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Staying a Step Ahead: Wearable Technology for Predictive Medicine

By Tess Skyrme, Senior Technology Analyst, IDTechEx 

Did you know your smartwatch could know you’re ill before you notice any symptoms? Wearable technology is now evolving from recording the state of our health to predicting it. These advancements come in the post-pandemic era, where the demand for digital health solutions is also rising. In this article, IDTechEx discusses the resulting opportunities and challenges in the wearable technology market for predictive medicine and infection control.

Maturing wearables market – lower cost hardware

Optical sensors mounted into wrist-worn devices like fitness trackers and smart-watches can measure a variety of vital signs, including heart rate, HRV, blood oxygen and breathing rate. Now that the fitness tracker industry is over a decade old, commoditization has made access to these health insights more affordable. As such, the widespread adoption of wearable devices has seen attention turn to the potential power of the data within remote patient monitoring – and beyond that, predictive medicine and infection control.

Sensor innovation – higher value data

Wearable sensor innovation remains a highly active area of research in both academia and industry. There is ongoing investment in the development of wearables able to compete with medical devices, with multiple OEMs pursuing FDA clearance or even approval. This is largely being achieved through engineering improvements as to the number and arrangements of light sources and detectors, with noise minimization also crucial. Moreover, advancements in data processing, machine learning, and artificial intelligence are also expanding the list of vital signs accessible at the wrist. For example, it is already possible to monitor blood pressure with a wearable from Biobeat or Aktiaa – albeit with regular cuff calibration.

The quality of the data now available is a key enabler for predictive medicine. A recent study by Biosency, using their proprietary Bora Band, demonstrated an application of wearables in predicting a COPD crisis three days ahead of hospitalization. Sensor innovation remains a key differentiator for players in the predictive medicine space, particularly regarding access to accurate breathing rate data. Biosency are believed to be utilizing not only the optical sensors but gyroscopic measurements from the inertial measurement unit (IMU).

Going forward, it is anticipated that the potential for wearables to predict hospitalization events will continue, especially those such as chronic respiratory diseases constituting a high-value problem for struggling healthcare services. Wearable technology has already been adopted in limited numbers within clinical trials to research Parkinson’s, stroke, Diabetes, Epilepsy, and Asthma – patients of which would likely all value a crisis prediction tool.

Pandemic impact – demonstratable value

In 2020, Fitbit launched one of the largest wearables research projects to date, collecting data from over 100,000 students in their COVID-19 Study. It was found that not only could wearable data be seen to visibly change with the onset of recorded symptoms, but in some cases preceding them. Infection control was, of course, the main challenge throughout the pandemic, in which early detection played a key role in limiting hospital admission. As such, the pandemic has served to demonstrate the potential value of wearable data within predictive medicine into the public consciousness, driving investment today and potentially market growth in the future.

COVID-19 may have kick-started the industry, but infection control may not prove to be the killer commercial application for this technology in the long term. While in a mission control environment – predictive data of cold and flu spreading offers a potential return on investment, the business models applicable in the mass market aren’t as obvious. Users may be reluctant to livestream the probability of their infection to third parties seeking to monetize it. Moreover, the question remains as to what ‘actionable insight’ the data could potentially offer. Much of the world has quickly reverted to socializing despite coughs and sneezes, and the personal space available on public transport at peak times is once again negligible. If life now continues as normal once symptoms have arrived, the general response to an early flu detection warning from a smart-watch may well be ‘so-what’.

Conclusions and Market Outlook

In the future, as wearable sensor technology advances, it is possible that digital predictive medicine could become a much more powerful tool. Early diagnosis platforms are highly sought after to optimize the cost and effectiveness of medical treatment. There is a compelling opportunity for mass adoption of advanced wearables to enable early diagnosis of multiple challenging diseases, particularly chronic respiratory and cardiovascular diseases. As for infection control, maybe it will be crucial in the future for wearable data to trigger the social distancing or isolation habits of millions. Yet, given historical differences between major viral epidemics – one can’t help feeling designing such a solution today would fall foul of rear-view problem-solving.

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