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1.
IEEE Trans Haptics ; 15(1): 200-211, 2022.
Article in English | MEDLINE | ID: mdl-34529575

ABSTRACT

The objective of this paper is to develop and evaluate a directional vibrotactile feedback interface as a guidance tool for postural adjustments during work. In contrast to the existing active and wearable systems such as exoskeletons, we aim to create a lightweight and intuitive interface, capable of guiding its wearers towards more ergonomic and healthy working conditions. To achieve this, a vibrotactile device called ErgoTac is employed to develop three different feedback modalities that are able to provide a directional guidance at the body segments towards a desired pose. In addition, an evaluation is made to find the most suitable, comfortable, and intuitive feedback modality for the user. Therefore, these modalities are first compared experimentally on fifteen subjects wearing eight ErgoTac devices to achieve targeted arm and torso configurations. The most effective directional feedback modality is then evaluated on five subjects in a set of experiments in which an ergonomic optimisation module provides the optimised body posture while performing heavy lifting or forceful exertion tasks. The results yield strong evidence on the usefulness and the intuitiveness of one of the developed modalities in providing guidance towards ergonomic working conditions, by minimising the effect of an external load on body joints. We believe that the integration of such low-cost devices in workplaces can help address the well-known and complex problem of work-related musculoskeletal disorders.


Subject(s)
Ergonomics , Vibration , Feedback , Humans , Posture , Torso
2.
Front Robot AI ; 5: 89, 2018.
Article in English | MEDLINE | ID: mdl-33500968

ABSTRACT

This work presents a bio-inspired grasp stiffness control for robotic hands based on the concepts of Common Mode Stiffness (CMS) and Configuration Dependent Stiffness (CDS). Using an ellipsoid representation of the desired grasp stiffness, the algorithm focuses on achieving its geometrical features. Based on preliminary knowledge of the fingers workspace, the method starts by exploring the possible hand poses that maintain the grasp contacts on the object. This outputs a first selection of feasible grasp configurations providing the base for the CDS control. Then, an optimization is performed to find the minimum joint stiffness (CMS control) that would stabilize these grasps. This joint stiffness can be increased afterwards depending on the task requirements. The algorithm finally chooses among all the found stable configurations the one that results in a better approximation of the desired grasp stiffness geometry (CDS). The proposed method results in a reduction of the control complexity, needing to independently regulate the joint positions, but requiring only one input to produce the desired joint stiffness. Moreover, the usage of the fingers pose to attain the desired grasp stiffness results in a more energy-efficient configuration than only relying on the joint stiffness (i.e., joint torques) modifications. The control strategy is evaluated using the fully actuated Allegro Hand while grasping a wide variety of objects. Different desired grasp stiffness profiles are selected to exemplify several stiffness geometries.

3.
Front Neurorobot ; 11: 15, 2017.
Article in English | MEDLINE | ID: mdl-28367121

ABSTRACT

An emerging approach to design locomotion assistive devices deals with reproducing desirable biological principles of human locomotion. In this paper, we present a bio-inspired controller for locomotion assistive devices based on the concept of motor primitives. The weighted combination of artificial primitives results in a set of virtual muscle stimulations. These stimulations then activate a virtual musculoskeletal model producing reference assistive torque profiles for different locomotion tasks (i.e., walking, ascending stairs, and descending stairs). The paper reports the validation of the controller through a set of experiments conducted with healthy participants. The proposed controller was tested for the first time with a unilateral leg exoskeleton assisting hip, knee, and ankle joints by delivering a fraction of the computed reference torques. Importantly, subjects performed a track involving ground-level walking, ascending stairs, and descending stairs and several transitions between these tasks. These experiments highlighted the capability of the controller to provide relevant assistive torques and to effectively handle transitions between the tasks. Subjects displayed a natural interaction with the device. Moreover, they significantly decreased the time needed to complete the track when the assistance was provided, as compared to wearing the device with no assistance.

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