On-line Synergy Identification for Personalized Active Arm Prosthesis: a Feasibility Study

Garcia-Rosas, Ricardo; Tan, Ying; Oetomo, Denny; Manzie, Chris

doi:10.23919/acc.2018.8431310

Cited by 7 publications

(12 citation statements)

References 25 publications

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“…For the studies with elbow prostheses, 14 participants performed the protocol in a virtual environment to emulate amputation and prosthesis [58], [59]. The other studies in upper limb wearable robots were assessed by 30 healthy participants in total.…”

Section: Taskmentioning

confidence: 99%

“…With respect to upper limb wearable robots, the overview is different because of the tasks. In this case, mostly muscle activity [63], [67], [68], [69] or muscle synergy [58], [59], [62] are used as an objective function. Hamaya et al [61] was the only study that aimed at maximizing user preference by asking the participant preference level in each trial given the controller parameters.…”

Section: Reinforcement Learningmentioning

confidence: 99%

“…Control strategy where the joint torque or position are directly computed from joint angles or ground reaction forces. Garcia Rosas et al [58], [59], [62], computed the desired lower arm prosthesis position from the instant shoulder and upper arm angles. Hence, the control strategy was named "function of upper limb instant states", and its optimization control parameters characterize the shoulder-elbow kinematic synergy.…”

Section: ) Other Of Joints Instant Statesmentioning

confidence: 99%

“…An overview of the duration of the training sessions in the studies with upper limb wearable robots shows that 50% of the studies included some training trials (between 1 and 5) before testing [59], [63], [67], [69] and 25% of the studies stated that participants were allowed to have sufficient training time without providing details about the training protocol or time spent on training [58], [62]. The remaining 25% of the studies did not mention any previous training or familiarization.…”

Section: Experimental Protocols 1)mentioning

confidence: 99%

See 3 more Smart Citations

Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human–Robot Interaction: A Systematic Review

Díaz

Voss

Dillen

et al. 2023

IEEE Trans. Cybern.

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show abstract

Section: Taskmentioning

confidence: 99%

Section: Reinforcement Learningmentioning

confidence: 99%

Section: ) Other Of Joints Instant Statesmentioning

confidence: 99%

Section: Experimental Protocols 1)mentioning

confidence: 99%

See 2 more Smart Citations

Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human–Robot Interaction: A Systematic Review

Díaz

Voss

Dillen

et al. 2023

IEEE Trans. Cybern.

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“…Simultaneous controls have also been proposed without the use of ANNs, such as on-line optimization techniques in transhumeral amputees [10]. Wrist or elbow rotation could also be directly coupled to shoulder abduction [11].…”

Section: Trajectory Control -An Effective Strategy For Controlling Mu...mentioning

confidence: 99%

Trajectory Control–An Effective Strategy for Controlling Multi-DOF Upper Limb Prosthetic Devices

Gloumakov

Bimbo

Dollar

2022

IEEE Trans. Neural Syst. Rehabil. Eng.

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Despite great innovations in upper-extremity prosthetic hardware in recent decades, controlling a multiple joint upper limb prosthesis such as an elbow/wrist/hand system is still an open clinical challenge, in large part due to an insufficient number of control inputs available to users. While simultaneous control is in its early stages, the common control approach is sequential control, in which joints and grasps are driven one at a time. In this paper, we introduce and evaluate a concept we call trajectory control, that builds upon this approach, in which motions of the wrist, elbow, and shoulder DOFs (and subsets of them) are coupled into predefined sets of coordinated trajectories; to be selected by the user and driven with a single input variable. These trajectories were designed based on an earlier motion study of activities of daily life obtained from human demonstrations. We experimentally evaluate the efficacy of our approach through a human subjects study in which tasks are performed in a virtual environment. The results show that as device complexity increased (i.e. greater number of DOFs corresponding to more proximal amputations), participants were able to complete tasks faster with trajectory control while exhibiting similar levels of body compensation when compared to sequential and simultaneous control. Additionally, participants found trajectory control to be more intuitive and displayed more natural movement.

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The synergy complement control approach for seamless limb-driven prostheses

Kühn,

Hu,

Tödtheide

et al. 2024

Nat Mach Intell

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Limb-driven control allows for direct control by using residual limb movements rather than unnatural and complex muscle activation. Existing limb-driven methods simultaneously learn a variety of possible motions, ranging from a residual limb to entire arm motions, from human templates by relying on linear or nonlinear regression techniques. However, the map between a low-dimensional residual limb movement and high-dimensional total limb movement is highly underdetermined. Therefore, this complex, high-dimensional coordination problem cannot be accurately solved by treating it as a data-driven black box problem. Here we address this challenge by introducing the residual limb-driven control framework synergy complement control. Firstly, the residual limb drives a one-dimensional phase variable to simultaneously control the multiple joints of the prosthesis. Secondly, the resulting prosthesis motion naturally complements the movement of the residual limb by its synergy components. Furthermore, our framework adds information on contextual tasks and goals and allows for seamless transitions between these. Experimental validation was conducted using subjects with preserved arms employing an exo-prosthesis setup, and studies involving participants with and without limb differences in a virtual reality setup. The findings affirm that the restoration of lost coordinated synergy capabilities is reliably achieved through the utilization of synergy complement control with the prosthesis.

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On-line Synergy Identification for Personalized Active Arm Prosthesis: a Feasibility Study

Cited by 7 publications

References 25 publications

Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human–Robot Interaction: A Systematic Review

Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human–Robot Interaction: A Systematic Review

Trajectory Control–An Effective Strategy for Controlling Multi-DOF Upper Limb Prosthetic Devices

The synergy complement control approach for seamless limb-driven prostheses

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