Stroke Rehabilitation (III): Impairments in Somatosensation

(1) Prevalence of somatosensory loss post-stroke

Evidence-based practice and research have established that impairments resulting from a stroke happen not only in motor domains (e.g. inability to perform reaching, loss of balance, and slurred speech) but also in somatosensory domains (loss of tactile sensation, limb position sense, and perceiving force). Carey LM (1995) stated that the loss of somatosensation occurs in about 60% of stroke survivors and has detrimental impacts on the quality of life, e.g. in spontaneous use of the hand and object manipulation. 

Intact somatosensation is essential for motor control since it is reliant on both intact feedforward and intact feedback from afferent inputs. It has been suggested that a learned non-use phenomenon with sensory loss leads to further deterioration of motor abilities. Despite this fact, the association between sensory impairment and outcomes following stroke has received limited focus in rehabilitation research. One reason is that most clinicians assume that spontaneous motor recovery occurs in the first 4 weeks post-stroke in the acute phase (Jia-Ching et al, 2005; Wing et al, 1990; Heller A et al, 1991; Lincoln NB et al, 1991), and that somatosensory recovery will arguably follow suit and therefore receives less attention. Another reason is the complexity in measuring the sensing ability of different modalities.

More recently, Connell et al (2008) conducted a newer prospective study with 70 patients with a first stroke assessed on admission day, and 2, 4, and 6 months post-stroke. Their findings did not contradict the earlier findings by Carey LM (1995). Of the sample collected, the authors found that 7–53% had impaired tactile sensations, 31–89% impaired stereognosis, and 34–64% impaired proprioception. Specifically, proprioception and stereognosis (the ability to perceive 3D shape and depth) were more frequently impaired than tactile sensations. This is in contrast to a study by Kim et al. [16] on acute stroke patients, who found that proprioception was less impaired when compared with localization and two-point discrimination regardless of the lesion.

Connell et al further said that the different somatosensory modalities showed only slight agreement between impairment within the same body areas, suggesting that the modalities are independent of each other. This suggests that it is necessary to include all somatosensory modalities while assessing one body part. In contrast, the high agreement between sensory modalities in adjacent body areas means that it is probably not necessary to assess all related body parts, e.g. there was redundancy between the wrist and hand, or between the ankle and foot.

(2) NSA and RASP scales

One challenge of sensory assessment post-stroke is the variety of sensing modalities of somatosensation, ranging from tactile or touch, pressure, position sense, movement direction, pain, to temperature. Another important barrier is the lack of standardization and low reliability of the clinical assessment scale (Winward, et al 1999). At the moment, there are three common clinical assessment scales for sensory impairment: the sensation parts of the Fugl-Meyer Assessment for UE/LE, Nottingham Sensory Assessment (NSA), and Rivermead Assessment of Somatosensory Performance (RASP). All sensory tests are conducted in the absence of vision.

NSA was developed as a standardized clinical sensory assessment, assessing both sides of the body and all areas. The original version uses a 5-scale rating system, has good intra-rater reliability (the same clinicians did multiple times), but poor inter-rater reliability (different clinicians did the same assessment) and was time-consuming (Lincoln NB, et al, 1991). The NSA measures tactile sensations (light touch, temperature, pinprick, pressure, tactile localization, and bilateral simultaneous touch), on the face, trunk, shoulder, elbow, wrist, hand, hip, knee, ankle, and foot, on both the paretic and normal side. The poor reliability has prompted a revision of NSA according to the Erasmus MC version (Em-NSA) (Stolk-Hornsveld, 2006) with lesser items to test but uses 3-scale rating system. Although NSA was shown to have concurrent validity with the more established and gold standard Fugl-Meyer Assessment for sensorimotor impairments (Scalha et al, 2011), this scale is still less attractive, with some clinicians view this to be a mere screening tool at best.

The RASP is a multi-modal sensory tool that tests six sensations (sharp/dull discrimination, surface pressure, tactile localization, temperature discrimination, joint movement, and joint movement direction discrimination), and two secondary sensations (sensory extinction and two-point discrimination) (Winward et al, 2002). The scale for proprioception was shown to have excellent test-retest reliability among sub-acute survivors and good concurrent validity with Motricity Index and Barthel Index, an ordinal scale used to measure performance in activities of daily living (ADL).

