A VR-haptic locomotor system to retrain anticipatory postural adjustments post stroke Alison R Oates, Claire F Perez and Joyce Fung stroke each year [1]. The inability to walk is one of the more devastating consequences of stroke. Regaining ambulatory ability and independence is the most common rehabilitation goal expressed by stroke patients [2]. The main characteristics of gait following stroke are slow walking speed, asymmetrical weight bearing and difficulty overcoming environmental barriers such as surface changes, inclines and obstacles [3]. Locomotion requires the integration of sensory and motor systems to produce coordinated movement and dynamically maintain balance. Following stroke, multiple motor and sensory impairments may cause a composite of problems impacting balance and walking. One study [4] found balance difficulties in over 80% of first time stroke subjects. In order to maintain balance during locomotion, the COM stability must be controlled. Researchers have found that COM stability in standing and walking is significantly reduced in people post stroke as compared to age-matched controls [5]. In walking tasks that are more challenging such as walking up inclines, the sensorimotor demands are increased and necessitate specific modifications. The adaptation to walking on an inclined surface, for example, requires changes in gait pattern and rapid adjustments in COM position [6], [7]. This flexibility in is diminished post-stroke thus people poststroke cannot readily adapt to increased environmental demands. Individuals following stroke are limited in their ability for independent community ambulation. In stroke, sensory input from all systems can be affected, resulting in visual field deficits, problems with vertical perception as well as impaired sensation and proprioception. It is still unknown how the central nervous system (CNS) integrates multiple sources of sensory information and how the sensory systems interact to produce the necessary motor output to maintain stability during gait. Peterka [8] theorizes a dynamic regulation of sensorimotor interaction with a continuously re-weighting of sensory input and motor output according to environmental context and personal factors. In conditions when the environmental demands are high and the individual has sensory impairments, re-weighting would allow the more reliable sensory functions to contribute more to the maintenance of postural control. Task-oriented interventions [9] and intense task practice [10] promote the re-acquisition of locomotor skills. The incorporation of motor learning strategies [11] into the training is effective in combination with task-specific gait activities. Clinicians, using motor learning concepts, can change the environmental contexts and alter the physical demands of the task to improve motor learning and locomotor rehabilitation. Clinicians, however, face time and space constraints which make the regular set-up of complex gait tasks (surface changes, ramps, obstacles, etc.) difficult.
Abstract—The ability to use haptic input through light contact to improve stability while walking post-stroke is investigated in a virtual environment (VE). Persons with stroke and healthy participants walk in a VE where they encounter changes in the slope of the support surface. Kinematic, kinetic, and electromyographic data analyses will be used to show the anticipatory postural adjustments made leading up to and after a transition to a sloped surface. Pilot testing shows that the transition to sloped surface is more challenging for the stroke participant tested, as compared to an age-matched control. Modifications to the current protocol will improve the feasibility of not only task completion by both healthy and neurologically impaired participants, but also the ability to use and evaluate the use of haptic information for stability while walking in a VE with slope changes.
T
I. INTRODUCTION
HE use of a virtual environment (VE) allows users to interact with environments that are similar to real world situations and events. VEs provide many advantages in a rehabilitation setting including the ability to objectively measure behavior in a challenging but safe and ecologicallyvalid environment. A VE maintains strict experimental control over stimulus delivery which permits precise manipulation and augmentation of sensory feedback and environmental conditions. Task and environmental constraints, along with augmented sensory feedback, can all be finely controlled in a VE in ways that are not possible in real world settings. VEs and technology have enabled researchers to reproduce real-life and functional settings within which they can explore very specific components for enhancing postural control and locomotion. Stroke is the leading cause of disability worldwide. In Canada, over 300,000 people presently live with the effects of stroke. An additional 50,000 individuals will have a
Manuscript received April 16, 2008. This work was supported in part by a CIHR team grant funded to the Multidisciplinary Team in Locomotor Rehabilitation and by an infrastructure grant co-funded by the Canada Foundation for Innovation (CFI) and the Quebec Ministry of Health and Social Services,. A. R. Oates is a postdoctoral research fellow with the School of Physical and Occupational Therapy (P & OT), McGill University and the Jewish Rehabilitation Hospital (JRH) research site of CRIR in Montreal, Quebec, Canada. A.R. Oates is supported by a fellowship from the Multidisciplinary Team in Locomotor Rehabilitation, CIHR team grant (corresponding author phone: 450-688-9550 ext. 4810; fax: 450-688-3673; e-mail:
[email protected]). C. F. Perez (e-mail:
[email protected]) is an MSc candidate with the School of P & OT, McGill University, and a physical therapist at the JRH research site of CRIR in Montreal, Quebec, Canada. She is supported by a studentship from the Fonds de la recherche en Santé du Québec. J Fung is an Associate Professor and William Dawson Scholar with the School of P & OT, McGill University, and the JRH research site of CRIR in Montreal, Quebec, Canada (e-mail:
[email protected]).
