Linking compression mechanics and pressure redistribution in hybrid support surfaces for pressure ulcer prevention

Development and production of hybrid surfaces

The hybrid support surfaces combine a soft cotton pile upper layer with a resilient polyester spacer layer, providing softness, microclimate control, and pressure redistribution at low cost. This user-centered design supports use in wheelchair cushions, hospital beds, and home-care mattresses. Thus, six double-layer support surfaces were produced by layering cotton weft-knitted pile fabric over warp-knitted polyester spacer fabric without binding(Fig. 1.(a)).

Loop pile fabrics were produced on a 7-gauge STOLL CMS-T330 flat knitting machine using 20/2Ne cotton yarn for the pile and 16/1Ne cotton-lycra yarn for the ground(Table 1). In the fabric unit cell schematic, darker and lighter regions indicate pile-covered and ground surfaces, respectively. The polyester hexagonal mesh spacer fabric(c.p.c = 7.03(cm⁻¹), w.p.c = 10.04(cm⁻¹), Thickness(mm) = 12.01, Weight(g/m²) = 512.31; Density(kg/m³) = 42.64) was supplied by Sprich Baft Textile Co.(Fig. 1.(b)). The pile density coefficient(λ) of unit cell was calculated as:

Table 1.

Schematic and real images of weft-knitted loop pile fabrics’ unit cell and their structural parameters.

Structure	Side and front view of fabric unit cell(Schematic and real image)
S1
S2
S3
S4
S5
S6

Structure	c.p.c Pile		w.p.c Pile		Unit cell’s pile-covered ratio(µ)	Thickness(mm)		Weight(g/m 2 )		λ(cm − 2 )	Density(kg/m 3 )
	Mean	SD	Mean	SD		Mean	SD	Mean	SD
S1	3.91	0.120	2.66	0.052	1.000	8.55	0.275	630.78	12.32	10.40	73.79
S2	3.89	0.032	2.75	0.053	0.500	8.05	0.119	554.28	10.87	5.35	68.85
S3	3.82	0.042	2.81	0.057	0.500	7.91	0.209	549.43	9.87	5.37	69.44
S4	3.98	0.042	2.76	0.070	0.500	7.96	0.104	525.31	14.99	5.49	65.95
S5	3.81	0.120	2.81	0.057	0.686	8.32	0.226	570.10	27.96	7.34	68.53
S6	4.05	0.053	2.81	0.032	0.500	6.17	0.198	513.34	12.59	5.69	83.14

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1

µ represents the unit cell’s pile-covered ratio, while c.p.c_Pile(cm⁻¹) and w.p.c_Pile(cm⁻¹) indicate the number of piles per unit fabric length in course and wale directions, respectively. Calculated λ(cm⁻²) values are shown in Table 1. The pile density coefficient(λ) utilized in this study is defined as a “structural engineering index” based on the physical properties of the cotton fabric layers. Unlike statistical regression models, this parameter represents a “physics-based constant” used in textile engineering to predict, optimize and analysis of the mechanical response of technical fabrics. The CO/PES ratio was calculated based on the average weight of the constituent layers, as defined in Eq. (2). Specifically, the weights of the individual cotton and polyester layers were measured for each structure, and their average values were used to determine the CO/PES ratio(Table 2).

2

Compression test

Compression, recovery, and thickness were measured using an Instron 5566(Fig. 1.(c), (d)). Samples (15 × 15 cm²) were compressed at 12 mm/min to 80% strain following ASTM D575, with five samples per condition. Compression work was analyzed using the Kawabata KES-F system²⁸:

3

where P_c(N) is the compression force, T₀(mm) is initial fabric thickness, T_m(mm) is thickness at maximum pressure^25–28. Compression elastic modulus was the slope of the second region of the stress-strain curve of the support surfaces. Yield strain was identified at the end of elastic deformation before plateau onset(Fig. 2). In this study, the KES-F system was therefore used as a complementary technique to ASTM D575 rather than as an alternative method. While ASTM D575 characterizes the overall compressive performance at higher loads, the KES-F-derived compression work provides additional insight into the energy absorption behavior that is particularly relevant for spacer fabric cushioning applications.

