Posts Tagged visual feedback
Walking deficits in people post-stroke are often multiple and idiosyncratic in nature. Limited patient and therapist resources necessitate prioritization of deficits such that some may be left unaddressed. More efficient delivery of therapy may alleviate this challenge. Here, we look to determine the utility of a novel principal component-based visual feedback system that targets multiple, patient-specific features of gait in people post-stroke.
Ten individuals with stroke received two sessions of visual feedback to attain a walking goal. This goal consisted of bilateral knee and hip joint angles of a typical ‘healthy’ walking pattern. The feedback system uses principal component analysis (PCA) to algorithmically weight each of the input features so that participants received one stream of performance feedback. In the first session, participants had to explore different patterns to achieve the goal, and in the second session they were informed of the goal walking pattern. Ten healthy, age-matched individuals received the same paradigm, but with a hemiparetic goal (i.e. to produce the pattern of an exemplar stroke participant). This was to distinguish the extent to which performance limitations in stroke were due neurological injury or the PCA based visual feedback itself.
Principal component-based visual feedback can differentially bias multiple features of walking toward a prescribed goal. On average, individuals with stroke typically improved performance via increased paretic knee and hip flexion, and did not perform better with explicit instruction. In contrast, healthy people performed better (i.e. could produce the desired exemplar stroke pattern) in both sessions, and were best with explicit instruction. Importantly, the feedback for stroke participants accommodated a heterogeneous set of walking deficits by individually weighting each feature based on baseline walking.
People with and without stroke are able to use this novel visual feedback to train multiple, specific features of gait. Important for stroke, the PCA feedback allowed for targeting of patient-specific deficits. This feedback is flexible to any feature of walking in any plane of movement, thus providing a potential tool for therapists to simultaneously target multiple aberrant features of gait.
Gait impairment following stroke often presents with multiple deficits. Some of the most common deficits include decreased paretic leg knee flexion during swing, hip circumduction, step length asymmetry, pelvic tilt, and decreased ankle dorsiflexion [1,2,3,4,5]. Unfortunately, resources (e.g. patient time/finances, therapist time, insurance coverage, etc), are limited, making it difficult to address all existing deficits in a single episode of care. Consequently, therapists are confronted with the challenge of using their clinical judgement to prioritize deficits, serially targeting those that they believe will most improve walking function and independence. Addressing one deficit in isolation of the others may introduce unintended compensations that further impair gait. Indeed, when manipulating a lower-limb movement pattern, lower-limb sagittal plane kinematics (e.g. hip/knee angles) are closely coupled [6,7,8].Thus, there remains a need for both the systematic prioritization of gait deficits and improvement in the efficiency of training so as to simultaneously address multiple patient-specific deficits.
Real-time visual feedback of gait kinematics has proven useful in altering targeted features of gait in healthy and neurological populations [9,10,11,12,13,14]. For example, Cherry-Allen et al. used visual feedback of joint angles to increase peak knee angle in people post-stroke . Moreover, visual feedback has been effective in improving gait speed, stride length, and stride width in people post-stroke [16,17,18]. Still, research protocols using visual feedback of kinematic gait parameters have two prominent issues when looking to improve individual patient deficits: 1) they are focused on altering one feature of walking while leaving others unconstrained and 2) they are predicated on the assumption that the targeted parameter is the most prominent deficit for the entire group of patients included in the particular study. Given the heterogeneity of deficits following stroke, it would be most beneficial to have a system that can accommodate a wide array of walking patterns.
We developed a novel method to generate individualized, yet simple, visual feedback for re-training walking on a treadmill. An innovative element of this process is the use of principal component analysis (PCA) to display a simple ‘summary’ of a multi-dimensional movement pattern that continuously updates on a screen in front of participants as they walk. PCA has applied to motion data in a number of previous studies to characterize whole-body movement in both healthy [19, 20] and pathological populations [21,22,23,24,25]. The question that we ask here is whether this novel, PCA-based visual feedback system can address multiple, patient-specific deficits simultaneously. For stroke patients, we established a goal walking pattern that included four kinematic dimensions (bilateral hip and knee joint angles) of an average ‘healthy’ walking pattern. Each of the four kinematic dimensions was individually weighted based on a participant’s baseline deficits (defined as the difference between baseline walking and the goal walking pattern). Thus, weights varied across participants and were specific to their deficit.
