Hindawi Publishing Corporation BioMed Research International Volume 2013, Article ID 279197, 6 pages http://dx.doi.org/10.1155/2013/279197 Research Article Differences in Trunk Kinematic between Frail and Nonfrail Elderly Persons during Turn Transition Based on a Smartphone Inertial Sensor Alejandro Galán-Mercant 1 and Antonio I. Cuesta-Vargas 1,2 1 Department of Physical Terapy, School of Medicine, University of M´ alaga, 29071 M´ alaga, Spain 2 School of Clinical Sciences of the Faculty of Health at the Queensland University of Technology, Brisbane, QLD 4000, Australia Correspondence should be addressed to Antonio I. Cuesta-Vargas; acuesta.var@gmail.com Received 27 September 2013; Revised 30 October 2013; Accepted 14 November 2013 Academic Editor: Giuseppe Passarino Copyright © 2013 A. Gal´ an-Mercant and A. I. Cuesta-Vargas. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. Firstly, to, through instrumentation with the iPhone4 smartphone, measure and describe variability of tridimensional acceleration, angular velocity, and displacement of the trunk in the turn transition during the ten-meter Extended Timed-Get-up- and-Go test in two groups of frail and physically active elderly persons. Secondly, to analyse the diferences and performance of the variance between the study groups during turn transition (frail and healthy). Design. Tis is a cross-sectional study of 30 subjects over 65 years, 14 frail subjects, and 16 healthy subjects. Results. Signifcant diferences were found between the groups of elderly persons in the accelerometry ( < 0.01) and angular displacement variables ( < 0.05), obtained in the kinematic readings of the trunk during the turning transitions. Te results obtained in this study show a series of defcits in the frail elderly population group. Conclusions. Te inertial sensor found in the iPhone4 is able to study and analyse the kinematics of the turning transitions in frail and physically active elderly persons. Te accelerometry values for the frail elderly are lower than the physically active elderly, whilst variability in the readings for the frail elderly is also lower than the control group. 1. Background Clinical frailty syndrome is a common geriatric syndrome which is characterized by physiological reserve decreases and increased vulnerability and which may, in the event of unexpected intercurrent processes, result in falls, hospital- ization, institutionalization, or even death [1]. Te changes associated with ageing and frailty are associated with changes in gait characteristics and the basic functional capacities of the individual [2]. Tis variability in diferent movement patterns has been interpreted as a more conservative gait pattern in order to increase gait stability and reduce the risk of falls [3]. Tis new, more conservative gait pattern has greater cognitive involvement and produces a result focused entirely on movement, whilst the perception of unexpected trigger factors may be overlooked [4]. Dual tasks have been shown to afect normal gait development even in healthy persons [5]. Turning while walking is a common occurrence in every- day life [6]. Turning requires transfer and rotation of the body towards the new walking direction while maintaining dynamic stability [7]. Te Timed Get Up and Go (TGUG) test is a widely used tool to evaluate balance and some functional tasks through clinical evaluation of mobility and the risk of falls [2, 8–10]. Te clinical potential of the TGUG test comes from the possibility of sequencing several basic functional abilities, such as standing up and sitting down transitions, and transitions which require balance, such as turning [11]. Te TGUG test, despite being widely used in clinical practice, has limitations. As a consequence, the TGUG test is currently carried out in an instrumented manner by attaching inertial sensors to the body [2, 9, 12–16]. Te latest generation of smartphones ofen includes inertial sensors with subunits such as accelerometers and gyroscopes which can detect acceleration and inclination