Smartphone-based solutions for fall detection and prevention: the FARSEEING approach

Mellone, Sabato; Tacconi, Carlo; Schwickert, Lars; Klenk, Jochen; Becker, Clemens; Chiari, Lorenzo

doi:10.1007/s00391-012-0404-5

Cited by 100 publications

(82 citation statements)

References 23 publications

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“…Mellone and colleagues [80]-[83] utilized the accelerometer in an Android-based smartphone and designed an elderly-friendly user interface to self-administer the TUG test. The interface contains a button to start the exam and data collection and a button to stop.…”

Section: Tug Technologiesmentioning

confidence: 99%

Toward Automating Clinical Assessments: A Survey of the Timed Up and Go

Sprint

Cook

Weeks³

2015

IEEE Rev. Biomed. Eng.

100

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Older adults often suffer from functional impairments that affect their ability to perform everyday tasks. To detect the onset and changes in abilities, healthcare professionals administer standardized assessments. Recently, technology has been utilized to complement these clinical assessments to gain a more objective and detailed view of functionality. In the clinic and at home, technology is able to provide more information about patient performance and reduce subjectivity in outcome measures. The timed up and go (TUG) test is one such assessment recently instrumented with technology in several studies, yielding promising results towards the future of automating clinical assessments. Potential benefits of technological TUG implementations include additional performance parameters, generated reports, and the ability to be self-administered in the home. In this paper, we provide an overview of the TUG test and technologies utilized for TUG instrumentation. We then critically review the technological advancements and follow up with an evaluation of the benefits and limitations of each approach. Finally, we analyze the gaps in the implementations and discuss challenges for future research towards automated, self-administered assessment in the home.

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Section: Tug Technologiesmentioning

confidence: 99%

Toward Automating Clinical Assessments: A Survey of the Timed Up and Go

Sprint

Cook

Weeks³

2015

IEEE Rev. Biomed. Eng.

100

View full text Add to dashboard Cite

show abstract

“…Requests for the user's feedback can be attempted by using the external speakers on the phone and requesting a vocal or keypad response from the user [21]. Combinations of alarm systems and graphical user interface of SPs are also used for collecting the feedback of the user [9,54]. After requesting a response from the user, the system waits for a pre-defined period (typically ≤ 1 min).…”

Section: Sp Based Fall Detection and Preventionmentioning

confidence: 99%

Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues

Habib

Mohktar

Kamaruzzaman

et al. 2014

Sensors

186

105

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This paper presents a state-of-the-art survey of smartphone (SP)-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention. Required hardware for both fall detection and prevention are also available in SPs. Consequently, researchers' interest in finding SP-based solutions has increased dramatically over recent years. To the best of our knowledge, there has been no published review on SP-based fall detection and prevention. Thus in this paper, we present the taxonomy for SP-based fall detection and prevention solutions and systematic comparisons of existing studies. We have also identified three challenges and three open issues for future research, after reviewing the existing articles. Our time series analysis demonstrates a trend towards the integration of external sensing units with SPs for improvement in usability of the systems.

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“…In another work of the same authors [42], an impact is presumed if the acceleration is greater than an empirically adjusted threshold of 2.3 g. An impact is only considered to be a fall if the final user orientation is horizontal.…”

Section: Related Workmentioning

confidence: 99%

Comparison and Characterization of Android-Based Fall Detection Systems

Luque

Casilari

Morón

et al. 2014

Sensors

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Falls are a foremost source of injuries and hospitalization for seniors. The adoption of automatic fall detection mechanisms can noticeably reduce the response time of the medical staff or caregivers when a fall takes place. Smartphones are being increasingly proposed as wearable, cost-effective and not-intrusive systems for fall detection. The exploitation of smartphones' potential (and in particular, the Android Operating System) can benefit from the wide implantation, the growing computational capabilities and the diversity of communication interfaces and embedded sensors of these personal devices. After revising the state-of-the-art on this matter, this study develops an experimental testbed to assess the performance of different fall detection algorithms that ground their decisions on the analysis of the inertial data registered by the accelerometer of the smartphone. Results obtained in a real testbed with diverse individuals indicate that the accuracy of the accelerometry-based techniques to identify the falls depends strongly on the fall pattern. The performed tests also show the difficulty to set detection acceleration thresholds that allow achieving a good trade-off between false negatives (falls that remain unnoticed) and false positives (conventional movements that are erroneously classified as falls). In any case, the study of the evolution of the battery drain reveals that the extra power consumption introduced by the Android monitoring applications cannot be neglected when evaluating the autonomy and even the viability of fall detection systems.

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Smartphone-based solutions for fall detection and prevention: the FARSEEING approach

Cited by 100 publications

References 23 publications

Toward Automating Clinical Assessments: A Survey of the Timed Up and Go

Toward Automating Clinical Assessments: A Survey of the Timed Up and Go

Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues

Comparison and Characterization of Android-Based Fall Detection Systems

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