Robot-Aided Bimanual Assessment of Wrist Proprioception in People with Acute Stroke

Abstract

Proprioception the sense of body awareness is frequently impaired after stroke. Clinical tests used to detect proprioceptive impairments require substantial amounts of time and lack sensitivity. In contrast, robotic devices proprioceptive acuity. We here present results of a robot-aided bimanual test for wrist proprioception. Ten acute stroke patients with hemiplegic arm weakness and ten healthy subjects, participated to the experiment. Subjects actively moved the wrist of the unaffected limb to match the reference position of the affected wrist, which was passively displaced by the robot to a target across six directions.Our results are as follows. First, healthy individuals showed no effect of hand dominance. No acuity differences were found for between dominant or non-dominant hand. Second, the matching error varied significantly across movement directions. Third, subjects with stroke were less accurate than healthy individuals in matching the wrist position. Fourth, the assessment is clinically feasible. Stroke patients completed the test in about 8 minutes. We conclude that assessment of proprioception in stroke should map positions at different joint degrees of freedom to detect underlying proprioceptive abnormalities.

A wearable wrist haptic display for motion tracking and force feedback in the operational space

“…Plenty of examples of grounded, joint-space displays (GJS-KHD) can be found in literature, involving one or more fingers (Agarwal et al, 2015 ), wrist (Gupta et al 2008 ; Pehlivan et al 2012 ; Martinez et al 2013 ; Andrikopoulos et al 2015 ; Pezent et al 2017 ; Basteris et al 2018 ; Lee et al 2018 ; Pezent et al 2019 ), and full-arm (Frisoli et al, 2005 ; Gupta and O’Malley, 2006 ; Mallwitz et al, 2015 ; Barsotti et al, 2018 ). Several are also the wearable, joint-space solutions (WJS-KHD), in which is not present, and therefore all the weight of the structure has to be compensated by the user (the interface represented in Figure 1 would start from the contact point corresponding to the force ).…”

Assessing quality of upper limb movements after stroke with prospects of wearable technologies

“…Novel technologies for kinematic signal detection and processing provide the opportunity for an objective and accurate motion analysis, which allow to overcome the limitations of standard clinical assessments in stroke research and rehabilitation . Among the different approaches, it is worth mentioning (i) device-based assessments (Lambercy et al, 2013;Basteris et al, 2018), and (ii) less interfering wearable systems for bio-signal and motion capture processing (Camardella et al, 2018;Lorussi et al, 2016). However, although promising, the state-of-the-art solutions need to face with important issues, such as operator and patient safety and costs of the procedure (i).…”