Thermal modulation of skin friction at the finger pad.

Preliminary human studies show that reduced skin temperature minimises the risk of mechanically induced skin damage. However, the mechanisms by which cooling enhances skin tolerance to pressure and shear remain poorly understood. We hypothesized that skin cooling below thermo-neutral conditions will decrease kinetic friction at the skin-material interface. To test our hypothesis, we measured the friction coefficient of a thermally pre-conditioned index finger pad sliding at a normal load (5N) across a plate maintained at three different temperatures (38, 24, and 16 °C) in 8 healthy young adults (29±5y). To quantify the temperature distribution of the skin tissue, we used 3D surface scanning and Optical Coherence Tomography to develop an anatomically representative thermal model of the finger. Our group-level data indicated that the sliding finger with thermally affected tissues (up to 8 mm depth) experienced significantly lower frictional forces (p<0.01) at plate temperatures of 16 °C (i.e. 32% decrease) and 24 °C (i.e. 13% decrease) than at 38 °C, respectively. This phenomenon occurred consistently across participants (i.e. N = 6/8, 75%) and without large changes in skin hydration during sliding. Our complementary experimental and theoretical results provide new insights into thermal modulation of skin friction that can be employed for developing thermal technologies to maintain skin integrity under mechanical loading and shearing.

Optimization of Spatial and Temporal Configuration of a Pressure Sensing Array to Predict Posture and Mobility in Lying.

Commercial pressure monitoring systems have been developed to assess conditions at the interface between mattress/cushions of individuals at risk of developing pressure ulcers. Recently, they have been used as a surrogate for prolonged posture and mobility monitoring. However, these systems typically consist of high-resolution sensing arrays, sampling data at more than 1 Hz. This inevitably results in large volumes of data, much of which may be redundant. Our study aimed at evaluating the optimal number of sensors and acquisition frequency that accurately predict posture and mobility during lying. A continuous pressure monitor (ForeSitePT, Xsensor, Calgary, Canada), with 5664 sensors sampling at 1 Hz, was used to assess the interface pressures of healthy volunteers who performed lying postures on two different mattresses (foam and air designs). These data were down sampled in the spatial and temporal domains. For each configuration, pressure parameters were estimated and the area under the Receiver Operating Characteristic curve (AUC) was used to determine their ability in discriminating postural change events. Convolutional Neural Network (CNN) was employed to predict static postures. There was a non-linear decline in AUC values for both spatial and temporal down sampling. Results showed a reduction of the AUC for acquisition frequencies lower than 0.3 Hz. For some parameters, e.g., pressure gradient, the lower the sensors number the higher the AUC. Posture prediction showed a similar accuracy of 63-71% and 84-87% when compared to the commercial configuration, on the foam and air mattress, respectively. This study revealed that accurate detection of posture and mobility events can be achieved with a relatively low number of sensors and sampling frequency.

Retrospective evaluation of factors affecting successful fit testing of respiratory protective equipment during the early phase of COVID-19.

OBJECTIVES: Respiratory protective equipment is critical to protect healthcare workers from COVID-19 infection, which includes filtering facepiece respirators (FFP3). There are reports of fitting issues within healthcare workers, although the factors affecting fitting outcomes are largely unknown. This study aimed to evaluate factors affecting respirator fitting outcomes. DESIGN: This is a retrospective evaluation study. We conducted a secondary analysis of a national database of fit testing outcomes in England between July and August 2020. SETTINGS: The study involves National Health Service (NHS) hospitals in England. PARTICIPANTS: A total of 9592 observations regarding fit test outcomes from 5604 healthcare workers were included in the analysis. INTERVENTION: Fit testing of FFP3 on a cohort of healthcare workers in England, working in the NHS. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome measure was the fit testing result, that is, pass or fail with a specific respirator. Key demographics, including age, gender, ethnicity and face measurements of 5604 healthcare workers, were used to compare fitting outcomes. RESULTS: A total of 9592 observations from 5604 healthcare workers were included in the analysis. A mixed-effects logistic regression model was used to determine the factors which affected fit testing outcome. Results showed that males experienced a significantly (p<0.05) higher fit test success than females (OR 1.51; 95% CI 1.27 to 1.81). Those with non-white ethnicities demonstrated significantly lower odds of successful respirator fitting; black (OR 0.65; 95% CI 0.51 to 0.83), Asian (OR 0.62; 95% CI 0.52 to 0.74) and mixed (OR 0.60; 95% CI 0.45 to 0.79. CONCLUSION: During the early phase of COVID-19, females and non-white ethnicities were less likely to have a successful respirator fitting. Further research is needed to design new respirators which provide equal opportunity for comfortable, effective fitting of these devices.

