Fall detection system for elderly with GSM communication and GPS localization

Dumitrache, Mihail; Pasca, Sever

doi:10.1109/atee.2013.6563429

Cited by 10 publications

(2 citation statements)

References 6 publications

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“…Sum vector magnitude (F5) has been used in most studies for detecting abnormal signals. The highest peak during the sudden change of this value is used to indicate a fall [ 32 , 38 , 46 , 48 – 50 , 53 , 65 , 67 – 70 , 72 – 75 , 77 – 82 , 84 – 86 , 89 – 91 , 93 , 96 , 97 , 101 , 102 , 104 , 106 , 107 ]. In [ 85 ], F5 was used to indicate the free-fall state ( i.e.…”

Section: Wearable Fall Detection Systemsmentioning

confidence: 99%

Automatic Fall Monitoring: A Review

Pannurat

Thiemjarus

Nantajeewarawat

2014

Sensors

216

113

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Falls and fall-related injuries are major incidents, especially for elderly people, which often mark the onset of major deterioration of health. More than one-third of home-dwelling people aged 65 or above and two-thirds of those in residential care fall once or more each year. Reliable fall detection, as well as prevention, is an important research topic for monitoring elderly living alone in residential or hospital units. The aim of this study is to review the existing fall detection systems and some of the key research challenges faced by the research community in this field. We categorize the existing platforms into two groups: wearable and ambient devices; the classification methods are divided into rule-based and machine learning techniques. The relative merit and potential drawbacks are discussed, and we also outline some of the outstanding research challenges that emerging new platforms need to address.

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Section: Wearable Fall Detection Systemsmentioning

confidence: 99%

Automatic Fall Monitoring: A Review

Pannurat

Thiemjarus

Nantajeewarawat

2014

Sensors

216

113

View full text Add to dashboard Cite

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“…That is, a Wi-Fi module can be applied for fall detection [ 43 ] or communication, which is a main component of an IOT device. However, considering that the WiFi signal is sometimes unstable and that the device easily drops out of the network, the redundant alarm mechanism can be added to conduct online alarm and positioning in combination with GSM [ 44 , 45 ], which can increase the reliability of life-saving alarms. Owing to the cost, it is also not suitable to transmit the big data by GSM, so edge computing is very essential.…”

Section: Introductionmentioning

confidence: 99%

A Non-Contact Fall Detection Method for Bathroom Application Based on MEMS Infrared Sensors

Liu

Zhong

et al. 2023

Micromachines

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The ratio of the elderly to the total population around the world is larger than 10%, and about 30% of the elderly are injured by falls each year. Accidental falls, especially bathroom falls, account for a large proportion. Therefore, fall events detection of the elderly is of great importance. In this article, a non-contact fall detector based on a Micro-electromechanical Systems Pyroelectric Infrared (MEMS PIR) sensor and a thermopile IR array sensor is designed to detect bathroom falls. Besides, image processing algorithms with a low pass filter and double boundary scans are put forward in detail. Then, the statistical features of the area, center, duration and temperature are extracted. Finally, a 3-layer BP neural network is adopted to identify the fall events. Taking into account the key factors of ambient temperature, objective, illumination, fall speed, fall state, fall area and fall scene, 640 tests were performed in total, and 5-fold cross validation is adopted. Experimental results demonstrate that the averages of the precision, recall, detection accuracy and F1-Score are measured to be 94.45%, 90.94%, 92.81% and 92.66%, respectively, which indicates that the novel detection method is feasible. Thereby, this IOT detector can be extensively used for household bathroom fall detection and is low-cost and privacy-security guaranteed.

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