Sleeping mattress determinants and evaluation: a biomechanical review and critique

A method for calculating vector forces at human-mattress interface during sleeping positions utilizing image registration

The vector forces at the human-mattress interface are not only crucial for understanding the distribution of vertical and shear forces exerted on the human body during sleep but also serves as a significant input for biomechanical models of sleeping positions, whose accuracy determines the credibility of predicting musculoskeletal system loads. In this study, we introduce a novel method for calculating the interface vector forces. By recording indentations after supine and lateral positions using a vacuum mattress and 3D scanner, we utilize image registration techniques to align body pressure distribution with the mattress deformation scanning images, thereby calculating the vector force values for each unit area (36.25 mm × 36.25 mm). This method was validated through five participants attendance from two perspectives, revealing that (1) the mean summation of the vertical force components is 98.67% ± 7.21% body weight, exhibiting good consistency, and mean ratio of horizontal component force to body weight is 2.18% ± 1.77%. (2) the predicted muscle activity using the vector forces as input to the sleep position model aligns with the measured muscle activity (%MVC), with correlation coefficient over 0.7. The proposed method contributes to the vector force distribution understanding and the analysis of musculoskeletal loads during sleep, providing valuable insights for mattress design and evaluation.

Sleep quality and comfort in fully automated vehicles: A comparison of two seat configurations

As autonomous driving technology advances, the possibility of using vehicles as sleeping environments becomes increasingly relevant. To investigate the feasibility of this concept, a sleep study was conducted with twelve participants who were given a 4-h opportunity window to sleep in both reclined and flat seat configurations. The evaluation involved both objective measures, including polysomnographic (PSG) data analysis, and subjective measures through questionnaires, assessing sleep quality and comfort. While the sleep quantity results were comparable between the two sleeping positions, the reclined position showed a slight advantage in sleep quantity (TST and WASO). Interestingly, a trend highlighting a possible difference was found between the seat positions regarding non-rapid eye movement stage 3 (NREM 3). NREM 3 tended to be in a higher proportion of total sleep time in the flat seat position. Sleep onset latency (SOL) also showed a trend of a shorter latency by participants in the flat position. Additionally, most participants reported a preference for the flat position over the reclined position. These findings suggest that a flat seat configuration could offer a more comfortable and restful sleep environment for passengers in autonomous vehicles.

Engineering the perfect mattress: The influence of substrate mechanics on deep tissue stresses in supine

BACKGROUND

With increasing global interest in sleep hygiene, sleep ergonomics is an area that has been largely understudied. During sleep individuals turn over during the night to restore blood flow in occluded blood vessels, indicating that control of local tissue pressure may play a role in improving sleep comfort. This study investigates the influence of mattress stiffness on tissue compressive stresses during supine lying.

METHODS

A subject-specific 3D finite element (FE) model of the pelvis area has been developed to simulate supine lying on substrates of varying firmness. Constitutive parameters for the adipose-skin tissue and muscle-organ tissue were calibrated using a novel application of the inverse finite element method.

FINDINGS

The compressive stress was consistently greatest in the muscle interfacing the sacrum at 18.5 kPa on the soft foam, and 30.9 kPa on the firm foam. From soft to firm, the compressive stress increased by 67% at the sacrum, 20% at the ischium, 42% at the lesser trochanter, and 50% at the skin.

INTERPRETATION

The non-linearity of the foam substrate had a pressure distributing effect, relieving the peak compressive stresses at the sacrum, indicating that it may be possible to design arrays of foam substrates that can provide most efficient pressure relief.

