Affiliations: Adaptive Systems Research Group, The University of Hertfordshire, Hertfordshire, UK | Centre for Rehabilitation and Engineering Studies, School of Mechanical and Systems Engineering, The University of Newcastle, Newcastle, UK
Note: [] Corresponding author: Dr Farshid Amirabdollahian, MIET, MIEEE, Adaptive Systems Research Group, The University of Hertfordshire, School of Computer Science, College Lane, Hatfield, Hertfordshire, AL10 9AB, UK. Tel.: +44 1707 286 125; Fax: +44 1707 284 303. E-mail: [email protected]
Abstract: Haptic and robotic technologies have the potential to provide assessment during interaction with humans. This manuscript presents our earlier research during the I-Match project where a haptic peg-in-hole test was used in order to compare between healthy volunteers' performance and those with neurological impairment. Subjects all performed a series of haptic virtual peg-in-hole tasks with varying degrees of difficulty determined by the hole diameter. Haptic instrument, Phantom Desktop 1.5, allowed for recording of biomechanical data which is used to present some variant features between the two subject groups. This paper analyses the placement time, maximum peg transfer velocity, collision forces recorded during peg placement and also insertion accuracy. The first three parameters showed statistically significant differences between the two groups while the last, insertion accuracy, showed insignificant differences (p = 0.152). This is thought to be due to the large clearance value between the smallest hole diameter and the peg. To identify differences between the haptic peg-in-hole and the established NHPT, we are currently in process of conducting a further experiment with a haptic replica of the NHPT test, in order to investigate effects resulting from addition of haptic force feedback compared to the original NHPT test, as well as allowing to explore influences caused by the 1 mm clearance value as originally proposed by Wade.Furthermore, in order to investigate if this method can identify differences between subjects with different neurological conditions, a larger group of subjects with neurological conditions such as stroke, multiple sclerosis, and traumatic brain injury is required to explore potency of this approach for identifying differences between these different conditions.
Keywords: Haptics, peg-in-hole, i-match, robotic for assessment, outcome measures
