http://iet.metastore.ingenta.com
1887

Fall prevention and detection

Fall prevention and detection

For access to this article, please select a purchase option:

Buy chapter PDF
$16.00
(plus tax if applicable)
Buy Knowledge Pack
10 chapters for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Active and Assisted Living: Technologies and Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In both research and clinical settings a fall incident is commonly defined as unintentionally coming to rest on the ground, floor, or other lower level. Such a fall incident is experienced at least once a year by approximately one in three adults older than 65. This number increases with age and frailty level. Yearly, 37.3 million fall incidents have physiological consequences. Additionally, psychological consequences, such as loss of mobility and independence often restrict the ability of older adults to perform daily activities. By detecting when a person has an elevated fall risk, and taking preventive measures when necessary, the number of fall incidents can be reduced. The first part of this chapter will therefore focus on automatic fall risk assessment techniques. Following this, the second part focuses on fall detection systems. As not all fall incidents can be prevented these systems can reduce the consequences of a fall incident by ensuring that timely aid is given.

Chapter Contents:

  • 11.1 Introduction
  • 11.2 Fall risk estimation
  • 11.2.1 Using gait parameters to automatically assess the fall risk of a person
  • 11.2.2 Sensors which measure fall risk-related parameters
  • 11.2.2.1 Monitoring gait velocity using video cameras
  • 11.2.2.2 Assessing temporal and spatial gait parameters through footstep detection algorithms using audio nodes
  • 11.2.2.3 Measuring activity levels with PIR sensors
  • 11.2.2.4 Other sensors
  • 11.2.3 Closing the loop
  • 11.2.3.1 Data visualisation
  • 11.2.3.2 Automatic data interpretation
  • 11.3 Fall detection
  • 11.3.1 Accelerometer-based fall detection systems
  • 11.3.2 Radar-based fall detection
  • 11.3.3 Video-based fall detection
  • 11.3.4 Kinect-based fall detection
  • 11.4 Conclusion
  • References

Inspec keywords: biomechanics; geriatrics; risk management; accident prevention; injuries

Other keywords: fall prevention; psychological consequences; timely aid; clinical settings; older adults; fall detection; fall incident; automatic fall risk assessment techniques; frailty level; physiological consequences

Subjects: Patient care and treatment; Physics of body movements

Preview this chapter:
Zoom in
Zoomout

Fall prevention and detection, Page 1 of 2

| /docserver/preview/fulltext/books/he/pbhe006e/PBHE006E_ch11-1.gif /docserver/preview/fulltext/books/he/pbhe006e/PBHE006E_ch11-2.gif

Related content

content/books/10.1049/pbhe006e_ch11
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address