We meet Jaikishan- a 62 year old rural farmer in the state of Maharashtra suffering from diabetes since the past 10 years. Working barefeet in sugarcane fields, his diabetic neuropathy consequently progressed to a sequelae of infection, ulceration and gangrene ultimately resulting in amputation of his left foot. This is the plight of over 62 million diabetic Indians of which nearly 25% are affected by adverse complications of diabetes like diabetic foot ulcers. Such complications are often detected at a chronic and irreversible stage, where the treatment options are limited to amputation of the affected region. LMICs like India face a herculean challenge of screening and early detection of Diabetic Foot Ulcers, which contribute to approximately 80% of all non-traumatic amputations in India, annually. The global burden of diabetes is immense, with nearly 422 million cases worldwide. Our purpose is to solve this limitation of early detection of diabetic neuropathy with an aim to reduce the incidence of chronic diabetic ulcers and amputations in diabetics.
Current approaches to this problem including physical examination and blood glucose monitoring have been limited in their effectiveness largely due to patient unawareness and delayed consultation. Newer methods like infrared thermography, although promising, present challenges with mass implementation, cost and image processing. To reduce this gap, we propose Kshitij- an AI coupled Thermochromic screening device which uses Thermochromic Chiral Nematic Liquid Crystals to detect temperature changes in the dorsum of the foot in patients affected with diabetic neuropathy.
Each subsequent layer of the LC is rotated at a certain angle from the upper layer such that the distance between two layers with the same rotation is defined as the chiral pitch. Decreased temperatures cause an increase in chiral pitch thus reflecting light waves of longer wavelengths ie- red end of the spectrum. Conversely, Increased temperatures cause greater rotation of molecular planes which reduces the chiral pitch therefore reflecting light waves are of shorter wavelengths ie- blue. The thermographic pattern thus obtained is a combination of red, green and blue and is compared between cases and controls.
The patient first stands on a thermochromic sheet for about 20 secs during which the temperature difference of the plantar surface of their feet produce a thermochromic pattern over the sheet. Patients or HCWs can then capture an image of the pattern using the Kshitij app on their smartphones which has an inbuilt AI architecture that analyses the thermochromic pattern and interprets the same.
The development of our unique pattern recognition AI algorithm consists of two datasets- for training and validation respt. The training dataset consists of recorded temperature patterns of 250 diabetic neuropathy patients and the same of 250 controls. During the validation stage, our algorithm independently identifies positive cases and stratifies patients based on their risk of developing chronic foot ulcers as high, moderate or low risk through analysis of their temperature patterns, and also suggests appropriate measures accordingly.
Our unique value propositions include a cost-effective novel method to facilitate screening and early detection of diabetic neuropathy. The patient is screened twice weekly and their progression is regularly monitored. We intend to implement Kshitij at the individual level and also at the level of PHCs. Such a model helps encourage self-awareness and also cultivates a mindset of self-care and monitoring in patients suffering from diabetes. Kshitij offers an accessible, affordable and sustainable method of early detection and screening of diabetic neuropathy. Our competitive advantages include better durability and reusability as compared to approaches like infrared thermography.
Our journey with Kshitij has only just begun. Our future roadmap is constructed in 3 phases. Following the development of our prototype, Phase 1 involves pilot testing in hospital departments, clinics and primary healthcare centres with Continuous testing enabling improvement of the pattern detection algorithms. Phase 2 would be directed towards cost reduction of prototyping and continued pilot testing while solving limitations of image processing and sensitivity of temperature detection. In Phase 3, we would employ a patient centric business model and interact with our key partners and customer segments to increase the outreach of our innovation.
Our vision with Kshitij is to inculcate community awareness about the essence of self-care and monitoring in diabetes. Through our solution, we appeal to millions of individuals like Jaikishan who should not have to suffer the consequences of amputation due mere unawareness and lack of accessible healthcare. Our team at Kshitij is dedicated towards reaching the horizons of health and therefore reinforcing healthcare delivery at the ground level.
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