Compression Property of TPEE-3D Fibrous Material and Its Application in Mattress Structural Layer

Thermoplastic poly(ether/ester) elastomer (TPEE) has great potential as a mattress material due to its high resilience, breathability, and light weight. This study aimed to evaluate the feasibility of TPEE-3D fibrous material (T3DF), a three-dimensional block material made of TPEE fibers randomly aligned and loop-connected, for mattress application. After testing the compression properties of T3DF, the effects of T3DF structural layers on mattress firmness were investigated. The results showed that T3DF had good energy absorption capacity, broad indentation hardness range (126.94-333.82 N), and high compression deflection coefficient (2.79-4.39). The thickness and density of T3DF were the main factors influencing mattress firmness, and the impact of thickness was more significant (p < 0.05). Owing to the hard and soft segments contained in TPEE, T3DF could be used for both the padding and core layers of the mattress. The hardness value and Dsurface of the mattress with a T3DF padding layer increased with T3DF density but decreased with T3DF thickness. Moreover, the hardness value and Dsurface of the mattress with a T3DF core layer increased with T3DF density, while with T3DF thickness, its Dsurface increased and Dbottom decreased. Therefore, the thick and low-density T3DF padding layer could improve the comfort of the mattress surface, a thin T3DF core layer could satisfy both the softer surface and the firmer bottom of the mattress.

Effect of a mattress on lumbar spine alignment in supine position in healthy subjects: an MRI study

BACKGROUND

Humans should sleep for about a third of their lifetime and the choice of the mattress is very important from a quality-of-life perspective. Therefore, the primary aim of this study was to assess the changes of lumbar angles, evaluated in a supine position using magnetic resonance imaging (MRI), on a mattress versus a rigid surface.

METHODS

Twenty healthy subjects (10 females, 10 males), aged 32.3 ± 6.5 (mean ± standard deviation), with body mass index 22.4 ± 2.9, completed three evaluations: (i) spine MRI in supine position on a mattress (MAT); (ii) spine MRI in supine position on rigid surface (CON); and (iii) biplanar radiographic imaging in standing position. The following indexes were calculated for both MAT and CON: lumbar lordosis angles L1-L5, L1-S1, L5-S1, and the sacral slope (SS). Further, pelvic incidence (PI) was calculated from the biplanar radiographic images.

RESULTS

Main findings were (i) L1-L5 and SS were greater in MAT than CON (L1:L5: +2.9°; SS: +2.0°); (ii) L5-S1 was lower in MAT than CON (-1.6°); (iii) L1-S1 was greater in MAT than CON only for male subjects (+2.0°); (iv) significant and positive correlations between PI and L1-L5, L1-S1 and SS were observed in both CON and MAT.

CONCLUSIONS

The use of a mattress determined small but statistically significant changes in lumbar angles.

RELEVANCE STATEMENT

The use of a mattress determines small but statistically significant changes in radiological angles describing the sagittal alignment of the lumbar spine when lying in the supine position.

KEY POINTS

• Lordosis angle L1-L5 was greater in MAT than in CON condition (+2.9°). • Sacral slope was greater in MAT than in CON condition (+2.0°). • Lordosis angle L5-S1 was lower in MAT than in CON condition (-1.6°).

Computational Biomechanics of Sleep: A Systematic Mapping Review

Biomechanical studies play an important role in understanding the pathophysiology of sleep disorders and providing insights to maintain sleep health. Computational methods facilitate a versatile platform to analyze various biomechanical factors in silico, which would otherwise be difficult through in vivo experiments. The objective of this review is to examine and map the applications of computational biomechanics to sleep-related research topics, including sleep medicine and sleep ergonomics. A systematic search was conducted on PubMed, Scopus, and Web of Science. Research gaps were identified through data synthesis on variants, outcomes, and highlighted features, as well as evidence maps on basic modeling considerations and modeling components of the eligible studies. Twenty-seven studies (n = 27) were categorized into sleep ergonomics (n = 2 on pillow; n = 3 on mattress), sleep-related breathing disorders (n = 19 on obstructive sleep apnea), and sleep-related movement disorders (n = 3 on sleep bruxism). The effects of pillow height and mattress stiffness on spinal curvature were explored. Stress on the temporomandibular joint, and therefore its disorder, was the primary focus of investigations on sleep bruxism. Using finite element morphometry and fluid-structure interaction, studies on obstructive sleep apnea investigated the effects of anatomical variations, muscle activation of the tongue and soft palate, and gravitational direction on the collapse and blockade of the upper airway, in addition to the airflow pressure distribution. Model validation has been one of the greatest hurdles, while single-subject design and surrogate techniques have led to concerns about external validity. Future research might endeavor to reconstruct patient-specific models with patient-specific loading profiles in a larger cohort. Studies on sleep ergonomics research may pave the way for determining ideal spine curvature, in addition to simulating side-lying sleep postures. Sleep bruxism studies may analyze the accumulated dental damage and wear. Research on OSA treatments using computational approaches warrants further investigation.

