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

被引:37
作者
Di Rosa, Mirko [1 ]
Hausdorff, Jeff M. [2 ,3 ,4 ,5 ,6 ]
Stara, Vera [1 ]
Rossi, Lorena [1 ]
Glynn, Liam
Casey, Monica [7 ]
Burkard, Stefan [8 ]
Cherubini, Antonio [9 ]
机构
[1] Natl Inst Hlth & Sci Aging INRCA, Sci Direct, Via S Margherita 5, I-60124 Ancona, Italy
[2] Tel Aviv Sourasky Med Ctr, Dept Neurol, Ctr Study Movement Cognit & Mobil, Tel Aviv, Israel
[3] Rush Univ, Rush Alzheimers Dis Ctr, Med Ctr, Chicago, IL 60612 USA
[4] Rush Univ, Med Ctr, Dept Orthopaed Surg, Chicago, IL 60612 USA
[5] Tel Aviv Univ, Sackler Fac Med, Sagol Sch Neurosci, Tel Aviv, Israel
[6] Tel Aviv Univ, Sackler Fac Med, Dept Phys Therapy, Tel Aviv, Israel
[7] NUI Galway, Sch Med, Gen Practice, Galway, Ireland
[8] Spring Techno GmbH & Co KG, Bremen, Germany
[9] Natl Inst Hlth & Sci Aging INRCA, Geriatr & Geriatr Emergency Care, Ancona, Italy
关键词
Fall risk; Gait analysis; Insole; Pressure sensors; Self-learning analysis algorithms; Pattern analysis; GAIT ANALYSIS; OLDER-PEOPLE; WEARABLE DEVICE; ELDERLY-PEOPLE; HOME; ACCELEROMETERS; CIRCUMSTANCES; PREVALENCE; PREVENTION; PARAMETERS;
D O I
10.1016/j.gaitpost.2017.03.037
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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 intend 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 theVVIISEL 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.
引用
收藏
页码:6 / 11
页数:6
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