978-1-4244-2701-7/08/$25.00 ©2008 IEEE
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To date, there are very few studies which investigate the role of haptic information in locomotion. Only two studies were found which examined the role of light touch in a CNS condition such as stroke where postural instability and balance problems are often major impairments. One study [20] has demonstrated the positive effect of using haptic input in a stroke population for stabilizing stance and walking during unexpected surface perturbations. Another study [21] explored the use of haptic information for balance control while walking sideways. These findings highlight the benefit of haptic information for improving postural control in people with stroke and its potential impact for enhancing gait capacity. The objective of this paper is to present the feasibility of a protocol design to effectively investigate the use of haptic information during slope changes while walking in a virtual environment. After initial, pilot testing, revisions have been made to improve the protocol design to better examine the sensorimotor integration capabilities of someone post stroke during locomotion. The underlying hypothesis is that haptic information will improve dynamic stability control during the anticipatory postural adjustments associated with changes in the support surface inclination.
A VE may remove some of the physical and time barriers to applying these motor learning techniques during rehabilitation by providing flexibility in the environment constructs. Rehabilitation techniques targeting the sensory systems are also of benefit for improving gait capacity. Therapists may initially facilitate movement and postural control by providing a high degree of sensory feedback (use of mirrors, biofeedback, etc.) and gradually reduce the input as gait improves. This additional visual or auditory input provided to stroke patients appears to enhance gait rehabilitation and has been shown to be successful [12]. Although the concept of augmented sensory feedback in stroke rehabilitation is not new, researchers now are discovering more about the biophysiological mechanism and role of feedback control for motor learning and skill acquisition. The term haptics refers to the sense of touch and is usually applied to the hand/finger’s ability to detect and perceive specific environmental features. Haptic touch has emerged as a novel and efficient technique to improve postural control and dynamic stability. It has been theorized that haptic cues serve as a reference for postural orientation adding to that information provided by the visual and vestibular systems [13]. Haptic information is used to “anchor” the body position with respect to the environment through augmented proprioceptive feedback and the perception of the earth vertical position. Studies have revealed that a very light finger-tip contact (less than 4 N) with an external rigid object can reduce postural sway in stance in healthy, young subjects [13]. Some studies have found similar results using even lighter contact forces (lower than 1 N) clearly demonstrating that no mechanical support is provided. Improved postural stability with haptic touch has also been shown during unexpected surface perturbations and during lower leg muscle vibration-induced perturbations in healthy subjects [14]. Baccini [19] and Tremblay [15] investigated the differences in the effect of haptic information in healthy young and older people. Their results revealed that haptic cues are more useful for balance control in older people (mean age of 75 years) than in younger adults. Recently Nagano [16] demonstrated that a light finger touch on one’s own body (upper legs) can also aid in the control of posture and balance by reducing sway. Rogers [17] has shown that even passive tactile cues (applied to either the neck or leg) help control posture and balance. Haptic information has also been shown to be effective in improving stability in populations with known sensory problems. People with sensory losses secondary to diabetic neuropathies [15], [16] or vestibular deficits [13], [19] demonstrated significant improvements in stability with a haptic cue, that were significantly higher than those in healthy controls. These studies suggest that light touch is of greatest use when there is a notable need for additional postural information such as when one or more of the other sensory systems is impaired. Most of the research into the use of haptic information for stabilizing postural control has been done in standing positions with or without laboratory induced perturbations.