(3) Sensory impairments over time

One focus area in stroke rehab is the ability of a clinical assessment to predict recovery. The power of predictability helps clinicians to assess the stroke severity and to provide the most accurate intervention given a particular condition. Connell et al (2008) found the initial somatosensory impairment was significantly related to sensing ability at 6 months, accounting for 46–71% of the variance. The authors argued that the remaining factors were attributed e.g. to more cognitive factors, perceptual ability, and motivation. The spontaneous recovery over time was more obvious in the upper limb compared to the lower limb. 

In a study by Meyer and colleagues in Belgium (Meyer S. et al, 2016), the authors recruited acute stroke patients (< 1 week) and conducted sensory tests. Confirming earlier studies, they found that 41–63% of stroke survivors in the acute phase had a sensory loss in one of the modalities within the first week, but the deficits improved to 3–50% when assessed 6-month post-stroke. Proprioception score of Em-NSA moderately predicts motor ability at 6-month post-stroke as measured by the Fugl-Meyer UE and Action Research Arm Test. As a comparison, stereognosis moderately predicted motor ability at six months post-stroke as measured by Fugl-Meyer UE, the Motricity Index, and Action Research Arm Test. 

Using RASP, the somatosensory subtest of proprioception demonstrated the greatest level of recovery, but no patient achieved full recovery on all somatosensory subtests (Winward et al, 2007). In another study using the original NSA, Connell et al (2008) reported that most recovery of the upper limb tactile sensations and stereognosis occurred in the first 4 months, whereas recovery in proprioception continued over 6 months. Although the motor and functional recovery demonstrated continual improvement over time, somatosensory recovery showed marked variation in subtests both within and between patients. Both Connell's and Winward's studies reported that individual somatosensory modality recovery may be independent of other somatosensory modalities, despite the existence of parallel processing in the central nervous system.

Functional MRI has been beneficial to elucidate plastic changes in the brain following a stroke. Recently Carey et al. (2002) demonstrated in a single case study of severe sensory loss that there was little evidence of neural plastic changes in the early stages after stroke (2 weeks). However, a return of activation in ipsilesional primary and bilateral secondary somatosensory cortices was observed at 3 months and this was maintained at 6 months.

(4) Somatosensory recovery

Kessner et al (2016): Most cortical reorganization within the motor system occurs within 2–3 months post-stroke and stabilizes after 6 months. However, much less is known about the time course of recovery from somatosensory deficits, and about the mutual interaction of somatosensory and motor recovery. The deficits recovered at least partially, mostly within 3 months. Interestingly, some modalities (graphesthesia impairment and movement detection) even appeared to deteriorate during the time course after initial recovery (Julkunen, et al 2005). After about 6 months of recovery, the prevalence of somatosensory deficits seems to be lower. The initial somatosensory deficit was the strongest predictor for long-term somatosensory ability. Taken together, most patients recover at least partially from their somatosensory deficits, mainly during the first three to six months after stroke (Fig. 1). However, not all modalities necessarily recover with positive results. 

The probability and duration to reach a good rehabilitative plateau phase (Barthel index > 60, ambulation > 150 ft) are significantly worse, if stroke patients had combined motor and somatosensory deficits compared to motor deficits only. The authors summarized that somatosensory deficits after stroke have an important negative effect on motor and functional performance, especially proprioceptive impairments!

(5) Somatosensory-specific interventions

Retraining focusing on somatosensory-specific interventions is lacking. Stroke survivors with sensory impairments share that they often feel this is often a neglected aspect in their rehab program (Doyle, Bennet, Fasoli, & McKenna, 2010). 

A randomized controlled trial of sensory retraining has shown improvement in stroke patients’ sensory discrimination functions following a series of tactile and proprioceptive training (Carey et al., 2011). Such improvement was maintained and slightly increased at 6 weeks and 6 months follow-up. Evidently, the impact of somatosensory interventions on the recovery of sensation post-stroke is thought to be positive and significant. The authors have also argued that such a form of intervention is clinically beneficial, where reduction in deficit was targeted to improve lost abilities. 

