Accurate Fall Detection and Localization for Elderly People Based on Neural Network and Energy-Efficient Wireless Sensor Network

Falls are the main source of injury for elderly patients with epilepsy and Parkinson’s disease. Elderly people who carry battery powered health monitoring systems can move unhindered from one place to another according to their activities, thus improving their quality of life. This paper aims to det...

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Vydáno v:	Energies (Basel) Ročník 11; číslo 11; s. 2866
Hlavní autoři:	Gharghan, Sadik Kamel, Mohammed, Saleem Latteef, Al-Naji, Ali, Abu-AlShaeer, Mahmood Jawad, Jawad, Haider Mahmood, Jawad, Aqeel Mahmood, Chahl, Javaan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.11.2018
Témata:	accelerometer sensor Accelerometers Accuracy Blood pressure Cameras data-driven algorithm Engineering fall detection Global positioning systems GPS Health care International conferences Localization Methods neural network Neural networks Older people Sensors tilt sensor Wireless networks wireless sensor network (WSN) ZigBee Baghdad Iraq Australia Iraq
ISSN:	1996-1073, 1996-1073
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Abstract	Falls are the main source of injury for elderly patients with epilepsy and Parkinson’s disease. Elderly people who carry battery powered health monitoring systems can move unhindered from one place to another according to their activities, thus improving their quality of life. This paper aims to detect when an elderly individual falls and to provide accurate location of the incident while the individual is moving in indoor environments such as in houses, medical health care centers, and hospitals. Fall detection is accurately determined based on a proposed sensor-based fall detection algorithm, whereas the localization of the elderly person is determined based on an artificial neural network (ANN). In addition, the power consumption of the fall detection system (FDS) is minimized based on a data-driven algorithm. Results show that an elderly fall can be detected with accuracy levels of 100% and 92.5% for line-of-sight (LOS) and non-line-of-sight (NLOS) environments, respectively. In addition, elderly indoor localization error is improved with a mean absolute error of 0.0094 and 0.0454 m for LOS and NLOS, respectively, after the application of the ANN optimization technique. Moreover, the battery life of the FDS is improved relative to conventional implementation due to reduced computational effort. The proposed FDS outperforms existing systems in terms of fall detection accuracy, localization errors, and power consumption.
AbstractList	Falls are the main source of injury for elderly patients with epilepsy and Parkinson’s disease. Elderly people who carry battery powered health monitoring systems can move unhindered from one place to another according to their activities, thus improving their quality of life. This paper aims to detect when an elderly individual falls and to provide accurate location of the incident while the individual is moving in indoor environments such as in houses, medical health care centers, and hospitals. Fall detection is accurately determined based on a proposed sensor-based fall detection algorithm, whereas the localization of the elderly person is determined based on an artificial neural network (ANN). In addition, the power consumption of the fall detection system (FDS) is minimized based on a data-driven algorithm. Results show that an elderly fall can be detected with accuracy levels of 100% and 92.5% for line-of-sight (LOS) and non-line-of-sight (NLOS) environments, respectively. In addition, elderly indoor localization error is improved with a mean absolute error of 0.0094 and 0.0454 m for LOS and NLOS, respectively, after the application of the ANN optimization technique. Moreover, the battery life of the FDS is improved relative to conventional implementation due to reduced computational effort. The proposed FDS outperforms existing systems in terms of fall detection accuracy, localization errors, and power consumption. The degree of danger from a fall for aging persons is frequently decided by the location of the fall, time of fall detection, duration and time of transfer and rescue services. [...]automatic detection of elderly people’s falls along with the locations of the incident is important so that medical rescue staff can be dispatched immediately and so that the family of the elderly can be informed about the incident through a specific wireless network or mobile telephone. [...]the power consumption of the sensor node is improved in the present study with the use of a data-driven algorithm (DDA) along with a low-power wireless communication module (i.e., Zigbee) and a standalone microcontroller. [...]the CN supported by a monitoring system such as PC, tablet, and notepad can estimate the location of the fallen subject to be sent to the caregivers. 3.3. [...]the fall detection accuracy is satisfactory, and results indicate that the proposed FDS is energy efficient and can be used for accurate fall detection.
