Detecting and monitoring frailty among the elderly

Infonomy sell and license products that monitor and analyze the activity of users in order to identify fall-accidents, frailty and an increased risk of falling. The products are wearable sensors, including back- and frontend applications, and biokinetic algorithms that can be integrated into our customers products.

Drawing on a deep knowledge of physics, physiology and IT, Infonomy’s products are the result of more than twelve years of intense R&D. The product development is always done in close cooperation with end users and leading universities and research institutes

Infonomy products such as the Fall-hunter™ algorithms and the Snubblometer® set out to change the game of fall prevention. Infonomy’s iCore™ platform delivers cloud services based on information from sensor data to a wide variety of customers.

Fighting Fall Accidents

Falls present a significant threat to the health and well-being of older people and are a major cause and contributor to their morbidity, disability and premature death.

Falls result in significant costs incurred both by the individual and care-giver in terms of physical and psychosocial costs, and to society in terms of healthcare and social service utilization.

On average one in three persons aged of 65 and over suffer a serious fall each year increasing to 50% for those over 75 years of age. Those who survive a fall run a great risk of functional decline in physical and social activities and are at a greater risk of institutionalization.

Infonomy fight the battle against the increasing number of fall injuries. Our strategies are:

Fall Detection

Fall Detection aims to detect and inform that a fall has occurred. In this area, Infonomy’s “Fall Hunter” algorithms are licensed to leading international partners. The Snubblometer® is a tool optimized to detect fall accidents.

Fall Protection

Fall Protection aims to either passively or actively protect against fall injuries as they occur. In this area, Infonomy’s algorithms analyze sensor data and activate protection when fall injury is imminent. Infonomy cooperate with, and license algorithms to, several world leading industrial partners. As co-founders of Cocoon Airbag Protection AB Infonomy support the development of the world’s first airbag protection for bicycle child seats.

Fall Prevention

Fall prevention aims to prevent falls altogether by means of timely intervention. In this arena, Infonomy’s algorithms collect and analyze data from sensors such as the Snubblometer®, establish when the risk of falling changes and assess the effectiveness of interventions such as personalized training programs.

The Snubblometer®

The Snubblometer® is a small wearable unit that identifies fall accidents and risk-of-falling. The Snubblometer® is patented and scientifically validated through clinical trials. It is easy to introduce and implement and does not affect the user during daily life.

The Snubblometer® has been scientifically proven to measure and analyze changes in gait, activity patterns, balance and adverse events such as fall accidents. It is easy to introduce and implement into your operations and have been developed in close cooperation with end-users, which has resulted in a perfectly ergonomic and user-friendly solution. It cannot be sensed by the wearer and is thus completely unobtrusive and non-stigmatizing.

The Snubblometer® is developed for the following use cases:

Screening for frailty and fall risk: Snubblometer® measures balance, activity and sleeping patterns and conducts gait analysis over a shorter period of time to identify frailty and/or fall risk.

Monitoring: Snubblometer® continuously measures and classifies activity and stability and identifies discrete events such as falls. This enables the customer to save money as interventions can be directed at the patients who need them the most.

Rehabilitation: Snubblometer® is very well suited to follow a rehabilitation process in a very cost-effective way. By monitoring the development of stability and activity, costs can be saved in the rehabilitation of, for example, hip fractures.

Alarm: The device can detect e.g. when a patient gets out of bed or leave a facility alerting the personnel if the patient is at risk. It can also detect when a fall occurs, reducing suffering and the costs resulting from a fall accident.

The product reports and analyses information that has a well-documented diagnostic relevance for example:

  • Gait analysis – continual analysis of number of steps and intermittent steps, step length, step frequency, balance and sway parameters and more over periods of sustained movement.
  • Measurement of activity levels and sleeping patterns quality.
  • Measurement of balance – the Snubblometer® can also measures balance in terms of postural sway.

The iCore™ Platform

Infonomy’s iCore™ is an end-to-end solution for sensor networks built on the philosophy that the world is changing and so are your information needs. It’s been designed as a universal platform that is adaptable and future safe. It allows you to collect, extract, structure and visualize your business-critical information and truly enables machine-to-machine communication and the internet of things. iCore™ adapts as sensors are added to your network, when new sensor types are introduced, and as you want to do more with your collected data.

The iCore™ platform provides an ecosystem of microservices that can be deployed to a site as a complete solution or customized to your specific needs using a modular approach. An example of the latter could be using just the datapipe and machine learning microservices to collect, analyze and deliver sensor data when integrating with a third-party platform.

Algorithms, A.I. and Big Data

When a sensor measures the physical behavior of a person or machine, the produced amount of data can be overwhelming. Infonomy has extensive experience analyzing massive amounts of data. Our sophisticated analysis can substantially improve decision making, minimize risks and find valuable insights that would otherwise remain hidden.