The primary objective of this study was to evaluate the efficacy of our novel visual feedback in altering gait post-stroke. Thus, to contrast performance of participants with chronic stroke who received a control goal walking pattern (i.e. stroke-to-control), we evaluated the performance of healthy, age-matched controls who receive a hemiparetic goal walking pattern (i.e. control-to-stroke) using the same visual feedback. This contrast allows us to further validate our method by investigating the extent to which performance in stroke-to-control was limited by neurological injury compared to limitations imposed by the method itself. We hypothesized that participants in both groups would be able to use this summary visual feedback to simultaneously alter multiple aspects of their gait (albeit to varying extends depending on their impairment) toward the prescribed goal pattern while walking on a treadmill.
Ten adults with chronic stroke (3 female; age: 59.0 ± 7.4 yr) and ten group age-matched neurologically intact adults (7 female; age: 57.3 ± 6.8 yr) were recruited for this experiment. All participants with chronic stroke met inclusion and exclusion criteria (Table 1). All participants provided written, informed consent before taking part in the experiment. The experimental protocol was approved by the Johns Hopkins Medicine Institutional Review Board.
Participants with chronic stroke underwent clinical examination prior to the experiment. To quantify motor impairment we administered the lower extremity subscale of the Fugl-Meyer test (FM-LE) . This test includes 17 items scored on an ordinal scale (0–2) with 34 possible points and higher scores representing less impairment. We measured self-selected and fastest comfortable over ground walking speeds by having participants walk two passes at each speed across a six-meter electronic walkway (Zeno Walkway, ProtoKinetics, Havertown, PA). Baseline knee and hip flexion angles, used to determine study eligibility, were measured using motion capture while participants walked on the treadmill at their self-selected speed. Participants who customarily wore an ankle-foot orthosis continued using these items throughout the study.
We also tested for sensory impairment in participants with chronic stroke. For proprioception testing, participants were supine with their eyes closed. The examiner stabilized the proximal joint segment and passively moved the distal segment to a position above or below the neutral starting position (neutral position was midway through the joint’s range of motion). The participant reported whether the position of the specified joint was above or below the starting position. Paretic hip, knee, and ankle joints were each tested at six different positions (18 total probes). Participants with stroke also completed The Star Cancellation Test, a screening tool that detects the presence of unilateral spatial neglect . Scores less than 44/54 stars cancelled is suggestive of unilateral spatial neglect.
We assessed cognitive function in both participants with chronic stroke and control participants using the Montreal Cognitive Assessment (MoCA) . Scores greater than 26/30 possible points reflect normal cognitive function.
We recorded participants’ kinematics using an Optotrak Certus motion capture system (Northern Digital, Waterloo, ON) as they walked on a split-belt treadmill (Woodway, Waukesha, WI) with a separate belt for each leg. This type of treadmill allowed us to detect right and left foot contacts via distinct force plates under each belt, but the belt speeds were equal throughout all experiments. Kinematic data were collected at 100 Hz from 12 infrared-emitting diodes placed bilaterally on the foot (fifth metatarsal head), ankle (lateral malleolus), knee (lateral epicondyle), hip (greater trochanter), pelvis (iliac crest), and shoulder (acromion process; Fig. 1a).
[ARTICLE] A Feasibility Study of SSVEP-Based Passive Training on an Ankle Rehabilitation Robot – Full Text
Objective. This study aims to establish a steady-state visual evoked potential- (SSVEP-) based passive training protocol on an ankle rehabilitation robot and validate its feasibility. Method. This paper combines SSVEP signals and the virtual reality circumstance through constructing information transmission loops between brains and ankle robots. The robot can judge motion intentions of subjects and trigger the training when subjects pay their attention on one of the four flickering circles. The virtual reality training circumstance provides real-time visual feedback of ankle rotation. Result. All five subjects succeeded in conducting ankle training based on the SSVEP-triggered training strategy following their motion intentions. The lowest success rate is 80%, and the highest one is 100%. The lowest information transfer rate (ITR) is 11.5 bits/min when the biggest one of the robots for this proposed training is set as 24 bits/min. Conclusion. The proposed training strategy is feasible and promising to be combined with a robot for ankle rehabilitation. Future work will focus on adopting more advanced data process techniques to improve the reliability of intention detection and investigating how patients respond to such a training strategy.
