Assessment method of balance ability of older adults using an in-shoe motion sensor.

Falls rank as the second main cause of accidental death and injury in older adults, so technologies are urgently needed that are accurate, inexpensive, and easy to use to administer fall risk assessments in daily living. In this study, as the first stage of assessing fall risk in daily living, by using in-shoe motion sensor (IMS), we aim to develop an assessment method for dynamic balance ability that is an important factor for fall risk assessment. Sixty-four elderly participants were recruited for constructing the assessment model, and 20 other participants were recruited for model validation. We used statistical parametric mapping to analyze the correlation between the IMS signals and the outcome of FRT, the clinical score for evaluating dynamic balance ability, and then constructed predictors from highly correlated parts. Intra-class correlation coefficients (ICCs) were used for evaluating and limits of agreement (LoA) of Bland-Altman plots was used for validating the constructed model. In the results for both men and women, the estimation model achieved "excellent" ICC inter-rater agreement between true and estimated values, and in the validation, 90% of participants were effectively estimated inside the LoA.