title: Missing Sample Recovery for Wireless Inertial Sensor-Based Human Movement Acquisition.
abstract: This paper presents a novel, practical, and effective routine to reconstruct missing samples from a time-domain sequence of wirelessly transmitted IMU data during high-level mobility activities. Our work extends previous approaches involving empirical mode decomposition (EMD)-based and auto-regressive (AR) model-based interpolation algorithms in two aspects: 1) we utilized a modified sifting process for signal decomposition into a set of intrinsic mode functions with missing samples, and 2) we expand previous AR modeling for recovery of audio signals to exploit the quasi-periodic characteristics of lower-limb movement during the modified Edgren side step test. To verify the improvements provided by the proposed extensions, a comparison study of traditional interpolation methods, such as cubic spline interpolation, AR model-based interpolations, and EMD-based interpolation is also made via simulation with real inertial signals recorded during high-speed movement. The evaluation was based on two performance criteria: Euclidian distance and Pearson correlation coefficient between the original signal and the reconstructed signal. The experimental results show that the proposed method improves upon traditional interpolation methods used in recovering missing samples.
authors.forename: Kyoung Jae
authors.initials: KJ
authors.lastname: Kim
authors.forename: Vibhor
authors.initials: V
authors.lastname: Agrawal
authors.forename: Ignacio
authors.initials: I
authors.lastname: Gaunaurd
authors.forename: Robert S
authors.initials: RS
authors.lastname: Gailey
authors.forename: Christopher L
authors.initials: CL
authors.lastname: Bennett
mesh_terms: D061725:Accelerometry / Q000295:instrumentation / Q000379:methods; D056044:Actigraphy / Q000295:instrumentation* / Q000379:methods*; D000465:Algorithms; D016477:Artifacts; D003195:Computer Communication Networks / Q000295:instrumentation; D003627:Data Interpretation, Statistical; D004867:Equipment Design; D019544:Equipment Failure Analysis; D015444:Exercise / Q000502:physiology*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D014159:Transducers; D059015:Wireless Technology / Q000295:instrumentation*