Vision Transformers (ViT) for Blanket-Penetrating Sleep Posture Recognition Using a Triple Ultra-Wideband (UWB) Radar System

Sleep posture has a crucial impact on the incidence and severity of obstructive sleep apnea (OSA). Therefore, the surveillance and recognition of sleep postures could facilitate the assessment of OSA. The existing contact-based systems might interfere with sleeping, while camera-based systems introduce privacy concerns. Radar-based systems might overcome these challenges, especially when individuals are covered with blankets. The aim of this research is to develop a nonobstructive multiple ultra-wideband radar sleep posture recognition system based on machine learning models. We evaluated three single-radar configurations (top, side, and head), three dual-radar configurations (top + side, top + head, and side + head), and one tri-radar configuration (top + side + head), in addition to machine learning models, including CNN-based networks (ResNet50, DenseNet121, and EfficientNetV2) and vision transformer-based networks (traditional vision transformer and Swin Transformer V2). Thirty participants (n = 30) were invited to perform four recumbent postures (supine, left side-lying, right side-lying, and prone). Data from eighteen participants were randomly chosen for model training, another six participants' data (n = 6) for model validation, and the remaining six participants' data (n = 6) for model testing. The Swin Transformer with side and head radar configuration achieved the highest prediction accuracy (0.808). Future research may consider the application of the synthetic aperture radar technique.

Depth-Camera-Based Under-Blanket Sleep Posture Classification Using Anatomical Landmark-Guided Deep Learning Model

Emerging sleep health technologies will have an impact on monitoring patients with sleep disorders. This study proposes a new deep learning model architecture that improves the under-blanket sleep posture classification accuracy by leveraging the anatomical landmark feature through an attention strategy. The system used an integrated visible light and depth camera. Deep learning models (ResNet-34, EfficientNet B4, and ECA-Net50) were trained using depth images. We compared the models with and without an anatomical landmark coordinate input generated with an open-source pose estimation model using visible image data. We recruited 120 participants to perform seven major sleep postures, namely, the supine posture, prone postures with the head turned left and right, left- and right-sided log postures, and left- and right-sided fetal postures under four blanket conditions, including no blanket, thin, medium, and thick. A data augmentation technique was applied to the blanket conditions. The data were sliced at an 8:2 training-to-testing ratio. The results showed that ECA-Net50 produced the best classification results. Incorporating the anatomical landmark features increased the F1 score of ECA-Net50 from 87.4% to 92.2%. Our findings also suggested that the classification performances of deep learning models guided with features of anatomical landmarks were less affected by the interference of blanket conditions.