II. PROCEDURES TABLE I CRITERIA FOR PARTICIPATION IN THE STUDY
Inclusion Single, uni-hemispheric stroke 45-80 years old Ability to walk 40m without walking aid Ability to walk with arm lightly touching force transducer
Exclusion Less than three months and more than one year post stroke Sensory deficit in limbs Unilateral neglect Extinction
A. Participants Participants will include independently ambulating persons (between the ages of 45-80 years old), greater than three months and less than one year post-stroke. Table I summarizes the stroke participant inclusion and exclusion criteria for participation in the study. These participants will be age- and gender- matched to healthy controls. B. Measurement The VE set up is similar to the one described previously by Fung et al., [22] and as illustrated in fig 1. A force transducer (AMTI MC25-500) is used to measure the amount of force under the fingertip while walking in the haptic conditions. The device is mounted on a rail that can be adjusted for height or width. Subjects will walk on a selfpaced motorized treadmill mounted on a 6-degree-offreedom motion platform. While wearing polarized glasses and a harness (attached to an overhead suspension system) subjects walk on the treadmill, interacting within the VE.
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The participants, at times, will lightly place their finger on the force transducer at hip level. The force transducer will be placed on the non-affected side for the stroke participants and on the dominant or preferred side for the control participants. An auditory cue is given if that force exceeds 4N in the haptic conditions. The VE is used within the CAREN (Computer Assisted Rehabilitation Environment; http://www.e motek.com/medical/ index.htm) system. This system simultaneously synchronizes the instantaneous treadmill speed and scene progression such that the subject has full control of his movement within the virtual environment. In addition, motions of the body and limbs are captured in real-time with a 6-camera Vicon motion analysis system (Oxfordmetrics, UK) at 120 Hz. Subjects wear reflective markers placed on various anatomical landmarks of the body which will be detected by the camera system to monitor body movements. Kinematic data will be used to calculate step parameters such as stride length and duration, step velocity, etc. as well as calculate centre of mass (COM) stability. Kinematic data beyond stride length will be presented at the conference. Muscle activity will be monitored through electromyography (EMG) recordings from muscles in the lower limbs and trunk using a 16-channel telemetric Telemyo900 system (NoraxonUSA Inc.). Disposable bipolar silver/silver-chloride electrodes are placed bilaterally over the belly of the following muscles: Tibialis anterior, soleus, vastus medialis, biceps femoris, tensor fascia latae, lower
and presented at the time of the conference.
Figure 2: Virtual scene as viewed by a participant standing on the treadmill. This scene involves one up-slope section with a level surface both before and after the inclined surface.
C. Protocol The protocol of the VR experience as begins with habituation to the self-paced treadmill, the haptic input and auditory signal, and the level of slope change at a constant rate (i.e., participants will walk over a level ground and at a constant slope of +/-5º). The habituation trials are performed without the VE. Following the habituation trials without the scene, participants will walk in a VE containing constant slope values of 0, +/- 5º for a distance of 40m. These habituation trials, both with and without the VE, will serve as baseline comparison for the trials with a transition between surface slopes. Following habituation and baseline trials, participants will walk in a VE with a scene similar to that shown in fig 2. Both control and stroke participants will walk in the VE scenes and in the two experimental conditions: with and without haptic information. Participants will walk in a VE where there are +/- 5º slope changes in the visual scene that will be matched to +/- 5º slope changes on the platform/treadmill. The varying dimensions of the scenes are illustrated in fig 3. Participants will ideally experience a block of 4 trials each within the VE: With and without haptic information for both the transition to upslope and the transition to down-slope. These blocks will be repeated three times so that each participant will receive a total of 12 trials in the transitional VE scenes. The information from the steady-state trials (i.e., with a constant surface slope) will be averaged over the trial. The information from the transition trials will be sampled at n-2, n-1, n, n+1, n+2, where n = the first step onto the sloped surface.
