Sensor-Based Wireless Wearable Systems for Healthcare and Falls Monitoring

Hou, Huilian; Huo, Meimei; Wu, Minghui

doi:10.21307/ijssis-2017-634

Cited by 9 publications

(7 citation statements)

References 19 publications

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“…In contrast with most studies, the consumption and lifetime of the mote is carefully studied. In [ 59 ] the accelerometer is connected to a specific wrist-worn ZigBee device. In [ 60 ] the sensed data from a triple axis accelerometer and a gyroscope (located at waist and ankles) are received via ZigBee by an agent module and then retransmitted to a mobile device.…”

Section: A Classification Of Fall Detection Systems (Fdss): Advantmentioning

confidence: 99%

“…CARA architecture [ 62 ] proposes to send the data of a wearable accelerometer to an external not-portable gateway which applies a thresholding method to asses if a fall occurs. Similarly, ZigBee is the wireless technology between the BAN and a central server in the system portrayed in [ 59 ]. In that system, Android handset devices can be utilized to remotely monitor the biosignals from the server as well as the fall alarms.…”

Section: A Classification Of Fall Detection Systems (Fdss): Advantmentioning

confidence: 99%

“…Table 1 does not include those works [ 55 , 56 , 59 , 96 , 97 ] where Android SPs are considered as specific RMUs ( i.e. , with particularized apps to receive fall alarms).…”

Section: Analysis Of the Typology Role And Complexity Of Android-mentioning

confidence: 99%

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Analysis of Android Device-Based Solutions for Fall Detection

Casilari

Luque

Morón

2015

Sensors

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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.

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Section: A Classification Of Fall Detection Systems (Fdss): Advantmentioning

confidence: 99%

Section: A Classification Of Fall Detection Systems (Fdss): Advantmentioning

confidence: 99%

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Analysis of Android Device-Based Solutions for Fall Detection

Casilari

Luque

Morón

2015

Sensors

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“…The end-user interface circuit requires only a 3-bit pseudo flash analog-to-digital converter (ADC) in place of the conventional/typical design comprising ADC, digital signal processor and memory. In the paper [13], based-on the algorithms research, a ubiquitous personal health monitoring and system is designed, which integrates health-related sensory devices with the healthcare center cost-effectively. It can aid senior citizens and patients, especially elderly, who need long-term attention to their physical condition, like chronic diseases and falls, with ubiquitous surveillance and remote management of the recorded health data, and timely help.…”

Section: Introductionmentioning

confidence: 99%

The Smart Home System Based on the Iap15F2K61S2 and Gsm

Xin¹,

Chen²,

Li³

et al. 2014

International Journal on Smart Sensing and Intelligent Systems

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At home, there are all kinds of electrical devices. Also the gas may leak to fire. Once the danger happens, it will result in the huge losses. The smart home system is necessary for the safety. The system integrated the sensors to monitor the appliances whether they work normally. Once the exceptions have been tested, the owner can get the text massage immediately with the help of GSM. This system has a light cube. It has 512 lights. After test, this system works to monitor the home appliances very well at the low cost.

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“…So the second is using the ubiquitous intelligent phones as the control terminals. They control the home appliances based on the WiFi, Bluetooth, GSM, the wireless sensor internet based on the Zigbee and the CC2530 chip, and other systems [10][11][12][13][14][15]…”

Section: Introductionmentioning

confidence: 99%

The Implementation For The Intelligent Home Control System Based On The Android And Zigbee

Xin

Chen

et al. 2014

International Journal on Smart Sensing and Intelligent Systems

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The intelligent home system finished the wireless or remote control for all the indoor electric devices through the intelligent terminals. The description about the integrated network architecture and the interconnecting mechanisms for the reliable measurement of parameters by smart sensors and transmission of data via internet is being presented. The wireless communication technology includes the WiFi, Zigbee and mobile communications. The system presented the design of the hardware part and the software part. The forward are fixed in the variety of appliances based on CC2530 chip and sensors. The connection between different devices can be finished by the standard interfaces RS232 and RS485. The software can be installed in the tablet PC, the personal computer or smart telephones. It can be realized on the open Android platform or Eclipse. The system has been applied in the actual intelligent house. Results are encouraging as the reliability of sensing information transmission is with very little error in the peak of the internet. The home owners are satisfied with the test results. The prototype was tested to generate real-time graphical information rather than a test bed scenario. This will be widely applied in the future of the smart home.

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Sensor-Based Wireless Wearable Systems for Healthcare and Falls Monitoring

Cited by 9 publications

References 19 publications

Analysis of Android Device-Based Solutions for Fall Detection

Analysis of Android Device-Based Solutions for Fall Detection

The Smart Home System Based on the Iap15F2K61S2 and Gsm

The Implementation For The Intelligent Home Control System Based On The Android And Zigbee

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