DETERMINISTIC AND EVOLUTIONARY EXTRACTION OF DELTA-LOGNORMAL PARAMETERS: PERFORMANCE COMPARISON

2007 ◽  
Vol 21 (01) ◽  
pp. 21-41 ◽  
Author(s):  
MOUSSA DJIOUA ◽  
RÉJEAN PLAMONDON ◽  
ANTONIO DELLA CIOPPA ◽  
ANGELO MARCELLI
Keyword(s):  
Real Data ◽  
Human Movement ◽  
Realistic Model ◽  
Performance Comparison ◽  
Deterministic Approach ◽  
Handwriting Analysis ◽  
Kinematic Theory ◽  
Human Movements ◽  
Analysis And Synthesis ◽  
Noisy Conditions

A theory, called the Kinematic Theory of Rapid Human Movement, was proposed a few years ago to analyze rapid human movements, called the Kinematic Theory of Rapid Human Movements, based on a delta-lognormal equation that globally describes the basic properties of the velocity profiles of an end-effector using seven parameters. This realistic model has been very useful for proposing original solutions to various pattern recognition problems (signature segmentation and verification, handwriting analysis and synthesis, etc.). Most of these applications rely on the use of an efficient algorithm to extract the delta-lognormal parameters from real data with the best possible fit. In this paper, we compare two such algorithms: a deterministic one, based on nonlinear regression, and a Breeder Genetic algorithm. The performance of these two algorithms and of their combinations are compared using the same artificial database, composed of analytical delta-lognormal profiles and their noisy versions (20 dB SNR). In the free-noise case, the analysis of the experimental results shows that the deterministic approach leads to better results than the evolutionary one, while under the extremely noisy conditions selected, the evolutionary approach seems to be less sensitive to noise, but is nevertheless less successful than the deterministic search.

THE GENERATION OF VELOCITY PROFILES WITH AN ARTIFICIAL SIMULATOR

2004 ◽  
Vol 18 (07) ◽  
pp. 1207-1219 ◽  
Author(s):  
MOUSSA DJIOUA ◽  
RÉJEAN PLAMONDON
Keyword(s):  
Pattern Recognition ◽  
Human Subjects ◽  
Realistic Model ◽  
Velocity Profiles ◽  
The Other ◽  
Signature Verification ◽  
Handwriting Analysis ◽  
Kinematic Theory ◽  
Human Movements ◽  
Psychophysical Studies

A few years ago, a Kinematic Theory was proposed to analyze rapid human movements. The theory is based on a delta-lognormal equation which can be used to globally describe the basic properties of velocity profiles using seven parameters. This realistic model has been of great use to solve pattern recognition problems (signature verification, handwriting analysis and segmentation, etc.). To go further in that direction, a better understanding of the model is a prerequisite. This can be either in the context of psychophysical studies involving human subjects or in the context of computer simulations. In this paper, we use the same model form to develop a simulator that generates human-like velocity profiles. A basic subsystem model is both proposed and constructed with a Simulink Matlab tool; then many of these are connected to create an artificial neuromuscular network. Combining two networks in parallel, one agonist and the other antagonist, a synergy simulator is constructed. The similarity of the velocity patterns produced by the simulator is analyzed using a delta-lognormal parameter extractor. It is shown that the parameters extracted from artificially generated profiles vary in the same intervals as those of experimental profiles produced by human subjects. In future works the simulator tool will be used to study the control of rapid human movements.