Stroke is one of the main root causes leading patients unable to comfortably control their muscles and bodies in the daily living, and even lose the ability [1–3]. The ability of body controlling is inversely proportional to the distance between brains and limbs, which means that the longer the distance is, the lower the ability is . Motor function of injured ankles will be recovered more difficult than one of the hands with a similar disability.
For early stage rehabilitation of injured ankles, if without sufficient rotations, ankle joints could gradually become stiff, and finally, foot drop will be generated [5, 6]. In order to avoid being stiff, muscle stretching and joint rotating are regarded as one of the important methods in traditional therapy of injured ankle joints. Traditional physical therapy is usually operated manually by therapists. It has a unique advantage, which therapists can observe real-time feedback from patients through their body reaction and communication and thus adjust the process accordingly. However, it also has several limitations: (1) therapists can feel weary for long-time operation; (2) operating strength cannot be kept uniformly during the whole process; (3) mental state of therapists is one of the key factors to affect therapy effect .
In order to release manpower and address those limitations, robots have been invented to substitute partial functions of traditional therapy [8, 9]. For ankle rehabilitation, there are two kinds of robots invented, one of which is platform-based robots, and the other is wearable devices . When training on platform-based robots, subjects are normally in a sitting position to train their physical function of muscle stretching and joint rotating [8, 10]. When training on wearable ankle robots, subjects are required to be in a standing position to improve their ability on walking . Therefore, platform-based robots can provide better rehabilitation for subjects with weak motion ability of ankle joints, while targeted subjects of wearable ankle robots are those whose motion ability of ankle joints is strong enough to walk, but gait needs to be rebuilt and improved further recovery .
Passive training is one of the basic functions of platform-based robots. Different with common passive stretching with constant speed, Zhang et al.  proposed an intelligent passive stretching strategy in ankle dorsiflexion/plantarflexion (DF/PF) for safety. During intelligent passive stretching, rotating speed of the robot was inversely proportional to resistance torque. As soon as predefined maximum resistance torque was reached, ankle joints would be held at the extreme position for a period of time to allow stress relaxation. For robot-assisted passive ankle training, subjects are requested to keep relaxed to follow up trajectories of robots [3, 10]. After experiencing passive training, physic function of ankle joints can be kept to a certain degree and foot drop can be alleviated correspondingly [5, 8, 12].
Active training is another function of platform-based robots, where subjects are requested to actuate robots to track targets by allowing the foot to follow visual or auditory instructions [1, 10, 13, 14]. Visual reality circumstance has been widely applied in robot-assisted active ankle training. Girone et al.  proposed a virtual reality exercise library on the Rutgers Ankle. Subjects could conduct simulation exercise of strength, flexibility, and balance with haptic and visual feedback. Burdea et al.  proposed rehabilitation games including the airplane game and breakout 3D game. Michmizos et al.  proposed three goal-directed serious games especially for children. In this study, visual reality circumstance is set as a game of whack-a-mole, which four hamsters are arranged in four directions as targets, and a hammer is initially located in the center as the movable cursor. The vertical trajectory of hammer is projected to DF/PF, while the horizontal one is corresponded to inversion/eversion (INV/EV).
For passive training, subjects do not need to exert active effort, and thus few information transmission loops between brains and ankles exist . A prerequisite of conducting active training is that subjects should have enough motion ability of ankle joints to trigger robots . Therefore, for subjects whose motion intentions of ankle joints cannot be detected by built-in force sensors of robots, solving the problem of how they can actively conduct ankle training is a big challenge. This study aims to construct an information transmission loop between brains and ankle robots and enable subjects with weak motion ability of ankle joints to actively conduct robot-assisted ankle training.
When subjects focus their attention on a flickering source with frequency above 6 Hz, electroencephalography (EEG) signals originated from their visual cortex are named SSVEP, spectrum of which shows peak at the flickering frequency and its harmonics . SSVEP signals have been extracted and applied in many fields, such as controlling the robotic wheelchair , the humanoid robot navigation [20, 21], the semiautonomous mobile robotic car operation , and the artificial upper limb .
In this study, SSVEP signals are introduced and used for passive training on an ankle rehabilitation robot, in which motion intentions of subjects can be extracted to trigger related passive training. Four flickering circles with the diameter of 22 mm are arranged in four directions. Flickering frequencies are set as 10 Hz for the upper, 12 Hz for the bottom, 8.6 Hz for the left, and 15 Hz for the right . For subjects, gazing at the upper flickering circle represents the motion intention for DF, the bottom for PF, the left for INV, and the right for EV.
