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Wireless Sensor Localization for Human Motion Tracking

Explore the use of wireless sensors for tracking human body movement and developing a formal language to describe motion. This presentation focuses on sensor localization and the potential for high-precision movement measurement. Discover technologies like Cricket and GPS alongside their advantages, limitations, and potential for improvement in tracking smaller body movements. Dive into the details of the Cricket Indoor Location System, its configurations, advantages, and ongoing research for enhanced accuracy.

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Wireless Sensor Localization for Human Motion Tracking

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  1. Michael Baswell CS526 Semester Project, Spring 2006 Wireless Sensor LocalizationDecoding Human Movement

  2. Goal: to measure human body movement and, ultimately, to create a formal language describing this motion. Not a new idea, but new tech- nologies may allow better/more accurate results Wireless sensors are small enough to be wearable; can they be useful in this research? This presentation focuses on sensor localization; if we can localize with high precision, we can measure movement Introduction & Background

  3. Motion Tracking Technologies • Markers on joints – LotR/Gollum • Markers can be • Visual (cameras track movement) • Electromagnetic • Inertial sensors • Drawbacks: • Line-of-sight • Surrounding environment can cause interference & errors • COST! Proprietary Systems can run $30-40 thousand or more.

  4. Current Wireless Location Systems • GPS – outside only, accuracy in meters to 10's of meters • ActiveBadge – indoor, IR-based. Locates badge to the current room only. • Wireless motes • have been simulated to locate to within meters (Rupp, Sinha, etc.) • Work via RSS (Radio Signal Strength) approximations; signal attenuates over distance & due to obstacles

  5. Mote Localization & RSSI (continued) • Drawbacks: • RSSI provides, at best, approximate distance info from broadcaster to recipient • Obstructions cause further attenuation, again this can only be approximated • Empirical measurements at Berkeley, using Mica2 mote sensor network: • Outdoors, flat field, no obstruction: 3-meter resolution • Indoors, lab environment: no distance information • Clearly, if the environment is nonstatic, approximations will be even further off • This is not good enough!

  6. Cricket Indoor Location System • MIT project • Indoor location system • “fine-grained location information” • accuracy 1-3 cm • Currently on 2nd version; ongoing development & research • Based on Mica2 platform, but adds ultrasound

  7. Cricket v2 (continued) • Cricket motes can be configured as either a “beacon” or as a “listener” (or can be configured to do both) • Beacons broadcast an RF indentifier signal, and at the same time emit an ultrasonic “chirp” • Passive listeners measure the time lapse between the two, and compute distance to that beacon • RF propagates at speed of light • Ultrasound propagates at speed of sound

  8. Cricket Advantages • Because listeners are passive, the system scales well. • Good resolution – possibly good enough already for our purposes • Inexpensive - ~$225 / mote • Distance-finding research at Berkeley has found similar degrees of accuracy: • Varying accuracy due to distance from beacons • Also varies by frequency of ultrasonic pulse • Further research could increase accuracy

  9. Cricket Config Screen

  10. Cricket Limitations • Too low, at least in default config (avg 1 sec / broadcast) • Accuracy of 1-3 cm is good, but is it good enough? • Due to limited range from beacons, large movements may not be capturable (think about a ballet leap) • Due to these limitations, additional sensors such as flex sensors or inertial sensors, may need to be integrated into the system as well

  11. Cricket In Action • Videos online at Cricket web site • http://cricket.csail.mit.edu/ • Tracking a moving train • Auto-configuring robots (Roomba video)

  12. Summary • For the goal of this project, we need highly accurate, quick measurements • Cricket is good, but there is room for improvement still • May need to use a hybrid system: • cricket sensors plus cameras/markers? • Flex sensors? • May need to focus on smaller movements or individual body parts • Further development of this platform may remove some of the limitations

  13. References • http://cricket.csail.mit.edu/ • http://www.cs.berkeley.edu/%7Ekamin/localization.html • Yifei Wang, “Human movement tracking using a wearable wireless sensor network,” Masters Thesis, Iowa State University, 2005 • Cricket v2 User Manual, Cricket Project, MIT Computer Science and Artificial Intelligence Lab, January 2005 • Hari Balakishnan, Roshan Baliga, Dorothy Curtis, Michel Goraczko, Allen Miu, Bodhi Priyantha, Adam Smith, Ken Steele, Seth Teller, Kevin Wang, “ Lessons from Developing and Deploying the Cricket Indoor Location System,” MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), November 2003

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