Author	Chahl, Javaan Jawad, Haider Mahmood Gharghan, Sadik Kamel Jawad, Aqeel Mahmood Mohammed, Saleem Latteef Al-Naji, Ali Abu-AlShaeer, Mahmood Jawad
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Cites_doi	10.1016/j.compag.2014.04.012 10.1016/j.pmcj.2015.06.010 10.1007/978-3-319-50212-0 10.3390/s17010198 10.1109/RADAR.2017.7944316 10.1016/j.pmcj.2016.05.002 10.1109/UIC-ATC.2010.44 10.1155/2015/657241 10.1155/2015/452078 10.1109/TMC.2016.2557792 10.1016/j.eswa.2013.07.031 10.1109/JSEN.2013.2257731 10.1016/j.asoc.2015.11.031 10.1155/2015/576364 10.1007/s13534-015-0174-2 10.1109/JIOT.2016.2624800 10.1109/ISMICT.2012.6203028 10.4236/wsn.2010.28072 10.1109/TMC.2016.2557795 10.3390/s150511741 10.1016/j.procs.2017.01.191 10.1109/TCE.2016.7514671 10.1109/JETCAS.2013.2256832 10.1007/978-981-10-3023-9 10.3390/s17010176 10.3390/s141019806 10.1007/s11390-017-1725-z 10.1007/s10044-017-0660-5 10.3390/electronics7020019 10.3390/s17020307 10.1109/ICCASE.2011.5997582 10.1109/TSP.2012.2199314 10.1109/JBHI.2013.2274479 10.1016/j.autcon.2017.09.015 10.1109/LWC.2016.2595576 10.1109/JBHI.2014.2361252 10.3390/s16040546 10.1109/DATE.2010.5457055 10.1155/2013/254629 10.1145/2248341.2248349 10.1371/journal.pone.0180318 10.3390/s17061393 10.3390/app7040316 10.1016/j.procs.2012.06.079 10.1109/MSP.2015.2502784 10.1016/j.procs.2011.07.010 10.1080/10739149.2015.1123161 10.1109/TSMCB.2003.811119 10.1145/2600617.2600621 10.1109/ICOIN.2012.6164365 10.1109/ICDMIC.2014.6954228 10.1007/s11276-017-1557-3 10.1049/iet-rsn.2014.0214 10.1016/j.gaitpost.2017.03.037 10.1016/j.adhoc.2011.12.008 10.3390/s150923004 10.17485/ijst/2017/v10i5/111274 10.3390/s17020341 10.1109/TII.2016.2587761 10.1007/s11227-016-1785-9 10.1109/LCOMM.2014.2318031 10.1016/j.neucom.2013.01.032 10.1016/j.jpdc.2018.07.003 10.1155/2014/896030 10.1007/978-3-319-59060-8 10.1155/2015/195297 10.1109/JSEN.2015.2483745 10.5121/ijcnc.2016.8105 10.1016/j.pmcj.2012.08.003 10.3390/s140610691 10.1016/j.micpro.2017.10.014 10.1007/s11036-013-0448-9 10.1109/TITB.2012.2226905 10.1016/j.mejo.2010.06.014 10.1016/j.asoc.2015.10.062 10.1007/s11517-016-1504-y 10.1117/12.2257902 10.3390/s16010117 10.1155/2013/935026 10.3390/s17081781 10.1007/s10586-013-0335-y 10.1016/j.dcan.2015.12.001 10.1016/j.procs.2017.01.188 10.3390/s140407181 10.1109/ICIT.2017.7915565 10.1007/s00391-012-0404-5 10.1109/TBME.2014.2367038 10.1109/TITB.2011.2171704 10.1155/2016/2308183 10.1080/10739149.2016.1268155 10.1155/2015/192454 10.1155/2016/5747961 10.3390/s141018543 10.1109/ACCESS.2018.2789918 10.1109/TC.2013.151 10.1155/2016/7314207 10.1007/s11227-017-2082-y 10.1109/JBHI.2014.2319372 10.1109/SECON.2012.6275823 10.3390/s16081043 10.1007/s00779-010-0292-x 10.1007/s11277-015-2362-x 10.1109/TSMCC.2010.2049649 10.3390/ijerph110404233 10.1007/978-3-642-37484-5 10.1109/ACCESS.2017.2716359 10.1016/j.neucom.2011.09.037 10.3390/s16081161
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References	Barshan (ref_29) 2014; 14 ref_13 Charlon (ref_34) 2013; 40 ref_10 Huynh (ref_38) 2015; 2015 ref_98 ref_97 ref_95 Luque (ref_40) 2014; 14 Gharghan (ref_71) 2017; 12 ref_18 ref_15 Kulkarni (ref_104) 2010; 40 Kumar (ref_107) 2016; 8 Ozcan (ref_89) 2017; 47 Ndzi (ref_58) 2014; 105 Rescio (ref_31) 2013; 2013 Chen (ref_3) 2013; 2013 ref_23 ref_120 ref_121 Zaidi (ref_20) 2016; 5 Chen (ref_28) 2012; 16 Yu (ref_52) 2013; 17 ref_26 Su (ref_54) 2015; 62 Abbate (ref_47) 2012; 8 Kukolj (ref_65) 2004; 34 ref_72 ref_70 Cotuk (ref_62) 2014; 63 Liang (ref_115) 2014; 19 Gharghan (ref_21) 2016; 2016 ref_78 Pal (ref_19) 2010; 2 ref_75 ref_73 Amin (ref_1) 2016; 33 Xu (ref_14) 