Evolution of the Humble Stethoscope – AI-enabled evolution

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September 16, 2022


AI / Healthcare


Evolution of the Humble Stethoscope – AI-enabled evolution

When we think of a doctor, most probably the first image that coming to our mind is a Stethoscope, the device derives its origin from two Greek words, “stethos” (chest) and scopos (examination). It’s is used to ‘auscultate’ that enables the physician to identify specific sounds within the body such as the lungs, heart, other organs, bowel sounds, and blood flow noises in arteries and veins. The abnormal sounds detected by stethoscope helps the doctor to identify many diseases.

The first stethoscope was a wooden tube that René Laennec invented in France in 1816. Later in 1852, George Cammann modified this diagnostic instrument for commercial purposes. Its weight was reduced, and the acoustic quality was improved so that external noises could be filtered out while performing auscultation. The stethoscope innovations made it available in a wide range of styles and designs, including electronic versions of the iconic device while keeping the basic working principle unchanged.

Other than the traditional acoustic (analog) stethoscope, electronic stethoscope, digital stethoscope, fetal stethoscope, and doppler stethoscope, physicians and scientists are also being used by physicians and scientists to amplify, enhance and transmit sounds of different body parts.

AI-enabled digital stethoscope

In the present-day scenario, digital healthcare and telemedicine are taking care of many healthcare needs. James West invented a digital stethoscope at Johns Hopkins University, AI-enabled for automatic detection of lung abnormalities and has active noise-cancellation features.

One significant advantage is that the readings can be taken even in noisy surroundings, unlike conventional stethoscopes, where the diagnosis is adversely affected by surrounding noises. Since it does not need the training to use the digital instrument, the recordings can be taken by anyone and telemetered to the physician. This also reduces their risk for exposure to COVID-19 and facilitates better medical support in inaccessible geographical regions and in patients who are chronically sick.

The need to upgrade traditional stethoscopes was also felt by alumni of Berkeley Engineering, Tyler Crouch and Connor Landgraf, who developed algorithms to help physicians accurately predict the patients’ risk of cardiac disease. FDA has approved many of their algorithms that detect heart murmurs, atrial fibrillation, and irregular heartbeats suggestive of stroke or blood clots. These algorithms need to be combined with a digital stethoscope and AI software for it to function. Their “breakthrough” device also detects heart failure by picking up the heart’s erratic electrical impulses.

The emergence of artificial intelligence (AI) and machine learning has allowed computers to recognize patterns of disease and abnormalities from enormous amounts of clinical data. The same principle is utilized here as blood being through normal arteries is different from the sounds of blood flowing around a blood clot in the blood vessels. California-based Eko Digital Stethoscope has developed an AI-based algorithm that can recognize these sounds characteristic of turbulence around blood flow around blood clots. Eko and the Mayo Clinic’s recent collaboration found that their algorithm had good diagnostic accuracy in identifying asymptomatic left ventricular dysfunction (ALVD). Their study in 50,000 patients showed a high ( 87%) sensitivity and (87%) specificity in identifying heart murmurs, which is, in fact, much better performance than the average physician. Many challenges need to be addressed, such as higher specificity and sensitivity to avoid false positives and negative readings.

Polish startup StethoMe is a wireless stethoscope that detects and identifies abnormal sounds in a child’s lung. Its Bluetooth equipped smartphone app leverages AI algorithms to reveal these pathological sounds in the child’s body. Once an irregularity is detected, the recordings are sent to the physician for consultation through telemedicine.

Thinklabs One is a round-shaped stethoscope with a headphone that can be connected to smart devices. It visually presents the waveforms made by the sounds, records the file and can fit in the palm of your hand. It magnifies and filters sounds to identify abnormal heart sounds like murmurs and rumbles.

Sonali Labs is a startup that has developed a digital stethoscope called the Feelix that enables on-the-spot screenings that local health workers can handle. They hope their reengineered scope finds a solution for the global health crisis of childhood pneumonia by early detection.

Future Perspectives

AI and machine learning are changing the way medicine is being practiced. It is a disruptive technology that supports and augments physicians’ daily diagnostic activities so that they can spend more time doing clinical jobs and performing surgeries. Although AI cannot fully replace humans in the medical field, it is imperative for medical professionals to keep abreast of AI technology developments.

Keeping the patient’s best interest, AI-based solutions can be utilized to provide better diagnostic outcomes to the patients. In the future, the stethoscope will not be just a device to gather information about the heart or lungs, but it collects sounds and electrical impulses from all over the body to meet many of the unrealized clinical diagnostic needs.

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