A combined imaging, deformation and registration methodology for predicting respirator fitting.

N95/FFP3 respirators have been critical to protect healthcare workers and their patients from the transmission of COVID-19. However, these respirators are characterised by a limited range of size and geometry, which are often associated with fitting issues in particular sub-groups of gender and ethnicities. This study describes a novel methodology which combines magnetic resonance imaging (MRI) of a cohort of individuals (n = 8), with and without a respirator in-situ, and 3D registration algorithm which predicted the goodness of fit of the respirator. Sensitivity analysis was used to optimise a deformation value for the respirator-face interactions and corroborate with the soft tissue displacements estimated from the MRI images. An association between predicted respirator fitting and facial anthropometrics was then assessed for the cohort.

Continuous pressure monitoring of inpatient spinal cord injured patients: implications for pressure ulcer development.

STUDY DESIGN: Cohort observational study. OBJECTIVES: To examine the movement profiles of individuals with spinal cord injury (SCI) during their inpatient rehabilitative phase using continuous pressure monitoring (CPM), evaluating the trends in those with skin damage. SETTING: SCI specialist rehabilitation centre in the United Kingdom. METHODS: Individuals with SCI (n = 12) were assessed using CPM in the bed and chair over a 24-72 h. Pressure data was used as a surrogate for movement using both nursing interpretation and an intelligent algorithm. Clinical features were obtained including participants age, injury level, ASIA score, co-morbidities and prescribed support surfaces. Trends between movement profiles (frequency and intervals), SCI demographics and observed skin damage were assessed using cross-tabulation and histograms. RESULTS: The data revealed significant correlations (p < 0.05) between the nursing observation and algorithm for predicting movement, although the algorithm was more sensitive. Individuals with high level injuries (C1-T6) were observed to have a lower frequency of movement and larger intervals between movements when compared to low level injuries (T7-L5) during both lying and sitting periods. The individuals observed to have skin damage were predominantly those who had both a low frequency of movement and extended gaps between movements. CONCLUSIONS: Movements for pressure relief in both the bed and chair environments were dependent on the level of injury in individuals with SCI during their inpatient rehabilitation. Distinct movement patterns corresponded with those who acquired skin damage, revealing the potential clinical applications for technologies to monitor PU risk and inform personalised care.

Biomechanical and Physiological Evaluation of Respiratory Protective Equipment Application.

Purpose: Respiratory protective equipment is widely used in healthcare settings to protect clinicians whilst treating patients with COVID-19. However, their generic designs do not accommodate the variability in face shape across genders and ethnicities. Accordingly, they are regularly overtightened to compensate for a poor fit. The present study aims at investigating the biomechanical and thermal loads during respirator application and the associated changes in local skin physiology at the skin-device interface. Materials and Methods: Sixteen healthy volunteers were recruited and reflected a range of gender, ethnicities and facial anthropometrics. Four single-use respirators were evaluated representing different geometries, size and material interfaces. Participants were asked to wear each respirator in a random order while a series of measurements were recorded, including interface pressure, temperature and relative humidity. Measures of transepidermal water loss and skin hydration were assessed pre- and post-respirator application, and after 20 minutes of recovery. Statistical analysis assessed differences between respirator designs and associations between demographics, interface conditions and parameters of skin health. Results: Results showed a statistically significant negative correlation (p < 0.05) between the alar width and interface pressures at the nasal bridge, for three of the respirator designs. The nasal bridge site also corresponded to the highest pressures for all respirator designs. Temperature and humidity significantly increased (p < 0.05) during each respirator application. Significant increases in transepidermal water loss values (p < 0.05) were observed after the application of the respirators in females, which were most apparent at the nasal bridge. Conclusion: The results revealed that specific facial features affected the distribution of interface pressures and depending on the respirator design and material, changes in skin barrier function were evident. The development of respirator designs that accommodate a diverse range of face shapes and protect the end users from skin damage are required to support the long-term use of these devices.

