Smartphone-based Cough Diagnosis Helps Detect Potential TB Cases in AP
11 May 2026 10:34 AM IST11 May 2026 10:34 AM IST
In villages across East Godavari district, healthcare workers carrying smartphones are helping identify Tuberculosis (TB) and respiratory illnesses among people who otherwise may hardly undergo medical screening
Smart phone (File Photo)
Amaravati: A Hyderabad-based startup has come up with a unique, smartphone-based respiratory sound diagnosis to help identify potential TB infections with the involvement of the Andhra Pradesh government and the RTIH. Swaasa, deployed its AI-powered respiratory screening platform across Primary Health Centres (PHCs) in Andhra Pradesh's East Godavari district on a pilot basis under the MedTech Innovation Challenge 2025 in collaboration with the state government and Ratan Tata Innovation Hub (RTIH).
In villages across East Godavari district, healthcare workers carrying smartphones are helping identify Tuberculosis (TB) and respiratory illnesses among people who otherwise may hardly undergo medical screening.
Instead of depending only on conventional field surveys, Auxiliary Nurse Midwives (ANMs) are now asking villagers to cough into a mobile phone application developed by Swaasa which analyses respiratory sounds using Artificial Intelligence (AI) and recommends further diagnostic tests.
"Our vision is to make respiratory screening accessible to every individual. This pilot shows how a simple cough, captured on a smartphone, can enable early detection even in asymptomatic cases," Salcit Technologies Founder and CTO Narayana Rao told PTI.
The initiative, implemented under the MedTech Innovation Challenge 2025, screened close to 8,000 people within six weeks through Swaasa, the AI-powered respiratory health screening platform developed by Salcit Technologies.
For many villagers, especially elderly residents, daily wage workers and people living in remote pockets, the screening process took only a few minutes.
Health workers involved in the programme said the technology became useful in rural areas where healthcare access is limited and many people delay tests until illnesses become serious.
The AI-based platform analyses cough sounds recorded through a smartphone to identify people at risk of Tuberculosis (TB), Chronic Obstructive Pulmonary Disease (COPD), and asthma.
Integrated into public health workflows, the pilot enabled door-to-door screening by ANMs, instant AI-based risk stratification, targeted referrals for confirmatory tests such as Nucleic Acid Amplification Test (NAAT), chest X-rays and spirometry, followed by medical officer-led follow-up and treatment linkage.
The project was conducted under the aegis of Andhra Pradesh Health Department. According to Rao, nearly 36 percent of identified TB cases during the pilot were asymptomatic and could have remained undetected during traditional screening exercises.
The screening initiative reportedly improved TB diagnostic yield by around 15 percent compared to conventional Active Case Finding methods used in field surveys.
Apart from TB detection, the screening revealed a hidden burden of chronic respiratory illnesses among villagers, with COPD risk ranging between 6.5 percent and 9.5 percent and asthma risk between 1.6 per cent and 1.9 percent.
Among asymptomatic individuals flagged during the screening, nearly 50 percent reportedly showed abnormal lung patterns during
further examination, highlighting the importance of early detection, said Rao.
Healthcare officials said the deployment also helped identify operational challenges and improve infection-control practices in field settings while understanding frontline workers' expectations and usability needs.
The pilot project used structured micro-planning at sub-centre level with defined screening targets for ANMs, active supervision by medical officers and field managers, and real-time monitoring through digital dashboards.
Medical officers and field teams tracked daily screenings, referrals, treatment linkage and follow-up care through the monitoring system across Primary Health Centres and villages.
According to Rao, the platform demonstrated up to 95 percent concordance with spirometry tests while maintaining less than one percent failure rate during field deployment.
The system is non-invasive, radiation-free and requires no consumables or specialised technicians, making it suitable for large-scale deployment in public healthcare programmes.
The platform is also integrated with Ayushman Bharat Digital Mission (ABDM) systems, enabling patient registration through ABHA IDs and linkage with national TB monitoring platforms such as Nikshay.
Further efforts are in progress to support smoother adoption within national healthcare programmes, Rao said.
Building on the Andhra Pradesh pilot, Salcit Technologies aims to expand the AI-enabled screening model across multiple districts in the state, strengthen integration with state and national TB programmes, and support efficient allocation of diagnostic resources through better triaging.
India has been intensifying efforts under its TB Mukt Abhiyaan to eliminate Tuberculosis through screening, testing, treatment and tracking mechanisms, particularly among rural and vulnerable populations.
For villagers in East Godavari, however, the process remains remarkably simple, a cough into a smartphone that could help detect disease before it turns life-threatening.
The deployment was designed as a closed-loop, AI-enabled screening-to-care model.
The initiative followed with defined daily screening targets for each ANM and active supervision by medical officers and field managers.
Healthcare teams also used real-time dashboards for monitoring, tracking referrals and ensuring follow-up care, allowing officials to make field-level corrections wherever required.
The field-level deployment further helped authorities understand infection-control challenges in rural field conditions and frontline worker expectations regarding usability and workflow integration.
Swaasa has conducted more than five lakh respiratory assessments so far and is licensed under the Health Insurance Portability and Accountability Act (HIPAA), International Organization for Standardization (ISO) 27001 and ISO 13485/International Electrotechnical Commission (IEC) 62304 standards, the company said.
The platform is also licensed under Central Drugs Standard Control Organisation (CDSCO) Class B certification through the Drugs Control Administration, Telangana, as a Software as a Medical Device (SaMD).
Officials and company representatives described the Andhra Pradesh initiative as a replicable model for wider statewide and national deployment of AI-assisted respiratory screening programmes.
( Source : PTI )
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