Speed/accuracy trade-offs in target-directed movements

1997 ◽  
Vol 20 (2) ◽  
pp. 279-303 ◽  
Author(s):  
Réjean Plamondon ◽  
Adel M. Alimi
Keyword(s):  
Human Movement ◽  
Critical Survey ◽  
Kinematic Theory ◽  
Trade Offs ◽  
Human Movements ◽  
Target Article ◽  
Points Of View ◽  
High Degree ◽  
Speed Accuracy ◽  
Kinematic Properties

This target article presents a critical survey of the scientific literature dealing with the speed/accuracy trade-offs in rapid-aimed movements. It highlights the numerous mathematical and theoretical interpretations that have been proposed in recent decades. Although the variety of points of view reflects the richness of the field and the high degree of interest that such basic phenomena attract in the understanding of human movements, it calls into question the ability of many models to explain the basic observations consistently reported in the field. This target article summarizes the kinematic theory of rapid human movements, proposed recently by R. Plamondon (1993b; 1993c; 1995a; 1995b), and analyzes its predictions in the context of speed/accuracy trade-offs. Data from human movement literature are reanalyzed and reinterpreted in the context of the new theory. It is shown that the various aspects of speed/ accuracy trade-offs can be taken into account by considering the asymptotic behavior of a large number of coupled linear systems, from which a delta-lognormal law can be derived to describe the velocity profile of an end-effector driven by a neuromuscular synergy. This law not only describes velocity profiles almost perfectly, it also predicts the kinematic properties of simple rapid movements and provides a consistent framework for the analysis of different types of speed/accuracy trade-offs using a quadratic (or power) law that emerges from the model.

scholarly journals Sigma-Lognormal Modeling of Speech

2021 ◽  
Author(s):  
C. Carmona-Duarte ◽  
M. A. Ferrer ◽  
R. Plamondon ◽  
A. Gómez-Rodellar ◽  
P. Gómez-Vilda
Keyword(s):  
Human Movement ◽  
The Other ◽  
Lognormal Model ◽  
Inverse Approach ◽  
Kinematic Theory ◽  
Human Movements ◽  
The One ◽  
Speech Kinematics ◽  
Speech Motor ◽  
Timit Database

AbstractHuman movement studies and analyses have been fundamental in many scientific domains, ranging from neuroscience to education, pattern recognition to robotics, health care to sports, and beyond. Previous speech motor models were proposed to understand how speech movement is produced and how the resulting speech varies when some parameters are changed. However, the inverse approach, in which the muscular response parameters and the subject’s age are derived from real continuous speech, is not possible with such models. Instead, in the handwriting field, the kinematic theory of rapid human movements and its associated Sigma-lognormal model have been applied successfully to obtain the muscular response parameters. This work presents a speech kinematics-based model that can be used to study, analyze, and reconstruct complex speech kinematics in a simplified manner. A method based on the kinematic theory of rapid human movements and its associated Sigma-lognormal model are applied to describe and to parameterize the asymptotic impulse response of the neuromuscular networks involved in speech as a response to a neuromotor command. The method used to carry out transformations from formants to a movement observation is also presented. Experiments carried out with the (English) VTR-TIMIT database and the (German) Saarbrucken Voice Database, including people of different ages, with and without laryngeal pathologies, corroborate the link between the extracted parameters and aging, on the one hand, and the proportion between the first and second formants required in applying the kinematic theory of rapid human movements, on the other. The results should drive innovative developments in the modeling and understanding of speech kinematics.

scholarly journals Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Karen McCulloch ◽  
Nick Golding ◽  
Jodie McVernon ◽  
Sarah Goodwin ◽  
Martin Tomko
Keyword(s):  
Spatial Scales ◽  
Predictive Ability ◽  
Movement Patterns ◽  
Human Movement ◽  
Continental Scale ◽  
Movement Characteristics ◽  
Human Movements ◽  
Movement Models ◽  
Epidemiology Data

AbstractUnderstanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics, however, strongly depend on the scale and type of movement captured for a given study. The models that have so far been proposed for human movement are best suited to specific spatial scales and types of movement. Selecting both the scale of data collection, and the appropriate model for the data remains a key challenge in predicting human movements. We used two different data sources on human movement in Australia, at different spatial scales, to train a range of statistical movement models and evaluate their ability to predict movement patterns for each data type and scale. Whilst the five commonly-used movement models we evaluated varied markedly between datasets in their predictive ability, we show that an ensemble modelling approach that combines the predictions of these models consistently outperformed all individual models against hold-out data.

