Visuomotor behaviours when using a myoelectric prosthesis

Sobuh, Mohammad; Kenney, Laurence; Galpin, Adam; Thies, Sibylle B.; McLaughlin, Jane; Kulkarni, Jai; Kyberd, Peter

doi:10.1186/1743-0003-11-72

Cited by 79 publications

(106 citation statements)

References 29 publications

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“…This suggests that manipulating the feedback available to actors should fundamentally alter eye gaze. Recent studies with users of prosthetic limbs (Sobuh et al, 2014) and participants controlling artificial hands (Parr et al, 2017) confirm that this is the case-with reduced proprioceptive and tactile feedback, fixations to the hand and object in flight are massively increased. Put into the theoretical framework, these prolonged fixations to the hand and object during interaction arise because without sensory feedback, a lack of confidence in the object manipulation essentially freezes the landscape, leaving the object as the most relevant location and preventing the eyes from moving ahead to the drop-off site.…”

Section: Discussionmentioning

confidence: 96%

Using synchronized eye and motion tracking to determine high-precision eye-movement patterns during object-interaction tasks

et al. 2018

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This study explores the role that vision plays in sequential object interactions. We used a head-mounted eye tracker and upper-limb motion capture to quantify visual behavior while participants performed two standardized functional tasks. By simultaneously recording eye and motion tracking, we precisely segmented participants' visual data using the movement data, yielding a consistent and highly functionally resolved data set of real-world object-interaction tasks. Our results show that participants spend nearly the full duration of a trial fixating on objects relevant to the task, little time fixating on their own hand when reaching toward an object, and slightly more time-although still very little-fixating on the object in their hand when transporting it. A consistent spatial and temporal pattern of fixations was found across participants. In brief, participants fixate an object to be picked up at least half a second before their hand arrives at the object and stay fixated on the object until they begin to transport it, at which point they shift their fixation directly to the drop-off location of the object, where they stay fixated until the object is successfully released. This pattern provides additional evidence of a common system for the integration of vision and object interaction in humans, and is consistent with theoretical frameworks hypothesizing the distribution of attention to future action targets as part of eye and hand-movement preparation. Our results thus aid the understanding of visual attention allocation during planning of object interactions both inside and outside the field of view.

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Section: Discussionmentioning

confidence: 96%

Using synchronized eye and motion tracking to determine high-precision eye-movement patterns during object-interaction tasks

et al. 2018

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“…This visual feedback delay, combined with the lack of proprioception, influences the operation strategy. For example, when using a prosthetic arm to complete simple motor tasks such as reaching and grasping, subjects typically fixate on the prosthesis rather than the object of interest, even when significant training is provided (Sobuh et al 2014). This is in contrast to normal movement, during which eye movements are directed to the parts of the environment critical for action completion rather than the hand movement (Flanagan and Johansson 2003;Johansson et al 2001).…”

Section: Discussionmentioning

confidence: 99%

The absence or temporal offset of visual feedback does not influence adaptation to novel movement dynamics

McKenna

Bray

Zhou

et al. 2017

Journal of Neurophysiology

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Delays in transmitting and processing sensory information require correctly associating delayed feedback to issued motor commands for accurate error compensation. The flexibility of this alignment between motor signals and feedback has been demonstrated for movement recalibration to visual manipulations, but the alignment dependence for adapting movement dynamics is largely unknown. Here we examined the effect of visual feedback manipulations on force-field adaptation. Three subject groups used a manipulandum while experiencing a lag in the corresponding cursor motion (0, 75, or 150 ms). When the offset was applied at the start of the session (continuous condition), adaptation was not significantly different between groups. However, these similarities may be due to acclimation to the offset before motor adaptation. We tested additional subjects who experienced the same delays concurrent with the introduction of the perturbation (abrupt condition). In this case adaptation was statistically indistinguishable from the continuous condition, indicating that acclimation to feedback delay was not a factor. In addition, end-point errors were not significantly different across the delay or onset conditions, but end-point correction (e.g., deceleration duration) was influenced by the temporal offset. As an additional control, we tested a group of subjects who performed without visual feedback and found comparable movement adaptation results. These results suggest that visual feedback manipulation (absence or temporal misalignment) does not affect adaptation to novel dynamics, independent of both acclimation and perceptual awareness. These findings could have implications for modeling how the motor system adjusts to errors despite concurrent delays in sensory feedback information. A temporal offset between movement and distorted visual feedback (e.g., visuomotor rotation) influences the subsequent motor recalibration, but the effects of this offset for altered movement dynamics are largely unknown. Here we examined the influence of ) delayed and) removed visual feedback on the adaptation to novel movement dynamics. These results contribute to understanding of the control strategies that compensate for movement errors when there is a temporal separation between motion state and sensory information.

