Concurrent validation of an index to estimate fall risk in community dwelling seniors through a wireless sensor insole system: A pilot study

Mirko Di Rosa*, Jeff M. Hausdorff, Vera Stara, Lorena Rossi, Liam Glynn, Monica Casey, Stefan Burkard, Antonio Cherubini

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Falls are a major health problem for older adults with immediate effects, such as fractures and head injuries, and longer term effects including fear of falling, loss of independence, and disability. The goals of the WIISEL project were to develop an unobtrusive, self-learning and wearable system aimed at assessing gait impairments and fall risk of older adults in the home setting; assessing activity and mobility in daily living conditions; identifying decline in mobility performance and detecting falls in the home setting. The WIISEL system was based on a pair of electronic insoles, able to transfer data to a commercially available smartphone, which was used to wirelessly collect data in real time from the insoles and transfer it to a backend computer server via mobile internet connection and then onwards to a gait analysis tool. Risk of falls was calculated by the system using a novel Fall Risk Index (FRI) based on multiple gait parameters and gait pattern recognition. The system was tested by twenty-nine older users and data collected by the insoles were compared with standardized functional tests with a concurrent validity approach. The results showed that the FRI captures the risk of falls with accuracy that is similar to that of conventional performance-based tests of fall risk. These preliminary findings support the idea that theWIISEL system can be a useful research tool and may have clinical utility for long-term monitoring of fall risk at home and in the community setting.

Original languageEnglish
Pages (from-to)6-11
Number of pages6
JournalGait and Posture
Volume55
DOIs
StatePublished - 1 Jun 2017

Keywords

  • Fall risk
  • Gait analysis
  • Insole
  • Pattern analysis
  • Pressure sensors
  • Self-learning analysis algorithms

Fingerprint

Dive into the research topics of 'Concurrent validation of an index to estimate fall risk in community dwelling seniors through a wireless sensor insole system: A pilot study'. Together they form a unique fingerprint.

Cite this