2014; 18 Habib (ref_45) 2014; 14 Li (ref_105) 2013; 117 ref_83 Gibson (ref_81) 2016; 39 Mi (ref_16) 2012; 10 ref_88 Wang (ref_69) 2016; 12 ref_87 Chen (ref_93) 2017; 45 ref_86 Kumar (ref_66) 2014; 39 ref_85 Zhu (ref_99) 2017; 5 Kwolek (ref_80) 2016; 40 Bian (ref_51) 2015; 19 ref_50 Liu (ref_17) 2012; 60 (ref_96) 2017; 34 Zhao (ref_106) 2015; 11 Cheng (ref_27) 2013; 17 Xu (ref_60) 2010; 2 Benocci (ref_24) 2010; 41 Wu (ref_111) 2018; 7 ref_59 Wang (ref_22) 2015; 5 Zhao (ref_42) 2012; 10 Sokolova (ref_57) 2013; 2013 Gharghan (ref_63) 2016; 16 Payal (ref_64) 2015; 82 Jun (ref_110) 2016; 9 Wang (ref_25) 2016; 62 Kianoush (ref_101) 2017; 4 ref_68 ref_67 Wang (ref_92) 2017; 16 Majumder (ref_43) 2014; 14 Permpol (ref_113) 2016; 29 Aziz (ref_100) 2017; 55 Chen (ref_79) 2016; 44 Dai (ref_44) 2010; 14 ref_114 ref_117 ref_116 ref_119 Wang (ref_74) 2017; 16 ref_36 ref_35 ref_33 Ismail (ref_94) 2017; 32 Felisberto (ref_30) 2015; 2015 ref_112 Mubashir (ref_12) 2013; 100 ref_39 Hakim (ref_84) 2017; 105 Lim (ref_32) 2014; 2014 ref_37 Huang (ref_49) 2011; 5 Delahoz (ref_11) 2014; 14 Fang (ref_82) 2017; 84 Garripoli (ref_56) 2015; 19 Shojafar (ref_7) 2017; 73 Huang (ref_76) 2014; 11 ref_103 Yang (ref_8) 2016; 2 ref_108 Nizam (ref_91) 2017; 105 ref_109 Hausdorff (ref_90) 2017; 55 Naranjo (ref_4) 2017; 73 Saleh (ref_5) 2018; 6 ref_41 ref_102 Zhang (ref_77) 2014; 17 ref_2 ref_48 ref_9 Ozcan (ref_53) 2013; 3 Sarker (ref_118) 2018; 56 Mellone (ref_46) 2012; 45 Sahu (ref_61) 2013; 13 ref_6 Sachs (ref_55) 2015; 9
References_xml	– volume: 105 start-page: 83 year: 2014 ident: ref_58 article-title: Wireless sensor network coverage measurement and planning in mixed crop farming publication-title: Comput. Electron. Agric. doi: 10.1016/j.compag.2014.04.012 – volume: 29 start-page: 17 year: 2016 ident: ref_113 article-title: Soft computing-based localizations in wireless sensor networks publication-title: Pervasive Mob. Comput. doi: 10.1016/j.pmcj.2015.06.010 – ident: ref_39 – ident: ref_78 doi: 10.1007/978-3-319-50212-0 – ident: ref_98 doi: 10.3390/s17010198 – ident: ref_86 doi: 10.1109/RADAR.2017.7944316 – volume: 34 start-page: 3 year: 2017 ident: ref_96 article-title: Mobile activity recognition and fall detection system for elderly people using ameva algorithm publication-title: Pervasive Mob. Comput. doi: 10.1016/j.pmcj.2016.05.002 – ident: ref_41 doi: 10.1109/UIC-ATC.2010.44 – volume: 11 start-page: 9 year: 2015 ident: ref_106 article-title: Amorphous localization algorithm based on BP artificial neural network publication-title: Int. J. Distrib. Sens. Netw. doi: 10.1155/2015/657241 – ident: ref_108 – volume: 2015 start-page: 452078 year: 2015 ident: ref_38 article-title: Optimization of an accelerometer and gyroscope-based fall detection algorithm publication-title: J. Sens. doi: 10.1155/2015/452078 – volume: 16 start-page: 581 year: 2017 ident: ref_92 article-title: Wifall: Device-free fall detection by wireless networks publication-title: IEEE Trans. Mob. Comput. doi: 10.1109/TMC.2016.2557792 – volume: 40 start-page: 7316 year: 2013 ident: ref_34 article-title: Design and evaluation of a device worn for fall detection and localization: Application for the continuous monitoring of risks incurred by dependents in an alzheimer’s care unit publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2013.07.031 – volume: 13 start-page: 3115 year: 2013 ident: ref_61 article-title: Durt: Dual RSSI trend based localization for wireless sensor networks publication-title: IEEE Sens. J. doi: 10.1109/JSEN.2013.2257731 – volume: 40 start-page: 305 year: 2016 ident: ref_80 