One of the 1st “Sound” or acoustic stimuli anybody in this world is exposed to – is the voice of the mother and her heart beats in womb. AiSteth is a smart stethoscope built to further enhance the well being & research of mother and child health during the first 1000 days of child birth.


94% of all maternal deaths occur in low and middle-income countries – i.e. about 295,000 women died during and/or following pregnancy and childbirth. Similarly, close to a million children (under-five) die every year. Sustainable Development Goals 3 recommendation is to reduce by 2030, one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being. Research suggests that exposure to mother’s voice and heart beat sounds are instrumental in the development of neural pathways, hearing and language skills of the baby. On the other hand, women are usually taught to self-monitor the movements of the fetus to track the growth & the wellness of the baby during pregnancy. Hence, AiSteth is a tool which can be used to monitor mother & child health for the first 1000 days (from womb/during pregnancy to the first few years of child health).

To study the impact of AiSteth – as a remote self-monitoring tool by pregnant mothers to track the health and wellness of mother and child during the 1st 1000 days.

AiSteth has 3 components:
A) Device – AiSteth is a smart stethoscope which can be used by pregnant mothers to self-monitor, track the health and well being of the fetus and self during pregnancy and the 1st 1000 days. Vital parameters along with Heart, Lung and Abdominal Sounds are transmitted to a mobile application via Bluetooth.
B) Data – Mobile application which helps the pregnant mother to see/listen to the baby heart sounds and track the movements + engage with the baby throughout the pregnancy.
C) Intelligence – Ai/ML is the intelligence layer which tracks any abnormal vital parameters and triggers alert to access remote advice by healthcare professional connected via telemedicine.

A. Device – We have working prototype of AiSteth which can record, store and share heart and lung sounds to a mobile application via bluetooth
B. Data – Mobile Application which can visualise the heart and lung sounds
C. Intelligence – Initial Dataset which helps classify normal/abnormal heart sounds

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