title: Detection of anticipatory postural adjustments prior to gait initiation using inertial wearable sensors.
abstract: BACKGROUND
  The present study was performed to evaluate and characterize the potential of accelerometers and angular velocity sensors to detect and assess anticipatory postural adjustments (APAs) generated by the first step at the beginning of the gait. This paper proposes an algorithm to automatically detect certain parameters of APAs using only inertial sensors.
  
  
  METHODS
  Ten young healthy subjects participated in this study. The subjects wore an inertial unit containing a triaxial accelerometer and a triaxial angular velocity sensor attached to the lower back and one footswitch on the dominant leg to detect the beginning of the step. The subjects were standing upright on a stabilometer to detect the center of pressure displacement (CoP) generated by the anticipatory adjustments. The subjects were asked to take a step forward at their own speed and stride length. The duration and amplitude of the APAs detected by the accelerometer and angular velocity sensors were measured and compared with the results obtained from the stabilometer. The different phases of gait initiation were identified and compared using inertial sensors.
  
  
  RESULTS
  The APAs were detected by all of the sensors. Angular velocity sensors proved to be adequate to detect the beginning of the step in a manner similar to the footswitch by using a simple algorithm, which is easy to implement in low computational power devices. The amplitude and duration of APAs detected using only inertial sensors were similar to those detected by the stabilometer. An automatic algorithm to detect APA duration using triaxial inertial sensors was proposed.
  
  
  CONCLUSIONS
  These results suggest that the feasibility of accelerometers is improved through the use of angular velocity sensors, which can be used to automatically detect and evaluate APAs. The results presented can be used to develop portable sensors that may potentially be useful for monitoring patients in the home environment, thus encouraging the population to participate in more personalized healthcare.
authors.affiliation: Graduate School of Engineering, Chiba University, Chiba, Japan. rigo@graduate.chiba-u.jp
authors.forename: Rigoberto
authors.initials: R
authors.lastname: Martinez-Mendez
authors.forename: Masaki
authors.initials: M
authors.lastname: Sekine
authors.forename: Toshiyo
authors.initials: T
authors.lastname: Tamura
mesh_terms: D000328:Adult; D000465:Algorithms; D000886:Anthropometry / Q000379:methods*; D020811:Biomedical Technology / Q000295:instrumentation* / Q000379:methods; D004582:Electronics, Medical / Q000295:instrumentation* / Q000379:methods; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D004856:Postural Balance / Q000502:physiology*; D055815:Young Adult