Shaping Human Movement Via Bimanually-Dependent Haptic Force Feedback

Overview

Journal World Haptics Conf

Publisher IEEE

Date 2024 Jan 15

PMID 38222039

Authors

Jacob R Boehm

Nicholas P Fey

Ann Majewicz Fey

Affiliations

Soon will be listed here.

Abstract

Haptic feedback can enhance training and performance of human operators; however, the design of haptic feedback for bimanual coordination in robot-assisted tasks (e.g., control of surgical robots) remains an open problem. In this study, we present four bimanually-dependent haptic force feedback conditions aimed at shaping bimanual movement according to geometric characteristics: the number of targets, direction, and symmetry. Haptic conditions include a virtual spring, damper, combination spring-damper, and dual springs placed between the hands. We evaluate the effects of these haptic conditions on trajectory shape, smoothness, and speed. We hypothesized that for subjects who perform worse with no haptic feedback (1) a spring will improve the shape of parallel trajectories, (2) a damper will improve the shape of point symmetric trajectories, (3) dual springs will improve the shape of trajectories with one target, and (4) a damper will improve smoothness for all trajectories. Hypotheses (1) and (2) were statistically supported at the < 0.001 level, but hypotheses (3) and (4) were not supported. Moreover, bimanually-dependent haptic feedback tended to improve shape accuracy for movements that subjects performed worse on under no haptic condition. Thus, bimanual haptic feedback based on geometric trajectory characteristics shows promise to improve performance in robot-assisted motor tasks.

References

Patton J, Stoykov M, Kovic M, Mussa-Ivaldi F . Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors. Exp Brain Res. 2005; 168(3):368-83. DOI: 10.1007/s00221-005-0097-8. View

Liu J, Cramer S, Reinkensmeyer D . Learning to perform a new movement with robotic assistance: comparison of haptic guidance and visual demonstration. J Neuroeng Rehabil. 2006; 3:20. PMC: 1569852. DOI: 10.1186/1743-0003-3-20. View

Shadmehr R, Mussa-Ivaldi F . Adaptive representation of dynamics during learning of a motor task. J Neurosci. 1994; 14(5 Pt 2):3208-24. PMC: 6577492. View

van der Meijden O, Schijven M . The value of haptic feedback in conventional and robot-assisted minimal invasive surgery and virtual reality training: a current review. Surg Endosc. 2009; 23(6):1180-90. PMC: 2686803. DOI: 10.1007/s00464-008-0298-x. View

Criscimagna-Hemminger S, Bastian A, Shadmehr R . Size of error affects cerebellar contributions to motor learning. J Neurophysiol. 2010; 103(4):2275-84. PMC: 2853280. DOI: 10.1152/jn.00822.2009. View

Held J, Klaassen B, van Beijnum B, Luft A, Veltink P . Usability Evaluation of a VibroTactile Feedback System in Stroke Subjects. Front Bioeng Biotechnol. 2017; 4:98. PMC: 5263126. DOI: 10.3389/fbioe.2016.00098. View

Hogan N, Sternad D . Sensitivity of smoothness measures to movement duration, amplitude, and arrests. J Mot Behav. 2009; 41(6):529-34. PMC: 3470860. DOI: 10.3200/35-09-004-RC. View

Rosenbaum D, Dawson A, Challis J . Haptic tracking permits bimanual independence. J Exp Psychol Hum Percept Perform. 2006; 32(5):1266-75. DOI: 10.1037/0096-1523.32.5.1266. View

Boehm J, Fey N, Majewicz A . Inherent Kinematic Features of Dynamic Bimanual Path Following Tasks. IEEE Trans Hum Mach Syst. 2022; 50(6):613-622. PMC: 9555814. DOI: 10.1109/thms.2020.3016084. View

10.

Staude G . Precise onset detection of human motor responses using a whitening filter and the log-likelihood-ratio test. IEEE Trans Biomed Eng. 2001; 48(11):1292-305. DOI: 10.1109/10.959325. View

11.

Klein J, Spencer S, Reinkensmeyer D . Breaking it down is better: haptic decomposition of complex movements aids in robot-assisted motor learning. IEEE Trans Neural Syst Rehabil Eng. 2012; 20(3):268-75. PMC: 4015469. DOI: 10.1109/TNSRE.2012.2195202. View

12.

Shirota C, Jansa J, Diaz J, Balasubramanian S, Mazzoleni S, Borghese N . On the assessment of coordination between upper extremities: towards a common language between rehabilitation engineers, clinicians and neuroscientists. J Neuroeng Rehabil. 2016; 13(1):80. PMC: 5017057. DOI: 10.1186/s12984-016-0186-x. View