The Influence of Mattress Stiffness on Spinal Curvature and Intervertebral Disc Stress-An Experimental and Computational Study

Sleeping support systems can influence spinal curvature, and the misalignment of the spinal curvature can lead to musculoskeletal problems. Previous sleep studies on craniocervical support focused on pillow variants, but the mattress supporting the pillow has rarely been considered. This study used a cervical pillow and three mattresses of different stiffnesses, namely soft, medium, and hard, with an indentation load deflection of 20, 42, and 120 lbs, respectively. A novel electronic curvature measurement device was adopted to measure the spinal curvature, whereby the intervertebral disc loading was computed using the finite element method. Compared with the medium mattress, the head distance increased by 30.5 ± 15.9 mm, the cervical lordosis distance increased by 26.7 ± 14.9 mm, and intervertebral disc peak loading increased by 49% in the soft mattress environment. Considering that the pillow support may increase when using a soft mattress, a softer or thinner pillow is recommended. The head distance and cervical lordosis distance in the hard mattress environment were close to the medium mattress, but the lumbar lordosis distance reduced by 10.6 ± 6.8 mm. However, no significant increase in intervertebral disc loading was observed, but contact pressure increased significantly, which could cause discomfort and health problems.

Spine Posture, Mobility, and Stability of Top Mobile Esports Athletes: A Case Series

Professional esports athletes spend a long time in the same sitting posture during training and competition. Mobile esports may exacerbate potential postural problems because of the closer and unsupported arms and because athletes spend more time in a forward-/flexed-head posture. Prolonged sitting in these postures carries significant health risks and may lead to musculoskeletal problems and injuries. The objective of this retrospective study is to assess the posture, mobility, and stability of the spine for professional mobile esports athletes. We collected spine-assessment data from 48 athletes participating in a top-tier league on a real-time-strategy battle-arena online game. The spinal assessment was conducted using the SpinalMouse® under upright standing and trunk flexion in addition to the Matthiass test. Measurements were converted into Idiag Scores by the SpinalMouse® software. The Idiag Posture, Idiag Mobility, and Idiag Stability scores were 62.50 (IQR: 21), 63.50 (IQR: 19.5), and 54.50 (IQR: 14.5), respectively, and were significantly lower (p < 0.001) than the reference normative value (100). Age was found to have a weak positive correlation with the posture score (ρ = 0.29, p = 0.048). Although career duration appeared to lower the scores, the association was insignificant (p > 0.05). The scores also had no significant association with body height, body mass, body mass index, and esports team (p > 0.05). It was anticipated that mobile-based esports would attenuate the biomechanics of the spine and increase the likelihood of musculoskeletal problems, such as neck and back pain.

A Night-Time Monitoring System (eNightLog) to Prevent Elderly Wandering in Hostels: A Three-Month Field Study

Older people are increasingly dependent on others to support their daily activities due to geriatric symptoms such as dementia. Some of them stay in long-term care facilities. Elderly people with night wandering behaviour may lose their way, leading to a significant risk of injuries. The eNightLog system was developed to monitor the night-time bedside activities of older people in order to help them cope with this issue. It comprises a 3D time-of-flight near-infrared sensor and an ultra-wideband sensor for detecting human presence and to determine postures without a video camera. A threshold-based algorithm was developed to classify different activities, such as leaving the bed. The system is able to send alarm messages to caregivers if an elderly user performs undesirable activities. In this study, 17 sets of eNightLog systems were installed in an elderly hostel with 17 beds in 9 bedrooms. During the three-month field test, 26 older people with different periods of stay were included in the study. The accuracy, sensitivity and specificity of detecting non-assisted bed-leaving events was 99.8%, 100%, and 99.6%, respectively. There were only three false alarms out of 2762 bed-exiting events. Our results demonstrated that the eNightLog system is sufficiently accurate to be applied in the hostel environment. Machine learning with instance segmentation and online learning will enable the system to be used for widely different environments and people, with improvements to be made in future studies.

