Gaze anticipation during human locomotion

Bernardin, Delphine; Kadone, Hideki; Bennequin, Daniel; Sugar, Thomas G.; Zaoui, Mohamed; Berthoz, Alain

doi:10.1007/s00221-012-3241-2

Cited by 58 publications

(52 citation statements)

References 44 publications

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“…It was shown in [15] that head rotation immobilisation resulted in anticipatory trunk rotations and reduction of stability in trunk orientation during turning. Similar results were reported on gaze-head-trunk turning anticipatory behaviour in walking and standing [1,4,[14][15][16][17]19].…”

Section: Introductionsupporting

confidence: 87%

Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance

2017

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Many wearable lower-limb robots for walking assistance have been developed in recent years. However, it remains unclear how they can be commanded in an intuitive and efficient way by their user. In particular, providing robotic assistance to neurologically impaired individuals in turning remains a significant challenge. The control should be safe to the users and their environment, yet yield sufficient performance and enable natural human-machine interaction. Here, we propose using the head and trunk anticipatory behaviour in order to detect the intention to turn in a natural, non-intrusive way, and use it for triggering turning movement in a robot for walking assistance. We therefore study head and trunk orientation during locomotion of healthy adults, and investigate upper body anticipatory behaviour during turning. The collected walking and turning kinematics data are clustered using the k-means algorithm and cross-validation tests and k-nearest neighbours method are used to evaluate the performance of turning detection during locomotion. Tests with seven subjects exhibited accurate turning detection. Head anticipated turning by more than 400-500 ms in average across all subjects. Overall, the proposed method detected turning 300 ms after its initiation and 1230 ms before the turning movement was completed. Using head anticipatory behaviour enabled to detect turning faster by about 100 ms, compared to turning detection using only pelvis orientation measurements. Finally, it was demonstrated that the proposed turning detection can improve the quality of human-robot interaction by improving the control accuracy and transparency. PAPEROriginal content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence.

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Section: Introductionsupporting

confidence: 87%

Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance

2017

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“…Head yaw anticipates heading and body yaw. In other words, subjects tend to turn their head towards the direction of the turn before the turn begins (Bernardin et al 2012;Kadone et al 2010). This kind of behavior is not generated by a feedback mechanism as it begins before the turn takes place.…”

Section: Head Stabilization In Humansmentioning

confidence: 94%

Head stabilization in a humanoid robot: models and implementations

et al. 2016

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Neuroscientific studies show that humans tend to stabilize their head orientation, while accomplishing a locomotor task. This is beneficial to image stabilization and in general to keep a reference frame for the body. In robotics, too, head stabilization during robot walking provides advantages in robot vision and gaze-guided locomotion. In order to obtain the head movement behaviors found in human walk, it is necessary and sufficient to be able to control the orientation (roll, pitch and yaw) of the head in space. Based on these principles, three controllers have been designed. We developed two classic robotic controllers, an inverse kinematics based controller, an inverse kinematics differential controller and a bio-inspired adaptive controller based on feedback error learning. The controllers use the inertial feedback from a IMU sensor and control neck joints in order to align the head orientation with the global orientation reference. We present the results for the head stabilization controllers, on two sets of experiments, validating the robustness of the proposed control methods. In particular, we focus our analysis on the effectiveness of the bio-inspired adaptive controller against the classic robotic controllers. The first set of experiments, tested on a simulated robot, focused on the controllers response to a set of disturbance frequencies and a step function. The other set of experiments were carried out on the SABIAN robot, where these controllers were implemented in conjunction with a model of the vestibulo-ocular reflex (VOR) and opto-kinetic reflex (OKR). Such a setup permits to compare the performances of the considered head stabilization controllers in conditions which mimic the human stabilization mechanisms composed of the joint effect of VOR, OKR and stabilization of the head. The results show that the bio-inspired adaptive controller is more beneficial for the stabilization of the head in tasks involving a sinusoidal torso disturbance, and it shows comparable performances to the inverse kinematics controller in case of the step response and the locomotion experiments conducted on the real robot

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“…Statistical analysis has been carried out with R 2.2.2 (http://www.R-project.org). Body motion capture data were Butterworth filtered with a cutoff frequency of 15 Hz (Bernardin et al, 2012, with a zero-phase procedure that did not induce lag in the signal). For each trial, three phases were considered: (1) the waiting phase , from the first fixation on the screen to the audio signal indicating the direction to follow, (2) the preparation phase , i.e., the subject started walking (12 cm from the starting point, t = 0, Figure 2C), and (3) the walking phase , from walk initiation to reaching 40 cm before the aimed door position or 85 cm before the screen (center, t = T, Figure 2C).…”

Section: Methodsmentioning

confidence: 99%

Adaptive Gaze Strategies for Locomotion with Constricted Visual Field

Authié

Berthoz

Sahel

et al. 2017

Front. Hum. Neurosci.

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In retinitis pigmentosa (RP), loss of peripheral visual field accounts for most difficulties encountered in visuo-motor coordination during locomotion. The purpose of this study was to accurately assess the impact of peripheral visual field loss on gaze strategies during locomotion, and identify compensatory mechanisms. Nine RP subjects presenting a central visual field limited to 10–25° in diameter, and nine healthy subjects were asked to walk in one of three directions—straight ahead to a visual target, leftward and rightward through a door frame, with or without obstacle on the way. Whole body kinematics were recorded by motion capture, and gaze direction in space was reconstructed using an eye-tracker. Changes in gaze strategies were identified in RP subjects, including extensive exploration prior to walking, frequent fixations of the ground (even knowing no obstacle was present), of door edges, essentially of the proximal one, of obstacle edge/corner, and alternating door edges fixations when approaching the door. This was associated with more frequent, sometimes larger rapid-eye-movements, larger movements, and forward tilting of the head. Despite the visual handicap, the trajectory geometry was identical between groups, with a small decrease in walking speed in RPs. These findings identify the adaptive changes in sensory-motor coordination, in order to ensure visual awareness of the surrounding, detect changes in spatial configuration, collect information for self-motion, update the postural reference frame, and update egocentric distances to environmental objects. They are of crucial importance for the design of optimized rehabilitation procedures.

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Gaze anticipation during human locomotion

Cited by 58 publications

References 44 publications

Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance

Anticipatory detection of turning in humans for intuitive control of robotic mobility assistance

Head stabilization in a humanoid robot: models and implementations

Adaptive Gaze Strategies for Locomotion with Constricted Visual Field

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