Medicine is one of the fields that is benefiting most from technological innovation: operating rooms with augmented reality, surgical robots, artificial intelligence to analyze CT scans… In addition to all that, several devices enable monitoring patients’ health and the effects of therapies. Known as “digital therapeutics,” this field’s value could reach up to fourteen billion dollars by the year 2027. This new generation of wearables is being used together with artificial intelligence algorithms to offer hitherto unheard of diagnostics.
For example, a company in Singapore has launched a new wearable called “Biotvitals,” which analyzes the slightest variations in the pulse and anticipates cardiac problems. Some studies show that this technology can predict a heart problem up to two weeks in advance, which is especially useful in the case of people who have undergone surgery and are at risk. The main advantage is that the patient has access to the alerts through an app on their cell phone, but the information is also available to medical specialists.
Put yourself in the (remote) hands of a specialist
The classic “consult with your specialist” recommendation is all very well, but everyone knows that these professionals are not always available at short notice. Thus, medical specialists’ ability to access the information and alerts provided by these wearables in real-time could revolutionize medical care. Besides monitoring cardiac problems remotely, the developers of Biotvitals are also participating in a technology project that quantifies pain intensity in patients with endometriosis.
Wearables, the future in the detection of infectious diseases?
Stanford University has partnered with Fitbit to evaluate the potential for detecting diseases of wearables. In this case, however, the focus would be on infectious diseases that alter constants such as body temperature. Although one of the initial goals of this technology project is focusing on the detection of Covid-19, the researchers intend to use artificial intelligence algorithms to detect all types of viral infections, even in asymptomatic patients.
By combining different parameters such as heart rate or body temperature, the system may recognize infection patterns. The research will be based on an algorithm created in 2017 by the Stanford Medicine team, and the results will be carried over to different types of smartwatches and bracelets.
In addition to detecting the disease among the study participants, the medium-term goal is to combine information received from multiple devices to establish infection rates in wider groups.