IoMT at the Edge – Role of Telecoms in flattening the curve

Beware the Ides of March

We are living in a world where a deadly virus is spreading and much of the world is sheltering at home or maintaining social distancing. The World Health Organisation announced COVID-19 as global health crisis earlier in March this year. Since then, it almost seems like a plot directly out of post-apocalyptic thrillers such as “Contagion,” which depicts the spread of a lethal virus from China, and “Outbreak,” about a killer virus in the U.S.

Now, imagine you are a character in these cinematic ensembles, walking into a closed neon-lit kiosk, getting assessed for a series of medical tests using technology that combines touch-less biometric scans, with a broad array of virtual AI assistant apps, and are injected with a COVID-19 vaccine shot of ChAdOx1 nCoV-19 without any human intervention at all. With Internet of Medical Things (IoMT), 5G and Edge Computing – this will soon become a reality. 

Internet of things, more commonly known as IoT, is already commonplace in our everyday lives and is paving the way for IoMT – a connected infrastructure of medical devices, software applications, and health systems and services. Today, the IoMT market is steadily expanding and is expected to reach $254.2B globally by 2026. IoMT promises to streamline clinical workflow management for both in-hospital and remote care patients, by applying advanced analytics to the data generated from connected medical smart devices including – wearables, thermal scanners, geofencing devices, telemedicine sensors, invasive pills and mobile phone apps.

It is important to note here, that the IoMT data is of minimal use if it cannot be collated and computed real-time, thereby providing critical insights and empowering better decision-making to cure patients and save lives. In this article, I will discuss some COVID-19 use cases and apply them to a connected healthcare architecture model driven by telecom service orchestration and edge computing.

Outbreak – “Casey Schuler: I hate this bug”

As we continue our battle with COVID-19, the network of connected devices keeps growing with each passing day. Today, several medtech giants, government agencies, city councils and healthcare organisations are developing specialised IoMT solutions to contain and remediate the viral threat. Exhibit-1 below, is an illustrative view of some of the leading healthcare service providers in the industry, by COVID-19 use case. 

<Exhibit-1: COVID-19 Healthcare Partner Ecosystem>

Let’s take a brief look at these seven uses cases – 

1. Contact tracing systems – using mobile phones, as an exposure notification system, where mobile apps track users who are in the vicinity of an infected person for at least five minutes and anonymously notify them using Bluetooth technology – e.g.; Apple and Google apps, along with several government apps in different countries.
2. Frontline healthcare protection – using wearables in hospitals, medical offices and nursing homes to track their vital statistics and monitoring them for potential symptoms – e.g.; VitalPatch by VitalConnect – a biosensor monitoring 8 physiological measurements continuously in real-time, Proteus Patch used to monitor heart and respiration rates, sleep activity and daily movements.
3. Public place fever detection – using thermal scanners to perform real-time temperature checks – e.g.; KroniKare sensors with Intel’s RealSense, Baidu’s infra-red sensors, SmartXHub’s and Ibertronix's thermal scanning system.
4. Virus tracking using NLP and ML algorithms to analyse data from various sensors and track the virus origins – down to Patient-zero! – e.g.; Metabiodata is working with US DoD and intelligence services; and BlueDot an outbreak risk software.
5. Quarantine management – using sensors to create geofences or virtual perimeters for real-world geographic areas and helping governments enforce quarantine measures – e.g.; Hong Kong introduced a 14-day quarantine upon entry of overseas arrivals, enforcing each new arrival to install StayHomeSafe mobile app and pairing it with a geofencing wristband. Other examples of similar mobile apps are CovidWatch (developed in collaboration with Stanford University) and HaMagen (launched by the Health Ministry of Israel).
6. In-hospital Patient Monitoring – using telemedicine sensors to track the disease progression, improve patient outcomes, accelerate the recovery time and prevent re-admission into the hospital – e.g.; Apollo Hospitals partnered with UK firm Behold.AI to deploy chest x-ray diagnosis for quick triage of suspected COVID-19 patients; and ADAMM by Health Care Originals is a cardiopulmonary wearable system comprising of a full stack hardware and software solution to track coughing, respiration, presence of wheeze, temperature, heart rate and activity levels.
7. Remote Patient Monitoring – using disposable health sensors where several connected IoMT devices including clinical grade wearables, embedded devices, and invasive sensors are continuously worn or placed in direct contact with human skin to closely monitor coronavirus patients, without interrupting or limiting their normal movement – e.g.; Proteus Discover uses an ingestible sensor the size of a grain of sand, a small wearable sensor patch applicable on a mobile device to monitor discharged patients; and EVOLV by OMRON Healthcare – an all-in-one upper arm blood pressure monitor that takes readings in any position around the upper arm and tracks progress via a smartphone.

