Implementation of the Personal Emergency Response System using a 3-axial Accelerometer

Jeon, Ah-young; Kim, J.H.; Kim, I.C.; Jung, Jae Hee; Ye, S.Y.; Ro, Jung Hoon; Yoon, S.H.; Son, Jeong-Hueon; Kim, B.C.; Shin, Bhum Jae; Jeon, Gye-Rok

doi:10.1109/itab.2007.4407387

Cited by 13 publications

(10 citation statements)

References 6 publications

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“…Jeon et.al [19] developed a Personal Emergency Response System (PERS) that uses a 3-axis accelerometer to detect fall and generates the alarm on the Personal Digital Assistant (PDA). Once a fall has been detected, an alarm will be generated.…”

Section: Wearable Device Approachmentioning

confidence: 99%

Zigbee-Based Smart Fall Detection and Notification System With Wearable Sensor (E-Safe)

Gannapathy¹

2013

IJRET

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Fall is one of the serious health issues among elderly population in Malaysia. In the event of a fall, a strong impact may be inflicted on the elderly causing severe injuries or even death. Another research by the National Institutes of Health found that 67% of elderly who fall and fail to seek help within 72 hours are unlikely to survive. Current Personal Emergency Respond System (PERS) often employs the use of a manual emergency button. However this approach may not be useful if the fall victim become unconscious or even not be able to move to reach the emergency button. In addition, such as this approach also requires more time and inadequate to notify and seek for immediate help. This paper attempts to design and implement a smart fall detection system for real time notification known as e-SAFE. This system will automatically detect a fall and notifies the incident instantly to internal and external correspondence. The e-SAFE equipped with a wearable accelerometer sensor, microcontroller, ZigBee transceiver module and Global System for Mobile communications (GSM) device. The in-house correspondence will be notifies though the ZigBee technology, meanwhile the external correspondence will be notified through GSM. Once a fall has been detected by e-SAFE system, a Short Message Service (SMS) and an E-mail will be sent to predefined contacts which is stored in the system. This system will provide a path toward independent living for the elderly while keeping them save.

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Section: Wearable Device Approachmentioning

confidence: 99%

Zigbee-Based Smart Fall Detection and Notification System With Wearable Sensor (E-Safe)

Gannapathy¹

2013

IJRET

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“…Activity recognition using inertial sensors has been a topic of great interest to the research community for the last two decades [7]. It promises to have great impact on a variety of domains like elder care [6], fitness monitoring [9,14], and intelligent contextaware applications [5].…”

Section: Related Workmentioning

confidence: 99%

“…It promises to have great impact on a variety of domains like elder care [6], fitness monitoring [9,14], and intelligent contextaware applications [5]. Recently several researchers have used the accelerometers embedded in smartphones to detect activities such as walking, standing, running and sitting with the goal of developing context-aware applications [8,10].…”

Section: Related Workmentioning

confidence: 99%

Coarse In-Building Localization with Smartphones

Parnandi

Le²,

Vaghela³

et al. 2010

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. Geographic location of a person is important contextual information that can be used in a variety of scenarios like disaster relief, directional assistance, context-based advertisements, etc. GPS provides accurate localization outdoors but is not useful inside buildings. We propose an coarse indoor localization approach that exploits the ubiquity of smart phones with embedded sensors. GPS is used to find the building in which the user is present. The Accelerometers are used to recognize the user's dynamic activities (going up or down stairs or an elevator) to determine his/her location within the building. We demonstrate the ability to estimate the floor-level of a user. We compare two techniques for activity classification, one is naive Bayes classifier and the other is based on dynamic time warping. The design and implementation of a localization application on the HTC G1 platform running Google Android is also presented.

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“…The accelerometers are widely used in studies such as human health monitoring [1][2][3][4], gesture (head, posture, etc.) detection [5][6][7][8][9][10] and driving safety systems [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Design and realization of multi-channel wireless data acquisition system for laboratory-scale experiments on structural health monitoring

Gürkan¹,

Gürkan²,

Dindar³

2018

J. meas. eng.

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In this paper, we present the design steps of a low cost multi-channel accelerometer system accompanied with an open-source data acquisition software. Hardware part of the system, named KACC, is composed of battery powered tri-axial MEMS accelerometers that use IEEE 802.15.1 protocol for data transmission. The software part, named PyKACC, is developed under Python© open-source environment and handles initiation of data acquisition, data synchronization and data logging. The developed system is tested for synchronization and reliability via shake-table tests and results are presented.

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Implementation of the Personal Emergency Response System using a 3-axial Accelerometer

Cited by 13 publications

References 6 publications

Zigbee-Based Smart Fall Detection and Notification System With Wearable Sensor (E-Safe)

Zigbee-Based Smart Fall Detection and Notification System With Wearable Sensor (E-Safe)

Coarse In-Building Localization with Smartphones

Design and realization of multi-channel wireless data acquisition system for laboratory-scale experiments on structural health monitoring

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