Self-powered fall detection system using pressure sensing triboelectric nanogenerators

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With the rapidly increasing number of older people in our societies, fall detection is becoming more important: Older adults may fall at home when they are alone and they may not be found in time for them to get help. In addition, a fall itself can cause serious injuries such as lacerations, fractures and hematomas. Although many previous studies have been reported on various fall detection technologies based on wearable sensors, the inconvenience of wearing them is problematic. Vision or ambient based methods may be alternatives, but high cost and complex installation process limit applicable areas. We propose a cost-effective, ambient-based fall detection system based on a pressure sensing triboelectric nanogenerator (TENG) array. Apart from simple observation of output signal waveforms according to different actions, key technologies, including appropriate filtering and distinguishing between falls and daily activities, are demonstrated with data acquisition from 48 daily activities and 48 falls by eight participants. The proposed system achieves a classification accuracy of 95.75% in identifying actual falls. Due to its low cost, easy installation and notable accuracy, the proposed system can be immediately applied to smart homes and smart hospitals to prevent additional injuries caused by falls.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2017-11
Language
English
Article Type
Article
Keywords

WIND ENERGY; CONTACT ELECTRIFICATION; ACTIVE SENSOR; SMART FLOOR; INJURIES; ARRAY

Citation

NANO ENERGY, v.41, pp.139 - 147

ISSN
2211-2855
DOI
10.1016/j.nanoen.2017.09.028
URI
http://hdl.handle.net/10203/228514
Appears in Collection
ME-Journal Papers(저널논문)EE-Journal Papers(저널논문)
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