Ergonomic Consideration in Pillow Height Determinants and Evaluation

(1) Background: Sleep problems have become one of the current serious public health issues. Pillow height affects the alignment of the cervical spine and is closely related to the mechanical environment of the cervical spine. An appropriate pillow height can provide adequate support for the head and neck to reduce the stress in the cervical spine and relax the muscles of the neck and shoulder, thereby relieving pain and improving sleep quality. (2) Methods: We reviewed the current trends, research methodologies, and determinants of pillow height evaluation, summarizing the evidences published since 1997. In particular, we scrutinized articles dealing with the physiological and mechanical characteristics of the head-neck-shoulder complex. (3) Results: Through the investigation and analysis of these articles, we presented several quantitative and objective determinants for pillow height evaluation, including cervical spine alignment, body dimension, contact pressure, and muscle activity. The measurement methods and selection criteria for these parameters are described in detail. However, the suggested range for achieving optimal cervical spine alignment, appropriate pressure distribution, and minimal muscle activity during sleep cannot yet be identified considering the lack of sufficient evidence. Moreover, there remain no firm conclusions about the optimal pillow height for the supine and lateral positions. (4) Conclusions: A comprehensive evaluation combining the above determinants provides a unique solution for ergonomic pillow design and proper pillow height selection, which can effectively promote the public sleep health. Therefore, it is necessary to develop a reasonable algorithm to weigh multiple determinants.

A Blanket Accommodative Sleep Posture Classification System Using an Infrared Depth Camera: A Deep Learning Approach with Synthetic Augmentation of Blanket Conditions

Surveillance of sleeping posture is essential for bed-ridden patients or individuals at-risk of falling out of bed. Existing sleep posture monitoring and classification systems may not be able to accommodate the covering of a blanket, which represents a barrier to conducting pragmatic studies. The objective of this study was to develop an unobtrusive sleep posture classification that could accommodate the use of a blanket. The system uses an infrared depth camera for data acquisition and a convolutional neural network to classify sleeping postures. We recruited 66 participants (40 men and 26 women) to perform seven major sleeping postures (supine, prone (head left and right), log (left and right) and fetal (left and right)) under four blanket conditions (thick, medium, thin, and no blanket). Data augmentation was conducted by affine transformation and data fusion, generating additional blanket conditions with the original dataset. Coarse-grained (four-posture) and fine-grained (seven-posture) classifiers were trained using two fully connected network layers. For the coarse classification, the log and fetal postures were merged into a side-lying class and the prone class (head left and right) was pooled. The results show a drop of overall F1-score by 8.2% when switching to the fine-grained classifier. In addition, compared to no blanket, a thick blanket reduced the overall F1-scores by 3.5% and 8.9% for the coarse- and fine-grained classifiers, respectively; meanwhile, the lowest performance was seen in classifying the log (right) posture under a thick blanket, with an F1-score of 72.0%. In conclusion, we developed a system that can classify seven types of common sleeping postures under blankets and achieved an F1-score of 88.9%.

Pillow Support Model with Partitioned Matching Based on Body Pressure Distribution Matrix

(1) Objective: Sleep problems have become one of the current serious public health issues. The purpose of this research was to construct an ideal pressure distribution model for head and neck support through research on the partitioned support surface of a pillow in order to guide the development of ergonomic pillows. (2) Methods: Seven typical memory foam pillows were selected as samples, and six subjects were recruited to carry out a body pressure distribution experiment. The average value of the first 10% of the samples in the comfort evaluation was calculated to obtain the relative ideal body pressure distribution matrix. Fuzzy clustering was performed on the ideal matrix to obtain the support surface partition. The ideal body pressure index of each partition was calculated, and a hierarchical analysis of each partition was then performed to determine the pressure sensitivity weight of each partition. Using these approaches, the key ergonomic node coordinates of the partitions of four different groups of people were extracted. The ergonomic node coordinates and the physical characteristics of the material were used to design a pillow prototype. Five subjects were recruited for each of the four groups to repeat the body pressure distribution experiment to evaluate the pillow prototype. (3) Results: An ideal support model with seven partitions, including three partitions in the supine position and four partitions in the lateral position, was constructed. The ideal body pressure distribution matrix and ideal body pressure indicators and pressure sensitivity weights for each partition were provided. The pillow that was designed and manufactured based on this model reproduced the ideal pressure distribution matrix evaluated by various groups of people. (4) Conclusion: The seven-partition ideal support model can effectively describe the head and neck support requirements of supine and lateral positions, which can provide strong support for the development of related products.

