41 research outputs found

    Entrainment and synchronization in networks of Rayleigh-van der Pol oscillators with diffusive and Haken-Kelso-Bunz couplings

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    We analyze a network of non-identical Rayleigh–van der Pol (RvdP) oscillators interconnected through either diffusive or nonlinear coupling functions. The work presented here extends existing results on the case of two nonlinearly coupled RvdP oscillators to the problem of considering a network of three or more of them. Specifically, we study synchronization and entrainment in networks of heterogeneous RvdP oscillators and contrast the effects of diffusive linear coupling strategies with the nonlinear Haken–Kelso–Bunz coupling, originally introduced to study human bimanual experiments. We show how convergence of the error among the nodes’ trajectories toward a bounded region is possible with both linear and nonlinear coupling functions. Under the assumption that the network is connected, simple, and undirected, analytical results are obtained to prove boundedness of the error when the oscillators are coupled diffusively. All results are illustrated by way of numerical examples and compared with the experimental findings available in the literature on synchronization of people rocking chairs, confirming the effectiveness of the model we propose to capture some of the features of human group synchronization observed experimentally in the previous literature

    Dynamic similarity promotes interpersonal coordination in joint-action

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    Human movement has been studied for decades and dynamic laws of motion that are common to all humans have been derived. Yet, every individual moves differently from everyone else (faster/slower, harder/smoother etc). We propose here an index of such variability, namely an individual motor signature (IMS) able to capture the subtle differences in the way each of us moves. We show that the IMS of a person is time-invariant and that it significantly differs from those of other individuals. This allows us to quantify the dynamic similarity, a measure of rapport between dynamics of different individuals' movements, and demonstrate that it facilitates coordination during interaction. We use our measure to confirm a key prediction of the theory of similarity that coordination between two individuals performing a joint-action task is higher if their motions share similar dynamic features. Furthermore, we use a virtual avatar driven by an interactive cognitive architecture based on feedback control theory to explore the effects of different kinematic features of the avatar motion on the coordination with human players

    Unravelling socio-motor biomarkers in schizophrenia

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    We present novel, low-cost and non-invasive potential diagnostic biomarkers of schizophrenia. They are based on the ‘mirror-game’, a coordination task in which two partners are asked to mimic each other’s hand movements. In particular, we use the patient’s solo movement, recorded in the absence of a partner, and motion recorded during interaction with an artificial agent, a computer avatar or a humanoid robot. In order to discriminate between the patients and controls, we employ statistical learning techniques, which we apply to nonverbal synchrony and neuromotor features derived from the participants’ movement data. The proposed classifier has 93% accuracy and 100% specificity. Our results provide evidence that statistical learning techniques, nonverbal movement coordination and neuromotor characteristics could form the foundation of decision support tools aiding clinicians in cases of diagnostic uncertainty

    BeatWalk: Personalized Music-Based Gait Rehabilitation in Parkinson’s Disease

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    Taking regular walks when living with Parkinson’s disease (PD) has beneficial effects on movement and quality of life. Yet, patients usually show reduced physical activity compared to healthy older adults. Using auditory stimulation such as music can facilitate walking but patients vary significantly in their response. An individualized approach adapting musical tempo to patients’ gait cadence, and capitalizing on these individual differences, is likely to provide a rewarding experience, increasing motivation for walk-in PD. We aim to evaluate the observance, safety, tolerance, usability, and enjoyment of a new smartphone application. It was coupled with wearable sensors (BeatWalk) and delivered individualized musical stimulation for gait auto-rehabilitation at home. Forty-five patients with PD underwent a 1-month, outdoor, uncontrolled gait rehabilitation program, using the BeatWalk application (30 min/day, 5 days/week). The music tempo was being aligned in real-time to patients’ gait cadence in a way that could foster an increase up to +10% of their spontaneous cadence. Open-label evaluation was based on BeatWalk use measures, questionnaires, and a six-minute walk test. Patients used the application 78.8% (±28.2) of the prescribed duration and enjoyed it throughout the program. The application was considered “easy to use” by 75% of the patients. Pain, fatigue, and falls did not increase. Fear of falling decreased and quality of life improved. After the program, patients improved their gait parameters in the six-minute walk test without musical stimulation. BeatWalk is an easy to use, safe, and enjoyable musical application for individualized gait rehabilitation in PD. It increases “walk for exercise” duration thanks to high observance.This research was supported by a European grant: BeatHealth: Health and Wellness on the Beat for VC, DD, CL, AGi, VD, RV, EH, ED, ML, BB, and SB (EU FP7-ICT contract #610633)

    Effects of Facial Emotions on Social-motor Coordination in Schizophrenia

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    Schizophrenia patients are known to be impaired in their ability to process social information and to engage in social interactions. To understand better social cognition in schizophrenia, we investigate the links between these impairments. In this paper, we focus primarily on the influence of social feedback, such as facial emotions, on motor coordination during joint action. To investigate and quantify this influence, we exploited systematically-controlled social and nonsocial feedback provided by a humanoid robot. Humanoid robotics technology offers interactive designs and can precisely control the properties of the feedback provided during the interaction. In this work, a joint-action task with a robot is performed to investigate how social cognition is affected by cognitive capabilities and symptomatology. Results show that positive social feedback has a facilitatory effect on social-motor coordination in the control participants compared to nonsocial positive feedback. This facilitation effect is not present in schizophrenia patients, whose social-motor coordination is similar in social and nonsocial feedback conditions. This result is strongly correlated with performances in the Trail Making Test (TMT), which highlights the link between cognitive deficits and social-motor coordination in schizophrenia

    Beyond in-phase and anti-phase coordination in a model of joint action

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    In 1985, Haken, Kelso and Bunz proposed a system of coupled nonlinear oscillators as a model of rhythmic movement patterns in human bimanual coordination. Since then, the Haken–Kelso–Bunz (HKB) model has become a modelling paradigm applied extensively in all areas of movement science, including interpersonal motor coordination. However, all previous studies have followed a line of analysis based on slowly varying amplitudes and rotating wave approximations. These approximations lead to a reduced system, consisting of a single differential equation representing the evolution of the relative phase of the two coupled oscillators: the HKB model of the relative phase. Here we take a different approach and systematically investigate the behaviour of the HKB model in the full four-dimensional state space and for general coupling strengths. We perform detailed numerical bifurcation analyses and reveal that the HKB model supports previously unreported dynamical regimes as well as bistability between a variety of coordination patterns. Furthermore, we identify the stability boundaries of distinct coordination regimes in the model and discuss the applicability of our findings to interpersonal coordination and other joint action tasks

    International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

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    Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

    Dynamics of the locomotor–respiratory coupling at different frequencies

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    Changes in phase space during learning an unstable balance

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    International audienceSix participants learned to maintain an unstable balance on a stabilometer, during 6 consecutive days of practice (total of 90 trials). Lateral and angular variations of body segments and body center of mass were analysed, and their evolution over the learning period was compared to the changes in dimensional variables capturing the structure of the movement itself (embedding and correlation dimension, largest Lyapunov exponent). Results indicated that (i) learning occurred, (ii) was accompanied by persistence in the dimension of the movement, and (iii) by a reduction in chaotic (or stochastic) components. Compared to other results in the learning literature, these results suggest that dimensional changes over learning are task-specific

    Skills training in multimodal virtual environments

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