Infonomy have developed a portfolio of proprietary algorithms that transform sensor data into valuable information. We optimize our algorithms for specific needs of the customer and for the device that they are integrated into. The algorithms can learn from the input data and adapt, allowing for customization. Most of our algorithms track and analyze human movement, but some are used to track movement of machines and vehicles as well. Furthermore, we have a long history of developing and managing image processing algorithms for e.g. automated meter reading.

People

Helmuth Kristen

Helmuth has a background in a number of different cutting edge technology companies including Precise Biometrics where he was the Advanced Research Specialist. Helmuth holds a Master of Science degree in Engineering Physics from the Royal Institute of Technology and a PhD in Astrophysics from Stockholm University. Following his doctoral studies Helmuth was a post doctoral affiliate at Harvard University.

Jonas Källmén

Jonas has a background in finance and administration. He served as CFO of a number of listed technology and life science companies. Jonas holds a Master of Science degree in International Economics and Business Administration from Linköping University.

Christer Wretfors

Christer is a systems architect and the product owner of Infonomy’s iCore™. He joined the team at Infonomy in 2013. He holds multiple degrees including a Master of Science in Biology with a focus on systems modeling and analysis from the Swedish University of Agricultural Sciences (SLU), a Licentiate in Technology (SLU) and a degree in Development of eServices from Dalarna University (DU). Christer’s research background includes work at the New Jersey – NASA Specialized Center of Research and Training (NJ-NSCORT) for his Master’s thesis, followed by several years of research into plant fibers and renewable construction materials at SLU in Alnarp. He also has an entrepreneurial background, co-founding several small start-up companies in life science and security management.

Simon Bjerkborn

Simon is an algorithm developer and the product owner of the Snubblometer™. He has a background in reactive turbulence modeling, self-learning systems and data visualization. At Infonomy he creates software and algorithms in close cooperation with the user. Simon holds a Master of Science degree in Physics from Lund University.

Lotta Åstrand

Lotta has studied andragogy (adult education) at Malmö University and has worked as an adult educator and a project leader within municipalities and organisations. Lotta has a background as freelance reporter for Swedish National Radio and holds a degree in Political Science from Stockholm University and has also studied political science at Harvard Extension School in Boston.

Daniel Smedberg

Daniel is a registered Physiotherapist, with a Master of Science degree in Public Health and a Bachelor of Arts with majors in Spanish and Social anthropology. Many years of experience working in the Swedish care sector, especially municipal eldercare, and geriatrics, in clinic as well as project manager and care development advisor.

Emma Garatea

Emma is the founder and CEO of Cocoon Airbag Protection, wich is an associated company to Infonomy. She is an international award-winning industrial designer with extensive experience in developing successful campaigns, both in Sweden and internationally. She is an expert in marketing strategies and has also worked as business advisor. Her educational background is in Product Design, studying in Lunds University, Malmö University and in the academy of fine arts in Milan.

News

Over 50 000 licenses for Infonomy’s fall detection algorithm now sold

2024-04-08

Following delivery of a major order to a Spanish customer, Legrand Care have now sold over 50 000 fall alarms that feature Infonomy´s fall-detection algorithm in Europe.

Infonomy and Legrand Care have a long-term collaboration in fall-detection in elderly patients. One result is the product “SMILE FALL” that features the Infonomy Fall-Hunter™ algorithm.

The algorithm ensures that an automatic alarm is sent in case of a hard fall. The algorithm adjusts to the mobility level of the user, thus combining sensitivity with low power consumption. The product’s battery life is over one year. The Legrand Care product complies with the European regulations for telecare peripherals, which guarantees its safety and quality.

“In addition to bringing a substantial contribution to our revenue, this milestone shows that our R&D effort finds traction in the European markets” says Helmuth Kristen, CEO of Infonomy.

About Legrand Care:

Legrand Care is a brand specializing in the innovative development of connected solutions for the health and social care sectors.

About Infonomy:

Infonomy sell and license products that monitor and analyze the activity of users to identify fall-accidents, frailty and an increased risk of falling. The products are wearable sensors, including back- and frontend applications, and biokinetic algorithms that can be integrated into our customers products. Drawing on a deep knowledge of physics, physiology and IT, Infonomy’s products are the result of intense R&D. The product development is always done in close cooperation with end users and leading universities and research institutes. Infonomy products such as the Fall-hunter™ algorithms and the Snubblometer® set out to change the game of fall prevention. Infonomy’s iCore™ platform delivers cloud services based on information from sensor data to a wide variety of customers.

For further information contact Jonas Källmén by telephone +46 708 774807 or e-mail: jonas.kallmen@infonomy.com

Infonomy AB • Medicon Village • SE-223 81 Lund • Sweden • info@infonomy.com • www.infonomy.com