Fig. 1. Virtual scene

Deficits in obstacle avoidance behaviour in individuals with good arm recovery after stroke

Melanie C. Baniña, Aditi A. Mullick, Mindy F. Levin School of Physical and Occupational Therapy

McGill University Montreal, Canada

Feil/Oberfeld Research Centre Jewish Rehabilitation Hospital site of CRIR

Laval, Canada

Abstract–The ability to avoid obstacles during reaching in a virtual environment (VE) was compared between post-stroke individuals with well-recovered upper limbs (UL) and healthy controls. Stroke subjects ranked well in UL clinical assessments. However, even though well-recovered, stroke subjects still had residual movement deficits and made more errors in the obstacle avoidance reaching task compared to controls. Reaching movement deficits were only revealed because of the challenging motor task. Therefore, the potential of using complex UL tasks to challenge the sensorimotor system and reveal deficits in higher-order sensorimotor function should be considered when assessing individuals after stroke.

Keywords—stroke; upper limb; reaching; obstacle avoidance; coordination

I. INTRODUCTION After stroke, the majority of individuals have varying levels

of upper limb (UL) hemiparesis. Although many individuals are likely to regain some functional UL use, movements often remain clumsy and slow [1]. Different factors may contribute to this problem including abnormal muscle torque patterns [2], changes in proprioception [3], and deficits in coordination between trunk, shoulder and elbow movements [4,5]. However, some post-stroke individuals who are identified as “well-recovered” but still have some residual motor deficits can have scores on clinical measures of UL sensorimotor function ranging from mild impairment to complete recovery. Based on clinical assessments indicating good recovery, patients are expected to be capable of independently performing activities of daily living (ADL), but this is not always the case [6]. Residual motor deficits may be identified when individuals have to perform more challenging tasks requiring more complex coordination. However, higher-order motor functions are not routinely assessed by clinical scales or even kinematically. One higher-order motor function, the ability to avoid obstacles while reaching, commonly occurs in everyday cluttered working environments and requires a fine motor coordination between movements of different body segments. Reaching trajectories are planned so that the hand is kept at a minimal distance from the obstacle [7] while still arriving at the target location. The minimal clearance value changes with different UL orientations and joint positions and tasks [8]. Since it varies, minimal clearance of the endpoint is not the only factor that determines avoidance trajectories.

Successful obstacle avoidance also depends on the contributions of and coordination between rotations of the shoulder, elbow and wrist to the reaching movement. In this study the ability to avoid obstacles during reaching in a VE was compared between post-stroke individuals with well-recovered ULs and healthy individuals. We hypothesized that well-recovered individuals would have difficulty making rapid corrections of endpoint movement to avoid an obstacle and the difficulty in obstacle avoidance behaviour would be related to deficits in interjoint and intersegment coordination that are not identified in clinical tests.

II. METHODS Two groups were recruited: individuals who had a stroke

(n=17) 1.8±1.5yrs previously with good recovery of their UL (dominant arm affected, Chedoke McMaster Stroke Assessment arm score ≥ 5/7 [9], and healthy controls (n=11) of similar age range (stroke=62.7±9.3yrs, controls=60.8±8.1yrs), hereinafter referred to as stroke and control subjects. Subjects underwent a clinical evaluation and then participated in a one hour experimental session. A VE simulating a grocery store aisle with shelves and a commercial refrigerator with double sliding doors was rear-projected onto a screen and viewed with 3D stereoscopic glasses (Figure 1).

An Optotrak Certus motion capture system tracked and recorded markers placed on the UL and trunk. Subjects sat 1m in front of the screen and interacted within the VE by controlling the movements of an avatar arm with their own arm movements. The avatar position as well as the relationship between the avatar and objects viewed on the screen were calibrated to the actual movements performed by the subject, such that the object was placed at 80% of the subject’s arm length. Movements made in the 3D CAREN system have previously been reported to have high kinematic validity [10]. Refrigerator door closure was triggered when the wrist marker

Supported by: Canadian Institutes of Health Research (MFL); Richard and Edith Strauss Doctoral Fellowship in Rehabilitation Science, McGill University (MCB). MFL holds a Canada Research Chair in Motor Recovery and Rehabilitation.