To enable subjects with weak motion ability of ankle joints to conduct motion intention-directed passive training, this study develops a SSVEP-based passive training strategy through combining SSVEP signals and virtual reality circumstance on an ankle robot. To verify its feasibility, this study recruited five healthy subjects for preliminary evaluation.
2.1. Ankle Rehabilitation Robot
The ankle rehabilitation robot applied in this study is an improved version of the one used in  by adding adjustable robot structure and was briefly introduced as in Figure 1(a). The footplate of the ankle robot could move with three degrees of freedom, which are corresponding to ankle DF/PF, INV/EV, and adduction/abduction (AA). The robot is actuated in parallel by four FFMs (FESTO DMSP-20-400N), pressure control of which is regulated by four proportional pressure regulators (FESTO VPPM-6L-L-1-G18-0L6H). Three magnetic rotary encoders (AMS AS5048A) are installed along each axis to measure angular positions forming a three-dimensional coordinate system of the footplate. Four single-axis load cells (FUTEK LCM 300) are installed to measure contraction forces generated by FFMs. A six-axis load cell (SRI M3715C) is installed below the footplate to measure interaction forces and torques between human feet and the footplate.[…]
[Abstract] Hand Sensory Rehabilitation System Which Incorporated Visual and Tactile Feedback – IEEE Conference Publication
[Abstract+References] Design and test of a Microsoft Kinect-based system for delivering adaptive visual feedback to stroke patients during training of upper limb movement
The present paper describes the design and test of a low-cost Microsoft Kinect-based system for delivering adaptive visual feedback to stroke patients during the execution of an upper limb exercise.
Eleven sub-acute stroke patients with varying degrees of upper limb function were recruited. Each subject participated in a control session (repeated twice) and a feedback session (repeated twice). In each session, the subjects were presented with a rectangular pattern displayed on a vertical mounted monitor embedded in the table in front of the patient.
The subjects were asked to move a marker inside the rectangular pattern by using their most affected hand. During the feedback session, the thickness of the rectangular pattern was changed according to the performance of the subject, and the color of the marker changed according to its position, thereby guiding the subject’s movements. In the control session, the thickness of the rectangular pattern and the color of the marker did not change.
The results showed that the movement similarity and smoothness was higher in the feedback session than in the control session while the duration of the movement was longer. The present study showed that adaptive visual feedback delivered by use of the Kinect sensor can increase the similarity and smoothness of upper limb movement in stroke patients.
[ARTICLE] Effects of Mirror Therapy on the Lower Limb Functionality Hemiparesis after Stroke – Full Text PDF
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Purpose of Review
Ramachandran (Nature 377:489–490, 1995) showed that in amputees, phantom limb pain described as a spasming or immobile phantom limb can be alleviated by watching their reflection of the intact limb in a parasagittally placed mirror while moving the intact limb and the phantom simultaneously. This suggested that therapy via mirror visual feedback—mirror therapy—might be considered for other diseases and conditions characterized by poor mobility. We were the first to show that mirror therapy might be beneficial for hemiparesis following stroke. There have now been numerous case reports and studies of mirror therapy for hemiparesis following stroke.
Overall, the majority of studies done thus far on patients with hemiparesis in the subacute or chronic phase following stroke find mirror therapy to be more beneficial than control treatments. Even when mirror therapy is not superior to control therapy, the reason for this is there are similar improvements in both groups. There have not been adverse effects in patients that perform mirror therapy for hemiparesis following stroke.
There appears to be a benefit of mirror therapy for hemiparesis following stroke in the subacute and chronic phase. Trial of mirror therapy for hemiparesis may be warranted. Further study of mirror therapy for hemiparesis following stroke will be welcomed; in particular, it would be important to study different groups of patients given the heterogeneity of stroke.
[ARTICLE] Effects of Visual Feedback on Motion Mimicry Ability during Video-Based Rehabilitation – Full Text PDF
The motion mimicry ability of patients facilitates execution of therapy moves based on visual observation of rehabilitation exercise videos, which can help speed up the recovery process.
This study investigates the effects of visual feedback on the mimicking ability of human subjects in video-based rehabilitation. Inertial Measurement Unit (IMU) sensors was used, which provide a portable system to detect human motion tracking, allowing for experiments to be conducted without space restrictions and provide a greater variety of actions that can be tested. In the experiment, healthy subjects were shown a video of an instructor performing a certain movement task and had to mimic actions to the best of their ability.
