Ekkono Solutions and Peninsula Medical Technology Ltd. (PenMed) are collaborating to identify new approaches for optimizing the care of patients whilst in emergency care. Using Ekkono’s edge machine learning software add-on to Qt Design Studio, PenMed are combining the experience and expertise of clinical end users and the power of machine learning.
With the ongoing Covid-19 pandemic, healthcare units throughout the world report about inadequate ICU capacity and equipment to save lives. By 2025, more than 20% of Europeans are expected to be over the aged above 65, with a rapid increase in the 80+ age group who have a very high prevalence of respiratory disease. More 30 million people in Europe suffer from asthma and around 300,000 deaths are cause due to Chronic Obstructive Pulmonary Disease. The need to speed up the development of modern emergency care has never been more pressing.
PenMed was formed during a collaboration between Dr. Sebastian Brown and Swagelok Bristol (Bristol Fluid Systems) that produced the Piranvent, a finalist design for the Covid19 UK Ventilator Challenge. PenMed is a British R&D company focused on the field of critical care and anesthesia, with the development of an anesthesia machine and ICU ventilator. Ekkono Solutions edge machine learning software streamlines the machine learning process and make sure the input data is used in the most effective way possible to provide the potential to provide individual patient care.
– We have been looking at the MedTech industry for a while now and when PenMed presented the idea of a smart and more personalized approach using edge machine learning, it was a perfect fit. Now we get to tailor the machine learning process even more with our unique incremental learning method, says Anders Alneng, Co-founder and VP Sales at Ekkono Solutions.
Ekkono and The Qt Company launched a joint offer earlier this year; a streamlined method to implement machine learning models. New and existing customers can with the new offer explore the field of edge in an easy deployment environment using Ekkono’s code in the Qt Design Studio. MedTech is an industry that benefits great from using machine learning, and Ekkono and PenMed initiated a joint project after the summer to see if Ekkono’s software integration can help invent the most optimized and personalized approaches, using Qt Design Studio for easy implementation.
– We believe novel applications of AI in the management of respiratory disease have major potential benefits to be realized from AI for research and innovation. We are extremely pleased with the results so far and with our partnership with Ekkono, The Qt Company and the support we received from our academic partners led by Dr Kyle Wedgewood from the University of Exeter, says Dr Sebastian Brown, Founder of PenMed.
For more information about Ekkono and The Qt Company’s joint solution, watch this On-demand webinar: ‘Machine Learning meets Embedded Development‘
Anders Alneng, VP Sales Ekkono Solutions
+46 70 254 76 46
David Whitehouse, Commercial Director, PenMed
+44 7775 978087
About Ekkono Solutions
Ekkono is a Swedish software company that does edge machine learning, i.e. enables machine learning to run at the edge of the network, onboard the connected device. Ekkono’s unique capabilities, which is the result of seven years of research at the University of Borås, enable developers and product OEMs to rapidly develop smart features that are self-learning, predictive and sustainable, down to an individual unit. Ekkono addresses all verticals, including industrial equipment, automotive and energy, and has a strong reference portfolio of tier-1 customers.
About Peninsula Medical Technology Ltd.
Peninsula Medical Technology Ltd is a medical devices company focusing in the field of critical care and anaesthesia, with the development of an anaesthesia machine/ICU ventilator that utilises cutting edge artificial intelligence/machine learning technologies.