Fall prevention intervention technologies: A conceptual framework and survey of the state of the art

In recent years, an ever increasing range of technology-based applications have been developed with the goal of assisting in the delivery of more effective and efficient fall prevention interventions. Whilst there have been a number of studies that have surveyed technologies for a particular sub-domain of fall prevention, there is no existing research which surveys the full spectrum of falls prevention interventions and characterises the range of technologies that have augmented this landscape. This study presents a conceptual framework and survey of the state of the art of technology-based fall prevention systems which is derived from a systematic template analysis of studies presented in contemporary research literature. The framework proposes four broad categories of fall prevention intervention system: Pre-fall prevention; Post-fall prevention; Fall injury prevention; Cross-fall prevention. Other categories include, Application type, Technology deployment platform, Information sources, Deployment environment, User interface type, and Collaborative function. After presenting the conceptual framework, a detailed survey of the state of the art is presented as a function of the proposed framework. A number of research challenges emerge as a result of surveying the research literature, which include a need for: new systems that focus on overcoming extrinsic falls risk factors; systems that support the environmental risk assessment process; systems that enable patients and practitioners to develop more collaborative relationships and engage in shared decision making during falls risk assessment and prevention activities. In response to these challenges, recommendations and future research directions are proposed to overcome each respective challenge.The Royal Society, grant Ref: RG13082

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

A Wii Bit of Fun: A Novel Platform to Deliver Effective Balance Training to Older Adults

BACKGROUND: Falls and fall-related injuries are symptomatic of an aging population. This study aimed to design, develop, and deliver a novel method of balance training, using an interactive game-based system to promote engagement, with the inclusion of older adults at both high and low risk of experiencing a fall.STUDY DESIGN: Eighty-two older adults (65 years of age and older) were recruited from sheltered accommodation and local activity groups. Forty volunteers were randomly selected and received 5 weeks of balance game training (5 males, 35 females; mean, 77.18 ± 6.59 years), whereas the remaining control participants recorded levels of physical activity (20 males, 22 females; mean, 76.62 ± 7.28 years). The effect of balance game training was measured on levels of functional balance and balance confidence in individuals with and without quantifiable balance impairments.RESULTS: Balance game training had a significant effect on levels of functional balance and balance confidence (P Peer reviewedFinal Published versio

Reducing fall risk with combined motor and cognitive training in elderly fallers

Background. Falling is a major clinical problem in elderly people, demanding effective solutions. At present, the only effective intervention is motor training of balance and strength. Executive function-based training (EFt) might be effective at preventing falls according to evidence showing a relationship between executive functions and gait abnormalities. The aim was to assess the effectiveness of a motor and a cognitive treatment developed within the EU co-funded project I-DONT-FALL. Methods. In a sample of 481 elderly people at risk of falls recruited in this multicenter randomised controlled trial, the effectiveness of a motor treatment (pure motor or mixed with EFt) of 24 one-hour sessions delivered through an i-Walker with a non-motor treatment (pure EFt or control condition) was evaluated. Similarly, a 24 one-hour session cognitive treatment (pure EFt or mixed with motor training), delivered through a touch-screen computer was compared with a non-cognitive treatment (pure motor or control condition). Results. Motor treatment, particularly when mixed with EFt, reduced significantly fear of falling (F(1,478) = 6.786, p = 0.009) although to a limited extent (ES -0.25) restricted to the period after intervention. Conclusions. This study suggests the effectiveness of motor treatment empowered by EFt in reducing fear of falling.Peer ReviewedPostprint (published version

Dance! Don’t Fall – Preventing Falls and Promoting Exercise at Home

Falling is a serious danger to older adults that is usually only addressed after a person has fallen, when doctors administer clinical tests to determine the patient´s risk of falling again. Having the technological capability of performing fall risk assessment tests with a smartphone, the authors set out to design a mobile application that would enable users to monitor their risk themselves and consequently prevent falls from occurring. The authors conducted a literature review and two observation sessions before beginning the iterative design process that resulted in the Dance! Don’t Fall (DDF) game, a mobile application that enables users to both monitor their fall risk and actively reduce it through fun and easy exercise

Custom-designed motion-based games for older adults: a review of literature in human-computer interaction

Many older adults, particularly persons living in senior residences and care homes, lead sedentary lifestyles, which reduces their life expectancy. Motion-based video games encourage physical activity and might be an opportunity for these adults to remain active and engaged; however, research efforts in the field have frequently focused on younger audiences and little is known about the requirements and benefits of motion-based games for elderly players. In this paper, we present an overview of motion-based video games and other interactive technologies for older adults. First, we summarize existing approaches towards the definition of motion-based video games – often referred to as exergames – and suggest a categorization of motion-based applications into active video games, exergames, and augmented sports. Second, we use this scheme to classify case studies addressing design efforts particularly directed towards older adults. Third, we analyze these case studies with a focus on potential target audiences, benefits, challenges in their deployment, and future design opportunities to investigate whether motion-based video games can be applied to encourage physical activity among older adults. In this context, special attention is paid to evaluation routines and their implications regarding the deployment of such games in the daily lives of older adults. The results show that many case studies examine isolated aspects of motion-based game design for older adults, and despite the broad range of issues in motion-based interaction for older adults covered by the sum of all research projects, there appears to be a disconnect between laboratory-based research and the deployment of motion-based video games in the daily lives of senior citizens. Our literature review suggests that despite research results suggesting various benefits of motion-based play for older adults, most work in the field of game design for senior citizens has focused on the implementation of accessible user interfaces, and that little is known about the long-term deployment of video games for this audience, which is a crucial step if these games are to be implemented in activity programs of senior residences, care homes, or in therapy

The design of a purpose-built exergame for fall prediction and prevention for older people

Background Falls in older people represent a major age-related health challenge facing our society. Novel methods for delivery of falls prevention programs are required to increase effectiveness and adherence to these programs while containing costs. The primary aim of the Information and Communications Technology-based System to Predict and Prevent Falls (iStoppFalls) project was to develop innovative home-based technologies for continuous monitoring and exercise-based prevention of falls in community-dwelling older people. The aim of this paper is to describe the components of the iStoppFalls system. Methods The system comprised of 1) a TV, 2) a PC, 3) the Microsoft Kinect, 4) a wearable sensor and 5) an assessment and training software as the main components. Results The iStoppFalls system implements existing technologies to deliver a tailored home-based exercise and education program aimed at reducing fall risk in older people. A risk assessment tool was designed to identify fall risk factors. The content and progression rules of the iStoppFalls exergames were developed from evidence-based fall prevention interventions targeting muscle strength and balance in older people. Conclusions The iStoppFalls fall prevention program, used in conjunction with the multifactorial fall risk assessment tool, aims to provide a comprehensive and individualised, yet novel fall risk assessment and prevention program that is feasible for widespread use to prevent falls and fall-related injuries. This work provides a new approach to engage older people in home-based exercise programs to complement or provide a potentially motivational alternative to traditional exercise to reduce the risk of falling