Fig. 1. Photographs of VE set-up showing self-paced treadmill, projection screen and harness and of the force transducer used for haptic information.
erector spinae, rectus abdominus and anterior deltoid. EMG signals will be amplified, band-pass filtered (10-350 Hz) and sampled at 1200 Hz. The amount of EMG activity will be reflected in the integrated EMG signal during stance and swing phases. As well, the pattern of muscle activity will be recorded to show the motor response to the walking onto an inclined or declined surface. The EMG data will be analyzed
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Transition to up-slope
Level walking Stroke affected side
Stride length (m)
20m
10m Transition to down-slope 10m
Figure 3: Schematic diagram of VE in testing protocol design. Each inclination change is +/-5º.
Early without haptic
III. RESULTS
Stroke non-affected side
Stride length (m)
Stride length (m)
Stroke non-affected side
Control
Early with haptic
Late without haptic
Late with haptic
Fig 4 illustrates the differences in stride length between the early and late trials with constant slope values. In both conditions (level and up-slope) the stride length of the participants increased with time suggesting a motor-learning effect within the testing session. As expected the control participant took longer strides than the stroke participant. The difficulty in transition can be seen in the steps surrounding the transitional step (n) as illustrated in the stride length values in fig 5. Stride length decreased as both participants prepared for, stepped onto and then continued to walk on the up-slope surface. IV. FEASIBILITY
Control
The current protocol was more challenging than anticipated to both the stroke and the control participant tested. The major difficulty was the task of holding the finger in place and responding to the auditory signal. The haptic condition and the difficulty of the task may be adding an attentional component to the protocol. To reduce the possibility of creating a dual-task paradigm, the haptic input will be provided by contacting an external, rigid surface from the side. A touch at the side of the surface will also remove the tendency to lean on the surface with a force greater than 4N as we saw in the stroke participant tested. This side-contact will also allow a more natural arm swing during walking as the participant will be able to move their hand forward and backward while still maintaining contact. This will allow the haptic condition to be more comparable to the non-haptic condition in terms of the postural demands
0.3 0.2 0.1 0.0 n+1
Late with haptic
Figure 5: Stride length values during the transition between level and upslope walking where n=the first step onto the inclined surface.
0.4
n
Late without haptic
1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Early without haptic
0.5
n-1
Early with haptic
Stroke affected side
0.6
n-2
Control
Upslope walking
The protocol has been pilot tested on one stroke and one age- and gender-matched control participant. The stroke participant was tested first and the amount of walking in the habituation trials and the number of trials in the VE scenes were matched in the control participant. The stroke participant was able to complete a series of habituation trials at a steady-state inclination (i.e., no transitions) but had considerable difficulty once immersed in the VE with transitions. The transition between level walking and a slope change was particularly difficult for both the stroke and control participant. Because the VE involving transitions were difficult, we limited the number of trials with the predetermined scenes and then re-evaluated with the conditions from the early habituation trials (i.e., constant level, up-slope or down-slope with no VE). As well, the task of maintaining both a fingertip contact position and a contact force lower than 4N proved to be difficult for the stroke participant. During the trials where haptic information was required, the stroke participant either became distracted by the auditory signal which created difficulties in her walking balance or she held onto the force transducer instead of lightly touching the surface of the force transducer. For the purpose of this abstract, the pilot data on the early and late steady-state trials are presented along with a sample of the data during one trial over a transition from level to up-slope walking. The left and right limb values for the control participant have been averaged whereas the data from the stroke participant has Stroke affected side
Stroke non-affected side
1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0
n+2
Figure 4: Stride length values for level and up-slope walking during early habituation trials and later trials of the same condition. All trials were without the VE. Values are averages over the trial +2SE.
been separated into the affected and non-affected sides.