A Fully Automated Pulsating Support System for Pressure Injury Prevention and Treatment in 10 Belgium Nursing Homes: An Observational Study

PURPOSE

We studied pressure injury (PI) stage II-IV cumulative incidence and the change of PI status in the sacral area of nursing home residents associated with the use of a fully automated pulsating support system air mattress in use for 30 days. We also assessed caregivers', residents', and their family members' experiences and perceptions of mattress comfort and other factors such as pain.

DESIGN

Multicenter cohort study.

SUBJECT AND SETTING

A convenience sample of 40 residents residing in 10 Belgian nursing homes was recruited.

METHODS

Pressure injury classification was confirmed using the European Pressure Ulcer Advisory Panel classification system. The Pressure Ulcer Scale for Healing (PUSH) tool was used to assess and measure PI status change. A comfort assessment was performed at end of the study. Cumulative PI incidence of stages II-IV was calculated, and frequencies and percentages were used to describe the results of the comfort assessments.

RESULTS

Residents were allocated to the prevention group (n = 22) and to the treatment group (n = 18). The cumulative PI incidence was 4.5% (n = 1/22) in the prevention group. In the treatment group, the mean score on the PUSH tool decreased from 9.36 to 7.70 during the observation period, indicating an overall improvement. Four of the existing PIs healed, 17 PIs remained stable, and 1 PI deteriorated. The comfort questionnaires were completed by 76 nursing home caregivers, 21 family members, and 11 residents in the 10 participating nursing homes; the mattress comfort was perceived as very good, and pain was noted to decrease.

CONCLUSIONS

Low cumulative PI incidence findings were observed with use of the mattress for the prevention of PIs and resulted in improvements in existing PIs, results which are consistent with several existing studies. The majority of the caregivers, residents, and family members evaluated the mattress as comfortable. Future research is needed to corroborate findings in larger randomized clinical trials.

Night-Time Monitoring System (eNightLog) for Elderly Wandering Behavior

Wandering is a common behavioral disorder in the community-dwelling elderly. More than two-thirds of caregivers believe that wandering would cause falls. While physical restraint is a common measure to address wandering, it could trigger challenging behavior in approximately 80% of the elderly with dementia. This study aims to develop a virtual restraint using a night monitoring system (eNightLog) to provide a safe environment for the elderly and mitigate the caregiver burden. The eNightLog system consisted of remote sensors, including a near infra-red 3D time-of-flight sensor and ultrawideband sensors. An alarm system was controlled by customized software and algorithm based on the respiration rate and body posture of the elderly. The performance of the eNightLog system was evaluated in both single and double bed settings by comparing to that of a pressure mat and an infrared fence system, under simulated bed-exiting scenarios. The accuracy and precision for the three systems were 99.0%, 98.8%, 85.9% and 99.2%, 97.8%, 78.6%, respectively. With higher accuracy, precision, and a lower false alarm rate, eNightLog demonstrated its potential as an alternative to physical restraint to remedy the workload of the caregivers and the psychological impact of the elderly.

Cardboard Bed Without Mattress Is Ineffective in Improving the body Contact Pressure-a Preliminary Study Using a Dummy Model

OBJECTIVE

This study aimed to describe and evaluate the dispersion of body-mattress contact pressure on a cardboard bed and investigate whether the cardboard bed has a positive effect on evacuees' musculoskeletal burden.

MATERIALS AND METHODS

A high-performance nursing simulator was used to measure the contact pressure and the body surface contour area of the bed, and these values were collected with the patient in the supine position using the Body Pressure Measurement System. Data of each test were acquired 10 times and were compared among 4 conditions (plastic sheet, cardboard bed, cardboard bed with a blanket, and cardboard bed with a mattress-topper). The data analysis for body-mattress contacts pressure and the surface contour area of the whole body, head, chest, and buttocks were conducted by one-way repeated analysis of variance and Bonferroni post-hoc test.

