Detecting Motion Patterns via Direction Maps with Application to Surveillance

2005 ◽  
Author(s):  
J.M. Gryn ◽  
R.P. Wildes ◽  
J.K. Tsotsos
Keyword(s):  
Motion Patterns

Tongue and Lip Motion Patterns in Alaryngeal Speech

2020 ◽  
Author(s):  
Kristin J. Teplansky ◽  
Alan Wisler ◽  
Beiming Cao ◽  
Wendy Liang ◽  
Chad W. Whited ◽  
...  
Keyword(s):  
Motion Patterns ◽  
Alaryngeal Speech

scholarly journals Using Different Combinations of Body-Mounted IMU Sensors to Estimate Speed of Horses—A Machine Learning Approach

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 798
Author(s):  
Hamed Darbandi ◽  
Filipe Serra Bragança ◽  
Berend Jan van der Zwaag ◽  
John Voskamp ◽  
Annik Imogen Gmel ◽  
...  
Keyword(s):  
Machine Learning ◽  
The Body ◽  
Biomechanical Analysis ◽  
Estimation Accuracy ◽  
Speed Estimation ◽  
Motion Patterns ◽  
Positioning Systems ◽  
Machine Learning Approach ◽  
Global Positioning ◽  
Measurement Units

Speed is an essential parameter in biomechanical analysis and general locomotion research. It is possible to estimate the speed using global positioning systems (GPS) or inertial measurement units (IMUs). However, GPS requires a consistent signal connection to satellites, and errors accumulate during IMU signals integration. In an attempt to overcome these issues, we have investigated the possibility of estimating the horse speed by developing machine learning (ML) models using the signals from seven body-mounted IMUs. Since motion patterns extracted from IMU signals are different between breeds and gaits, we trained the models based on data from 40 Icelandic and Franches-Montagnes horses during walk, trot, tölt, pace, and canter. In addition, we studied the estimation accuracy between IMU locations on the body (sacrum, withers, head, and limbs). The models were evaluated per gait and were compared between ML algorithms and IMU location. The model yielded the highest estimation accuracy of speed (RMSE = 0.25 m/s) within equine and most of human speed estimation literature. In conclusion, highly accurate horse speed estimation models, independent of IMU(s) location on-body and gait, were developed using ML.

scholarly journals Effect of post-stroke spasticity on voluntary movement of the upper limb

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Hadar Lackritz ◽  
Yisrael Parmet ◽  
Silvi Frenkel-Toledo ◽  
Melanie C. Baniña ◽  
Nachum Soroker ◽  
...  
Keyword(s):  
Upper Limb ◽  
Target Location ◽  
Distance Measure ◽  
Movement Time ◽  
Motor Impairment ◽  
Reach To Grasp ◽  
Motion Patterns ◽  
Post Stroke ◽  
The Impact ◽  
Elbow Motion

Abstract Background Hemiparesis following stroke is often accompanied by spasticity. Spasticity is one factor among the multiple components of the upper motor neuron syndrome that contributes to movement impairment. However, the specific contribution of spasticity is difficult to isolate and quantify. We propose a new method of quantification and evaluation of the impact of spasticity on the quality of movement following stroke. Methods Spasticity was assessed using the Tonic Stretch Reflex Threshold (TSRT). TSRT was analyzed in relation to stochastic models of motion to quantify the deviation of the hemiparetic upper limb motion from the normal motion patterns during a reaching task. Specifically, we assessed the impact of spasticity in the elbow flexors on reaching motion patterns using two distinct measures of the ‘distance’ between pathological and normal movement, (a) the bidirectional Kullback–Liebler divergence (BKLD) and (b) Hellinger’s distance (HD). These measures differ in their sensitivity to different confounding variables. Motor impairment was assessed clinically by the Fugl-Meyer assessment scale for the upper extremity (FMA-UE). Forty-two first-event stroke patients in the subacute phase and 13 healthy controls of similar age participated in the study. Elbow motion was analyzed in the context of repeated reach-to-grasp movements towards four differently located targets. Log-BKLD and HD along with movement time, final elbow extension angle, mean elbow velocity, peak elbow velocity, and the number of velocity peaks of the elbow motion were computed. Results Upper limb kinematics in patients with lower FMA-UE scores (greater impairment) showed greater deviation from normality when the distance between impaired and normal elbow motion was analyzed either with the BKLD or HD measures. The severity of spasticity, reflected by the TSRT, was related to the distance between impaired and normal elbow motion analyzed with either distance measure. Mean elbow velocity differed between targets, however HD was not sensitive to target location. This may point at effects of spasticity on motion quality that go beyond effects on velocity. Conclusions The two methods for analyzing pathological movement post-stroke provide new options for studying the relationship between spasticity and movement quality under different spatiotemporal constraints.

On the barn owl’s visual pre-attack behavior: I. Structure of head movements and motion patterns

2006 ◽  
Vol 192 (9) ◽  
pp. 927-940 ◽  
Author(s):  
Shay Ohayon ◽  
Robert F. van der Willigen ◽  
Hermann Wagner ◽  
Igor Katsman ◽  
Ehud Rivlin
Keyword(s):  
Head Movements ◽  
Attack Behavior ◽  
Motion Patterns

Coherent Compound Motion: Corners and Nonrigid Configurations

1990 ◽  
Vol 2 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Steven W. Zucker ◽  
Lee Iverson ◽  
Robert A. Hummel
Keyword(s):  
Neural Computation ◽  
Coherent Motion ◽  
Natural Scenes ◽  
Motion Patterns ◽  
Motion System ◽  
Sinusoidal Gratings ◽  
Single Compound ◽  
Sharp Corners ◽  
Wire Gratings ◽  
Planar Motions

Consider two wire gratings, superimposed and moving across each other. Under certain conditions the two gratings will cohere into a single, compound pattern, which will appear to be moving in another direction. Such coherent motion patterns have been studied for sinusoidal component gratings, and give rise to percepts of rigid, planar motions. In this paper we show how to construct coherent motion displays that give rise to nonuniform, nonrigid, and nonplanar percepts. Most significantly, they also can define percepts with corners. Since these patterns are more consistent with the structure of natural scenes than rigid sinusoidal gratings, they stand as interesting stimuli for both computational and physiological studies. To illustrate, our display with sharp corners (tangent discontinuities or singularities) separating regions of coherent motion suggests that smoothing does not cross tangent discontinuities, a point that argues against existing (regularization) algorithms for computing motion. This leads us to consider how singularities can be confronted directly within optical flow computations, and we conclude with two hypotheses: (1) that singularities are represented within the motion system as multiple directions at the same retinotopic location; and (2) for component gratings to cohere, they must be at the same depth from the viewer. Both hypotheses have implications for the neural computation of coherent motion.

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