System for monitoring and fall detection of patients using mobile 3-axis accelerometers sensors

Mostarac, Petar; Malarić, Roman; Jurčević, Marko; Hegeduš, Hrvoje; Lay-Ekuakille, A.; Vergallo, P.

doi:10.1109/memea.2011.5966724

Cited by 34 publications

(16 citation statements)

References 5 publications

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“…Often, magnetometers are used along with inertial sensors to improve movement tracking. Wearable sensors perform user tracking, monitoring, and diagnosis through motion sensing and both physiological and biochemical sensing [14,15]. Cardiotachometers that measure heart rates [16], bio-impedance sensors that measure blood flow resistance and skin tissue [17], and electromyography sensors that measure muscle status changes through hand movements [18] can also be employed.…”

Section: Quantified Self As Human Data Trackingmentioning

confidence: 99%

Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

et al. 2016

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This paper aims to elicit insights about sustainable wearables by investigating recent advancements in wearable technology and their applications. Wearable technology has advanced considerably from a technical perspective, but it has stagnated due to barriers without penetrating wider society despite early positive expectations. This situation is the motivation behind the focus on studies by many research groups in recent years into wearable applications that can provide the best value from a human-oriented perspective. The expectation is that a new means to resolve the issue can be found from a viewpoint of sustainability; this is the main point of this paper. This paper first focuses on the trend of wearable technology like bodily status monitoring, multi-wearable device control, and smart networking between wearable sensors. Second, the development intention of such technology is investigated. Finally, this paper discusses about the applications of current wearable technology from the sustainable perspective, rather than detailed description of the component technologies employed in wearables. In this paper, the definition of sustainable wearables is discussed in the context of improving the quality of individual life, social impact, and social public interest; those wearable applications include the areas of wellness, healthcare, assistance for the visually impaired, disaster relief, and public safety. In the future, wearables will not be simple data trackers or fun accessories but will gain extended objectives and meanings that play a valuable role for individuals and societies. Successful and sustainable wearables will lead to positive changes for both individuals and societies overall.

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Section: Quantified Self As Human Data Trackingmentioning

confidence: 99%

Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

et al. 2016

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“…The table shows the range of vital data and is described linguistically as low, normal and high. The fall detection parameters are taken from the work of Li et al (2009) and Mostarac et al (2011). Though there are different combinations required to arrive at a conclusion for definite fall of a person, decisions based on these parameters paves a way for immediate attention to extend the support to a person who is not physically well.…”

Section: Sensing and Monitoring Systemmentioning

confidence: 99%

Fuzzy logic for decision-enablement: a novel context-awareness framework for smarter environments

Rajaraajeswari

Selvarani

Raj³

et al. 2017

IJHPCN

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Abstract:With the emergence of pioneering technologies and tools in the information and communication technology (ICT) space, our everyday environments (personal, social, professional, etc.) are deeply ICT-enabled to be smarter in their operations and offerings. Smarter healthcare is one shining example. Provisioning real-time and precision-centric healthcare facilities for people especially those who are in disabled, debilitated, and diseased conditions is being made possible with the impressive advancements (the growing array of smart sensors, digitised entities, wearables, robots, controllers, and other disposable and diminutive actuators). The growing variety and volume of connected devices enable remote diagnostics, real-time monitoring, measuring, and management by transmitting various body health parameters for ensuring perfect decision-making and medication. In this paper, we have described an adaptive framework leveraging the pivotal power of fuzzy logic, which is famous for rule-based decision-making, for accelerating the systematic realisation of smarter environments especially for the healthcare segment.Keywords: sensors and actuators; body area networks; BANs; smarter homes; cloud; big data analytics; internet of things; IoT; context-awareness; fuzzy logic.Reference to this paper should be made as follows: Rajaraajeswari, S., Selvarani R., Raj, P. and Mohanavadivu, P. (2017) 'Fuzzy logic for decision-enablement: a novel context-awareness framework for smarter environments', Int. J. High Performance Computing and Networking, Vol. 10, Nos. 1/2, pp.64-77.Biographical notes: S. Rajaraajeswari is working as an Associate Professor in the Department of Computer Applications, Raja Rajeswari College of Engineering, Bangalore, India. She has more than 15 years of teaching and research experience. She has published more than 15 research papers in conferences and journals. Her fields of interests are fuzzy automata, wireless sensor network and cloud computing. Fuzzy logic for decision-enablement: a novel context-awareness framework for smarter environments 65R. Selvarani is working as a Professor and the Head in the Computer Science and Engineering Department, Alliance University, Bangalore, India. She has more than 25 years of teaching and research experience. She has two patents and published more than 50 research papers in conferences and peer-reviewed journals. Her fields of interests are software metrics, wireless sensor network, SOA and cloud computing.Pethuru Raj has been working as an Infrastructure Architect, IBM Global Cloud Center of Excellence, IBM India, Bangalore, India. He has more than 15 years of industrial working experience. He has authored five books and published more than 30 research papers in conferences and peer-reviewed journals. His fields of interests are cloud computing, big data analytics and IoT. P. Mohanavadivu has been working primarily in leading US-based software companies for the last 15+ years. Besides authoring several book chapters for technology books edited by acclaimed...

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“…Combining sensors can improve the accuracy. Tri-axial accelerometers [10] make it possible to recognize activities [11], thus improving fall detection systems. Pyroelectric InfraRed (PIR) sensors can also be used to classify different human activities [12].…”

Section: Wearable Devices and Sensorsmentioning

confidence: 99%

Towards a social and context-aware multi-sensor fall detection and risk assessment platform

Backere

Ongenae

Abeele

et al. 2015

Computers in Biology and Medicine

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For elderly people fall incidents are life-changing events that lead to degradation or even loss of autonomy. Current fall detection systems are not integrated and often associated with undetected falls and/or false alarms.In this paper, a social-and context-aware multi-sensor platform is presented, which integrates information gathered by a plethora of fall detection systems and sensors at the home of the elderly, by using a cloud-based solution, making use of an ontology. Within the ontology, both static and dynamic information is captured to model the situation of a specific patient and his/her (in)formal caregivers. This integrated contextual information allows to automatically and continuously assess the fall risk of the elderly, to more accurately detect falls and identify false alarms and to automatically notify the appropriate caregiver, e.g., based on location or their current task.The main advantage of the proposed platform is that multiple fall detection systems and sensors can be integrated, as they can be easily plugged in, this can be done based on the specific needs of the patient. systems and sensors leads to a more reliable system, with better accuracy. The proof of concept was tested with the use of the visualizer, which enables a better way to analyze the data flow within the back-end and with the use of the portable testbed, which is equipped with several different sensors.

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System for monitoring and fall detection of patients using mobile 3-axis accelerometers sensors

Cited by 34 publications

References 5 publications

Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

Fuzzy logic for decision-enablement: a novel context-awareness framework for smarter environments

Towards a social and context-aware multi-sensor fall detection and risk assessment platform

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