190978-1-4799-0774-8/13/$31.00 ©2013 IEEE

tangential velocity (Vw) reached 10% of the mean Vw calculated from template (T=non-obstructed) trials. The final door position partially obstructed a juice bottle on a shelf either from the left or right side of the screen. Subjects had to successfully reach as fast as possible around the door without touching it and retrieve the bottle. A successful (S) or failed (F) trial was indicated with different auditory signals. Subjects practiced 3 blocks of 30 trials with no door closure (template, T), right- and left-door closure. Then, subjects performed a randomized block of 60 trials in which the probability of occurrence of no door, right door or left door closure was 33% each. Marker position data were used to assess motor performance (based on movement characteristics of the endpoint (peak tangential velocity, EPV; trajectory path length, ETL) and joint kinematics contributing to endpoint movement (i.e., movement quality measures: arm joint ranges, interjoint coordination and trunk displacement at different time points of the reach). In addition, the point in the endpoint phase space at which the arm trajectory of the obstructed movement deviated from that of the non-obstructed movement (T), was defined as the divergence point (DP). The DP was determined by overlaying the T velocity/position movement profile with an S or F obstructed profile. The first point at which the profiles significantly differed (t-test, p<0.05) was the DP, reported as the percent of the reaching distance from start position. Outcome variables were compared using repeated measures ANOVAs and appropriate post-hoc testing.

III. RESULTS In T trials EPV, ETL and most joint angle displacements

were similar in both groups except that stroke subjects used less wrist flexion, wrist abduction and shoulder lateral rotation. In the randomized block, the acceptable success rate was set at 65% and more controls were successful (control=36% vs. stroke=12%, Z=2.248, p<0.05). For both groups, successful door avoidance was characterized by an earlier DP (Table 1). However, stroke subjects had a smaller margin of error to avoid the door: the mean position of endpoint divergence (DPSuccess) in the stroke group was closer to the door than that of controls.

TABLE I. ENDPOINT PEAK TANGENTIAL VELOCITY, ENDPOINT TRAJECTORY PATH LENGTH AND DIVERGENCE POINT

Peak Velocity EPL (mm/s)

Trajectory Length ETL (mm)

DP (% from start)

Control Template 2288.7 (236.5)

686.3 (28.4)

Success 1171.7 (99.6)a

804.0 (36.4)a

11.2 (7.0)

Fail 1499.0 (133.6)a,b

713.7 (30.8)

34.1 (37.3)

Stroke Template 1943.6 (148.1)

708.4 (19.9)

Success 1272.6 (112.1)a

818.1 (44.8)a

20.5 (16.1)

Fail 1538.0 (118.5)a,b

804.6 (59.8)

60.4 (33.7)

compared to Template, a: p˂0.01 compared to Success, b: p<0.01

IV. CONCLUSIONS This study was designed to identify the components of

obstacle avoidance performance and arm movement quality that are affected after stroke. Although the stroke subjects were clinically well-recovered, residual deficits were revealed when tested with a complex 3D reaching task. The results indicated that good scores on clinical outcome measures of arm function do not necessarily reflect the ability to perform complex reaching tasks representative of the abilities needed for ADL. Therefore, higher-order motor functions of individuals who are recovering from stroke need to be assessed in order to identify deficits and plan more effective treatment interventions. Higher -order motor deficits may be remediated by exposing post-stroke individuals to situations in which they have to practice using their arm to perform complex reaching tasks of increasing difficulty. Identifying the mechanisms underlying these deficits will contribute to the development of a VR toolkit for stroke rehabilitation which should also include other factors that may influence ADL such as balance, mobility, and cognition.

ACKNOWLEDGMENT The authors thank Rhona Guberek, Christian Beaudoin,

Valeri Goussev, and all participants for their valuable contributions to this project.

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