Continuous Gait Velocity Analysis Using Ambient Sensors in a Smart Home

Ahmed Nait Aicha, Gwenn Englebienne, Ben Kröse

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

9 Citations (Scopus)
76 Downloads (Pure)

Abstract

We present a method for measuring gait velocity using data from an existing ambient sensor network. Gait velocity is an important predictor of fall risk and functional health. In contrast to other approaches that use specific sensors or sensor configurations our method imposes no constraints on the elderly. We studied different probabilistic models for the description of the sensor patterns. Experiments are carried out on 15 months of data and include repeated assessments from an occupational therapist. We showed that the measured gait velocities correlate with these assessments.
Original languageEnglish
Title of host publicationAmbient Intelligence
Subtitle of host publication12th European Conference, AmI 2015 Athens, Greece, November 11–13, 2015 proceedings
EditorsBoris De Ruyter, Achilles Kameas, Periklis Chatzimisios, Irene Mavrommati
Place of PublicationCham
PublisherSpringer
Pages219-235
ISBN (Electronic)9783319260051
ISBN (Print)9783319260044
DOIs
Publication statusPublished - 2015
EventAmbient Intelligence: 12th European Conference - Athens, Greece
Duration: 11 Nov 201513 Nov 2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9425

Conference

ConferenceAmbient Intelligence
Abbreviated titleAML 2015
CountryGreece
CityAthens
Period11/11/1513/11/15

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