article-title: Fuzzy inference-based fall detection using kinect and body-worn accelerometer publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.11.031 – ident: ref_50 doi: 10.1155/2015/576364 – volume: 5 start-page: 1 year: 2015 ident: ref_22 article-title: Low-power technologies for wearable telecare and telehealth systems: A review publication-title: Biomed. Eng. Lett. doi: 10.1007/s13534-015-0174-2 – volume: 4 start-page: 351 year: 2017 ident: ref_101 article-title: Device-free rf human body fall detection and localization in industrial workplaces publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2016.2624800 – ident: ref_13 doi: 10.1109/ISMICT.2012.6203028 – volume: 2 start-page: 606 year: 2010 ident: ref_60 article-title: Distance measurement model based on RSSI in WSN publication-title: Wirel. Sens. Netw. doi: 10.4236/wsn.2010.28072 – volume: 16 start-page: 511 year: 2017 ident: ref_74 article-title: Rt-fall: A real-time and contactless fall detection system with commodity wifi devices publication-title: IEEE Trans. Mob. Comput. doi: 10.1109/TMC.2016.2557795 – ident: ref_70 doi: 10.3390/s150511741 – volume: 105 start-page: 131 year: 2017 ident: ref_91 article-title: Human fall detection from depth images using position and velocity of subject publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2017.01.191 – volume: 62 start-page: 128 year: 2016 ident: ref_25 article-title: An outdoor intelligent healthcare monitoring device for the elderly publication-title: IEEE Trans. Consum. Electron. doi: 10.1109/TCE.2016.7514671 – volume: 3 start-page: 125 year: 2013 ident: ref_53 article-title: Automatic fall detection and activity classification by a wearable embedded smart camera publication-title: IEEE J. Emerg. Sel. Top. Circuits Syst. doi: 10.1109/JETCAS.2013.2256832 – ident: ref_83 doi: 10.1007/978-981-10-3023-9 – volume: 2013 start-page: 217286 year: 2013 ident: ref_3 article-title: Implementation of fall detection and localized caring system publication-title: Math. Probl. Eng. – ident: ref_116 doi: 10.3390/s17010176 – volume: 14 start-page: 19806 year: 2014 ident: ref_11 article-title: Survey on fall detection and fall prevention using wearable and external sensors publication-title: Sensors doi: 10.3390/s141019806 – volume: 32 start-page: 356 year: 2017 ident: ref_94 article-title: Automatic fall detection using membership based histogram descriptors publication-title: J. Comput. Sci. Technol. doi: 10.1007/s11390-017-1725-z – ident: ref_97 – ident: ref_102 doi: 10.1007/s10044-017-0660-5 – volume: 7 start-page: 19 year: 2018 ident: ref_111 article-title: Rfid 3D-landmarc localization algorithm based on quantum particle swarm optimization publication-title: Electronics doi: 10.3390/electronics7020019 – ident: ref_103 doi: 10.3390/s17020307 – ident: ref_112 doi: 10.1109/ICCASE.2011.5997582 – volume: 60 start-page: 4350 year: 2012 ident: ref_17 article-title: Distributed, robust acoustic source localization in a wireless sensor network publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2012.2199314 – volume: 17 start-page: 1002 year: 2013 ident: ref_52 article-title: An online one class support vector machine-based person-specific fall detection system for monitoring an elderly individual in a room environment publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/JBHI.2013.2274479 – volume: 84 start-page: 214 year: 2017 ident: ref_82 article-title: Accelerometer-based fall-portent detection algorithm for construction tiling operation publication-title: Autom. Constr. doi: 10.1016/j.autcon.2017.09.015 – volume: 5 start-page: 504 year: 2016 ident: ref_20 article-title: Robust anns-based wsn localization in the presence of anisotropic signal attenuation publication-title: IEEE Wirel. Commun. Lett. doi: 10.1109/LWC.2016.2595576 – volume: 19 start-page: 92 year: 2015 ident: ref_56 article-title: Embedded dsp-based telehealth radar system for remote in-door fall detection publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/JBHI.2014.2361252 – volume: 2 start-page: 45 year: 2010 ident: ref_19 article-title: Localization algorithms in wireless sensor networks: Current approaches and future challenges publication-title: Netw. Protoc. Algorithms – ident: ref_2 doi: 10.3390/s16040546 – ident: ref_10 doi: 10.1109/DATE.2010.5457055 – volume: 2013 start-page: 254629 year: 2013 ident: ref_31 article-title: Supervised expert system for wearable mems accelerometer-based fall detector publication-title: J. Sens. doi: 10.1155/2013/254629 – ident: ref_120 doi: 10.1145/2248341.2248349 – ident: ref_73 doi: 10.1371/journal.pone.0180318 – ident: ref_68 doi: 10.3390/s17061393 – ident: ref_88 doi: 10.3390/app7040316 – volume: 10 start-page: 617 year: 2012 ident: ref_42 article-title: Fallalarm: Smart phone based fall detecting and positioning system publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2012.06.079 – volume: 33 start-page: 71 year: 2016 ident: ref_1 article-title: Radar signal processing for elderly fall detection: The future for in-home monitoring publication-title: IEEE Signal Process. Mag. doi: 10.1109/MSP.2015.2502784 – volume: 5 start-page: 58 year: 2011 ident: ref_49 article-title: Zigbee-based indoor location system by k-nearest neighbor algorithm with weighted rssi publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2011.07.010 – volume: 12 start-page: 433 year: 2017 ident: ref_71 article-title: Energy-efficient remote temperature monitoring system for patients based on GSM modem and microcontroller publication-title: J. Commun. – volume: 44 start-page: 333 year: 2016 ident: ref_79 article-title: Accelerometer-based fall detection using feature extraction and support vector machine algorithms publication-title: Instrum. Sci. Technol. doi: 10.1080/10739149.2015.1123161 – volume: 34 start-page: 272 year: 2004 ident: ref_65 article-title: Identification of complex systems based on neural and takagi-sugeno fuzzy model publication-title: IEEE Trans. Syst. Man Cybern. Part B Cybern. doi: 10.1109/TSMCB.2003.811119 – volume: 14 start-page: 41 year: 2014 ident: ref_43 article-title: A multi-sensor approach for fall risk prediction and prevention in elderly publication-title: ACM SIGAPP Appl. Comput. Rev. doi: 10.1145/2600617.2600621 – ident: ref_67 doi: 10.1109/ICOIN.2012.6164365 – ident: ref_109 doi: 10.1109/ICDMIC.2014.6954228 – volume: 9 start-page: 1323 year: 2016 ident: ref_110 article-title: A novel hybrid localization method for wireless sensor network publication-title: Int. J. Smart Sens. Intell. Syst. – ident: ref_85 doi: 10.1007/s11276-017-1557-3 – volume: 9 start-page: 125 year: 2015 ident: ref_55 article-title: M-sequence-based ultra-wideband sensor network for vitality monitoring of elders at home publication-title: IET Radar Sonar Navig. doi: 10.1049/iet-rsn.2014.0214 – volume: 55 start-page: 6 year: 2017 ident: ref_90 article-title: Concurrent validation of an index to estimate fall risk in community dwelling seniors through a wireless sensor insole system: A pilot study publication-title: Gait Posture doi: 10.1016/j.gaitpost.2017.03.037 – volume: 47 start-page: 31 year: 2017 ident: ref_89 article-title: Autonomous fall detection with wearable cameras by using relative entropy distance measure publication-title: IEEE Trans. Hum.