scholarly journals Psycho-physiological assessment of a prosthetic hand sensory feedback system based on an auditory display: a preliminary study

2012 ◽  
Vol 9 (1) ◽  
pp. 33 ◽  
Author(s):  
Jose Gonzalez ◽  
Hirokazu Soma ◽  
Masashi Sekine ◽  
Wenwei Yu
1996 ◽  
Vol 116 (11) ◽  
pp. 1246-1251 ◽  
Author(s):  
Ryuhei Okuno ◽  
Masaki Yoshida ◽  
Takanori Uchiyama ◽  
Kenzo Akazawa

2015 ◽  
Vol 32 (10) ◽  
pp. 851-856
Author(s):  
Ju-Hwan Bae ◽  
Sung Yoon Jung ◽  
Shinki Kim ◽  
Museong Mun ◽  
Chang-Yong Ko

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric J. Earley ◽  
Reva E. Johnson ◽  
Jonathon W. Sensinger ◽  
Levi J. Hargrove

AbstractAccurate control of human limbs involves both feedforward and feedback signals. For prosthetic arms, feedforward control is commonly accomplished by recording myoelectric signals from the residual limb to predict the user’s intent, but augmented feedback signals are not explicitly provided in commercial devices. Previous studies have demonstrated inconsistent results when artificial feedback was provided in the presence of vision; some studies showed benefits, while others did not. We hypothesized that negligible benefits in past studies may have been due to artificial feedback with low precision compared to vision, which results in heavy reliance on vision during reaching tasks. Furthermore, we anticipated more reliable benefits from artificial feedback when providing information that vision estimates with high uncertainty (e.g. joint speed). In this study, we test an artificial sensory feedback system providing joint speed information and how it impacts performance and adaptation during a hybrid positional-and-myoelectric ballistic reaching task. We found that overall reaching errors were reduced after perturbed control, but did not significantly improve steady-state reaches. Furthermore, we found that feedback about the joint speed of the myoelectric prosthesis control improved the adaptation rate of biological limb movements, which may have resulted from high prosthesis control noise and strategic overreaching with the positional control and underreaching with the myoelectric control. These results provide insights into the relevant factors influencing the improvements conferred by artificial sensory feedback.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1173
Author(s):  
Mingxiao Liu ◽  
Samuel Wilder ◽  
Sean Sanford ◽  
Soha Saleh ◽  
Noam Y. Harel ◽  
...  

Sensory feedback from wearables can be effective to learn better movement through enhanced information and engagement. Facilitating greater user cognition during movement practice is critical to accelerate gains in motor function during rehabilitation following brain or spinal cord trauma. This preliminary study presents an approach using an instrumented glove to leverage sense of agency, or perception of control, to provide training feedback for functional grasp. Seventeen able-bodied subjects underwent training and testing with a custom-built sensor glove prototype from our laboratory. The glove utilizes onboard force and flex sensors to provide inputs to an artificial neural network that predicts achievement of “secure” grasp. Onboard visual and audio feedback was provided during training with progressively shorter time delay to induce greater agency by intentional binding, or perceived compression in time between an action (grasp) and sensory consequence (feedback). After training, subjects demonstrated a significant reduction (p < 0.05) in movement pathlength and completion time for a functional task involving grasp-move-place of a small object. Future work will include a model-based algorithm to compute secure grasp, virtual reality immersion, and testing with clinical populations.


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