A real-time visual feedback system, based on input data from IMU sensors, was introduced to inform subjects of the accuracy of their mimicking actions. Subjects were tested with and without feedback and the relevant joint angle data was collected to determine the individual’s mimicking ability.
Our results showed a significant improvement in subject’s mimicking ability from ‘no feedback’ to ‘feedback’ condition. The key implication of the findings is that visual feedback provides an extrinsic source that allows patients to better synchronize their hand-eye coordination during mimicry. Potential prospective works will investigate the relevance of motion mimicry mechanism in home-based rehabilitation.
[THESIS] Effects of Treadmill Walking With Visual Feedback on Gait Outcomes in People Post Stroke. – Text PDF
Compromised gait is prevalent in people post stroke. Gait training is one of the major components in stroke rehabilitation. Treadmill walking is often used for gait training in people post stroke. Limited studies have examined the effects of a visual feedback system in combination with treadmill-based gait training.
Purpose: The purpose of this study was to investigate the effects of treadmill walking with realtime visual feedback on gait outcomes in people post stroke.
Methods: 6 participants (age 59.3+/-12.34 years old) participated in this case study. They were assigned to either visual feedback gait training group or control based on initial walking speed. Both groups performed 30 minutes of treadmill walking, three times a week, for eight weeks. The control group performed the training with no visual feedback (NVF). The experimental treatment group received real-time visual feedback (VF) on a LCD screen which displayed foot placement and prompts. Data collection was performed before and after the eight weeks, as well as four weeks after the completion of intervention. The kinematic and spatiotemporal variables were recorded and analyzed by using a 3D motion analysis system. (VICON Bonita System). Data process and analysis was performed using VICON Polygon software.
Results: Group averages demonstrated an increase in walking speed and cadence in the VF group. The VF group demonstrated an increase of 11.7% in cadence of the AF and NAF limb. Walking speed of the VF group increased by 21.7% from .95m/s to 1.16m/s. NVF group revealed no notable change in spatiotemporal, or kinematic variables. Neither VF nor NVF group demonstrated notable changes in the kinematic values or gait symmetry.
Conclusion: The findings indicate that gait training with visual feedback can be more effective in improving gait spatiotemporal values than conventional treadmill walking.
[ARTICLE] A changing stroke rehabilitation environment: Implications for upper limb interventions – Full Text PDF
Functional recovery of the upper limb is poor and as many as 50% of stroke survivors still have impairments at 6 months post stroke, despite rehabilitation efforts. With the move towards early supported discharge and community-based rehabilitation, novel solutions are needed to deliver the amount of quality therapy that is required for optimum recovery. We propose a rehabilitation aid that provides patients with augmented visual feedback of their motor performance during task orientated upper limb therapy with the aim of facilitating motor relearning and maximising patients functional outcomes.
[ARTICLE] Reflections on Mirror Therapy – A Systematic Review of the Effect of Mirror Visual Feedback on the Brain
Background. Mirror visual feedback (MVF), a phenomenon where movement of one limb is perceived as movement of the other limb, has the capacity to alleviate phantom limb pain or promote motor recovery of the upper limbs after stroke. The tool has received great interest from health professionals; however, a clear understanding of the mechanisms underlying the neural recovery owing to MVF is lacking.
Objective. We performed a systematic review to assess the effect of MVF on brain activation during a motor task.
Methods. We searched PubMed, CINAHL, and EMBASE databases for neuroimaging studies investigating the effect of MVF on the brain. Key details for each study regarding participants, imaging methods, and results were extracted.
Results. The database search yielded 347 article, of which we identified 33 suitable for inclusion. Compared with a control condition, MVF increases neural activity in areas involved with allocation of attention and cognitive control (dorsolateral prefrontal cortex, posterior cingulate cortex, S1 and S2, precuneus). Apart from activation in the superior temporal gyrus and premotor cortex, there is little evidence that MVF activates the mirror neuron system. MVF increases the excitability of the ipsilateral primary motor cortex (M1) that projects to the “untrained” hand/arm. There is also evidence for ipsilateral projections from the contralateral M1 to the untrained/affected hand as a consequence of training with MVF.
Conclusion. MVF can exert a strong influence on the motor network, mainly through increased cognitive penetration in action control, though the variance in methodology and the lack of studies that shed light on the functional connectivity between areas still limit insight into the actual underlying mechanisms.