2 research outputs found
Comparison and Characterization of Android-Based Fall Detection Systems
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.Ministerio de EconomÃa y Competitividad TEC2009-13763-C02-0
Analysis of Android Device-Based Solutions for Fall Detection
Falls are a major cause of health and psychological problems as well as
hospitalization costs among older adults. Thus, the investigation on automatic Fall
Detection Systems (FDSs) has received special attention from the research community
during the last decade. In this area, the widespread popularity, decreasing price, computing
capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based
devices (especially smartphones) have fostered the adoption of this technology to deploy
wearable and inexpensive architectures for fall detection. This paper presents a critical and
thorough analysis of those existing fall detection systems that are based on Android devices.
The review systematically classifies and compares the proposals of the literature taking into
account different criteria such as the system architecture, the employed sensors, the detection
algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the
evaluation methods that are employed to assess the effectiveness of the detection process.
The review reveals the complete lack of a reference framework to validate and compare the
proposals. In addition, the study also shows that most research works do not evaluate the
actual applicability of the Android devices (with limited battery and computing resources) to
fall detection solutions.Ministerio de EconomÃa y Competitividad TEC2013-42711-