Enhanced human movement analysis earns Fraunhofer Portugal AICOS a new patent



We are proud to announce that our research center has recently been awarded a new patent, marking the third patent for Fraunhofer Portugal AICOS (FhP-AICOS) in 2023. This patent introduces an innovative method for an integrated, multifactorial, and adaptive approach to fall risk evaluation, fall detection, and fall prevention. “This patent represents a significant milestone in our mission to improve quality of life through technological innovation. By offering a more personalized, dynamic solution for fall risk assessment and prevention, we are setting new standards in the field and reaffirming our commitment to advancing research that makes a real difference in people's lives”, underlines Vânia Guimarães, Senior Researcher at FhP-AICOS and part of the team that developed the patented solution.

“Since its foundation in 2009, Fraunhofer Portugal AICOS has dedicated itself to the research and development of technologies for monitoring human movement using sensors in smartphones or IoT devices”, enlightens Filipe Sousa, Head of Connected Things at FhP-AICOS. Despite the recent patent grant, the evolution of this technology has been marked by various awards and achievements. Filipe Sousa explains that "we started by developing an application for Android, which won 5th place in the Android Developer Challenge II and was designed to monitor physical activity and detect falls. We continued to develop solutions to detect the risk of falls and applications to stimulate people's physical and cognitive activity."


From falls to human movement

"The same technology (initially developed to monitor movement and detect falls) was applied to localise people inside buildings, securing 3rd place in the Microsoft Indoor Location Competition in 2014. Wearables and IoT devices have been developed to facilitate the monitoring of human movement and make it possible to analyse the physical movement of workers at their workstations, and a European patent for this technology was published in 2022. We have now been awarded a second patent focusing on the risk of falls. Its foundational ideas for an adaptive and multifactorial approach could be applied to other contexts, such as monitoring workers and assessing ergonomic risk”, concludes the Head of the Connected Things group.

At Fraunhofer Portugal AICOS, the study and research of human movement have long been a cornerstone of our expertise. From initial focus on fall detection and prevention in the elderly, our research has evolved to address broader contexts related to industry and job quality improvement. These efforts reflect our ongoing commitment to addressing major concerns and leading lines of investigation in our field. The patented technology has evolved over time, adapting to other realities and needs, particularly in the industrial sector. Currently, we have been using human movement analysis technologies to study and understand the movements of shop floor operaters, which has provided very relevant evidence from an ergonomic point of view and in terms of workers' well-being and quality of life. Other solutions have also been created more from a safety perspective, such as a technology currently being commercialized by the French company NEOVIGIE. It consists of a technology that includes a device (to be worn by a lone worker), connected to a centralised system that allows continuous, real-time communication. The use of sensing technology and artificial intelligence algorithms allows it to identify anomalous patterns and predict risky situations, such as falls. When such situations occur, the system sends alerts.

These are two use cases that perfectly illustrate the evolution of a technology and its adaptation to meet specific needs and problems.


About the patented technology

Existing solutions in fall risk evaluation, fall detection, and fall prevention are predominantly static, with algorithms and calculations that do not adapt to individual users, often leading to inaccurate results. Moreover, the interaction between different components lacks dynamism, failing to leverage outcomes from each module to learn and adjust algorithms to the individual. Our invention proposes an improved concept to determine fall risk that addresses these issues.

The patented method extracts information from a person's daily activities and their environment/context, learning automatically from the data to adjust the impact of each parameter on fall risk, the sensitivity of fall detection, and interventions. Vânia highlights that “Securing this patent is a significant achievement for FhP-AICOS, marking the culmination of years of research around human movement and falls. The patent introduces an adaptive multifactorial approach for fall risk assessment, detection, and prevention, representing a significant stride in our commitment to improve the well-being and safety of people”. “I take great pride in contributing to advancing knowledge and technology to mitigate the impact of falls, addressing this major health concern within the aging population”, states the researcher.