MEMS based sensing and algorithm development for fall detection and gait analysis

Piyush Gupta, Gabriel Ramirez, Donald Y.C. Lie, Tim Dallas, Ron E. Banister, Andrew Dentino

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Falls by the elderly are highly detrimental to health, frequently resulting in injury, high medical costs, and even death. Using a MEMS-based sensing system, algorithms are being developed for detecting falls and monitoring the gait of elderly and disabled persons. In this study, wireless sensors utilize Zigbee protocols were incorporated into planar shoe insoles and a waist mounted device. The insole contains four sensors to measure pressure applied by the foot. A MEMS based tri-axial accelerometer is embedded in the insert and a second one is utilized by the waist mounted device. The primary fall detection algorithm is derived from the waist accelerometer. The differential acceleration is calculated from samples received in 1.5s time intervals. This differential acceleration provides the quantification via an energy index. From this index one may ascertain different gait and identify fall events. Once a pre-determined index threshold is exceeded, the algorithm will classify an event as a fall or a stumble. The secondary algorithm is derived from frequency analysis techniques. The analysis consists of wavelet transforms conducted on the waist accelerometer data. The insole pressure data is then used to underline discrepancies in the transforms, providing more accurate data for classifying gait and/or detecting falls. The range of the transform amplitude in the fourth iteration of a Daubechies-6 transform was found sufficient to detect and classify fall events.

Original languageEnglish
Title of host publicationMicrofluidics, BioMEMS, and Medical Microsystems VIII
StatePublished - 2010
EventMicrofluidics, BioMEMS, and Medical Microsystems VIII - San Francisco, CA, United States
Duration: Jan 25 2010Jan 27 2010

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMicrofluidics, BioMEMS, and Medical Microsystems VIII
Country/TerritoryUnited States
CitySan Francisco, CA


  • Fall detection
  • Gait classification
  • MEMS
  • Tri-axial accelerometer
  • Wireless sensors


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