A systematic review of movement monitoring devices to aid the prediction of pressure ulcers in at-risk adults.

The present study sought to explore the impact of movement monitoring devices on risk prediction and prevention of pressure ulcers (PU) among adults. Using systematic review methodology, we included original research studies using a prospective design, written in English, assessing adult patients' movement in bed, using a movement monitoring device. The search was conducted in March 2021, using PubMed, CINAHL, Scopus, Cochrane, and EMBASE databases, and returned 1537 records, of which 25 met the inclusion criteria. Data were extracted using a pre-designed extraction tool and quality appraisal was undertaken using the evidence-based librarianship (EBL). In total, 19 different movement monitoring devices were used in the studies, using a range of physical sensing principles. The studies focused on quantifying the number and types of movements. In four studies the authors compared the monitoring system with PU risk assessment tools, with a variety of high and low correlations observed. Four studies compared the relationship between movement magnitude and frequency and the development of PUs, with variability in results also identified. Two of these studies showed, as expected, that those who made less movements developed more PU; however, the two studies also unexpectedly found that PUs occurred in both low movers and high movers. In the final two studies, the authors focused on the concordance with recommended repositioning based on the results of the monitoring device. Overall, concordance with repositioning increased with the use of a monitoring device. The synthesis of the literature surrounding bed monitoring technologies for PU risk prediction showed that a range of physical sensors can be used to detect the frequency of movement. Clinical studies showed some correlation between parameters of movement and PU risk/incidence, although the heterogeneity of approaches limits generalisable recommendations.

Detection of posture and mobility in individuals at risk of developing pressure ulcers.

Pressure mapping technologies provide the opportunity to estimate trends in posture and mobility over extended periods in individuals at risk of developing pressure ulcers. The aim of the study was to combine pressure monitoring with an automated algorithm to detect posture and mobility in a vulnerable population of Spinal Cord Injured (SCI) patients. Pressure data from able-bodied cohort studies involving prescribed lying and sitting postures were used to train the algorithm. This was tested with data from two SCI patients. Variations in the trends of the centre of pressure (COP) and contact area were assessed for detection of small- and large-scale postural movements. Intelligent data processing involving a deep learning algorithm, namely a convolutional neural network (CNN), was utilised for posture classification. COP signals revealed perturbations indicative of postural movements, which were automatically detected using individual- and movement-specific thresholds. CNN provided classification of static postures, with an accuracy ranging between 70-84% in the training cohort of able-bodied subjects. A clinical evaluation highlighted the potential of the novel algorithm to detect postural movements and classify postures in SCI patients. Combination of continuous pressure monitoring and intelligent algorithms offers the potential to objectively detect posture and mobility in vulnerable patients and inform clinical-decision making to provide personalized care.

Biomechanical monitoring and machine learning for the detection of lying postures.

BACKGROUND: Pressure mapping technology has been adapted to monitor over prolonged periods to evaluate pressure ulcer risk in individuals during extended lying postures. However, temporal pressure distribution signals are not currently used to identify posture or mobility. The present study was designed to examine the potential of an automated approach for the detection of a range of static lying postures and corresponding transitions between postures. METHODS: Healthy subjects (n = 19) adopted a range of sagittal and lateral lying postures. Parameters reflecting both the interactions at the support surface and body movements were continuously monitored. Subsequently, the derivative of each signal was examined to identify transitions between postures. Three machine learning algorithms, namely Naïve-Bayes, k-Nearest Neighbors and Support Vector Machine classifiers, were assessed to predict a range of static postures, established with a training model (n = 9) and validated with new input from test data (n = 10). FINDINGS: Results showed that the derivative signals provided a means to detect transitions between postures, with actimetry providing the most distinct signal perturbations. The accuracy in predicting the range of postures from new test data ranged between 82%-100%, 70%-98% and 69%-100% for Naïve-Bayes, k-Nearest Neighbors and Support Vector Machine classifiers, respectively. INTERPRETATION: The present study demonstrated that detection of both static postures and their corresponding transitions was achieved by combining machine learning algorithms with robust parameters from two monitoring systems. This approach has the potential to provide reliable indicators of posture and mobility, to support personalised pressure ulcer prevention strategies.

A sensitivity analysis to evaluate the performance of temporal pressure - related parameters in detecting changes in supine postures.

