Strength and balance training has been demonstrated to prevent physical decline and falls in older adults. The majority of fall prevention studies have focused on supervised group or home-based exercise interventions utilizing qualified personal. The implementation of these interventions on a community-wide level is limited due to home-bound status because of functional or cognitive decline, care-giving responsibilities, or transportation difficulties. High costs for personal, and lack of group exercie facilities are likewise problematic. A promising and cost-effective approach for tailoring strength and balance exercise to older adults in a community setting is to provide training via the internet. However, interactive web-based home exercise technologies, including virtually supervised training, have not yet been developed. The objective of this collaborative SHIFT SBIR project between BioSensics LLC (Cambridge, MA) and the University of Arizona (Interdisciplinary Consortium on Advance Motion Performance (iCAMP) and Arizona Center on Aging) is to develop a low cost, easy-to-use, interactive web application for home-based strength and balance training to improve mobility and reduce fall risk in older adults. The proposed system will be developed based on an existing non-interactive prototype web-based training program using a virtual on- screen trainer. The new interactive web application will include an on-screen 'user avatar' that mimics its users movements. This will be accomplished by developing an instrumented overshoe containing kinematic sensors. Based on the sensor signals, body segment kinematics (e.g., foot position, ankle angle, and hip angle) will be estimated in real-time using a simplified biomechanical model of the human body. The kinematic data will drive the on-screen user avatar, which will provide real-time feedback to the user regarding their exercise performance. Game-based features will be included for rewarding correctly performed exercises and motivating the user to achieve individually set exercise goals based on his/her initial motor performance. To ensure user-friendliness, the application will be developed based on established guidelines for media use in older adults. In the first of two clinical studies we will evaluate the accuracy of the estimates of lower extremity kinematics during exercise provided by the new system. In the second clinical study (a randomized controlled trial) we will evaluate the effectiveness of the proposed technology for improving mobility, gait, balance, quality of life, and risk of falling compared to unsupervised home trainin. Several validated outcome measures will be used to assess training-related changes in functional performance, as well as user perceived acceptability/usability of the new technology. A unique element of the present study is that both exercise adherence and exercise accuracy will be objectively assessed. A larger clinical study to further assess the benefits of the proposed technology for improving mobility and reducing falls in older adults is planned for Phase II of this project. In addition, in Phase II additional hardware and software development will be performed to make the system suitable for commercialization to the target population. The proposed technology could have an important effect on the US health care system by reducing the risk of falling and improving function, quality-of-life, and independence among older adults. This methodology addresses key issues for an aging population with high risk of falling and multiple disease processes. Moreover, the methods evaluated and refined in this study will be used in future web-based applications focused on exercise training in various disease processes that effect mobility and balance, such as stroke, diabetes, and dementia.