Infonomy uncovers digital biomarkers contributing to risk of falling – launches AI based metric identifying fall risk

Infonomy has taken the next step in the development of the Snubblometer system. An AI based metric is now being introduced that can identify individuals at high risk of falling, providing caregivers with powerful insights to intervene before a fall happens

Digital biomarkers from the Snubblometer® (SNU) device have been shown to reliably mirror results from the established Timed Up and Go (TUG) test, a clinical standard for assessing mobility and fall risk:

During the event Forskningens Dag in November 2023, data were collected from 83 individuals in Lund and Malmö. SNU devices recorded digital biomarkers such as step length, cadence, and lower body strength, while participants also performed the TUG test.

By applying Artificial Intelligence (AI) methods, the team developed a metric from the SNU biomarkers and compared it to TUG results. The findings revealed a strong positive correlation (r = 0.81, p < 0.001), providing evidence of concurrent validity.

Unlike TUG, which requires dedicated testing in a clinic or other controlled environment, SNU biomarkers can be collected continuously and unobtrusively in real life. This makes it possible to screen for mobility decline and fall risk more broadly, with less effort and potentially greater validity.

Infonomy’s AI based metric can facilitate early detection of mobility limitations and support preventive interventions, offering healthcare providers valuable real-world insights into patients’ functional status.

For further information contact Helmuth Kristen by telephone +46 708 11 36 05 or e-mail: helmuth.kristen@infonomy.com