Unobtrusive monitoring and identification of fall accidents

被引:12
|
作者
van de Ven, Pepijn [1 ]
O'Brien, Hugh [1 ]
Nelson, John [1 ]
Clifford, Amanda [2 ]
机构
[1] Univ Limerick, Dept Elect & Comp Engn, Limerick, Ireland
[2] Univ Limerick, Dept Clin Therapies, Limerick, Ireland
关键词
Fall sensing; Falls prevention; Accelerometry; Ambient assisted living; Mobile health; PEOPLE;
D O I
10.1016/j.medengphy.2015.02.009
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Falls are a societal and economic problem of great concern with large parts of the population, in particular older citizens, at significant risk and the result of a fall often being grave. It has long been established that it is of importance to provide help to a faller soon after the event to prevent complications and this can be achieved with a fall monitor. Yet, the practical use of currently available fall monitoring solutions is limited due to accuracy, usability, cost, and, not in the least, the stigmatising effect of many solutions. This paper proposes a fall sensor concept that can be embedded in the user's footwear and discusses algorithms, software and hardware developed. Sensor performance is illustrated using results of a series of functional tests. These show that the developed sensor can be used for the accurate measurement of various mobility and gait parameters and that falls are detected accurately. (C) 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:499 / 504
页数:6
相关论文
共 50 条
  • [41] EVALUATION OF HOME ACCIDENTS AND FALL BEHAVIORS OF ELDERLY
    Sahin, Hande
    Erkal, Sibel
    TURKISH JOURNAL OF GERIATRICS-TURK GERIATRI DERGISI, 2016, 19 (03): : 195 - 201
  • [42] Dual Architecture Platform for Unobtrusive Wheelchair User Monitoring
    Pinheiro, Eduardo C.
    Postolache, Octavian A.
    Girao, Pedro Silva
    2013 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS PROCEEDINGS (MEMEA), 2013, : 124 - 129
  • [43] Ballistocardiogram: Mechanism and Potential for Unobtrusive Cardiovascular Health Monitoring
    Chang-Sei Kim
    Stephanie L. Ober
    M. Sean McMurtry
    Barry A. Finegan
    Omer T. Inan
    Ramakrishna Mukkamala
    Jin-Oh Hahn
    Scientific Reports, 6
  • [44] Driving Behavior Monitoring with Unobtrusive Smart-glasses
    Huang, Hua
    Hoskeri, Rahul Sidramappa
    Sun, Yangqing
    PROCEEDINGS OF THE 2023 THE 22ND INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS, IPSN 2023, 2023, : 328 - 329
  • [45] Unobtrusive computer monitoring of sensory-motor function
    Jimison, H. B.
    Pavel, M.
    McKanna, J.
    2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 5431 - 5434
  • [46] Sleep Monitoring Classification Strategy for an Unobtrusive EEG System
    Gialelis, J.
    Panagiotou, C.
    karadimas, D.
    Samaras, I.
    Chondros, P.
    Serpanos, D.
    Koubias, S.
    2015 4TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO), 2015, : 402 - 406
  • [47] Ballistocardiogram: Mechanism and Potential for Unobtrusive Cardiovascular Health Monitoring
    Kim, Chang-Sei
    Ober, Stephanie L.
    McMurtry, M. Sean
    Finegan, Barry A.
    Inan, Omer T.
    Mukkamala, Ramakrishna
    Hahn, Jin-Oh
    SCIENTIFIC REPORTS, 2016, 6
  • [48] Evaluation of Capacitive ECG for Unobtrusive Atrial Fibrillation Monitoring
    Zhang, Winston
    Li, Zhi
    Gryak, Jonathan
    Gunaratne, Pujitha
    Wittrup, Emily
    Najarian, Kayvan
    IEEE SENSORS LETTERS, 2023, 7 (10)
  • [49] Unobtrusive Health Monitoring in Private Spaces: The Smart Vehicle
    Wang, Ju
    Warnecke, Joana M.
    Haghi, Mostafa
    Deserno, Thomas M.
    SENSORS, 2020, 20 (09)
  • [50] Trends of Fall Accidents in the US Construction Industry
    Kang, Youngcheol
    Siddiqui, Sohaib
    Suk, Sung Joon
    Chi, Seokho
    Kim, Changwan
    JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2017, 143 (08)