-Mach. Syst. – volume: 10 start-page: 946 year: 2012 ident: ref_16 article-title: Practical and secure localization and key distribution for wireless sensor networks publication-title: Ad Hoc Netw. doi: 10.1016/j.adhoc.2011.12.008 – ident: ref_9 doi: 10.3390/s150923004 – ident: ref_23 doi: 10.17485/ijst/2017/v10i5/111274 – ident: ref_114 doi: 10.3390/s17020341 – volume: 12 start-page: 2302 year: 2016 ident: ref_69 article-title: Low-power fall detector using triaxial accelerometry and barometric pressure sensing publication-title: IEEE Trans. Ind. Inform. doi: 10.1109/TII.2016.2587761 – volume: 73 start-page: 733 year: 2017 ident: ref_4 article-title: P-sep: A prolong stable election routing algorithm for energy-limited heterogeneous fog-supported wireless sensor networks publication-title: J. Supercomput. doi: 10.1007/s11227-016-1785-9 – volume: 18 start-page: 1055 year: 2014 ident: ref_14 article-title: Rss-based source localization when path-loss model parameters are unknown publication-title: IEEE Commun. Lett. doi: 10.1109/LCOMM.2014.2318031 – volume: 117 start-page: 72 year: 2013 ident: ref_105 article-title: A dynamic neural network approach for solving nonlinear inequalities defined on a graph and its application to distributed, routing-free, range-free localization of wsns publication-title: Neurocomputing doi: 10.1016/j.neucom.2013.01.032 – ident: ref_6 doi: 10.1016/j.jpdc.2018.07.003 – volume: 2014 start-page: 896030 year: 2014 ident: ref_32 article-title: Fall-detection algorithm using 3-axis acceleration: Combination with simple threshold and hidden markov model publication-title: J. Appl. Math. doi: 10.1155/2014/896030 – ident: ref_117 doi: 10.1007/978-3-319-59060-8 – ident: ref_15 doi: 10.1155/2015/195297 – volume: 16 start-page: 529 year: 2016 ident: ref_63 article-title: Accurate wireless sensor localization technique based on hybrid PSO-ANN algorithm for indoor and outdoor track cycling publication-title: IEEE Sens. J. doi: 10.1109/JSEN.2015.2483745 – volume: 8 start-page: 61 year: 2016 ident: ref_107 article-title: Localization for wireless sensor networks: A neural network approach publication-title: Int. J. Comput. Networks Commun. doi: 10.5121/ijcnc.2016.8105 – volume: 8 start-page: 883 year: 2012 ident: ref_47 article-title: A smartphone-based fall detection system publication-title: Pervasive Mob. Comput. doi: 10.1016/j.pmcj.2012.08.003 – volume: 14 start-page: 10691 year: 2014 ident: ref_29 article-title: Detecting falls with wearable sensors using machine learning techniques publication-title: Sensors doi: 10.3390/s140610691 – volume: 56 start-page: 34 year: 2018 ident: ref_118 article-title: Energy efficient wearable sensor node for IoT-based fall detection systems publication-title: Microprocess. Microsyst. doi: 10.1016/j.micpro.2017.10.014 – volume: 19 start-page: 303 year: 2014 ident: ref_115 article-title: Energy-efficient motion related activity recognition on mobile devices for pervasive healthcare publication-title: Mob. Netw. Appl. doi: 10.1007/s11036-013-0448-9 – volume: 17 start-page: 38 year: 2013 ident: ref_27 article-title: A framework for daily activity monitoring and fall detection based on surface electromyography and accelerometer signals publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/TITB.2012.2226905 – volume: 41 start-page: 703 year: 2010 ident: ref_24 article-title: Accelerometer-based fall detection using optimized zigbee data streaming publication-title: