This document discusses using wearable technologies to detect and prevent falls in elderly persons. It proposes using RFID tags strapped to a user's belt to detect falls based on changes in received signal strength or power delay profile when a fall occurs. It also suggests monitoring brain signals before, during, and after a fall using EEG and ECG to gain health insights and potentially prevent falls by identifying pre-fall conditions. Overall, the document examines technical approaches for fall detection using wearable sensors and neural monitoring to address the important issue of falls among elderly populations.

1. Fall detection and prevention in elderly
persons using wearable technologies
Reinhardt Rading
Feb 2020

2. Introduction
What is a fall?
Causes of a fall?
What are the consequences of a fall?

3. Introduction continued
https://www.youtube.com/w
atch?v=1IsM08Sh_wg

4. Problem Statement
How do we detect a fall?
How can we prevent a fall from
happening?

5. Fall detection- Proposed Solution
Using RFID tags and readers
Tags strapped onto the users’ belt
RFID tag
3.2mmx0.7mm

6. Fall detection- Possible Solution
Based on the concept of RSSI as in
wireless communication
Tags strapped onto the users’ belt
Delay in received signals is likely as a
result of a fall

7. Fall detection- Possible Solution
Further enhanced by using power delay profile.
Total average power 𝑃2 = 𝜇2 + 2𝛿2 = 𝐸 𝑓(𝑡) 2
Where 𝜇2 is power received by line of sight
2𝛿2
is power received by scattering
𝑃𝑡2
=
𝑙=0
𝑙
𝑃2
Fraction of power =
𝑃2
𝑃𝑡2

8. Fall Prevention – proposed solution
When we fall, a brain signal is produced
What if we monitor a patient pre-fall,
during, and post-fall using the generated
signals-EEG,ECG?
Rich information healthwise, i.e. breathing
rate, temperature

9. Fall Prevention – proposed solution

10. Future improvements?
Work still on course
??