Research Papers - Department of Electrical and Electronic Engineering

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Author: search.filters.author.Kahandawala, B, S

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    OcupHI: knowledge-driven colorimetric interpretation framework for high-precision real-time ocular pH diagnostics
    (Springer Nature, 2026-08-12) Kahandawala, B, S; Sandaruwan, H. H. P. B; Liyanage, P; Dassanayake, R.S; Costha, N.P; Liyanage, R.N; Wijenayake, U; Wijesinghe, R.E; Silva, B.N; Manatunga, D.C
    Ocular injuries due to chemical spills pose a substantial concern, representing 10–22% of all ocular trauma. Although precise detection of ocular pH is crucial for determining the optimal medical treatment, many existing methods remain invasive, biased, or insufficiently precise. Reliance on subjective visual assessment of subtle color differences limits the objectivity and hinders high-throughput analysis. Therefore, an advanced colorimetric knowledge-driven ocular pH detection method was developed using a biosensor (OcupHI) based on a Clitoria ternatea (Butterfly Pea) anthocyanin sensing agent. The proposed work delivers fast, high-precision, and easily measurable pH prediction across clinically relevant ranges, while supporting real-time decision support for eye physicians. The pH range from 1 to 12 was tested and compared with six different anthocyanin concentrations: 5, 10, 20, 30, 40, and 50 ppm, and five different machine learning models, namely, Decision Tree (DT), K-Nearest Neighbors (KNN), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machines (SVM). The results revealed that the 40 ppm anthocyanin concentration trained with the XGBoost model produced the most accurate ocular pH values, achieving superior performance with an overall accuracy of 96%, a significantly higher F1-score for early detection. Experimental validation clearly demonstrates strong predictive accuracy, robustness, and interpretability, highlighting the potential for next-generation ocular diagnostics. Further research findings support Sustainable Development Goal (SDG) 3 – good health and well-being through a real-time ocular pH monitoring kit, and SDG 12 – responsible consumption and production by optimizing the use of the natural colorant anthocyanin for sensor development.
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    High-resolution optical imaging for sustainable fish freshness and safety assessment
    (Elsevier GmbH, 2026-07) Madhubhashini, M. N; Kahandawala, B, S; Sandaruwan, H.H.P. B; Silva, B. N; Wijenayake, U; Wijesinghe, R. U
    Fish freshness evaluation is crucial to ensure consumer safety, and rapid assessment is essential for effective and accurate quality control. To overcome the limitations of the gold standards, such as lack of structural depth information, high-time consumption, and labor-intensiveness, high-resolution Optical Coherence Tomography (OCT) was employed for real-time monitoring of fish freshness non-invasively. Microstructural changes of eye and skin of Indian Anchovies ( Stolephorus indicus ) specimens were considered as the main freshness parameters during refrigeration storage. Both eye and skin tissues exhibited decreased internal scattering, loss of clarity, boundary weakening, and gradual structural degradations through the OCT observations. The quantitatively assessed variance intensity, entropy, energy, and edge density clearly revealed the internal tissue disruption over storage time due to protein denaturation, oxidative damage, and fluid imbalance. The findings of this study indicate that OCT shows an insightful correlation with microbiological and biochemical spoilage processes, enabling the advanced identification of subtle microstructural changes in fish skin and eye, even at a prior stage of deterioration. Such capability offers an objective and rapid freshness evaluation approach that could greatly benefit supply chain management and post-harvest seafood quality monitoring.