scholarly journals A kinematic theory of rapid human movements

1995 ◽  
Vol 73 (1) ◽  
pp. 95-95 ◽  
Author(s):  
Réjean Plamondon
Keyword(s):  
Kinematic Theory ◽  
Human Movements

scholarly journals Effect of daily periodic human movement on dengue dynamics: the case of the 2010 outbreak in Hermosillo, Mexico

2020 ◽  
Author(s):  
Mayra R. Tocto-Erazo ◽  
Daniel Olmos-Liceaga ◽  
José A. Montoya
Keyword(s):  
Real Data ◽  
Human Movement ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The South ◽  
South Side ◽  
Transmission Rates ◽  
The North ◽  
Local Properties ◽  
The City

AbstractThe human movement plays an important rol in the spread of infectious diseases. On an urban scale, people move daily to workplaces, schools, among others. Here, we are interested in exploring the effect of the daily local stay on the variations of some characteristics of dengue dynamics such as the transmission rates and local basic reproductive numbers. For this, we use a two-patch mathematical model that explicitly considers that daily mobility of people and real data from the 2010 dengue outbreak in Hermosillo, Mexico. Based on a preliminary cluster analysis, we divide the city into two regions, the south and north sides, which determine each patch of the model. We use a Bayesian approach to estimate the transmission rates and local basic reproductive numbers of some urban mobility scenarios where residents of each patch spend daily the 100% (no human movement between patches), 75% and 50% of their day at their place of residence. For the north side, estimates of transmission rates do not vary and it is more likely that the local basic reproductive number to be greater than one for all three different scenarios. On the contrary, tranmission rates of the south side have more weight in lower values when consider the human movement between patches compared to the uncoupled case. In fact, local basic reproductive numbers less than 1 are not negligible for the south side. If information about commuting is known, this work might be useful to obtain better estimates of some contagion local properties of a patch, such as the basic reproductive number.

scholarly journals Postural Synergy-Based Exoskeleton Reproducing Natural Human Movements to Improve Upper Limb Motor Control after Stroke

2020 ◽  
Author(s):  
Chang He ◽  
Cai-Hua Xiong ◽  
Ze-Jian Chen ◽  
Wei Fan ◽  
Xiao-Lin Huang
Keyword(s):  
Motor Control ◽  
Upper Limb ◽  
Degrees Of Freedom ◽  
Response Rate ◽  
Human Movement ◽  
Interaction Force ◽  
Human Anatomy ◽  
Clinical Trial Registration ◽  
Upper Limb Exoskeleton ◽  
Human Movements

Abstract Background: Upper limb exoskeletons have drawn significant attention in neurorehabilitation because of anthropomorphic mechanical structure analogous to human anatomy. Whereas, the training movements are typically underorganized because most exoskeletons only control the movement of the hand in space, without considering rehabilitation of joint motion, particularly inter-joint postural synergy. The purposes of this study were to explore the application of a postural synergy-based exoskeleton (Armule) reproducing natural human movements for robot-assisted neurorehabilitation and to preliminarily assess its effect on patients' upper limb motor control after stroke. Methods: We developed a novel upper limb exoskeleton based on the concept of postural synergy, which provided five degrees of freedom (DOF) , natural human movements of the upper limb. Eight participants with hemiplegia due to a first-ever, unilateral stroke were recruited and included. They participated in exoskeleton therapy sessions 45 minutes/day, 5 days/week for 4 weeks, with passive/active training under anthropomorphic trajectories and postures. The primary outcome was the Fugl-Meyer Assessment for Upper Extremities (FMA-UE). The secondary outcomes were the Action Research Arm Test(ARAT), modified Barthel Index (mBI) , and exoskeleton kinematic as well as interaction force metrics: motion smoothness in the joint space, postural synergy error, interaction force smoothness, and the intent response rate. Results: After the 4-weeks intervention, all subjects showed significant improvements in the following clinical measures: the FMA-UE ( p =0.02), the ARAT ( p =0.003), and the mBI score ( p <0.001). Besides, all subjects showed significant improvements in motion smoothness ( p =0.004), postural synergy error ( p =0.014), interaction force smoothness ( p =0.004), and the intent response rate ( p =0.008). Conclusions: The subjects were well adapted to our device that assisted in completing functional movements with natural human movement characteristics. The results of the preliminary clinical intervention indicate that the Armule exoskeleton improves individuals’ motor control and activities of daily living (ADL) function after stroke, which might be associated with kinematic and interaction force optimization and postural synergy modification during functional tasks. Clinical trial registration: ChiCTR, ChiCTR1900026656; Date of registration: October 17, 2019. http://www.chictr.org.cn/showproj.aspx?proj=44420

