Window into the mind:Advanced handheld spectroscopic eye-safe technology for point-of-care neurodiagnostic

Traumatic brain injury (TBI), a major cause of morbidity and mortality worldwide, is hard to diagnose at the point of care with patients often exhibiting no clinical symptoms. There is an urgent need for rapid point-of-care diagnostics to enable timely intervention. We have developed a technology for rapid acquisition of molecular fingerprints of TBI biochemistry to safely measure proxies for cerebral injury through the eye, providing a path toward noninvasive point-of-care neurodiagnostics using simultaneous Raman spectroscopy and fundus imaging of the neuroretina. Detection of endogenous neuromarkers in porcine eyes' posterior revealed enhancement of high-wave number bands, clearly distinguishing TBI and healthy cohorts, classified via artificial neural network algorithm for automated data interpretation. Clinically, translating into reduced specialist support, this markedly improves the speed of diagnosis. Designed as a hand-held cost-effective technology, it can allow clinicians to rapidly assess TBI at the point of care and identify long-term changes in brain biochemistry in acute or chronic neurodiseases.</p

Edge Impulse: An MLOps Platform for Tiny Machine Learning

Edge Impulse is a cloud-based machine learning operations (MLOps) platform for developing embedded and edge ML (TinyML) systems that can be deployed to a wide range of hardware targets. Current TinyML workflows are plagued by fragmented software stacks and heterogeneous deployment hardware, making ML model optimizations difficult and unportable. We present Edge Impulse, a practical MLOps platform for developing TinyML systems at scale. Edge Impulse addresses these challenges and streamlines the TinyML design cycle by supporting various software and hardware optimizations to create an extensible and portable software stack for a multitude of embedded systems. As of Oct. 2022, Edge Impulse hosts 118,185 projects from 50,953 developers

Point of care diagnostics for traumatic brain injury

Traumatic brain injury (TBI) is a major burden on healthcare services worldwide, which currently lacks an effective method for point-­of­-care (PoC) diagnostics and monitoring. In this thesis, the prospect of using Raman spectroscopy, as a non­invasive means to mea­sure chemical changes indicative of TBI from the back of the eye is explored. Through the development of multivariate analysis methods, self­ organising maps are highlighted as a superior alternative to principal component analysis and are successfully used to in­troduce a new means of classification. A classification accuracy of > 93 % is demonstrated over five tissue types applied to anatomical layers of ocular porcine eyes. Subsequently, in a clinically relevant murine model of TBI, an ability to accurately identify TBI and in­jury severity from Raman spectra of the retina is demonstrated for the first time. Using feature extraction, intrinsically linked to the classification result, the findings are associ­ated with a decrease in cardiolipin linked to metabolic distress, which is a hallmark of TBI. Finally, in an effort to translate the technology, a (patent pending) handheld system has been developed. Simultaneously, fundus photography is combined with eye safe Raman spectroscopy, measuring high wavenumber bands from a three­dimensional printed tissue phantom of the undilated human eye

Tuneable surface enhanced Raman scattering metamaterial-like platforms via three-dimensional block copolymer based nanoarchitectures

Surface enhanced Raman spectroscopy (SERS) pushes past the boundaries and inherent weaknesses of Raman spectroscopy, with a great potential for a broad range of applications particularly, for sensing. Yet, current real world applications are limited due to poor reproducibility, low-throughput and stability issues. Here, we present the design and fabrication of self-assembly guided structures based on adjustable block copolymer (BCP) nano-morphologies and demonstrate reproducible SERS enhancement across large areas. Golden three-dimensional (3D) nanostructured morphologies with controllable dimensions and morphologies exhibit high chemical stability, enhanced plasmonic properties and are highly suitable for SERS substrates due to the strong enhancement of the electromagnetic field. Adjustable, free standing porous nanostructures, continuous in the 3D space are achieved by removal of selected BCP constituents. Four BCP morphologies and the corresponding achievable enhancement factors are investigated at 633 and 785nm excitation wavelengths. The choice of excitation laser is shown to greatly affect the observed signal enhancement, highlighting the sensitivity of the technique to the underlying surface architecture and length scales. By using BCP assemblies, it is possible to reliably tune these parameters to match specific applications thus, bridging the gap towards the realization of applied metamaterials. The fabricated SERS platforms via three-dimensional block copolymer based nanoarchitectures provide a recipe for intelligent engineering and design of optimised SERS-active substrates for utilisation in the Raman spectroscopy-based devices towards enabling the next-generation technologies fulfilling a multitude of criteria