Pressure mapping systems have been traditionally used to assess load distributions in individuals at risk of pressure ulcers. Recently, the technology has been adapted to monitor pressures over prolonged periods. The present study aims to investigate the predictive ability of selected biomechanical parameters estimated from pressure distributions for detecting postural changes in lying. Healthy participants (n = 11) were recruited and positioned in different lying postures, by utilizing the head of bed (HOB) angle and an automated tilting system to achieve evoked movements in the sagittal and transverse planes, respectively. Measurements included continuous monitoring of interface pressures and accelerations from the trunk and waist. Selected interface pressure parameters included; centre of pressure, contact area and pressure gradient. A threshold range for all parameters was established and Receiver Operating Characteristic (ROC) curves presented to determine the sensitivity and specificity for detecting postural changes. Temporal trends in the data revealed significant variance in the signal perturbations during each evoked postural change. Indeed, sensitivity and specificity were influenced by the specific threshold values and the relative position of the individual. As an example, sensitivity of some parameters exhibited a compromised trend at higher HOB angles, with low corresponding area under the ROC curve. By contrast, contact area provided the highest values, with 7/12 signals achieve AUC >0.5. This corresponded with actimetry signals, which provided high discrimination between postures. Parameters estimated from a commercial pressure monitoring can have the potential to detect postural changes. Further research is required to convert the data into meaningful clinical information, to inform patient repositioning strategies.

Monitoring the biomechanical and physiological effects of postural changes during leisure chair sitting.

BACKGROUND: Individuals with limited mobility can spend prolonged periods in leisure chairs, increasing their risk of developing a seated acquired pressure ulcer. The present study aims to use objective measures of posture and tissue viability to identify the associated risks of leisure chair related pressure ulcers. METHODS: Healthy participants (n = 13) were recruited to sit on a leisure chair with either a viscoelastic foam or air cushion. Participants were asked to adopt four different postures for a period of 10 min followed by a 10 min refractory period. Measurements at the leisure chair-participant interface included interface pressure, transcutaneous tissue gas tensions at the ischial tuberosities, accelerometer data collected from the sternum and subjective comfort levels. RESULTS: Results indicated that interface pressures remained consistent, with peak pressure index values of less than 60 mmHg across all conditions. A proportion of participants exhibited decreased oxygen tensions associated with increased carbon dioxide tensions during one or more test condition. This was particularly prevalent during the right lean posture on the air cushion (46%). In all cases, normal tissue viability was restored during standing. The accelerometer was able to detect significant changes (p < 0.05) in relative trunk angles during slump and right lean when compared to optimal sitting posture. CONCLUSION: Commercially available leisure chairs have little evidence to support their pressure relieving properties. This study revealed that a proportion of healthy individuals demonstrated a compromised tissue viability in specific postures. Further research is required to assess the impact of these sitting conditions in vulnerable individuals.

Clinical assessment of gait in individuals with multiple sclerosis using wearable inertial sensors: Comparison with patient-based measure.

BACKGROUND: This study aims to verify the feasibility of use of wearable accelerometers in an ambulatory environment to assess spatiotemporal parameters of gait in people with Multiple Sclerosis (pwMS), as well as the correlation of objective data with patient-reported outcomes. METHODS: One hundred and five pwMS (Expanded Disability Status Scale, EDSS in the range 0-6.5) classified in three sub-groups (EDSS 0-1.5, EDSS 2-4, EDSS 4.5-6.5) and 47 healthy controls (HC) participated in the study. All the subjects were evaluated with the timed 25-foot walking test (T25FW) while wearing a commercially available accelerometer. PwMS also rated the impact of the disease on their walking abilities using the 12-item MS walking scale (MSWS-12). RESULTS: All parameters objectively measured, except stride length, were significantly modified in pwMS with higher EDSS, with respect to HC and lower disability participants. Moderate to high correlations (r =0.57-0.79) were observed between gait parameters and MSWS-12 for pwMS of higher EDSS. The correlation was found moderate for the intermediate EDSS category (r =0.42-0.62). CONCLUSION: Wearable accelerometers are a useful tool for assessing gait performance for pwMS in a clinical setting, especially in cases of mild to moderate disability. Compared with other quantitative techniques, these devices allow patient testing under realistic conditions (i.e., fully dressed, with their usual shoes) using a simple procedure with immediate availability of data.