Short list of desired features:
* This device can measure the acoustic impedance of heart and lung tissues even in non medical environment, no need to move to a medical center.
* This device measures the acoustic impedance of tissues by a home carer, without need for medical staff.
* This device mitigate issues due to unanticipated skin colors, sweating or medical conditions, as it can "phone home" if it found anomalous results. Conversely it receives updates automatically, so what is learn from a single case, is send to every devices at their next update.
* It is very low cost: Certainly less than $150 in its final version.
It can be used for a long time without creating skin problems, as it uses no gel and is easy to clean.
Actually ultrasound specialists also use such artifacts to detect
cysts, tumors, calcifications. B-line is an artifact that is used in ultrasound imaging (or lack of!) to infer medical conditions.
is well known that the density of degenerated tissues is lower than
those of normal tissues. This is due both to intracellular and
While using machine learning to detect heart failure is not new, using ML features symptomatic of fibrous tissues is entirely new.
Based on the acoustic impedance the tissue could be classified as: normal, degenerated, granulated and fibrous. Each category indicates specific problems mostly in connective tissues.
Changes in tissues acoustic impedance alone, do not mean in themselves that the medical condition changed. What makes it accurate is that this device can recognize signatures of degenerated tissue thanks to modern statistical technologies such as Hidden Markov Chains.