Fall Detection on the Road Felix ix B Bs sching hing, , Henning - - PowerPoint PPT Presentation

fall detection on the road
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Fall Detection on the Road Felix ix B Bs sching hing, , Henning - - PowerPoint PPT Presentation

Platzhalter fr Bild, Bild auf Titelfolie hinter das Logo einsetzen Fall Detection on the Road Felix ix B Bs sching hing, , Henning nning P Post, Matthia hias Gietze zelt lt, , an and L Lar ars Wol olf


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Platzhalter für Bild, Bild auf Titelfolie hinter das Logo einsetzen Felix ix B Büs üsching hing, , Henning nning P Post, Matthia hias Gietze zelt lt, , an and L Lar ars Wol

  • lf

buesching@ibr.cs.tu-bs.de

Fall Detection on the Road

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Felix Büsching | Fall Detection on the Road | 2

Personal Emergency Response System (PERS)

Observed behavior 1: Normal usage

  • Works – since several years

Fall occurs Button pressed Alarm initiated

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Felix Büsching | Fall Detection on the Road | 3

Personal Emergency Response System (PERS) – Non-Usage

Observed behavior 2: Non-usage

  • Forgets to wear sender
  • Doesn’t even know where it is

No button to press No alarm Fall occurs

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Felix Büsching | Fall Detection on the Road | 4

Personal Emergency Response System (PERS) – Refused Usage

Observed behavior 3: Refused usage

  • “The mobile nursing service will come anyway – in 2-4 hours”
  • “I’ll wait here on the floor – don’t want to bother anyone”

Fall occurs Button not pressed No alarm

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Felix Büsching | Fall Detection on the Road | 5

Personal Emergency Response System (PERS) – Anxious Usage

Observed behavior 4: Anxious usage

  • “I feel safe – I better wear that thing 24/7”
  • Many false alarms during nighttime

Bad dream occurs Button accidentally pressed False Alarm

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Felix Büsching | Fall Detection on the Road | 6

Personal Emergency Response System (PERS) – Avoidance Behavior

Observed behavior 5: Avoidance behavior

  • “System works good at home.”
  • ”So, why leave it and enter the unsafe outside?!”
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Summary: Personal Emergency Response System (PERS)

1. Normal usage

  • OK, this is boring…

2. Non-usage

  • Indoors: Fixed Sensors (Cameras, Laser Scanners, etc.)

3. Refused usage

  • Additional autonomous fall detection and automatic alarm notification
  • 4. Anxious usage
  • Only autonomous fall detection and automatic alarm notification

5. Avoidance behavior

  • System that also works “on the road”

 Mobile PERS with autonomous fall detection needed… here we go!

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Some Related Work

PerFallID [1], iFall [2]

  • Systems/Applications for Android Smartphones
  • Detect falls with built in sensors
  • Report falls via 2/3/4G connection
  • Additional location information via GPS

Everybody owns a smartphone!

  • Enough processing capabilities for fall detection
  • Communication interfaces for alarm messages

Problem solved?!

[1] J. Dai, X. Bai, Z. Yang, Z. Shen, and D. Xuan, “Mobile phone-based pervasive fall detection,” Personal and Ubiquitous Computing,

  • vol. 14, no. 7, pp. 633–643, 2010.

[2] F. Sposaro and G. Tyson, “ifall: An android application for fall monitoring and response,” in Engineering in Medicine and Biology Society,2009. EMBC 2009. Annual International Conference of the IEEE, 2009.

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Limitations of Smartphones

Position on the body

  • Pocket
  • Jacket
  • Handbag

Battery Lifetime – HTC Dream

  • PerFallID: 33.5 hours
  • Idle time: 402 hours (according to HTC)
  •  less than 10% of nominal time
  •  in reality: depends on usage
  •  never enough!
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One Single Device for Indoor and Outdoor Usage?!

Smartphone?!

  • Charging when returning home
  • Not able to detect falls @home
  • PSTN better suited for alarm messages
  • 2/3/4G networks are not that stable

 Smartphone cannot be the single PERS device! “Pimped” wearable sensor?!

  • Adding 2/3/4G communication interfaces
  • Lifetime decreased
  • Cost added

 No single device possible

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Proposed System: 3 Parts

  • One and the same senor for fall detection
  • Two systems for emergency calls: Home station & Smartphone

d >d >d A B

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System for Mobile Fall Detection

Android Smartphone: e.g. Motorola Milestone

  • ARM Cortex A8 550 MHz, 256 MB RAM, 512 MB ROM
  • Accelerometer, Compass, Light-Sensor
  • 3G, Bluetooth

INGA Wireless Sensor Node

  • 8-bit Microcontroller @ 8 MHz, 16 kB RAM, 128 kB Flash, SD
  • Accelerometer, Gyroscope, Barometric Pressure Sensor
  • IEEE 802.15.4 radio, additional Bluetooth radio
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On the Road…

Emergency Messages

  • Sent by Smartphone
  • Via 2/3/4G network

Where to Implement the Mobile Fall Detection?

  • Obviously not in the Home Station

Possible solutions 1. Sensor sampling and fall detection on smartphone 2. Sensor sampling on node, fall detection on smartphone 3. Sensor sampling and fall detection performed by node

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Evaluation: Energy Consumption of Smartphone

92 93 94 95 96 97 98 99 100 200 400 600 800 1000 1200 Battery Level [%] Time [min] Idle FD on INGA FD on Smartphone Receive & Process

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Evaluation: Energy Consumption of Smartphone – R&P Detailed

10 20 30 40 50 60 70 80 90 100 50 100 150 200 250 300 Battery Level [%] Time [min] Idle and Others R&P: 16 Sample/s R&P: 32 Sample/s R&P: 64 Sample/s

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Evaluation: Energy Consumption of INGA Node

3,70 3,75 3,80 3,85 3,90 3,95 4,00 4,05 4,10 4,15 4,20 50 100 150 200 250 300 Battery Level [V] Time [min]

Idle FD on INGA S&S: 16 Sample/s S&S: 32 Sample/s S&S: 64 Sample/s

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Conclusion

Mobile PERS with Fall Detection is needed to …

  • Cope with “avoidance behavior”
  • Handle “refused” and “anxious usage”

Sensor Node for Data Sampling

  • Determined position at body
  • One and the same device

Sensor Node for Fall Detection Algorithms

  • Takes advantage of interrupt routines
  • No continuous transmission -> low energy

Thanks for the attention!

  • buesching@ibr.cs.tu-bs.de