Feb 12, 2021

SOTI MobiControl aims to prevent injury and save billions

wearable tech
medical devices
elderly care
injury
Leila Hawkins
2 min
SOTI MobiControl aims to prevent injury and save billions
HAS Technology Group partners with SOTI MobiControl to prevent injuries resulting from falls and reduce cost to healthcare systems...

Falling is a common, yet overlooked cause of injury, particularly among adults over the age of 65 – around 1 in 3 people over this age fall at least once a year, and half of these will experience falls more frequently than this. 

As well as the distress this causes to the person, it costs healthcare systems billions each year, with the World Health Organisation (WHO) estimating that 37.3 million falls each year are severe enough to require medical attention, costing somewhere between $3600 and $1000 per person.  

In an attempt to remedy this, global tech company HAS Technology Group is deploying SOTI MobiControl in its wearable medical devices, with the aim of reducing the risk of falls in the elderly population, and thereby lowering associated costs. 

ARMED (Advanced Risk Monitoring for Early Detection), one of HAS’ solutions since 2016 and a registered medical device, uses wearable technology to collect key metrics associated with frailty and the risk of falling. It monitors the patient’s condition 24/7, and then uses this data to feed into its machine learning models. 

The SOTI MobiControl solution allows ARMED to help escalate risks in advance and create triggers for a quicker and more accurate diagnosis to happen, based on the early warning signals the data provides. 

The ARMED platform extracts data from smart watches. With a customized SOTI MobiControl application operated from a smartphone, the smart watch is paired with the phone via Bluetooth, and data is transferred from the watch to the phone. 

This data is captured, and machine learning algorithms are applied to forewarn of medical issues and changes in the behaviour of elderly patients. This advanced warning can also help healthcare practitioners to prioritise resources accordingly. 

“ARMED is now a registered medical device and this step, along with machine learning, is significantly contributing to understanding the longer-term impacts of health and lifestyle changes in a more preventative manner” Brian Brown, Director ARMED at HAS Technology Group said. 

“We are excited for the future with SOTI and making a huge difference to the quality of life for individuals.”

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Jun 15, 2021

 NHS trials test that predicts sepsis 3 days in advance 

sepsis
MachineLearning
clinicaltrial
blooddisorder
2 min
Queen Alexandra Hospital is trialling a new sepsis test by Presymptom Health that uses machine learning to detect the onset of the disease

A new test that can predict sepsis before the patient develops symptoms is being trialled at a National Health Service (NHS) hospital in the south of England. 

Clinicians at Portsmouth’s Queen Alexandra Hospital are leading medical trials of the blood test, which they hope will help them save thousands of lives a year. 

The test is being developed by government spin-out company Presymptom Health, but the research began over 10 years ago at the Defence Science and Technology Laboratory (Dstl). This included a study of 4,385 patients and more than 70,000 samples, the largest study of its kind at the time. 

From the samples taken, a clinical biobank and database were generated and then mined using machine learning to identify biomarker signatures that could predict the onset of sepsis. The researchers found they were able to provide an early warning of sepsis up to three days ahead of illness with an accuracy of up to 90%.

Unlike most other tests, Presymptom Health identifies the patient’s response to the disease as opposed to detecting the pathogen. This is an important differentiator, as sepsis occurs as a result of the patient's immune system’s overreaction to an infection or injury, which can then cause life-threatening organ dysfunction. 

Worldwide, an estimated 49 million people a year contract sepsis, while in the UK almost two million patients admitted to hospital each year are thought to be at risk of developing the condition. If Presymptom's test is effective, it could save billions of pounds globally and improve clinical outcomes for millions of sepsis patients.

The initial trials at Queen Alexandra Hospital will last 12 months, with two other sites planned to go live this summer. Up to 600 patients admitted to hospital with respiratory tract infections will be given the option to participate in the trial. The data collected will be independently assessed and used to refine and validate the test, which could be available for broader NHS use within two years. 

If successful, this test could also identify sepsis arising from other infections before symptoms appear, which could potentially include future waves of COVID-19 and other pandemics.

Dr Roman Lukaszewski, the lead Dstl scientist behind the innovation, said: “It is incredible to see this test, which we had originally begun to develop to help service personnel survive injury and infection on the front line, is now being used for the wider UK population, including those fighting COVID-19.”

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