Sudden Fall Detection and Protection for Epileptic Seizures

被引:0
作者
Padma, Tatiparti [1 ]
Kumari, Ch Usha [1 ]
机构
[1] GRIET, Dept ECE, Hyderabad, India
来源
2018 INTERNATIONAL CONFERENCE ON RECENT INNOVATIONS IN ELECTRICAL, ELECTRONICS & COMMUNICATION ENGINEERING (ICRIEECE 2018) | 2018年
关键词
Accelerometer; Epilepsy; seizures; threshold; Arduino; accuracy; RISK-FACTORS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
An Epileptic Seizure is a sudden and uncontrolled symptom originated in brain. They could be due to abnormal electrical activity start in brain for very brief period and also recurring seizures due to a brain disorder. Therefore during the event there is an effect due to bumps, cuts /bruises are commonly observed occurrences. The effect of injuries are seriously caused due to falling and losing alertness or realization during or after a seizure, for instance a broken bone or injury. This project used an Arduino based airbag protection system for the people suffering from seizures by using an accelerometer, which will detect the fall of the person and triggers the airbag. A push pull solenoid is used to puncture a canister that is present in the airbag. A relay is used to operate the solenoid. When the fall is detected, the Arduino will trigger the airbag. This project helps the people who are suffering from epilepsy and protect them from injuries. This project objectives to design and development of precise system for fall detection based on Arduino technology through noticeable perfection in accuracy and specificity of system. Initial phase a close approximation and selection of its relevant threshold values and prototype design. Later Phase consist of application on test subjects to visualise the accuracy in system design.
引用
收藏
页码:2334 / 2336
页数:3
相关论文
共 13 条
[1]   Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls [J].
Bagala, Fabio ;
Becker, Clemens ;
Cappello, Angelo ;
Chiari, Lorenzo ;
Aminian, Kamiar ;
Hausdorff, Jeffrey M. ;
Zijlstra, Wiebren ;
Klenk, Jochen .
PLOS ONE, 2012, 7 (05)
[2]   Risk factors for serious fall related injury in elderly women living at home [J].
Bergland, A ;
Wyller, TB .
INJURY PREVENTION, 2004, 10 (05) :308-313
[3]   A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor [J].
Bourke, A. K. ;
Lyons, G. M. .
MEDICAL ENGINEERING & PHYSICS, 2008, 30 (01) :84-90
[4]   Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm [J].
Bourke, A. K. ;
O'Brien, J. V. ;
Lyons, G. M. .
GAIT & POSTURE, 2007, 26 (02) :194-199
[5]   Risk factors in falls among the elderly according to extrinsic and intrinsic precipitating causes [J].
Bueno-Cavanillas, A ;
Padilla-Ruiz, F ;
Jiménez-Moleón, JJ ;
Peinado-Alonso, CA ;
Gálvez-Vargas, R .
EUROPEAN JOURNAL OF EPIDEMIOLOGY, 2000, 16 (09) :849-859
[6]   Challenges, issues and trends in fall detection systems [J].
Igual, Raul ;
Medrano, Carlos ;
Plaza, Inmaculada .
BIOMEDICAL ENGINEERING ONLINE, 2013, 12
[7]   Comparison of low-complexity fall detection, algorithms for body attached accelerometers [J].
Kangas, Maarit ;
Konttila, Antti ;
Lindgren, Per ;
Winblad, Ilkka ;
Jamsa, Timo .
GAIT & POSTURE, 2008, 28 (02) :285-291
[8]   Comparison and Characterization of Android-Based Fall Detection Systems [J].
Luque, Rafael ;
Casilari, Eduardo ;
Moron, Maria-Jose ;
Redondo, Gema .
SENSORS, 2014, 14 (10) :18543-18574
[9]  
Singapore. Department of Statistics, 2006, GEN HOUS SURV 2005 R
[10]  
Tinetti M. E, 1989, RISK FACTORS FALLS E