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Data Quality Is Key to the Success of Medical Wearables

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Medical wearables are an emerging technology that allows continuous ambulatory monitoring of human vital signs during daily life, be it at work, home, during sport activities, or even in the hospital. In a clinical environment, they provide the advantage of minimizing discomfort and interference with normal human activities.

A recent study showed that the data from medical wearables such as accelerometers let researchers to rank the death probability with 30-40-percent greater accuracy compared to using data about a patient’s smoking status or stroke or cancer history. Medical wearables such as fitness trackers, heart rate monitors, GPS tracking devices, and smart health watches are more effective than other methodologies, such as patient surveys, in providing key predictors of mortality. An October report from The Manifest surveyed more than 500 wearables users and found more than 38-percent of respondents cited exercise tracking as the primary health benefit of using a wearable, with 26-percent using the devices to monitor heart rate and other vital signs. But medical wearables can go beyond these to monitor other vital metrics including ECG, respiration rate, blood oxygen saturation, blood glucose, and body temperature.

The accuracy of data from medical wearables varies widely, however, so their use entails thorough analysis, especially for medical applications. One example is FitBit’s application in clinical trials. FitBit has been used in 500 or so clinical trials, including trials for congestive heart failure. Its use in pharmaceutical clinical trials for neurodegenerative disorders—where remotely tracking motion is very significant in terms of assessing how a drug impacts a patient’s daily life, instead of only gathering data from patient diaries—has also been studied. These data points on activity add value, but only if their accuracy can be assured.

As the medical wearable devices in today’s consumer market can gather the types of medical-grade data previously only accessible during a clinic visit, they are empowering patients and consumers to self-serve remotely and share the data with any provider that they choose — ushering in the rise of remote patient monitoring (RPM) and the Internet of Healthcare Things (IoHT).

Data quality, volume, and context

Product manufacturers that want to develop successful medical wearable devices should focus on data quality and volume — meaning the data should be accurate and manageable in volume. Sending a lot of data wirelessly takes a lot of power, which puts the onus on product designers and manufacturers to be careful about generating too much data.

Data context is also key to finding value in big data from medical wearables. Data context takes into consideration the environmental factors that impact the data. This means that the significance of available data varies from patient to patient, depending on their health conditions. Using multiple sensors and sensor fusion software can provide the needed contextual information.

Voler provides electronic product design engineering services and embedded system design, especially for IoT and wearable devices. Our team of engineers have been creating award-winning products since 1979. We are focused on what we have always been best at: high quality innovative engineering that saves our clients’ time and money.

In the medical wearables market, we do modern product design, embedded system design, medical device design, engineering services, instrumentation design, and data acquisition systems. For more information, contact us.

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