Grasping Embodiment: Haptic Feedback for Artificial Limbs

Moore, Christopher A.; Corbin, Sierra F.; Mayr, Riley; Shockley, Kevin; Silva, Paula L.; Lorenz, Tamara

doi:10.3389/fnbot.2021.662397

Cited by 10 publications

(3 citation statements)

References 49 publications

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“…Understanding such processes is required for designing appropriate strategies to enhance the embodiment of an artificial limb. First of all, it must be said that daily prosthetic practice, individual characteristics (like the cause of limb absence), and multisensory feedback congruency play fundamental roles in this process, which does not necessarily require cosmetic improvements or specific control patterns (body-powered or myoelectric) (Dornfeld et al 2016, Engdahl et al 2020b, Moore et al 2021, Zbinden et al 2021. Embodiment training strategies can also be explored in virtual and augmented settings (Barresi et al 2021), even if the generalization of their effects to actual prostheses must be investigated.…”

Section: Toward User-centered Upper Limb Prostheticsmentioning

confidence: 99%

Active upper limb prostheses: a review on current state and upcoming breakthroughs

et al. 2023

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The journey of a prosthetic user is characterized by the opportunities and the limitations of a device that should enable activities of daily living (ADL). In particular, experiencing a bionic hand as a functional (and, advantageously, embodied) limb constitutes the premise for promoting the practice in using the device, mitigating the risk of its abandonment. In order to achieve such a result, different aspects need to be considered for making the artificial limb an effective solution to accomplish activities of daily living. According to such a perspective, this review aims at presenting the current issues and at envisioning the upcoming breakthroughs in upper limb prosthetic devices. We first define the sources of input and feedback involved in the system control (at user-level and device-level), alongside the related algorithms used in signal analysis. Moreover, the paper focuses on the user-centered design challenges and strategies that guide the implementation of novel solutions in this area in terms of technology acceptance, embodiment, and, in general, human-machine integration based on co-adaptive processes. We here provide the readers (belonging to the target communities of researchers, designers, developers, clinicians, industrial stakeholders, and end-users) with an overview of the state-of-the-art and the potential innovations in bionic hands features, hopefully promoting interdisciplinary efforts for solving current issues of ULPs. The integration of different perspectives should be the premise to a transdisciplinary intertwining leading to a truly holistic comprehension and improvement of the bionic hands design. Overall, this paper aims to move the boundaries in prosthetic innovation beyond the development of a tool and towards the engineering of human-centered artificial limbs.

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Section: Toward User-centered Upper Limb Prostheticsmentioning

confidence: 99%

Active upper limb prostheses: a review on current state and upcoming breakthroughs

et al. 2023

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“…In this context, the research of user experience or improvement measures such as artificial feedback is scarce. Vibrotactile feedback is a commonly applied method to simplify the usage of electric protheses or smart devices (Antfolk et al, 2013;Moore, 2021). For this, the feedback stimulus has to be well adjusted and perceivable and must be easy to assign to the corresponding event (Choi and Kuchenbecker, 2013).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of precision, accuracy and threshold for the design of vibrotactile feedback in eye tracking applications

Fischer

Wendt

Stiglmeier

et al. 2023

J. Sens. Sens. Syst.

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Abstract. Novel approaches for the design of assistive technology controls propose the usage of eye tracking devices such as for smart wheelchairs and robotic arms. The advantages of artificial feedback, especially vibrotactile feedback, as opposed to their use in prostheses, have not been sufficiently explored. Vibrotactile feedback reduces the cognitive load on the visual and auditory channel. It provides tactile sensation, resulting in better use of assistive technologies. In this study the impact of vibration on the precision and accuracy of a head-worn eye tracking device is investigated. The presented system is suitable for further research in the field of artificial feedback. Vibration was perceivable for all participants, yet it does not produce any significant deviations in precision and accuracy.

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“…Often, no reasoning is given within the design of the feedback systems for the final placement of the stimulators. Some work has reported ideal placement of vibrating actuators [29,30]. Stephens-Fripp et al tested the just notable difference (JNS) at two locations with a mechanotactile system [31].…”

Section: Introductionmentioning

confidence: 99%

Experimental Evaluation of a Hybrid Sensory Feedback System for Haptic and Kinaesthetic Perception in Hand Prostheses

Sariyildiz,

Hanss,

Zhou

et al. 2023

Sensors

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This study proposes a new hybrid multi-modal sensory feedback system for prosthetic hands that can provide not only haptic and proprioceptive feedback but also facilitate object recognition without the aid of vision. Modality-matched haptic perception was provided using a mechanotactile feedback system that can proportionally apply the gripping force through the use of a force controller. A vibrotactile feedback system was also employed to distinguish four discrete grip positions of the prosthetic hand. The system performance was evaluated with a total of 32 participants in three different experiments (i) haptic feedback, (ii) proprioceptive feedback and (iii) object recognition with hybrid haptic-proprioceptive feedback. The results from the haptic feedback experiment showed that the participants’ ability to accurately perceive applied force depended on the amount of force applied. As the feedback force was increased, the participants tended to underestimate the force levels, with a decrease in the percentage of force estimation. Of the three arm locations (forearm volar, forearm ventral and bicep), and two muscle states (relaxed and tensed) tested, the highest accuracy was obtained for the bicep location in the relaxed state. The results from the proprioceptive feedback experiment showed that participants could very accurately identify four different grip positions of the hand prosthesis (i.e., open hand, wide grip, narrow grip, and closed hand) without a single case of misidentification. In experiment 3, participants could identify objects with different shapes and stiffness with an overall high success rate of 90.5% across all combinations of location and muscle state. The feedback location and muscle state did not have a significant effect on object recognition accuracy. Overall, our study results indicate that the hybrid feedback system may be a very effective way to enrich a prosthetic hand user’s experience of the stiffness and shape of commonly manipulated objects.

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Grasping Embodiment: Haptic Feedback for Artificial Limbs

Cited by 10 publications

References 49 publications

Active upper limb prostheses: a review on current state and upcoming breakthroughs

Active upper limb prostheses: a review on current state and upcoming breakthroughs

Evaluation of precision, accuracy and threshold for the design of vibrotactile feedback in eye tracking applications

Experimental Evaluation of a Hybrid Sensory Feedback System for Haptic and Kinaesthetic Perception in Hand Prostheses

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