FRACTAL-BASED CLASSIFICATION OF ELECTROMYOGRAPHY (EMG) SIGNAL BETWEEN FINGERS AND HAND’S BASIC MOVEMENTS, FUNCTIONAL MOVEMENTS, AND FORCE PATTERNS

Fractals ◽  
2019 ◽  
Vol 27 (04) ◽  
pp. 1950050 ◽  
Author(s):  
HAMIDREZA NAMAZI
Keyword(s):  
Linear Structure ◽  
Human Movement ◽  
The Body ◽  
Emg Signal ◽  
Human Movements ◽  
Main Indicator ◽  
Human Ability ◽  
Rehabilitation Science ◽  
Functional Movements

Analysis of human ability to move the body (hand, feet, etc.) is one of the major issues in rehabilitation science. For this purpose, scientists analyze different signals govern from human body. Electromyography (EMG) signal is the main indicator of human movement that can be analyzed using different techniques in order to classify different movements. In this paper, we analyze the complex non-linear structure of EMG signal from subjects while they underwent three exercises that include basic movements of the fingers and of the wrist, grasping and functional movements, and force patterns. For this purpose, we employ fractal dimension as indicator of complexity. The result of our analysis showed that the EMG signal experiences the greatest complexity when subjects think to press combinations of fingers with an increasing force (force pattern). The method of analysis employed in this research can be widely applied to analyze and classify different types of human movements.

A kinematic theory of rapid human movements

1995 ◽  
Vol 72 (4) ◽  
pp. 295-307 ◽  
Author(s):  
R�jean Plamondon
Keyword(s):  
Kinematic Theory ◽  
Human Movements

ON ANALYSIS AND SYNTHESIS OF ELEMENTARY AND COMPLEX INFORMATIONAL BISPECTRAL STRUCTURES

2008 ◽  
Vol 18 (09) ◽  
pp. 2753-2763 ◽  
Author(s):  
GERMAN N. BOCHKOV ◽  
KONSTANTIN V. GOROKHOV
Keyword(s):  
Spectral Line ◽  
High Frequency ◽  
Frequency Synthesizer ◽  
Realistic Model ◽  
Sectional Area ◽  
The Real ◽  
Analysis And Synthesis ◽  
Frequency Fluctuations

The problem regarding shapes of bispectral peak of the triplet representing the triharmonic signal is discussed. This triplet can be used as both standard diagnostic signal for a bispectral analyzers and a simplest element of complex informational patterns of bispectrally organized signals. The problem of analyzing and measuring the parameters of bispectral peak is equally fundamental as the well-known problem concerning the shape and width of spectral line of quasi-monochromatic oscillations. The sectional area of bispectral peak restricts the limiting informational volume of complex bispectral patterns. Two models of an actual triplet with frequency fluctuations are analyzed. Universal bispectral-peak shapes are found for a triplet with proportional frequencies for the limiting cases of extremely slow and extremely fast frequency fluctuations. The phenomenon of bispectral-peak superlocalization is discovered for quasi-static fluctuations and analyzed for the most realistic model of 1/f frequency fluctuations. The experiment investigating the bispectral peak of the real high-frequency synthesizer is presented.

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