical practice, subtle measurement errors can lead to significant differences. How was this challenge overcome in the research?

Author Response

Comment 1: In the study, the authors developed a volumetric pressure mapping knitted fabric integrated with fourteen silicone embedded fiber Bragg grating sensors to monitor real-time and overall force changes during brace treatment. However, the abstract only presents qualitative results or conclusions, lacking clear explanations of quantitative results. For example, research results indicate that the measured force is highly consistent with the force obtained from clinical studies. What are the measurement results and clinical outcomes?

Response 1: Thank you for your valuable suggestions. We have revised the abstract to enhance clarity and comprehensiveness, ensuring that the quantitative results are clearly articulated.

The findings indicate that the measured forces are in good agreement with those obtained from clinical studies, with peak forces around the padding regions reaching approximately 2N. and further validated by using finite element (FE) models. When comparing X-ray images, the estimated differences in Cobb angles were found to be 0.6° for the thoracic region and 2.1° for the lumbar region.

Comment 2. The manuscript mentions that the methods used for continuous monitoring of applied pressure have limitations and may cause discomfort due to limited wearability. So, how has the comfort of the methods or solutions proposed in this study been overcome? And how is its comfort evaluated? What parameters are used to obtain the quantitative evaluation? Can similar comfort and accuracy evaluation results be obtained through experiments and clinical trials using dummies?

Response 2: Thank you for your insightful comments and for highlighting the important issue of comfort in our study. We acknowledge that the current methods, including the BPMK, have limitations regarding comfort and accuracy, primarily due to the bulkiness of the interrogator and the fragility of the silica optical fiber.

In our study, we have taken initial steps to address these issues by using a validated soft AIS mannequin, which has provided promising results. However, we recognize that trials with actual human participants are crucial for further validation and to fully assess comfort and accuracy.

To enhance user comfort, we have identified several key areas for improvement. The bulkiness of the interrogator restricts movement, and the fragility of the silica optical fiber, along with the current undergarment design, can lead to discomfort or breakage. To address these challenges, we propose the following solutions:

Miniature Interrogator: We plan to use a smaller interrogator to significantly reduce bulk and improve wearability.
Polymer Optical Fibers: Transitioning to polymer optical fibers will provide more flexibility and resilience, enhancing user comfort.
Redesigning the Undergarment: Incorporating front openings in the undergarment design will facilitate easier wear and minimize discomfort.For evaluating comfort, we will prioritize user feedback and conduct motion range assessments. These evaluations will be quantitative, using specific metrics such as comfort scales and range of motion measurements, to assess the comfort level during trials.

Regarding the feasibility of human trials, we have detailed the limitations and our proposed solutions in the 'Limitations of Experiments and Future Work' section. While experiments with dummies provide valuable initial insights, human trials are essential for comprehensive evaluation.

We appreciate your feedback and believe that these steps will significantly enhance the comfort and accuracy of our methods, paving the way for successful human trials in the future.

Comment 3. In Table 3, we can see that almost all material authors in the model assumed it to be an elastic material. This is because in Figure 3, the author only provided the elastic modulus and Poisson's ratio of the relevant materials as two mechanical parameters. But in reality, all kinds of materials in nature are elastic-plastic. Is this assumption reasonable and accurate?

Response 3:

Thank you for your insightful comments regarding the assumption of elasticity in our model. We acknowledge the concern that most materials exhibit elastic-plastic behavior in reality, and we appreciate the opportunity to address this limitation in section 4, "Limitations of Experiments and Future Works."

The assumption of elasticity was chosen not only to simplify the computational model and reduce calculation time but also because it aligns with the primary objectives of our study. Our focus is on the correction of spinal curves in scoliosis patients, where small deformations are predominant [1] due to the presence of bony structures and the deformability of the soft brace. Under these conditions, the elastic behavior of materials provides a reasonable approximation.

Furthermore, this approach is consistent with precedent in the literature, where similar assumptions have been successfully employed in studies with comparable objectives and constraints. We conducted a sensitivity analysis to ensure that the assumption of elasticity does not significantly impact the key findings of our study, particularly the correlation between the FE model results and real X-ray data. As shown in Table 5 and Figure 7, we achieved a correlation coefficient of 0.87, demonstrating the accuracy and reliability of our model under the current assumptions.

