Abstract
This study investigated how modifications in the display of a computer trace under user control of grasp forces can co-modulate agency (perception of control) and performance of grasp on rigid and compliant surfaces. We observed positive correlation (p < 0.01) between implicit agency, measured from time-interval estimation for intentional binding, and grasp performance, measured by force-tracking error, across varying control modes for each surface type. The implications of this work are design directives for cognition-centered device interfaces for rehabilitation of grasp after neurotraumas such as spinal cord and brain injuries while considering if grasp interaction is rigid or compliant. These device interfaces should increase user integration to virtual reality training and powered assistive devices such as exoskeletons and prostheses. The modifications in control modes for this study included changes in force magnitude, addition of mild noise, and a measure of automation. Significant differences (p < 0.001) were observed for each surface type across control modes with metrics for implicit agency, performance, and grasp control efficiency. Explicit agency, measured from user survey responses, did not exhibit significant variations in this study, suggesting implicit measures of agency are needed for identifying co-modulation with grasp performance. Grasp on the compliant surface resulted in greater dependence of performance on agency and increases in agency and performance with the addition of mild noise. Noise in conjunction with perceived freedom at a flexible surface may have amplified visual feedback responses. Introducing automation in control decreased agency and performance for both surfaces, suggesting the value in continuous user control of grasp. In conclusion, agency and performance of grasp can be co-modulated across varying modes of control, especially for compliant grasp actions. Future studies should consider reliable measures of implicit agency, including physiological recordings, to automatically adapt rehabilitation interfaces for better cognitive engagement and to accelerate functional outcomes.
Highlights
The healthy hand is capable of exquisite grasp force control in manipulating objects during activities of daily living (Hubbard et al, 2009)
The control modes examined in this study considered modifications in gain, addition of mild noise, and automation
Significant differences (p < 0.05) in force variability between surfaces were observed in the lateral and normal dimensions. In this investigation of a precision grasp force task, we observed a positive relationship between implicit agency and performance and that both metrics can vary with modes of control
Summary
The healthy hand is capable of exquisite grasp force control in manipulating objects during activities of daily living (Hubbard et al, 2009). Following neuromuscular traumas, such as spinal cord or brain injury, it is critical to rehabilitate grasp function for maintaining quality of life. The primary objective with assistive or rehabilitative technologies is to enhance control of the hand and increase functional ability to perform manual tasks. Regardless of the rehabilitation approach, the person should be cognitively engaged and integrated with the therapeutic platform or the assistive device (Moore and Fletcher, 2012; Nataraj, 2017; Nataraj et al, 2020a,b,c). Improved perception of involvement and control of movement should better ensure continued participation and positive functional outcomes (Doyle, 2002; Behrman et al, 2005)
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