Wireless technology has transformed the lives of hundreds of thousands of Type 1 diabetics. And the developments keep coming.
There are only four things a human body needs to survive - water, food, oxygen, and a functioning nervous system. The body is, in some ways, that simple. Yet, it is a complex, highly organized structure of individual cells that work together to accomplish specific functions necessary for life.
Take, for example, the pancreas. This organ is, in fact, the body's factory for a range of digestive enzymes as well as insulin and glucagon, the hormones that ensure both our brains and bodies have a steady and reliable supply of energy. Or it is for most of us unless you happen to be one of the nine million or so people across the globe who have Type 1 diabetes.
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Living with Type 1 diabetes
Type 1 diabetes is a chronic disease that renders the insulin-producing cells in the pancreas ineffective and, left unchecked, can damage the heart, blood vessels, eyes, kidneys, and nerves. If untreated, it will result in coma and death. While people with diabetes can live a whole life thanks to technology, living with the disease is difficult. The individual has to measure and control their blood glucose level by taking insulin either through subcutaneous injection or an insulin infusion pump.
This ritual is often required up to four or five times a day for the rest of the person's life. And so it will be until a cure is found. While waiting, the promise of an easier life for sufferers awaits at the intersection of medical and wireless innovation in the form of the 'artificial pancreas.'
The artificial pancreas
Two devices make up the artificial pancreas' 'closed-loop system': A continuous glucose monitor (CGM) and an insulin infusion pump. The infusion pump can administer insulin at any time and for any duration, depending on the user's blood glucose levels. The CGM determines those glucose levels by measuring them every few minutes. It uses a sensor inserted under the skin that wirelessly relays the data to the pump using Bluetooth LE wireless connectivity.
The infusion pump uses a complex algorithm to calculate how much insulin is needed to maintain blood glucose levels within normal physiological thresholds. The pump delivers the insulin over an extended period via a catheter.
Bluetooth LE and cellular connectivity
In part thanks to the convenience of wireless technology, today's treatment have transformed the lives of hundreds of thousands of Type 1 diabetics. And the developments keep coming. For example, the latest infusion pumps now also use Bluetooth LE to communicate with smartphones enabling the devices to perform long-term data analysis and offer healthcare recommendations. Cellular connectivity also allows continuous contact with remote physicians - who can check if the patient is appropriately managing their condition and remind them to do so if they aren't.
The next step is to use machine learning (ML) to refine the closed-loop control of the artificial pancreas while also factoring in physiological parameters. Typically the patient's overall health, core temperature, heart rate, stress levels, and sleep patterns – all of which influence blood glucose levels. The availability of such data would allow reinforcement of ML algorithms to plan the insulin infusion regime with much greater sophistication and accuracy than currently possible and without the need for the patient ever to have to adjust the pump manually.
Advanced software and hardware
Advanced software requires advanced hardware support. Devices such as the Arm Cortex-M4 and -M33 embedded processors on Nordic's Systems-on-Chip (SoCs) and Systems-in-Package (SiPs) are more than capable of providing this support. Moreover, the Arm M-class processors are well suited to running TinyML, a scaled-down form of ML suitable for running on connected devices with an optimized processor and memory resources such as infusion pumps.
And the cellular IoT capability introduced by the nRF9160 SiP introduces direct connectivity between the infusion pump and the Cloud without the requirement for a smartphone gateway - opening up a host of remote ML and monitoring possibilities.
The key to future improvement will lie in further refinement of the software algorithms and the ability for resource-constrained chips to support them. That future is much nearer than you might think.