Top Medical Innovations of 2019

medical innovations

2019 has brought about many great medical innovations, with technologies such as virtual reality, artificial intelligence, 3D printing, and various others having significant applications in healthcare. As the year comes to a close, DocWire News has compiled some of the top medical innovations that have emerged this year.

Virtual Reality Helping those with Parkinson’s Disease Walk

Recent work has found virtual reality (VR) to be effective in building balance skills in patients with Parkinson’s disease. This system successfully improved patient’s obstacle negotiation and balance, as well as their confidence in moving around in their environment, according to their findings published in Experimental Biology.

The researchers utilized VR to create a virtual training system that provides a controlled environment in which the patients can refine their balance and muscle control when walking. The patients step over obstacles that appear in front of them while walking on a treadmill, with obstacles getting progressively larger as the patient becomes comfortable with the course.

Medical Breath Analyzer Successfully Detects 17 Diseases

A collaborative team of researchers from Israel, Latvia, China, France, and the US have recently created an AI system that detects diseases from exhaled breath. In their study, the scientists found the device successfully detected 17 diseases with 86% accuracy.

Led by Professor Hassam Haick of Technion-Israel Institute of Technology, the team collected breath samples from 1,404 participants that were either healthy or had one of 17 diseases. Among these diseases were lung cancer, colorectal cancer, head and neck cancer, ovarian cancer, bladder cancer, prostate cancer, kidney cancer, gastric cancer, Crohn’s disease, ulcerative colitis, irritable bowel syndrome, idiopathic Parkinson’s, atypical Parkinson ISM, multiple sclerosis, pulmonary hypertension, pre-eclampsia toxemia, and chronic kidney disease.

First AI Medical Monitoring Wearable Approved by FDA for Home Use

Current Health’s artificial intelligence (AI) wearable device that measures multiple vital signs has recently received FDA-clearance for patients to use at home. In February, the Edinburgh, Scotland-based company received clearance for the AI-enabled device in monitoring patients while in the hospital, but this recent approval means it can now be used between doctor visits at home too.

The wireless device, Current, measures a patient’s pulse, respiration, oxygen saturation, temperature and mobility. Current provides physicians with real-time updates regarding their patient’s health, allowing them to handle complications promptly. The technology utilizes machine learning to analyze the data it collects to detect problematic changes in data.

Cedars-Sinai Using Alexa in Smart Hospital Room Pilot Program

Cedars-Sinai, a non-profit hospital in Los Angeles, is conducting a pilot program using the Alexa-powered platform called Aiva to allow patients to control their experiences hands-free. Using the device in over 100 patient rooms at the hospital, the program aims to use voice-detection AI to let patients interact with nurses and control their entertainment using their voices. Aiva is the first patient-centered voice assistant platform created specifically for hospitals.

The hospital has equipped rooms with Amazon Echos for this pilot project, and patients simply tell the device when they need something. Patients are able to control entertainment aspects of their hospital stay, such as turning the TV on and off or changing channels by saying “Alexa, put on NBC.” Other commands the patient can give Aiva include assistance with clinical workers, such as summoning the nurse for assistance getting up to use the restroom.

AI Diagnosing Heart Disease With Accuracy Equal to Traditional Means

Machine learning may have the potential to provide a cardiovascular disease prognosis that is just as accurate as a professional’s prediction. Adoption of this artificial intelligence (AI) technology could not only facilitate the management of cardiovascular disease patients but would significantly reduce costs for the NHS as well.

This research recently emerged from a group of scientists at Cardiff University who produced evidence that portrays how well machine learning can assess patients. Published in PLOS One, the study showed how diagnostic AI can match traditional methods of providing reliable prognoses for cardiac conditions. Requiring no professional training or human interaction, this method has the potential to greatly alleviate the healthcare provider’s workload.