A Muscular and Cerebral Physiological Indices Assessment for Stress Measuring during Virtual Wheelchair Guidance.

The work presented in this manuscript has the purpose to assess the relationship between human factors and physiological indices. We discuss the relationship between stress as human factor and cerebral and muscular signals as features. Ten male paraplegic, right-handed subjects were volunteers for the experiment (mean age 34 ±6). They drove a virtual wheelchair in an indoor environment. They filled five missions where, in each one, an environmental parameter was changed. Meanwhile, they were equipped with Electromyography (EMG) sensors and Electroencephalography (EEG). Frequency and temporal features were filtered and extracted. Principal component analysis (PCA), Fisher's tests, repeated measure Anova and post hoc Tukey test (α = 0.05) were implemented for statistics. Environmental modifications are subject to induce stress, which impacts muscular and cerebral activities. While the time pressure parameter was the most influent, the transition from static to moving obstacles (avatars), tends to have a significant impact on stress levels. However, adding more moving obstacles did not show any impact. A synchronization factor was noticed between cerebral and muscular features in higher stress levels. Further examination is needed to assess EEG reliability in these situations.

Mental fatigue level detection based on event related and visual evoked potentials features fusion in virtual indoor environment.

The purpose of this work is to set up a model that can estimate the mental fatigue of users based on the fusion of relevant features extracted from Positive 300 (P300) and steady state visual evoked potentials (SSVEP) measured by electroencephalogram. To this end, an experimental protocol describes the induction of P300, SSVEP and mental workload (which leads to mental fatigue by varying time-on-task) in different scenarios where environmental artifacts are controlled (obstacles number, obstacles velocities, ambient luminosity). Ten subjects took part in the experiment (with two suffering from cerebral palsy). Their mission is to navigate along a corridor from a starting point A to a goal point B where specific flickering stimuli are introduced to perform the P300 task. On the other hand, SSVEP task is elicited thanks to 10 Hz flickering lights. Correlated features are considered as inputs to fusion block which estimates mental workload. In order to deal with uncertainties and heterogeneity of P300 and SSVEP features, Dempster-Shafer (D-S) evidential reasoning is introduced. As the goal is to assess the reliability for the estimation of mental fatigue levels, D-S is compared to multi layer perception and linear discriminant analysis. The results show that D-S globally outperforms the other classifiers (although its performance significantly decreases between healthy and palsied groups). Finally we discuss the feasibility of such a fusion proposal in real life situation.

Qualitative adaptive reward learning with success failure maps: applied to humanoid robot walking.

In the human brain, rewards are encoded in a flexible and adaptive way after each novel stimulus. Neurons of the orbitofrontal cortex are the key reward structure of the brain. Neurobiological studies show that the anterior cingulate cortex of the brain is primarily responsible for avoiding repeated mistakes. According to vigilance threshold, which denotes the tolerance to risks, we can differentiate between a learning mechanism that takes risks and one that averts risks. The tolerance to risk plays an important role in such a learning mechanism. Results have shown the differences in learning capacity between risk-taking and risk-avert behaviors. These neurological properties provide promising inspirations for robot learning based on rewards. In this paper, we propose a learning mechanism that is able to learn from negative and positive feedback with reward coding adaptively. It is composed of two phases: evaluation and decision making. In the evaluation phase, we use a Kohonen self-organizing map technique to represent success and failure. Decision making is based on an early warning mechanism that enables avoiding repeating past mistakes. The behavior to risk is modulated in order to gain experiences for success and for failure. Success map is learned with adaptive reward that qualifies the learned task in order to optimize the efficiency. Our approach is presented with an implementation on the NAO humanoid robot, controlled by a bioinspired neural controller based on a central pattern generator. The learning system adapts the oscillation frequency and the motor neuron gain in pitch and roll in order to walk on flat and sloped terrain, and to switch between them.

Walking, paddling, waddling: 3D kinematics anatidae locomotion (Callonetta leucophrys).

Walking and paddling motions were studied in a semiaquatic bird, the ringed teal (Callonetta leucophrys), to investigate the motions associated with movements in two environments with radically divergent physical properties. A three-dimensional (3D) kinematic reconstruction based on nonsynchronous biplanar cineradiographic data was used to quantify the 3D trajectories of the body and hind limb segments. Our study revealed that two subsystems interact to provide propulsion in water and on land. During paddling, the trunk, the femur, and the tibiotarsus are in a stable position and play the role of the hull. The femur and tibiotarsus are positioned laterally and parasagittaly and the intertarsal joint is fixed and positioned caudally allowing large amplitude movements of the "paddle" (tarsometatarsus and palmate foot). During walking, the center of mass is held above the medially oriented foot, providing stability during the single support phase. During stance, the foot is medially oriented because of the lateral and parasagittal positions of the tibiotarsus and tarsometatarsus during both walking and paddling. This position of the foot during walking imposes trunk translation and results in the typical waddling motion of Anatidae. This study provides new insights into how waddling motion relates to semiaquatic birds' ability to move in both terrestrial and aquatic environments.

Bird terrestrial locomotion as revealed by 3D kinematics.

Most birds use at least two modes of locomotion: flying and walking (terrestrial locomotion). Whereas the wings and tail are used for flying, the legs are mainly used for walking. The role of other body segments remains, however, poorly understood. In this study, we examine the kinematics of the head, the trunk, and the legs during terrestrial locomotion in the quail (Coturnix coturnix). Despite the trunk representing about 70% of the total body mass, its function in locomotion has received little scientific interest to date. This prompted us to focus on its role in terrestrial locomotion. We used high-speed video fluoroscopic recordings of quails walking at voluntary speeds on a trackway. Dorso-ventral and lateral views of the motion of the skeletal elements were recorded successively and reconstructed in three dimensions using a novel method based on the temporal synchronisation of both views. An analysis of the trajectories of the body parts and their coordination showed that the trunk plays an important role during walking. Moreover, two sub-systems participate in the gait kinematics: (i) the integrated 3D motion of the trunk and thighs allows for the adjustment of the path of the centre of mass; (ii) the motion of distal limbs transforms the alternating forward motion of the feet into a continuous forward motion at the knee and thus assures propulsion. Finally, head bobbing appears qualitatively synchronised to the movements of the trunk. An important role for the thigh muscles in generating the 3D motion of the trunk is suggested by an analysis of the pelvic anatomy.