RESULTS

The average body-contact pressure on the cardboard bed did not decrease compared with that on the floor with plastic sheets. In contrast, the body surface contour area was significantly different among any other conditions, but the gap was only approximately 16%. However, the body-contact pressure and the body surface contour area were improved when a mattress-topper was added on the cardboard bed. When a blanket was laid on the cardboard bed, the contact area was increased.

CONCLUSION

Our results indicate that the pressure dispersion ability of the cardboard bed was not sufficient; however, adding the mattress-topper or the blanket could contribute to an improvement in the evacuees' musculoskeletal burden. Many evacuees lay a mattress topper or futon on a cardboard bed after installing cardboard beds. Our findings may also support the scientific validity of the evacuees' actual sleeping style in Japan. This preliminary study provides the basis for future research on exploring an appropriate sleeping bed condition in evacuee shelters.

Comfort driven design of innovative products: A personalized mattress case study

BACKGROUND

Human-centred design asks for wellbeing and comfort of the customer/worker when interacting with a product. Having a good perception-model and an objective method to evaluate the experienced (dis)comfort by the product user is needed for performing a preventive comfort evaluation as early as possible in the product development plan. The mattress of a bed is a typical product whose relevance in everyday life of people is under-evaluated. Fortunately, this behaviour is quickly changing, and the customer wants to understand the product he/she buys and asks for more comfortable and for scientifically assessed products. No guidelines for designing a personalized mattress are available in the literature.

OBJECTIVES

This study deals with the experience of designing an innovative product whose product-development-plan is focused on the customer perceived comfort: a personalized mattress. The research question is: which method can be used to innovate or create a comfort-driven human-centred product?

METHODS

Virtual prototyping was used to develop a correlated numerical model of the mattress. A comfort model for preventively assessing the perceived comfort was proposed and experimentally tested. Mattress testing sessions with subjects were organized, and collected data were compared with already tested mattresses. Brainstorming and multi-expert methods were used to propose, realize, and test an archetype of a new mattress for final comfort assessment.

RESULTS

A new reconfigurable mattress was developed, resulting in two patents. The mattress design shows that personalized products can be tuned according to the anthropometric data of the customer in order to improve the comfort experience during sleep.

CONCLUSIONS

A "comfort-driven design guideline" was proposed; this method has been based on the use of virtual prototyping, virtual optimization and physical prototyping and testing. It allowed to improve an existing product in a better way and to bring innovation in it.

Pressure ulcer Cat. II-IV incidence on the CuroCell S.A.M. PRO powered reactive air support surface in a high-risk population: A multicentre cohort study in 12 Belgian nursing homes

The primary objective was to study pressure ulcer (PU) category II-IV (including suspected deep tissue injury and unstageable PUs) cumulative incidence and PU incidence density, in a 30day observation period, associated with the use of the CuroCell S.A.M. PRO powered reactive air support surface in nursing home residents at risk for PU development. Secondary objectives were to study (a) PU category I cumulative incidence and PU incidence density and (b) user (caregivers and residents) experiences and perceptions of comfort associated with the use of the support surface under study. A multicentre cohort study was set up in 37 care units of 12 Belgian nursing homes. The sample consisted of 191 residents at risk of PU development (Braden score ≤ 17). The cumulative PU incidence was 4.7% (n = 9). The PU incidence density was 1.7/1000 observation days (9 PU/5370 days). The experience and perceptions of comfort analysis revealed that the CuroCell S.A.M. PRO powered reactive air support surface was comfortable for daily use. The mode of action and the quietness of the pump function had a positive impact on sleep quality. Patient comfort and sleep quality are essential criteria in the selection of a support surface.