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[7] McIntosh A, Beatty, KT, Dwan LN and Vickers DR. Gait dynamics on an inclined walkway. Journal of Biomechanics 2006;39:2491-2502. [8] Peterka RJ, Loughlin PJ. Dynamic regulation of sensorimotor integration in human postural control. J Neurophysiol 2004;91(1):41023. [9] Salbach NM, Mayo NE, Robichaud-Ekstrand S, Hanley JA, Richards CL, Wood-Dauphinee S. The effect of a task-oriented walking intervention on improving balance self-efficacy post stroke: a randomized, controlled trial. J Am Geriatr Soc 2005;53(4):576-82. [10]Kwakkel G. Impact of intensity of practice after stroke: Issues for consideration. Disabil Rehabil 2006;28(13-14):823-30. [11] Krakauer JW. Motor learning: its relevance to stroke recovery and neurorehabilitation. Curr Opin Neurol 2006;19(1):84-90. [12] Bayouk JF, Boucher JP, Leroux A. Balance training following stroke: effects of task-oriented exercises with and without altered sensory input. Int J Rehabil Res 2006;29(1):51-59. [13] Jeka JJ. Light touch contact as a balance aid. Phys Ther 1997;77(5):476-87. [14] Lackner JR, Rabin E, DiZio P. Fingertip contact suppresses the destabilizing influence of leg muscle vibration. J Neurophysiol 2000;84(5):2217-24. [15] Baccini M, Rinaldi LA, Federighi G, Vannucchi L, Paci M, Masotti G. Effectiveness of fingertip light contact in reducing postural sway in older people. Age Ageing 2007;36(1):30-5. [16] Tremblay F, Mireault AC, Dessureault L, Manning H, Sveistrup H. Postural stabilization from fingertip contact: I. Variations in sway attenuation, perceived stability and contact forces with aging. Exp Brain Res 2004;157(3):275-85. [17] Nagano A, Yoshioka S, Hay DC, Fukashiro S. Light finger touch on the upper legs reduces postural sway during quasi-static standing. Motor Control 2006;10(4):348-58. [18] Rogers MW, Wardman DL, Lord SR, Fitzpatrick RC. Passive tactile sensory input improves stability during standing. Exp Brain Res 2001;136(4):514-22. [19] Lackner JR, DiZio P, Jeka J, Horak F, Krebs D, Rabin E. Precision contact of the fingertip reduces postural sway of individuals with bilateral vestibular loss. Exp Brain Res 1999;126(4):459-66. [20] Fung J, Boonsinsukh R. and Rapagna M. Postural responses triggered by surface perturbations are task-specific and goal directed. In: Latash M, Levin M (eds.) Progress in Motor Control III, Human Kinetics, 2003:169-181. [21] Trivino M, Lamontagne, A and Fung, J. 2005. In: International Symposium of Electrophysiology and Kinesiology. Boston, Ma. [22] Fung J, Richards CL, Malouin F, McFadyen BJ, Lamontagne A. A treadmill and motion coupled virtual reality system for gait training post-stroke. Cyberpsychol Behav 2006;9(2):157-62.
of the locomotor task. Trunk posture and arm swing will be analyzed to confirm that both conditions have similar postural and arm swing characteristics. Also, to ensure that participants are able to visually perceive the upcoming slope transition and to evaluate the level of confidence to maintain balance during each condition will be evaluated using visual analog scales following the testing. V. SUMMARY Modifications to the current protocol will improve the feasibility of not only completion of the tasks by both stroke and control participants but the ability to use and evaluate the use of haptic information for stability while walking in a VE with slope changes. ACKNOWLEDGMENT The authors would like to thank Christian Beaudoin, Yotam Bahat, Eric Johnstone, and Lucinda Hughey for their skilful and technical assistance in this project. REFERENCES [1] The Canadian Stroke Network. Accessed January 2008. www.canadianstrokenetwork.ca/eng/about/aboutstroke.php. [2] Lord SE, McPherson K, McNaughton HK, Rochester L, Weatherall M. Community ambulation after stroke: how important and obtainable is it and what measures appear predictive? Arch Phys Med Rehabil 2004;85(2):234-9. [3] De Bujanda E, Nadeau S, Bourbonnais D and Dickstein R. Associations between lower limb impairments, locomotor capacities and kinematic variables in the frontal plane during walking in adults with chronic stroke. J Rehabil Med 2003;35:259-264. [4] Tyson SF. Trunk kinematics in hemiplegic gait and the effect of walking aids. Clin Rehabil 1999;13(4):295-300. [5] Marigold DS, Eng JJ, Tokuno CD, Donnelly CA. Contribution of muscle strength and integration of afferent input to postural instability in persons with stroke. Neurorehabil Neural Repair 2004;18(4):222-9. [6] Leroux A, Fung J, Barbeau H. Postural adaptation to walking on inclined surfaces: I. Normal strategies. Gait Posture 2002;15(1):64-74.
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