Assessment Test Framework for Collecting and Evaluating Fall-Related Data Using Mobile Devices

Almer, Stefan; Kolbitsch, Josef; Oberzaucher, Johannes; Ebner, Martin

doi:10.1007/978-3-642-31534-3_13

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…Post-FPI intervention techniques consist of functional assessment, cognitive assessment, and environmental assessment. Functional assessment is the main intervention technique that is widely used to determine intrinsic fall risk factors such as functional ability deficits [ 54 , 55 , 56 , 57 , 58 ]. For instance, Majumder et al [ 59 ] developed a smart-phone-based fall risk assessment system to monitor abnormal gait patterns of older adults performing physical activities.…”

Section: Fall Prevention Systemsmentioning

confidence: 99%

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

Rajagopalan

Litvan

Jung

2017

Sensors

127

101

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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.

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Section: Fall Prevention Systemsmentioning

confidence: 99%

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

Rajagopalan

Litvan

Jung

2017

Sensors

127

101

View full text Add to dashboard Cite

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“…Most of the proposed fall prediction systems did not provide the user with an interactive interface, which implies their static nature. Majumder et al [ 96 ] and Almer et al [ 98 ] developed static applications that used smartphone sensors to collect fall relative data from older people’s behaviour while living in their own environment.…”

Section: State Of the Art And Research Results: Ict Healthcare Solmentioning

confidence: 99%

Directing and Orienting ICT Healthcare Solutions to Address the Needs of the Aging Population

2021

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Background: With an aging population, it is essential to maintain good health and autonomy for as long as possible. Instead of hospitalisation or institutionalisation, older people with chronic conditions can be assisted in their own home with numerous “smart” devices that support them in their activities of daily living, manage their medical conditions, and prevent fall incidents. Information and Communication Technology (ICT) solutions facilitate the monitoring and management of older people’s health to improve quality of life and physical activity with a decline in caregivers’ burden. Method: The aim of this paper was to conduct a systematic literature review to analyse the state of the art of ICT solutions for older people with chronic conditions, and the impact of these solutions on their quality of life from a biomedical perspective. Results: By analysing the literature on the available ICT proposals, it is shown that different approaches have been deployed by noticing that the more cross-interventions are merged then the better the results are, but there is still no evidence of the effects of ICT solutions on older people’s health outcomes. Furthermore, there are still unresolved ethical and legal issues. Conclusion: While there has been much research and development in healthcare ICT solutions for the aging population, ICT solutions still need significant development in order to be user-oriented, affordable, and to manage chronic conditions in the aging wider population.

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Assessment Test Framework for Collecting and Evaluating Fall-Related Data Using Mobile Devices

Cited by 2 publications

References 6 publications

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

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

Directing and Orienting ICT Healthcare Solutions to Address the Needs of the Aging Population

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