Development and Characterization of a Probe Device toward Intracranial Spectroscopy of Traumatic Brain Injury.

Traumatic brain injury is a leading cause of mortality worldwide, often affecting individuals at their most economically active yet no primary disease-modifying interventions exist for their treatment. Real-time direct spectroscopic examination of the brain tissue within the context of traumatic brain injury has the potential to improve the understanding of injury heterogeneity and subtypes, better target management strategies and organ penetrance of pharmacological agents, identify novel targets for intervention, and allow a clearer understanding of fundamental biochemistry evolution. Here, a novel device is designed and engineered, delivering Raman spectroscopy-based measurements from the brain through clinically established cranial access techniques. Device prototyping is undertaken within the constraints imposed by the acquisition and site dimensions (standard intracranial access holes, probe's dimensions), and an artificial skull anatomical model with cortical impact is developed. The device shows a good agreement with the data acquired a standard commercial Raman, and the spectra measured are comparable in terms of quality and detectable bands to the established traumatic brain injury model. The developed proof-of-concept device demonstrates the feasibility for real-time optical brain spectroscopic interface while removing the noise of extracranial tissue and with further optimization and validation, such technology will be directly translatable for integration into currently available standards of neurological care

Raman spectroscopy accurately differentiates mucosal healing from non-healing and biochemical changes following biological therapy in inflammatory bowel disease.

BACKGROUND Mucosal healing (MH) is a key treatment target in the management of inflammatory bowel disease (IBD) and is defined in endoscopic terms by the newly published PICaSSO score. Raman Spectroscopy (RS) is based on the scattering of inelastic light giving spectra that are highly specific for individual molecules. We aimed to establish spectral changes before and after treatment and whether Raman Spectroscopy is able to accurately differentiate between inflammation and MH. METHODS Biopsies were taken for ex vivo RS analysis alongside biopsies for histological analysis from IBD patients undergoing optical diagnosis endoscopic assessment. We compared pre- vs. post-biological treatment in IBD patients and healthy controls and active vs. MH in UC and CD. For spectral analysis, we used supervised self-organising maps for separation and classification. RESULTS A total of 23 patients (14 IBD, 9 HC) were recruited for comparison of pre- vs. post-biologic treatment and 74 IBD patients were included for the assessment of MH in IBD, giving 9700 Raman Spectra. Spectral differences were seen between pre- and post-treatment which were observed comparing MH vs. active inflammation. Reductions in intensity at 1003cm-1 and 1252cm-1 when a reduction in inflammation was seen post-treatment and when MH was present. MH was associated with an increase in intensity at 1304cm-1. The trained neural network differentiated MH from active inflammation with a sensitivity, specificity, PPV, NPV and accuracy in UC of 96.29% (sd 0.94), 95.03% (sd 1.52), 94.89% (sd 1.59), 96.33 (sd 0.97) and 95.65 (sd 0.99) and 96.19% (sd 1.46), 88% (sd 4.20), 86.60% (sd 5.39), 96.55% (sd 1.32) and 91.6% (sd 2.75) in CD respectively. CONCLUSION We demonstrated RS can demonstrate biochemical changes following treatment of IBD and accurately differentiates MH from active inflammation in IBD and might be a future tool to personalise therapeutic management in IBD