Microelectron. J. doi: 10.1016/j.mejo.2010.06.014 – volume: 39 start-page: 94 year: 2016 ident: ref_81 article-title: Multiple comparator classifier framework for accelerometer-based fall detection and diagnostic publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.10.062 – volume: 55 start-page: 45 year: 2017 ident: ref_100 article-title: A comparison of accuracy of fall detection algorithms (threshold-based vs. Machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials publication-title: Med. Biol. Eng. Comput. doi: 10.1007/s11517-016-1504-y – ident: ref_87 – ident: ref_95 doi: 10.1117/12.2257902 – ident: ref_48 doi: 10.3390/s16010117 – volume: 2013 start-page: 935026 year: 2013 ident: ref_57 article-title: Lateral inhibition in accumulative computation and fuzzy sets for human fall pattern recognition in colour and infrared imagery publication-title: Sci. World J. doi: 10.1155/2013/935026 – ident: ref_59 doi: 10.3390/s17081781 – ident: ref_72 – volume: 17 start-page: 711 year: 2014 ident: ref_77 article-title: A smartphone based real-time daily activity monitoring system publication-title: Clust. Comput. doi: 10.1007/s10586-013-0335-y – volume: 2 start-page: 24 year: 2016 ident: ref_8 article-title: 3D depth image analysis for indoor fall detection of elderly people publication-title: Digit. Commun. Netw. doi: 10.1016/j.dcan.2015.12.001 – volume: 105 start-page: 46 year: 2017 ident: ref_84 article-title: Smartphone based data mining for fall detection: Analysis and design publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2017.01.188 – volume: 14 start-page: 7181 year: 2014 ident: ref_45 article-title: Smartphone-based solutions for fall detection and prevention: Challenges and open issues publication-title: Sensors doi: 10.3390/s140407181 – ident: ref_121 doi: 10.1109/ICIT.2017.7915565 – volume: 45 start-page: 722 year: 2012 ident: ref_46 article-title: Smartphone-based solutions for fall detection and prevention: The farseeing approach publication-title: Z. Gerontol. Geriatr. doi: 10.1007/s00391-012-0404-5 – volume: 62 start-page: 865 year: 2015 ident: ref_54 article-title: Doppler radar fall activity detection using the wavelet transform publication-title: IEEE Trans. Biomed. Eng. doi: 10.1109/TBME.2014.2367038 – volume: 39 start-page: 820 year: 2014 ident: ref_66 article-title: Localization estimation using artificial intelligence technique in wireless sensor networks publication-title: J. Korea Inf. Commun. Soc. – volume: 16 start-page: 6 year: 2012 ident: ref_28 article-title: A reliable transmission protocol for zigbee-based wireless patient monitoring publication-title: IEEE Trans. Inf. Technol. Biomed. doi: 10.1109/TITB.2011.2171704 – ident: ref_35 doi: 10.1155/2016/2308183 – volume: 45 start-page: 382 year: 2017 ident: ref_93 article-title: Enhanced characterization of an accelerometer-based fall detection algorithm using a repository publication-title: Instrum. Sci. Technol. doi: 10.1080/10739149.2016.1268155 – volume: 2015 start-page: 192454 year: 2015 ident: ref_30 article-title: A distributed multiagent system architecture for body area networks applied to healthcare monitoring publication-title: BioMed Res. Int. doi: 10.1155/2015/192454 – ident: ref_36 doi: 10.1155/2016/5747961 – ident: ref_37 – ident: ref_18 – volume: 14 start-page: 18543 year: 2014 ident: ref_40 article-title: Comparison and characterization of android-based fall detection systems publication-title: Sensors doi: 10.3390/s141018543 – volume: 6 start-page: 6478 year: 2018 ident: ref_5 article-title: Energy-efficient architecture for