Wearable Sensor Systems for Fall Risk Assessment: A Review

被引:44
|
作者
Subramaniam, Sophini [1 ]
Faisal, Abu Ilius [2 ]
Deen, M. Jamal [1 ,2 ]
机构
[1] McMaster Univ, Sch Biomed Engn, Hamilton, ON, Canada
[2] McMaster Univ, Elect & Comp Engn, Hamilton, ON, Canada
来源
基金
加拿大自然科学与工程研究理事会;
关键词
fall risk assessment; fall detection; wearables; smart insole; inertial sensors; plantar pressure; gait analysis; machine learning; BERG BALANCE SCALE; HEALTH-CARE; GAIT; STABILITY; PARAMETERS; ALGORITHM; NETWORK; WALKING; PEOPLE;
D O I
10.3389/fdgth.2022.921506
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Fall risk assessment and fall detection are crucial for the prevention of adverse and long-term health outcomes. Wearable sensor systems have been used to assess fall risk and detect falls while providing additional meaningful information regarding gait characteristics. Commonly used wearable systems for this purpose are inertial measurement units (IMUs), which acquire data from accelerometers and gyroscopes. IMUs can be placed at various locations on the body to acquire motion data that can be further analyzed and interpreted. Insole-based devices are wearable systems that were also developed for fall risk assessment and fall detection. Insole-based systems are placed beneath the sole of the foot and typically obtain plantar pressure distribution data. Fall-related parameters have been investigated using inertial sensor-based and insole-based devices include, but are not limited to, center of pressure trajectory, postural stability, plantar pressure distribution and gait characteristics such as cadence, step length, single/double support ratio and stance/swing phase duration. The acquired data from inertial and insole-based systems can undergo various analysis techniques to provide meaningful information regarding an individual's fall risk or fall status. By assessing the merits and limitations of existing systems, future wearable sensors can be improved to allow for more accurate and convenient fall risk assessment. This article reviews inertial sensor-based and insole-based wearable devices that were developed for applications related to falls. This review identifies key points including spatiotemporal parameters, biomechanical gait parameters, physical activities and data analysis methods pertaining to recently developed systems, current challenges, and future perspectives.
引用
收藏
页数:20
相关论文
共 50 条
  • [21] Wearable Inertial Sensors for Fall Risk Assessment and Prediction in Older Adults: A Systematic Review and Meta-Analysis
    Montesinos, Luis
    Castaldo, Rossana
    Pecchia, Leandro
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2018, 26 (03) : 573 - 582
  • [22] A review of wearable sensors based fall-related recognition systems
    Liu, Jiawei
    Li, Xiaohu
    Huang, Shanshan
    Chao, Rui
    Cao, Zhidong
    Wang, Shu
    Wang, Aiguo
    Liu, Li
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2023, 121
  • [23] Revisiting sensor-based intelligent fall risk assessment for older people: A systematic review
    Yu, Xiaoqun
    Cai, Yuqing
    Yang, Rong
    Ma, Fengling
    Kim, Woojoo
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2025, 144
  • [24] Sensor-based fall detection systems: a review
    Sheikh Nooruddin
    Md. Milon Islam
    Falguni Ahmed Sharna
    Husam Alhetari
    Muhammad Nomani Kabir
    Journal of Ambient Intelligence and Humanized Computing, 2022, 13 : 2735 - 2751
  • [25] Sensor-based fall detection systems: a review
    Nooruddin, Sheikh
    Islam, Md Milon
    Sharna, Falguni Ahmed
    Alhetari, Husam
    Kabir, Muhammad Nomani
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 13 (5) : 2735 - 2751
  • [26] Quantitative Analysis of the Fall-Risk Assessment Test with Wearable Inertia Sensors
    Tmaura, Toshiyo
    Zakaria, Nor Aini
    Kuwae, Yutaka
    Sekine, Masaki
    Minato, Kotaro
    Yoshida, Masaki
    2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2013, : 7217 - 7220
  • [27] OBJECTIVE ASSESSMENT OF FALL RISK IN HOSPITALIZED OLDER ADULTS USING WEARABLE TECHNOLOGY
    Razjouyan, J.
    Grewal, G.
    Rishel, C.
    Parthasarathy, S.
    Mohler, M. J.
    Najafi, B.
    GERONTOLOGIST, 2015, 55 : 471 - 471
  • [28] Assessing fall risk using wearable sensors: a practical discussion A review of the practicalities and challenges associated with the use of wearable sensors for quantification of fall risk in older people
    Shany, T.
    Redmond, S. J.
    Marschollek, M.
    Lovell, N. H.
    ZEITSCHRIFT FUR GERONTOLOGIE UND GERIATRIE, 2012, 45 (08): : 694 - 704
  • [29] In-Home Fall Risk Assessment and Detection Sensor System
    Rantz, Marilyn J.
    Skubic, Marjorie
    Abbott, Carmen
    Galambos, Colleen
    Pak, Youngju
    Ho, Dominic K. C.
    Stone, Erik E.
    Rui, Liyang
    Back, Jessica
    Miller, Steven J.
    JOURNAL OF GERONTOLOGICAL NURSING, 2013, 39 (07): : 18 - 22
  • [30] Sensor-based Fall Risk Assessment - an Expert 'to go'
    Marschollek, M.
    Rehwald, A.
    Wolf, K. H.
    Gietzelt, M.
    Nemitz, G.
    Schwabedissen, H. Meyer Zu
    Haux, R.
    METHODS OF INFORMATION IN MEDICINE, 2011, 50 (05) : 420 - 426