The huge proliferation of interconnected IoMT devices, which when coupled with continued innovation in chipsets, device form factors, and battery life – will have the potential to generate unprecedented amounts of critical patient data. As I alluded to earlier, this presents a unique challenge as the true value of this data lies in the ability of enterprises to analyse it in real-time – requiring cost-efficient compute and analytical technology close to IoMT data sources and enabling real-time decisions and insights.

This is where edge computing on a cloud-native infrastructure comes in.

The Connected Healthcare Edge Architecture

In one of my previous articles, I talked about the IoT Application Ecosystem delivered on the Edge. For healthcare enterprises, edge computing will provide greater data transmission speed, less dependency on limited bandwidth, greater privacy and security, and the ability of devices to compute, process and analyse data without latency. This will decrease cost, increase efficiency and improve the patient experience, bringing us one step closer to autonomous care. This technology is most useful for devices whose data must be acted upon immediately because there isn’t time for it to be uploaded to the cloud. An example would be COVID-19 intensive care unit sensors, that require instantaneous analysis of data and execution of commands, such as closed-loop systems that maintain physiologic homeostasis. As sensors become more sophisticated, we’ll see similar closed-loop control of devices that monitor insulin levels, respiration, neurological activity, cardiac rhythms and GI functions.

Applying edge computing with cloud-native architectures, and the seven use cases above, we can implement a connected healthcare edge architecture model as illustrated in Exhibit-2. 

<Exhibit-2: Connected Healthcare Edge Architecture Model>

With this architecture telecoms can flatten the curve and prevent future disease outbreaks from happening. The five success measures for telecoms to achieve this are:

• To connect humans, IoMT sensors, machines, video surveillance monitors and remote devices with the highest security and reliability,
• To get the performance and ultra-low latencies that is required to enable machine-based applications, such as remote and robotic ventilator administration,
• To increase bandwidth capacity where it’s needed to support critical data transfers and processing,
• To use insights from medical data and electronic health records (EHR) to enable better patient outcomes, and
• To create value by applying analytics, operational systems and device management to any healthcare application.

Here are three related topics for you to read – 

• 5G “Sliced-Edge” Architecture: Enabling 8 business service lines
• Unlocking 5 Deep Learning AI apps with Quantum Computing
• Delivering AI-driven innovations in a post COVID-19 business boom

Conclusion

Applying edge computing in a Connected Healthcare Ecosystem, helps in creating an opportunity to identify, refine and understand data available from the IoMT sensors – and provide the fastest possible insights and action. This is a vast technological expanse and is evolving rapidly. However, the challenge is that there’s no one solution that fits them all. AT&T, Vodafone, BT, Telstra, Telefonica, Orange and several other telecoms have invested heavily in building Connected Healthcare solutions. We need to apply this technology intelligently, as it is necessary for the survival of humanity. In my subsequent articles, I will discuss how 5G Network Slicing can be applied to contain the COVID-19 pandemic.

Have you had any experience with IoMT devices lately? What are your views on the future of Connected Healthcare? Would you like to share any use cases that you feel, will benefit from this technology? Please leave your comments and questions below, and feel free to share this post if you found it interesting and valuable.

Also, if you would like the citations for this content, then reach out.

– Ashish Kar

Author is a Chief Architect @PCCW Solutions, with 24+ years in the ICT industry and an innovation gameplanning coach. He has built a Silicon Valley innovation lab and designed several AI-driven solutions and IoT applications for telecom and retail organisations. He can be reached on email at [email protected].