Percentiles and Reference Values for the Accelerometric Assessment of Static Balance in Women Aged 50xe2x80x9380 Years The identification of factors that alter postural stability is fundamental in the design of interventions to maintain independence and mobility. This is especially important for women because of their longer life expectancy and higher incidence of falls compared to men. The objective of this study was to construct the percentile box charts and determine the values of reference for the accelerometric assessment of the static balance in women. For this, an observational and crosssectional study with a sample composed of 496 women (68.8 xc2xb1 10.4 years old) was conducted. The measurement of accelerations used a triaxial accelerometer during three tests: two tests on the ground in monopodal support and a test on a mat with monopodal support for 30 s each. In all of the variables, an increase in the magnitude of the accelerations was detected as the age advanced. The box charts of the percentiles of the tests show the amplitude of the interquartile ranges, which increased as the age advanced. The values obtained can be used to assess changes in static balance due to aging, trauma and orthopaedic and neurodegenerative alterations that may alter postural stability and increase the risk of falling.

A RobotMediated Assessment of Tinetti Balance scale for Sarcopenia Evaluation in Frail Elderly* Aging society is characterized by a high prevalence of sarcopenia, which is considered one of the most common health problems of the elderly population. Sarcopenia is due to the agerelated loss of muscle mass and muscle strength. Recent literature findings highlight that the Tinetti Balance Assessment (TBA) scale is used to assess the sarcopenia in elderly people. In this context, this article proposes a model for sarcopenia assessment that is able to provide a quantitative assessment of TBAgait motor parameters by means of a cloud robotics approach. The proposed system is composed of cloud resources, an assistive robot namely ASTRO and two inertial wearable sensors. Particularly, data from two inertial sensors (i.e., accelerometers and gyroscopes), placed on the patientxe2x80x99s feet, and data from ASTRO laser sensor (position in the environment) were analyzed and combined to propose a set of motor features correspondent to the TBA gait domains. The system was preliminarily tested at the hospital of xe2x80x9cFondazione Casa Sollievo della Sofferenzaxe2x80x9d in Italy. The preliminary results suggest that the extracted set of features is able to describe the motor performance. In the future, these parameters could be used to support the clinicians in the assessment of sarcopenia, to monitoring the motor parameters over time and to propose personalized careplan.