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“…Despite the increasing sophistication of these devices, they still provide less than 50% of the capability of an intact limb [1,2], impose a high cognitive burden that results in fatigue and frustration [3], and are therefore frequently rejected [4]. The nature of this cognitive burden has recently been explored indirectly by examining disruption to visuomotor behaviours during prosthetic hand use [5,6]. For example, Parr et al [7] showed that when using a myoelectric prosthetic hand simulator, participants directed a greater amount of visual attention towards the prosthesis and objects being manipulated by it.…”

Section: Introductionmentioning

confidence: 99%

Visual attention, EEG alpha power and T7-Fz connectivity are implicated in prosthetic hand control and can be optimized through gaze training

Parr

Vine

Wilson

et al. 2019

J NeuroEngineering Rehabil

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Background: Prosthetic hands impose a high cognitive burden on the user that often results in fatigue, frustration and prosthesis rejection. However, efforts to directly measure this burden are sparse and little is known about the mechanisms behind it. There is also a lack of evidence-based training interventions designed to improve prosthesis hand control and reduce the mental effort required to use them. In two experiments, we provide the first direct evaluation of this cognitive burden using measurements of EEG and eye-tracking (Experiment 1), and then explore how a novel visuomotor intervention (gaze training; GT) might alleviate it (Experiment 2). Methods: In Experiment 1, able-bodied participants (n = 20) lifted and moved a jar, first using their anatomical hand and then using a myoelectric prosthetic hand simulator. In experiment 2, a GT group (n = 12) and a movement training (MT) group (n = 12) trained with the prosthetic hand simulator over three one hour sessions in a picking up coins task, before returning for retention, delayed retention and transfer tests. The GT group received instruction regarding how to use their eyes effectively, while the MT group received movement-related instruction typical in rehabilitation. Results: Experiment 1 revealed that when using the prosthetic hand, participants performed worse, exhibited spatial and temporal disruptions to visual attention, and exhibited a global decrease in EEG alpha power (8-12 Hz), suggesting increased cognitive effort. Experiment 2 showed that GT was the more effective method for expediting prosthesis learning, optimising visual attention, and lowering conscious controlas indexed by reduced T7-Fz connectivity. Whilst the MT group improved performance, they did not reduce hand-focused visual attention and showed increased conscious movement control. The superior benefits of GT transferred to a more complex tea-making task. Conclusions: These experiments quantify the visual and cortical mechanisms relating to the cognitive burden experienced during prosthetic hand control. They also evidence the efficacy of a GT intervention that alleviated this burden and promoted better learning and transfer, compared to typical rehabilitation instructions. These findings have theoretical and practical implications for prosthesis rehabilitation, the development of emerging prosthesis technologies and for the general understanding of human-tool interactions.

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Visuomotor behaviours when using a myoelectric prosthesis

Cited by 79 publications

References 29 publications

Using synchronized eye and motion tracking to determine high-precision eye-movement patterns during object-interaction tasks

Using synchronized eye and motion tracking to determine high-precision eye-movement patterns during object-interaction tasks

The absence or temporal offset of visual feedback does not influence adaptation to novel movement dynamics

Visual attention, EEG alpha power and T7-Fz connectivity are implicated in prosthetic hand control and can be optimized through gaze training

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