Micro-doppler-based in-home aided and unaided walking recognition with multiple radar and sonar systems

Published in IET Radar, Sonar and Navigation. Online first 21/06/2016.The potential for using micro-Doppler signatures as a basis for distinguishing between aided and unaided gaits is considered in this study for the purpose of characterising normal elderly gait and assessment of patient recovery. In particular, five different classes of mobility are considered: normal unaided walking, walking with a limp, walking using a cane or tripod, walking with a walker, and using a wheelchair. This presents a challenging classification problem as the differences in micro-Doppler for these activities can be quite slight. Within this context, the performance of four different radar and sonar systems – a 40 kHz sonar, a 5.8 GHz wireless pulsed Doppler radar mote, a 10 GHz X-band continuous wave (CW) radar, and a 24 GHz CW radar – is evaluated using a broad range of features. Performance improvements using feature selection is addressed as well as the impact on performance of sensor placement and potential occlusion due to household objects. Results show that nearly 80% correct classification can be achieved with 10 s observations from the 24 GHz CW radar, whereas 86% performance can be achieved with 5 s observations of sonar

Discovering Clusters in Motion Time-Series Data

A new approach is proposed for clustering time-series data. The approach can be used to discover groupings of similar object motions that were observed in a video collection. A finite mixture of hidden Markov models (HMMs) is fitted to the motion data using the expectation-maximization (EM) framework. Previous approaches for HMM-based clustering employ a k-means formulation, where each sequence is assigned to only a single HMM. In contrast, the formulation presented in this paper allows each sequence to belong to more than a single HMM with some probability, and the hard decision about the sequence class membership can be deferred until a later time when such a decision is required. Experiments with simulated data demonstrate the benefit of using this EM-based approach when there is more "overlap" in the processes generating the data. Experiments with real data show the promising potential of HMM-based motion clustering in a number of applications.Office of Naval Research (N000140310108, N000140110444); National Science Foundation (IIS-0208876, CAREER Award 0133825

Analysis of Radar Doppler Signature from Human Data

This paper presents the results of time (autocorrelation) and time-frequency (spectrogram) analyses of radar signals returned from the moving human targets. When a radar signal falls on the human target which is moving toward or away from the radar, the signals reflected from different parts of his body produce a Doppler shift that is proportional to the velocity of those parts. Moving parts of the body causes the characteristic Doppler signature. The main contribution comes from the torso which causes the central Doppler frequency of target. The motion of arms and legs induces modulation on the returned radar signal and generates sidebands around the central Doppler frequency, referred to as micro-Doppler signatures. Through analyses on experimental data it was demonstrated that the human motion signature extraction is better using spectrogram. While the central Doppler frequency can be determined using the autocorrelation and the spectrogram, the extraction of the fundamental cadence frequency using the autocorrelation is unreliable when the target is in the clutter presence. It was shown that the fundamental cadence frequency increases with increasing dynamic movement of people and simultaneously the possibility of its extraction is proportional to the degree of synchronization movements of persons in the group

Boxfishes (Teleostei: Ostraciidae) as a model system for fishes swimming with many fins: kinematics

Swimming movements in boxfishes were much more complex and varied than classical descriptions indicated. At low to moderate rectilinear swimming speeds (<5 TL s^(-1), where TL is total body length), they were entirely median- and paired-fin swimmers, apparently using their caudal fins for steering. The pectoral and median paired fins generate both the thrust needed for forward motion and the continuously varied, interacting forces required for the maintenance of rectilinearity. It was only at higher swimming speeds (above 5 TL s^(-1)), when burst-and-coast swimming was used, that they became primarily body and caudal-fin swimmers. Despite their unwieldy appearance and often asynchronous fin beats, boxfish swam in a stable manner. Swimming boxfish used three gaits. Fin-beat asymmetry and a relatively nonlinear swimming trajectory characterized the first gait (0–1 TL s^(-1)). The beginning of the second gait (1–3 TL s^(-1)) was characterized by varying fin-beat frequencies and amplitudes as well as synchrony in pectoral fin motions. The remainder of the second gait (3–5 TL s^(-1)) was characterized by constant fin-beat amplitudes, varying finbeat frequencies and increasing pectoral fin-beat asynchrony. The third gait (>5 TL s^(-1)) was characterized by the use of a caudal burst-and-coast variant. Adduction was always faster than abduction in the pectoral fins. There were no measurable refractory periods between successive phases of the fin movement cycles. Dorsal and anal fin movements were synchronized at speeds greater than 2.5 TL s^(-1), but were often out of phase with pectoral fin movements

A general formulation of Bead Models applied to flexible fibers and active filaments at low Reynolds number

This contribution provides a general framework to use Lagrange multipliers for the simulation of low Reynolds number fiber dynamics based on Bead Models (BM). This formalism provides an efficient method to account for kinematic constraints. We illustrate, with several examples, to which extent the proposed formulation offers a flexible and versatile framework for the quantitative modeling of flexible fibers deformation and rotation in shear flow, the dynamics of actuated filaments and the propulsion of active swimmers. Furthermore, a new contact model called Gears Model is proposed and successfully tested. It avoids the use of numerical artifices such as repulsive forces between adjacent beads, a source of numerical difficulties in the temporal integration of previous Bead Models.Comment: 41 pages, 15 figure