Looking ahead, we plan to develop more accurate FE models that incorporate elastic-plastic material properties. Additionally, we aim to include more detailed geometric representations, such as specific organs, to enhance the realism and applicability of our simulations. We appreciate your understanding and support as we continue to refine our approach.

Reference:

1. Verma, N., & Pullela, M. (2024). Material Models for Finite Element Analysis of Soft Tissues. In Microbiology-2.0 Update for a Sustainable Future (pp. 427-450). Singapore: Springer Nature Singapore.

Comment 4. What tools or methods were used in the research? Business software or self programming? If it is self transformation, the reviewer believes that specific relevant theories and solution methodologies need to be provided in the manuscript. If it is commercial software (such as ABAQUS or COMSOL), relevant information about the software or program needs to be provided.

Response 4: The finite element analysis (FEA) was conducted using commercial software called MSC Marc (version 2022.2.0, USA), which has been demonstrated to be effective and accurate for simulating human body behavior [1,2]. For clarification, the software version has been included in Section 2.3.2.

References:

1. Liang, R., Yip, J., Yu, W., Chen, L., & Lau, N. M. (2019). Numerical simulation of nonlinear

material behaviour: application to sports bra design. Materials & Design, 183, 108177.

2. Rodrigues, Y. L., Mathew, M. T., Mercuri, L. G., Da SIlva, J. S. P., Henriques, B., & Souza, J. C. M. (2018). Biomechanical simulation of temporomandibular joint replacement (TMJR) devices: a scoping review of the finite element method. International Journal of Oral and Maxillofacial Surgery, 47(8), 1032-1042.

Comment 5. Figure 9 needs to provide relevant legends to display the specific physical meanings represented by different color blocks.

Response 5: Thank you for your comment. The areas displayed in Figure 9 are generated by the FEA after inputting the forces at the corresponding locations. To avoid any potential misunderstanding, we will remove all color blocks and instead use the locations of the fiber Bragg grating (FBG) sensors to clearly represent the data. This change will enhance clarity and ensure that the figure accurately conveys the relevant information.

Comment 6. From Figure 10, it can be seen that the deformation of bones is at the millimeter level. Such small results are easy and accurate to obtain for numerical simulations. However, for clinical practice, subtle measurement errors can lead to significant differences. How was this challenge overcome in the research?

Response 6:

Thank you for your insightful feedback. In clinical practice, while measuring the precise deformation of the spine at a millimeter level is not typically necessary, the Cobb angle is the standard metric used to evaluate the severity of lateral curvature and inform treatment plans [1,2]. However, measurement errors in the Cobb angle have been noted, which has prompted ongoing research and the development of new technologies to enhance accuracy [3].

To address these challenges, our research leverages advanced technologies such as finite element (FE) modeling. Computer vision techniques can automatically or semi-automatically process X-ray, CT, MR, or ultrasound images, significantly reducing human error and improving the reliability of Cobb angle measurements. This automation helps mitigate the impact of subtle measurement errors that can occur in manual assessments.

Furthermore, FE technology plays a crucial role in accurately simulating spinal deformation at a millimeter level. This capability allows us to predict treatment outcomes with high precision, which is often difficult to achieve in real-world experiments or clinical consultations. By integrating FE simulations with clinical imaging data, we can provide a more comprehensive understanding of spinal biomechanics and enhance the accuracy of treatment planning [4].

In summary, the combination of computer vision and FE technology offers a robust solution to the challenge of subtle measurement errors, demonstrating significant advantages in both research and clinical practice.

References:

1. Wong, J., Reformat, M., Parent, E., & Lou, E. (2024). Validity and accuracy of automatic cobb angle measurement on 3D spinal ultrasonographs for children with adolescent idiopathic scoliosis: SOSORT 2024 award winner. European Spine Journal, 1-9.

2. Liu, J., Yuan, C., Sun, X., Sun, L., Dong, H., & Peng, Y. (2021). The measurement of Cobb angle based on spine X-ray images using multi-scale convolutional neural network. Physical and Engineering Sciences in Medicine, 44, 809-821.

3. Jin, C., Wang, S., Yang, G., Li, E., & Liang, Z. (2022). A review of the methods on cobb angle measurements for spinal curvature. Sensors, 22(9), 3258.

4. Aguilar Madeira, J. F., Pina, H. L., Pires, E. B., & Monteiro, J. (2010). Surgical correction of scoliosis: Numerical analysis and optimization of the procedure. International Journal for Numerical Methods in Biomedical Engineering, 26(9), 1087-1098.

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