Healthcare IoT and its diagnostic potential

Healthcare IoT and its diagnostic potential

November 28, 2019

Table of contents

Inga Shugalo

Healthcare Analyst

As an effect of increased consciousness and engagement of consumers in their own wellbeing, the demand for healthcare software, and especially for health monitoring technologies, keeps growing. According to ResearchAndMarket’s mHealth and Home Monitoring report, the number of home medical monitoring devices is expected to exceed 83 million by 2023.

More than ever, people are striving to decipher their body’s data without having to make a trip to their doctor’s office, which is why the internet of things (IoT) in healthcare is gaining momentum.

It may seem like healthcare IoT is predominately used in fitness trackers, pedometers, and sleep monitors. However, it is being used much more widely, and more technologies are being developed all the time. Various developers are coming up with innovative approaches and applications to vitality tracking sensors, both inside and outside clinical settings.

These innovations bear the promise of helping healthcare organizations provide more precise diagnostics and care while cutting costs. Providers are excited to carry out digital transformation in healthcare and jump on this bandwagon, with as many as 60% of healthcare organizations having implemented IoT-powered devices into their practices back in 2017.

Healthcare IoT in diagnostics

There are three main applications of IoT in healthcare:

  • Monitoring and maintenance
  • Energy tracking
  • Imaging

There are devices and medical software solutions that facilitate diagnostics on their own or in combination with technologies in big data, AI, and robotics. Here are some interesting examples of such IoT devices.

Diagnostic IoT: case studies

Tracking cardiac activity

Tracking cardiac activity

Many medical IoT visionaries aspire to improve cardiac activity tracking for research and clinical purposes.

MC10 came up with BioStamp nPoint®, a flexible body-worn sensor that uses a 3-axis accelerometer and a gyroscope to track movement and gather ECG and EMG data. The sensor can be placed on various body parts, including chest, thigh, forearm, sacrum, and more.

With no wires, cords or additional electrodes, this device doesn’t restrain the subject’s movements, which allows gathering objective data. Moreover, the subject can travel from lab to home freely, generating data during rest and activity periods throughout their daily lives.

The iRhythm company, in turn, dedicated their device to preventing atrial fibrillation via timely arrhythmia monitoring and diagnosis. iRhythm’s Zio XT is a long-term continuous cardiac monitoring patch. It is designed to gather a patient’s data for 3 to 14 consecutive days while using machine learning to understand a patient’s overall cardiac health.

The Zio XT patch, which has no leads or electrodes, gathers representative data and records abnormal heartbeats while allowing patients to live their regular lives. Additionally, post-monitoring data is generated into reports that can be integrated with the patient’s electronic health records, which is a major incentive for providers to adopt the device.

Excelling in diabetes management

Diabetes management

The key to a stable health status in diabetic patients is continuous blood glucose monitoring. Whether a patient has Type 1 or Type 2 diabetes, monitoring their glucose levels is a part of their daily lives. The most common method of doing this has been finger or stomach pricking, but advancements in IoT healthcare are changing this.

Eversense CGM System offers making a huge leap toward a better quality of life in patients with diabetes. Instead of weekly stomach pricking common to continuous glucose monitoring (CGM) systems, Eversense is implanted in the upper arm. The implant, which is good for 90 days, is complemented with a data-receiving smart patch. It calculates current glucose values and defines whether the blood glucose levels are expected to exceed pre-set higher and lower benchmarks.

The patch will alert patients via vibration prior to hyper- or hypoglycemia occurring. All collected data is automatically sent to the paired mobile app every 5 minutes, generating highly detailed blood glucose trends.

The Dexcom G6 is a wearable and interactive CGM system that has recently been approved by the FDA for use with compatible diabetes management systems. A patch on the abdomen transmits real-time glucose levels to the user’s smartphone or device. The sensor has the capability of sending predictive high and low alarms in advance of an actual potential event.

The device eliminates the need for finger sticks and provides more accurate results than this painful method of obtaining blood glucose levels. Alerts are customizable and can be shared remotely with a support team to enhance the chances of the patient getting the care they need.

Achieving portable eye diagnostics

Portable eye diagnostics

One of the meaningful changes that healthcare IoT introduces is accessibility to care. It is important to allow patients with mobility issues or situated in rural areas to access high-quality and timely assessments. EyeQue addresses this need by creating a mobile solution for ophthalmology. The device looks like a pair of half binoculars and straps onto a smartphone, presenting the user with a series of exams to test their vision.

