Accuracy of Tissue Oxygen Saturation Measurements of a Textile-Based NIRS Sensor.

Pressure injuries (PI) are dangerous tissue lesions that heal very slowly and pose a high risk of serious infections. They are caused by pressure applied to the tissue, which stops blood circulation and therefore induces hypoxia, i.e., low tissue oxygen saturation (StO2). PI cause severe suffering and are expensive to treat. Hence it is essential to prevent them with a device that detects a dangerous situation, e.g., by measuring StO2 using near-infrared spectroscopy (NIRS). For such a device to be wearable without causing PI, it must not introduce pressure points itself. This can be achieved by integrating optical fibers into a textile to transport light to and from the tissue.The aim of this paper is to investigate the accuracy of StO2 measurements using a NIRS device based only on textile-integrated optical fibers.Bundles of fibers were stitched into a textile in such a way that loops of <1 mm diameters were formed at the stitching locations. Detection points (DPs) on the fabric consisted of 8 fibers with 3 loops each. Emission points (EPs) were made from 4 fibers with 3 loops each. All fiber ends of a DP were connected to an avalanche photodiode. One end of each fiber belonging to an EP was connected to an LED (740 nm, 810 nm, or 880 nm; 290, 560, or 610 mW).To verify the accuracy of this textile-based sensor, we placed it on a subject's forearm and compared the derived StO2 during arterial occlusion to the values of a gold-standard NIRS device (ISS Imagent), which was placed on the forearm too.We found that our textile-based sensor repeatedly measured StO2 values over a range of 40% with a deviation of <10% from the reference device.By showing the ability to measure StO2 using textile-integrated optical fibers accurately, we have reached a significant milestone on our way to building a wearable device to monitor tissue health and prevent PI.

Numerical Optimisation of a NIRS Device for Monitoring Tissue Oxygen Saturation.

The present work aims to develop a wearable, textile-integrated NIRS-based tissue oxygen saturation (StO2) monitor for alerting mobility-restricted individuals - such as paraplegics - of critical tissue oxygen de-saturation in the regions such as the sacrum and the ischial tuberosity; these regions are proven to be extremely susceptible to the development of pressure injuries (PI).Using a combination of numerical methods including finite element analysis, image reconstruction, stochastic gradient descent with momentum (SGDm) and genetic algorithms, a methodology was developed to define the optimal combination of wavelengths and source-detector geometry needed for measuring the StO2 in tissue up to depths of 3 cm. The sensor design was optimised to account for physiologically relevant adipose tissue thicknesses (ATT) between 1 mm and 5 mm. The approach assumes only a priori knowledge of the optical properties of each of the three tissue layers used in the model (skin, fat, muscle) based on the absorption and scattering coefficients of four chromophores (O2Hb, HHb, H2O and lipid).The results show that the selected wavelengths as well as the source-detector geometries and number of sources and detectors depend on ATT and the degree and volume of the hypoxic regions. As a result of a genetic algorithm used to combine the various optimised designs into a single sensor layout, a group of four wavelengths was chosen, coinciding with the four chromophores and agreeing very well with literature. The optimised number of source points and detector points and their geometry resulted in good reconstruction of the StO2 across a wide range of layer geometries.

Detectability of low-oxygenated regions in human muscle tissue using near-infrared spectroscopy and phantom models.

The present work aims to describe the detectability limits of hypoxic regions in human muscle under moderate thicknesses of adipose tissue to serve as a groundwork for the development of a wearable device to prevent pressure injuries. The optimal source-detector distances, detection limits, and the spatial resolution of hypoxic volumes in the human muscle are calculated using finite element method-based computer simulations conducted on 3-layer tissue models. Silicone phantoms matching the simulation geometries were manufactured, and their measurement results were compared to the simulations. The simulations showed good agreement with the performed experiments. Our results show detectability of hypoxic volumes under adipose tissue thicknesses of up to 1.5 cm. The maximum tissue depth, at which hypoxic volumes could be detected was 2.8 cm. The smallest detectable hypoxic volume in our study was 1.2 cm3. We thus show the detectability of hypoxic volumes in sizes consistent with those of early-stage pressure injury formation and, consequently, the feasibility of a device to prevent pressure injuries.