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article imageQ&A: Patient monitoring sensors are set to improve healthcare Special

By Tim Sandle     Aug 10, 2019 in Health
VivaLNK, who are developing remote patient monitoring sensors, has shaken up the digital health market by opening up its platform for health tech solution providers to develop a new generation of wearable health items.
The company VivaLNK, is making advances with remote patient monitoring sensors. The company's mission is to become the Amazon Cloud of remote sensors in the healthcare field. Part of the developments include opening up the platform for health tech solution providers to build from, which is achieved by accessing VivaLNK's highly accurate and easily wearable e-Skin sensors.
Traditionally, health tech companies have had to build their products from the ground up which is expensive and time consuming. The VivaLNK open source approach offers something new for the health tech market, as Sam Liu at VivaLnk tells Digital Journal.
Digital Journal: What are the advantages of remote patient monitoring?
Sam Liu: Remote patient monitoring (RPM) has the advantages of collecting data on a continuous basis while the patient is in a natural state. This results in a more comprehensive and accurate picture of patient health rather than simply discrete data points taken in hospital environments.
DJ: What types of insights can be drawn from the data?
Liu: With a continuous spectrum of data in a natural setting, you can see a true picture of the patient’s health. In some cases, you can capture data that otherwise would not be feasible, such as during sleep. This can create a more accurate and timely diagnostic and prevent some health problems from happening in the first place.
DJ: What is different about eSkin sensors?
Liu: VivaLNK’s sensors combine the ease and comfort of consumer wearables with the accuracy and quality of medical devices. In addition, our sensors have the ability to capture multiple human vitals and biometrics on a single Band-Aid-like patch.
DJ: How important is the open source approach?
Liu: Open source and open platforms are common in the information technology (IT) world, and have resulted in a proliferation of compelling and lower cost solutions for the computing market. However, the medical device world has largely been a closed system - limiting solutions to a few large players. By taking an open platform approach in the medical device world, we are accelerating innovation and the availability of new healthcare solutions in the market.
DJ: What were the main challenges when developing the technology? What are some of the challenges health solution providers face in development?
Liu: For VivaLNK, one of the main challenges is the ability to combine multiple sensing capabilities into a very small form factor that is both comfortable and medical grade. This is one of the things that makes us unique.
For solution providers, much of the innovation is happening on the algorithm and software side. However, integrating their solution with medical wearable devices has been challenging due to both a lack of hardware expertise and availability of an open platform. By abstracting the complexities of the device hardware from the software and networking layer, we make it much easier for software developers to create solutions that integrate with medical wearable devices.
DJ: How have your sensors been evaluated?
Liu: VivaLNK currently has over 50 commercial healthcare partners developing with our medical wearable sensor platform. Our sensors are also being used in clinical research at Stanford, UCSF, Case Western and others.
DJ: How do you plan to roll out your new sensors?
Liu: We are focused on the goal of monitoring multiple human vitals and biometrics on a single wearable patch - replacing expensive, cumbersome hospital vitals monitoring equipment. We plan to roll this out through our healthcare solution partners who are building various vertical applications on our sensor platform. These include heart failure detection, chemotherapy remote monitoring, and patient health deterioration. Over time, we will also be looking into developing other advanced algorithms and vertical applications such as cardiac arrhythmia monitoring.
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