The exams comprise of nine attempts on each eye to overlap green and red blocks to make one yellow block. Using the buttons on top of the device, the user can bring the blocks together or move them further apart until they feel they have successfully overlapped the blocks. The device compiles the results and provides the user with an eyeglass number.

The eyeglass number is not a prescription, but it can be used to purchase glasses at online retailers. EyeQue does not provide prescriptions because it is not meant to replace annual visits to the eye doctor. Instead, it is meant to help manage and keep track of eye health and provide interim results between visits. Additionally, EyeQue does not test for everything an ophthalmologist does, such as degenerative conditions, colorblindness, eye strain, and more.

However, EyeQue can be a handy device for people who do not have easy access to an eye doctor or for those whose prescription changes frequently.

Revolutionizing in-home diagnostics

Revolutionizing in-home diagnostics

In most cases, patients would rather be anywhere else instead of sitting in the clinic and waiting for their next appointment. Taking tests is even more frustrating, especially when you’re not sure if you really need them. But what if you could take tests in the comfort of your own home, prior to scheduling an appointment?

Cue puts the control in patients’ hands by allowing them to monitor inflammation, influenza, vitamin D levels, testosterone levels, and LH levels. This self-diagnostic device consists of a dedicated app, a lab-in-a-box device with five cartridge types, and sampling sticks.

All that a Cue user needs to do is collect a sample and insert it into the chosen cartridge. A few minutes later, the app will receive test results and offer insights in one of the five health domains.

The system then provides the user with a set of prompts related to the test results. These include nutrition tips for fertility support or sports performance, recommendations to boost vitamin D levels with short walks in the sunshine, advice for inflammation management, and more.

Monitoring medication adherence

Monitoring medication adherence

Poor medication adherence remains one of the roadblocks on the way to improving health outcomes in patients with conditions that require regular medicine intake. Due to various reasons, patients can skip one or more doses, and providers won’t know or be able to intervene.

To assist healthcare organizations in monitoring medication adherence, Proteus created Proteus Discover. An ingestible sensor, it is complemented with a wearable sensor patch, a mobile app, and a provider portal.

To start the tracking process, a patient swallows a pill with the sensor inside. The sensor is made of copper, magnesium, and silicon—all human body-friendly elements. The pill then disintegrates in the stomach, leaving the sensor intact. It gets activated by gastric fluids and starts emitting the signal to the patch on the patient’s body.

The patch recognizes the signal and validates that the pill was taken, visualizing it on the app. The other role of the patch is to measure the patient’s rest, activity, steps, and heart rate to identify patterns and correlations and create a picture of the patient’s health. This data gets shared with providers via a dedicated portal, and the sensor then leaves the patient’s body in a natural way.

Enabling contact-free fertility predictions

Contact-free fertility predictions

While there are hundreds of cycle-tracking mobile applications that claim to predict ovulation and fertility windows, some women need a more advanced approach to family planning. This is where EarlySense’s Percept can come in handy.

Percept is a sensor that is put under a mattress, where it identifies three types of motions while the user sleeps: general body motions, breathing, and heartbeats. The original algorithm then processes this data, differentiating signals, and defining unique ovulation-related patterns. These patterns allow Percept to pinpoint the next period and ovulation dates as well as a 6-day fertility window.

Due to machine learning, the algorithm gets smarter over time and improves prediction accuracy from cycle to cycle.

The diagnostic IoT area is expanding, but not without challenges

Despite an ever-widening adoption of IoT in healthcare, there are multiple challenges along the way. While there is an array of possibilities that the internet of medical things will open up in a decade or two, we shouldn’t expect a quick clinical adoption yet.

Many questions will inevitably arise:

  • How will IoT devices defend protected health information and ensure HIPAA compliance?
  • How will the diagnostic data be synchronized with electronic health records?
  • If the data won’t get to electronic health record systems directly, where should it be stored for the providers to access it?
  • Will some of these devices get insurance coverage?
  • How about diagnostic IoT reimbursement?

While these questions shouldn’t hinder innovations, vendors need to think through their strategies if they want to get widespread clinical application. With providers’ support, the industry will move faster to embed patches, implants, ingestible sensors, and wearables, a typical application of AI in sports. Hopefully, it can get to the point where each patient will have the ability to access painless, continuous and non-invasive diagnostic solutions.