Abstract— Accidental falls remain an important problem in older people. Stepping is a common task to avoid a fall and requires good interplay between sensory functions, central processing and motor execution. Increased choice stepping reaction time has been associated with recurrent falls in older people. The aim of this study was to examine if a sensor-based Exergame Choice Stepping Reaction Time test can successfully discriminate older fallers from non-fallers. The stepping test was conducted in a cohort of 104 community-dwelling older people (mean age: 80.7 ± 7.0 years). Participants were asked to step laterally as quickly as possible after a light stimulus appeared on a TV screen. Spatial and temporal measurements of the lower and upper body were derived from a low-cost and portable 3D-depth sensor (i.e. Microsoft Kinect) and 3D- accelerometer. Fallers had a slower stepping reaction time (970 ± 228 ms vs. 858 ± 123 ms, P = 0.001) and a slower reaction of their upper body (719 ± 289 ms vs. 631 ± 166 ms, P = 0.052) compared to non-fallers. It took fallers significantly longer than non-fallers to recover their balance after initiating the step (2147 ± 800 ms vs. 1841 ± 591 ms, P = 0.029). This study demonstrated that a sensor-based, low-cost and easy to administer stepping test, with the potential to be used in clinical practice or regular unsupervised home assessments, was able to identify significant differences between performances by fallers and non-fallers. I. INTRODUCTION Falls in older people are common and a major public health problem. More than 30% of the people older than 65 years and more than 50% in those above 80 years fall at least once a year. Falls can be attributed to a wide variety of causes, with poor balance, limited mobility and slow reactions being commonly reported [1-2]. In real-life situations stepping is the most effective way to avoid a fall [3]. The selection of an appropriate response and its execution are important to maintain balance [4]. Studies have demonstrated that impaired stepping is prevalent in older people, especially in people with a higher risk of falls and balance impairments [3-5]. For a targeted and tailored fall prevention program it is necessary to identify people at high risk and to accurately determine their individual fall risk factors first. Clinical fall risk assessments are often described as subjective and qualitative [6]. Because of limited health care resources Andreas Ejupi is with the Austrian Institute of Technology, Assistive Healthcare Information Technology Group, Vienna, Austria (e-mail: andreas.ejupi.fl@ait.ac.at) and Neuroscience Research Australia, Sydney, Australia. Matthew Brodie, Yves J Gschwind, Daniel Schoene, Stephen Lord and Kim Delbaere are with Neuroscience Research Australia, University of New South Wales. objective test equipment (e.g. force platforms or electronic walkways) is not always available. In addition, such clinical assessments usually have to be administered by a trained health professional. Quick, easy to administer and simple tests are needed which can be applied by the individual to assess fall risk on a regular basis. Therefore, low-cost and portable measuring instruments have been increasingly used in laboratory research settings and hold great promise for more regular task-specific assessments [6-8]. In addition, Exergaming, which merges motion sensors and videogame technology to promote physical activity in a new form, is used. In an on-going research project “iStoppFalls” [9], where this work is part of it, this method is applied to deliver home-based balance and strength training to prevent falls in older people. We examined the feasibility of a low-cost and portable 3D-depth sensor (Microsoft Kinect) in combination with a 3D-accelerometer (Philips) to measure temporal and spatial stepping parameters in an Exergame Choice Stepping Reaction Time test. The test was conducted with 104 community-dwelling older people. With the long-term goal to use this stepping test in an unsupervised home assessment and to predict falls more accurate we analysed the performance differences in fallers and non-fallers. II. METHODS A. Participants A sample of 104 community-dwelling older adults (mean age: 80.7 ± 7.0 years) was recruited from retirement villages in Sydney, Australia. The sample was drawn from two randomized controlled trials, 71 people took part in the SureStep interactive step training trial (ACTRN12613000671763) and 33 took part in the iStoppFalls trial (ACTRN12614000096651). Participants in the SureStep trial undertook the assessments at the 4-month retest, while participants in the iStoppFalls trial underwent the assessments at baseline. The inclusion criteria were living in the community, aged 65 years or older and being ambulant with or without the use of a walking aid. The exclusion criteria were: medically unstable, suffering from major cognitive impairment (Mini-Cog < 3), neurodegenerative disease or color blindness. Written informed consent was obtained from all participants prior to data collection. The study was approved by the University of New South Wales Human Studies Ethics Committee. A medical history was recorded during a face-to-face interview, including the presence of medical conditions and self-reported history of falls in the past 12 months. A fall was Choice Stepping Reaction Time test using Exergame technology for fall risk assessment in older people Andreas Ejupi, IEEE Member, Matthew Brodie, IEEE Member, Yves J Gschwind, Daniel Schoene, Stephen Lord and Kim Delbaere 978-1-4244-7929-0/14/$26.00 ©2014 IEEE 6957