Mobile Apps Can Detect Anaemia, Nutrition Risks

The innovators, however, said that doctors, too, depend on specialised departments, machines, and laboratories to predict diseases.

Update: 2025-12-04 15:51 GMT
Smartphone-based technology can now detect conditions like anaemia, and daily consumption of salt, sugar, and oil, said food experts. (Source: Internet)

 Hyderabad: Smartphone-based technology can now detect conditions like anaemia, and daily consumption of salt, sugar, and oil, said food experts.

Speaking at an event organised by the ICMR–National Institute of Nutrition (NIN), Dr Rupam Das said people often pay doctors even when machines perform most diagnostic functions. “We plan to provide solutions to reduce costs and save time for individuals through our app LyfasOne. It is a clinical-grade, non-invasive digital health screening tool that uses a smartphone camera to assess more than 100 biomarkers.”

“With our app, an individual does not need to go anywhere; they can sit at home and do the tests with their own mobile. We even detected Covid-19 for patients — our app travelled, but we did not,” he explained.

Explaining how the app works, Dr Rupam Das said LyfasOne captures capillary blood-volume changes from the index finger to evaluate cardiovascular, metabolic, endocrine, pulmonary, musculoskeletal, and mental health using technologies such as PPG, APPG and photochromatography.

Questions were raised regarding the accuracy of measurements compared with blood tests.

The innovators, however, said that doctors, too, depend on specialised departments, machines, and laboratories to predict diseases. They added that their disclaimer clearly states that measurements may vary between readings. A single subscription to their platform, they argued, could significantly reduce the cost, time, and stress experienced by users.

Another innovator, Sourav Sinha, highlighted the challenges in rural areas where scientific bodies travel to assess anaemia prevalence. His application, Monere, powered by the Non-Invasive Anaemia Detection Algorithm (NiADA), uses AI to analyse a simple eyelid photograph to estimate anaemia risk, helping users assess iron deficiency without needles or lab visits.

Several innovators working in food technology presented their solutions, including tools that analyse nutritional intake and technologies aimed at reducing phytic acid in cereals, pulses, and oilseeds.

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