Body pressure distribution test

Interface pressure distribution was measured using the PT-Mat-F10L2000 system(Payafanavaran Ferdowsi Co.) placed between the participant and support surface(sample size: 140 × 60 cm²)(Fig. 1.(e), (f)). Tests involved a healthy child participant(Gender: female, Age: 6 years, Weight: 20 kg, Height: 118 cm, BMI: 14.36 kg/m²(13.4 < Normal BMI of 6-years female child²⁹< 17.1)) in supine and lateral positions(Table 3), as these are most relevant to pressure ulcer risk. The pressure distribution indicators were defined as following:

Average pressure(P_A)(Pa): The average interface pressure values of different points

Peak pressure(P_P)(Pa): The maximum pressure values measured on the sensor pad

Total contact surface(A_C)(cm²): The contact area between the sensor pad and the body

High-risk surface(A_H)(cm²): The contact area of the points in which pressure is more than 40 mmHg

To ensure the reliability and reproducibility of the interface pressure data, a rigorous standardized protocol was followed for each of the six hybrid construction types. Measurements were performed in both supine and lateral positions. Upon positioning the participant on each support surface, a 30-second stabilization period was strictly observed before data recording to allow for initial material compression and postural settling. To minimize potential positioning variability and experimental noise, three separate samples of each hybrid structure were tested. These three repetitions were performed on three distinct samples of the same construction type to account for potential material consistency variations. The interface pressure values reported in this study represent the mean of these measurements. All data collection was completed within a single controlled session to eliminate environmental or temporal variables, ensuring that the observed differences were primarily attributable to the mechanical properties of the hybrid structures.

In this study a preliminary human trial was conducted with a single participant to evaluate the behavior of the developed support surfaces under controlled conditions. This study was designed solely to illustrate feasibility and maintain consistent testing conditions for material performance assessment. It is important to note that this manuscript primarily addresses the material science aspects of the support surfaces rather than clinical outcomes. Consequently, statistical generalization from this single-subject trial is not possible.

The decision to employ static interface pressure testing is grounded in the clinical reality that prolonged, immobile positioning is a fundamental precursor to pressure ulcer formation. In individuals with significantly limited mobility, sustained mechanical loading of soft tissues against a support surface represents the primary physiological challenge. Consequently, static evaluation—a methodology widely adopted in biomechanical research for mattresses and cushions—offers a representative simulation of the critical conditions under which pressure redistribution is most vital. While dynamic factors like repositioning and shear forces are important, our findings provide essential baseline evidence on the foundational ability of these hybrid structures to mitigate sustained pressure. Future investigations will incorporate cyclic loading and shear stress analysis to further enhance clinical generalizability.

Statistical analysis

One-way ANOVA assessed the effect of surface structure on compression properties(α = 0.05), and two-way ANOVA evaluated the combined effects of structure and posture on pressure distribution outcomes(α = 0.05). Pearson’s correlation quantified relationships between compression properties and pressure distribution indices. While advanced statistical models and optimization algorithms (e.g., machine learning and hybrid metaheuristics) offer powerful predictive capabilities, they were not incorporated into this preliminary study to avoid overcomplicating the interpretation of the initial material-based results. These methods represent a promising direction for our future research as we transition to larger datasets. Drawing inspiration from these robust analytical methodologies, the present study employs systematic statistical tools to evaluate the mechanical performance of hybrid support surfaces.

Compression stress-strain behavior

Compression stress-strain curves of support surfaces(Fig. 2(a), (b)) reveal four regions:

1. Initial Linear Region(0–20% strain): The curve exhibits a lower slope, reflecting primarily the bending deformation of the pile fabric. At this stage, the support surface behavior closely follows that of the pile fabric, while the underlying spacer fabric deforms minimally.

2. Pile Compression and Spacer Buckling(20–40% strain): The slope increases as full compression of the pile fabric and buckling of spacer yarns occur. Friction among compressed piles contributes to initial non-linear behavior, while elastic deformation of the spacer dominates in the linear portion.

3. Spacer Plateau(40–60% strain): The spacer deforms easily, resulting in nearly constant pressure.

4. Spacer Compaction(60–80% strain): Rapid pressure increase occurs due to full compaction of the spacer and collapse of yarns within the fabric.

Relation between body pressure distribution and compression properties

Compression properties

As shown in Fig. 3.(a), the Spacer+S1 has the highest and the Spacer+S3 has the lowest WC. The statistical results confirm that the structure of support surfaces has no significant influence on the WC(p = 0.610 > 0.05). If one compares the WC of these surfaces with their constituents, it becomes clear that the spacer more strongly influences it. Thus, since the pile fabric plays a lesser role in the WC, statistically, there is no significant difference between the WC of the support surfaces despite their structural differences. The Spacer+S1 has the highest compression elastic modulus, while Spacer+S4 has the lowest. Statistical analysis indicates that the structure of the support surfaces significantly affects compression elastic modulus (p = 0.000 < 0.05). The results indicate that increasing the pile density coefficient(λ) in the pile fabric unit cell leads to a higher compression elastic modulus of the support surface made up of it(R² = 0.8524)(Table 1; Fig. 4.(c)). The Spacer+S2 has the highest yield strain, while Spacer+S3 has the lowest(Fig. 4.(a)). Statistical analysis indicates that the structure of the support surfaces significantly affects yield strain(p = 0.018 < 0.05).

