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 popular...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2015-07-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/15/8/17827 |
| _version_ | 1818015478195421184 |
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| author | Eduardo Casilari Rafael Luque María-José Morón |
| author_facet | Eduardo Casilari Rafael Luque María-José Morón |
| author_sort | Eduardo Casilari |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T06:57:27Z |
| format | Article |
| id | doaj.art-cc5c63f25c184dc3b661e590f29ba03c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T06:57:27Z |
| publishDate | 2015-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cc5c63f25c184dc3b661e590f29ba03c2022-12-22T02:06:51ZengMDPI AGSensors1424-82202015-07-01158178271789410.3390/s150817827s150817827Analysis of Android Device-Based Solutions for Fall DetectionEduardo Casilari0Rafael Luque1María-José Morón2Departamento de Tecnología Electrónica, ETSI Telecomunicación, Universidad de Málaga, 29071 Málaga, SpainDepartamento de Tecnología Electrónica, ETSI Telecomunicación, Universidad de Málaga, 29071 Málaga, SpainDepartamento de Tecnología Electrónica, ETSI Telecomunicación, Universidad de Málaga, 29071 Málaga, SpainFalls 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.http://www.mdpi.com/1424-8220/15/8/17827fall detectionsmartphoneeHealthAndroidaccelerometer |
| spellingShingle | Eduardo Casilari Rafael Luque María-José Morón Analysis of Android Device-Based Solutions for Fall Detection Sensors fall detection smartphone eHealth Android accelerometer |
| title | Analysis of Android Device-Based Solutions for Fall Detection |
| title_full | Analysis of Android Device-Based Solutions for Fall Detection |
| title_fullStr | Analysis of Android Device-Based Solutions for Fall Detection |
| title_full_unstemmed | Analysis of Android Device-Based Solutions for Fall Detection |
| title_short | Analysis of Android Device-Based Solutions for Fall Detection |
| title_sort | analysis of android device based solutions for fall detection |
| topic | fall detection smartphone eHealth Android accelerometer |
| url | http://www.mdpi.com/1424-8220/15/8/17827 |
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