wireless sensor networks in healthcare applications publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2789918 – volume: 63 start-page: 2866 year: 2014 ident: ref_62 article-title: The impact of transmission power control strategies on lifetime of wireless sensor networks publication-title: IEEE Trans. Comput. doi: 10.1109/TC.2013.151 – volume: 2016 start-page: 7314207 year: 2016 ident: ref_21 article-title: Energy efficiency of ultra-low-power bicycle wireless sensor networks based on a combination of power reduction techniques publication-title: J. Sens. doi: 10.1155/2016/7314207 – volume: 73 start-page: 5239 year: 2017 ident: ref_7 article-title: Flaps: Bandwidth and delay-efficient distributed data searching in fog-supported p2p content delivery networks publication-title: J. Supercomput. doi: 10.1007/s11227-017-2082-y – volume: 19 start-page: 430 year: 2015 ident: ref_51 article-title: Fall detection based on body part tracking using a depth camera publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/JBHI.2014.2319372 – ident: ref_119 doi: 10.1109/SECON.2012.6275823 – ident: ref_26 doi: 10.3390/s16081043 – volume: 14 start-page: 633 year: 2010 ident: ref_44 article-title: Mobile phone-based pervasive fall detection publication-title: Pers. Ubiquitous Comput. doi: 10.1007/s00779-010-0292-x – volume: 82 start-page: 2519 year: 2015 ident: ref_64 article-title: Analysis of some feedforward artificial neural network training algorithms for developing localization framework in wireless sensor networks publication-title: Wirel. Pers. Commun. doi: 10.1007/s11277-015-2362-x – volume: 40 start-page: 663 year: 2010 ident: ref_104 article-title: Bio-inspired algorithms for autonomous deployment and localization of sensor nodes publication-title: IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) doi: 10.1109/TSMCC.2010.2049649 – volume: 11 start-page: 4233 year: 2014 ident: ref_76 article-title: A zigbee-based location-aware fall detection system for improving elderly telecare publication-title: Int. J. Environ. Res. Public Health doi: 10.3390/ijerph110404233 – ident: ref_75 doi: 10.1007/978-3-642-37484-5 – volume: 5 start-page: 11364 year: 2017 ident: ref_99 article-title: Tagcare: Using rfids to monitor the status of the elderly living alone publication-title: IEEE Access doi: 10.1109/ACCESS.2017.2716359 – volume: 100 start-page: 144 year: 2013 ident: ref_12 article-title: A survey on fall detection: Principles and approaches publication-title: Neurocomputing doi: 10.1016/j.neucom.2011.09.037 – ident: ref_33 doi: 10.3390/s16081161
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Snippet	Falls are the main source of injury for elderly patients with epilepsy and Parkinson’s disease. Elderly people who carry battery powered health monitoring... The degree of danger from a fall for aging persons is frequently decided by the location of the fall, time of fall detection, duration and time of transfer and...
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SubjectTerms	accelerometer sensor Accelerometers Accuracy Blood pressure Cameras data-driven algorithm Engineering fall detection Global positioning systems GPS Health care International conferences Localization Methods neural network Neural networks Older people Sensors tilt sensor Wireless networks wireless sensor network (WSN) ZigBee
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Title	Accurate Fall Detection and Localization for Elderly People Based on Neural Network and Energy-Efficient Wireless Sensor Network
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