Pressure distribution characteristics

The average pressure(P_A) was lower for all support surfaces than for the reference condition(no support surface) in every position(Fig. 3.(a) and Table 5). In the supine position, Spacer+S4 produced the highest P_A and Spacer+S6 the lowest. Because pressure is a key factor in pressure-ulcer formation, all surfaces effectively reduced P_A. As participant weight was constant, larger contact areas resulted in lower P_A, consistent with A_C trends across all positions(Figs. 3.(a) and 4.(a). All support surfaces also showed lower peak pressure(P_P) than the reference state in the supine position (Fig. 3.(c); Table 5). Spacer+S4 had the highest P_P and Spacer+S1 the lowest. In the lateral position, only Spacer+S1 reduced P_P relative to the reference. Spacer+S6 showed the highest P_P laterally, while Spacer+S1 remained the lowest across all positions, indicating superior P_P performance. Surfaces with smaller or uneven pile-covered regions tended to concentrate stress and increase P_P, whereas smoother surfaces reduced P_P.

The total contact area(A_C) of all support surfaces exceeded that of the reference condition in all positions(Fig. 4.(a); Table 5). A larger contact area distributes body weight more effectively, lowering pressure-ulcer risk. In the supine position, Spacer+S2 yielded the greatest A_C, whereas the Spacer+S1 showed the smallest. In the lateral position, Spacer+S6 had the highest A_C and the Spacer+S3 the lowest. A_C was generally greater in supine than lateral, likely because lateral positioning increases body curvature and decreases the effective contact area.

In the supine position, all surfaces reduced the area prone to developing pressure ulcers(A_D) compared with the reference state(Fig. 4.(d); Table 5). In the lateral position, all surfaces except Spacer+S2 and Spacer+S4 lowered A_D. Spacer+S4 showed the highest A_D in supine and Spacer+S6 the lowest; laterally, Spacer+S2 produced the highest A_D and Spacer+S5 the lowest. Surfaces that reduced P_A and increased A_C generally showed lower A_D. Compared with the reference condition, support surfaces reduced high-risk areas by up to 44.6%(supine) and 20.12%(lateral). Statistical analysis indicated that surface structure significantly affected A_C(p = 0.000 < 0.05), whereas posture significantly affected all pressure indices except P_P(p = 0.000 < 0.05). A structure–posture interaction was found only for A_C(p = 0.000 < 0.05), underscoring the need to integrate material design with posture-specific ergonomics. From an assistive technology perspective, these hybrid surfaces demonstrate potential for:

Limitations and future work

This proof-of-concept study has several limitations that warrant acknowledgment. First, the use of a single healthy participant as a representative model for pediatric-scale loading limits the generalizability of the findings to broader adult populations or diverse clinical conditions. While this controlled setup enabled a clear assessment of mechanical–pressure relationships, future research involving larger, more heterogeneous cohorts—including individuals with limited mobility—is essential for clinical validation. Second, measurements were restricted to supine and lateral positions; incorporating prone and seated postures would broaden the applicability of these hybrid surfaces. Additionally, the spatial resolution of the pressure sensor pad (3.5 cm²/cell) may not capture fine-grained pressure gradients over smaller anatomical regions. Future investigations should utilize high-density sensor arrays and include physiological measurements, such as tissue perfusion and oxygenation, to provide a more comprehensive clinical evaluation. A limitation of this study is the small sample size used for correlation analysis. While sufficient for identifying preliminary trends in biomechanical testing, the statistical power is limited for broad generalizations. Therefore, these correlations should be interpreted as early indicators, requiring further validation with larger datasets in future research. Subsequent work will also focus on refining fabric combinations based on long-term monitoring and user feedback in real-world hospital and home-care settings.

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

The Ethics Review Board of Amirkabir University of Technology (Tehran Polytechnic) officially granted an ethical waiver for this research (Submission ID: e1acc686-1628-43ea-aed9-b8d151e8be09) as the procedures were entirely non-invasive and did not involve clinical interventions or medical risks. This study served as an initial biomechanical feasibility assessment using a healthy child to examine material–pressure relationships under controlled conditions. All procedures performed in this study involving a human participant were in accordance with the ethical standards of the institutional research committee and with the Declaration of Helsinki (2013). Formal written informed consent was obtained from the parents of the minor participant prior to the commencement of the study.