Reliable and Secure Body fall Detection Algorithm in a Wireless Mesh Network

Rakhecha, Sanjana; Hsu, K.

doi:10.4108/icst.bodynets.2013.253528

Cited by 9 publications

(2 citation statements)

References 36 publications

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“…In the same manner, Vilarinho et al connected a LG watch (G R1, LG Electronics, Seoul, Korea) and an Android Samsung Galaxy (S3, Samsung Electronics, Seoul, Korea). Rakesha reports falls only if confirmed by threshold-based analysis of the signals from the built-in accelerometers of both devices [24].…”

Section: Smart Wearablesmentioning

confidence: 97%

Automatic Information Exchange in the Early Rescue Chain Using the International Standard Accident Number (ISAN)

et al. 2021

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Thus far, emergency calls are answered by human operators who interview the calling person in order to obtain all relevant information. In the near future—based on the Internet of (Medical) Things (IoT, IoMT)—accidents, emergencies, or adverse health events will be reported automatically by smart homes, smart vehicles, or smart wearables, without any human in the loop. Several parties are involved in this communication: the alerting system, the rescue service (responding system), and the emergency department in the hospital (curing system). In many countries, these parties use isolated information and communication technology (ICT) systems. Previously, the International Standard Accident Number (ISAN) has been proposed to securely link the data in these systems. In this work, we propose an ISAN-based communication platform that allows semantically interoperable information exchange. Our aims are threefold: (i) to enable data exchange between the isolated systems, (ii) to avoid data misinterpretation, and (iii) to integrate additional data sources. The suggested platform is composed of an alerting, responding, and curing system manager, a workflow manager, and a communication manager. First, the ICT systems of all parties in the early rescue chain register with their according system manager, which tracks the keep-alive. In case of emergency, the alerting system sends an ISAN to the platform. The responsible rescue services and hospitals are determined and interconnected for platform-based communication. Next to the conceptual design of the platform, we evaluate a proof-of-concept implementation according to (1) the registration, (2) channel establishment, (3) data encryption, (4) event alert, and (5) information exchange. Our concept meets the requirements for scalability, error handling, and information security. In the future, it will be used to implement a virtual accident registry.

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Section: Smart Wearablesmentioning

confidence: 97%

Automatic Information Exchange in the Early Rescue Chain Using the International Standard Accident Number (ISAN)

et al. 2021

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“…In the watch-based fall detector presented in ref. [ 17 ], authors observe that the discrimination ratio clearly improves when the watch is attached to the waist or body trunk (an illogical location for a wrist-watch).…”

Section: Introductionmentioning

confidence: 99%

A Feasibility Study of the Use of Smartwatches in Wearable Fall Detection Systems

González-Cañete

Casilari

2021

Sensors

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Over the last few years, the use of smartwatches in automatic Fall Detection Systems (FDSs) has aroused great interest in the research of new wearable telemonitoring systems for the elderly. In contrast with other approaches to the problem of fall detection, smartwatch-based FDSs can benefit from the widespread acceptance, ergonomics, low cost, networking interfaces, and sensors that these devices provide. However, the scientific literature has shown that, due to the freedom of movement of the arms, the wrist is usually not the most appropriate position to unambiguously characterize the dynamics of the human body during falls, as many conventional activities of daily living that involve a vigorous motion of the hands may be easily misinterpreted as falls. As also stated by the literature, sensor-fusion and multi-point measurements are required to define a robust and reliable method for a wearable FDS. Thus, to avoid false alarms, it may be necessary to combine the analysis of the signals captured by the smartwatch with those collected by some other low-power sensor placed at a point closer to the body’s center of gravity (e.g., on the waist). Under this architecture of Body Area Network (BAN), these external sensing nodes must be wirelessly connected to the smartwatch to transmit their measurements. Nonetheless, the deployment of this networking solution, in which the smartwatch is in charge of processing the sensed data and generating the alarm in case of detecting a fall, may severely impact on the performance of the wearable. Unlike many other works (which often neglect the operational aspects of real fall detectors), this paper analyzes the actual feasibility of putting into effect a BAN intended for fall detection on present commercial smartwatches. In particular, the study is focused on evaluating the reduction of the battery life may cause in the watch that works as the core of the BAN. To this end, we thoroughly assess the energy drain in a prototype of an FDS consisting of a smartwatch and several external Bluetooth-enabled sensing units. In order to identify those scenarios in which the use of the smartwatch could be viable from a practical point of view, the testbed is studied with diverse commercial devices and under different configurations of those elements that may significantly hamper the battery lifetime.

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Social IoT Healthcare

Zamanifar

2019

Studies in Computational Intelligence

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Reliable and Secure Body fall Detection Algorithm in a Wireless Mesh Network

Cited by 9 publications

References 36 publications

Automatic Information Exchange in the Early Rescue Chain Using the International Standard Accident Number (ISAN)

Automatic Information Exchange in the Early Rescue Chain Using the International Standard Accident Number (ISAN)

A Feasibility Study of the Use of Smartwatches in Wearable Fall Detection Systems

Social IoT Healthcare

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