On the other hand, Gopaul et al. (2018) proposed that the combination of somatosensory training with motor training may result in greater improvements in both motor and somatosensory functions, as compared to interventions that focus on individual function recovery. Most studies of such combined interventions have comprised active training components as it has the potential to drive neural plasticity (produce greater cortical activation extending to multiple areas), particularly when delivered insufficient dose. For example, Byl and colleagues (2008) demonstrated that patients who received higher-dose (72 hours) of integrated active-somatosensory and passive-motor training performed sensory discrimination tasks more accurately as compared to those receiving lower-dose (12-13.3 hours) of training. Despite the improvements observed, motor improvements were considered smaller than somatosensory improvements due to the reinforcement of passive movement training (mental practice and mirror therapy) in their study.

Stroke Rehabilitation (II): Robotic Assessment of Proprioception

Previous studies have found the importance of somatosensory signals in motor control. Deaffarented patients are shown to have unique and distinct movement patterns compared to healthy control. Within the scope of motor behavior, movement-related somatosenses here means bodily senses that cover proprioception (sense of joint position), kinesthesia (sense of limb movement), and other senses originating from the mechanoreceptors, but does not include pain and thermal receptors. A large literature also shows that the somatosensory system is important for motor learning.

Neurological injuries (e.g. stroke, Parkinson's Disease, and multiple sclerosis) are often accompanied by somatosensory deficits. There has been a growing interest to assess and train the somatosensory system in a clinical setting. In the case of stroke, the somatosensory test is part of a standard clinical assessment. However, a recent systematic review (Connell & Tyson, 2012) has shown that such evaluation is known to be unreliable. The authors commented that the sensory section of the Fugl-Meyer Assessment and Erasmus version of Nottingham Sensory Assessment has the best balance between usability and robustness. In a stroke study, it was found that proprioception and stereognosis were more frequently impaired than tactile sensations and that there is little agreement in impairment among different somatosensory modalities (Connell et al, 2008). More research on assessments and interventions for somatosensory impairment post-stroke is warranted.

Broadly speaking, there are two classes in the assessment of proprioception: joint-position matching (JPM) tasks and psychophysical threshold method (PTM).

JPM tasks evaluate the ability to replicate the position or velocity of a joint angle or a limb position in the absence of vision. Participants respond by replicating the reference movement or position using the same limb (unilateral protocol) or the contralateral limb (bilateral). 

On the other hand, PTM tasks assess the ability to detect the intensity of proprioceptive stimuli, or discriminate two stimuli equal in nature but differ in amplitude/intensity. For example, the stimuli can be tactile, position, angle, or vibration. Participants respond typically with a verbal response.

Although some traditional tools such as goniometers can be used, the reliability of such measurements is unproven. For this reason, the use of robotic devices in the assessment of somatosensory integrity becomes popular. Robotics promise increased precision and accuracy, in addition to better reliability compared with standardized observer-based ordinal scales. Examples of such devices include KINARM (bimanual upper limb), MIT Manus (upper limb), Lokomat (lower limb), Wristbot (wrist), AMADEO (fingers). Other devices include an isokinetic dynamometer for the lower limb (Biodex).

Joint Position Matching Task
Joint position matching (JPM) tasks can be exercised on both lower and upper limbs, and either using unilateral or bilateral matching limbs. A thorough review of this test is described by Goble (2010). Instead of a pure sensory test, JPM is seen to involve some working memory component. Let's begin with the lower limb assessment. A few studies used Biodex lower limb devices to study lower limb proprioception. In a study by Willem et al (2002), subjects lied down in a supine position with the ankle in position 15° plantar-flexion. Active and passive joint-position sense using JPM method was assessed at the ankle, and muscle strength (isokinetic peak torque) was determined. This is also an example of a unilateral protocol, i.e. the same limb is used to replicate the movement.

Fig-1: An example of the joint position matching task using the same limb of lower extremities.

Another study investigates the hip and knee joint proprioception in healthy subjects and incomplete SCI subjects (Domingo and Lam, 2014) using a Lokomat exoskeleton. During the task, the subject's knee (or hip) was first moved passively by the robot into a position (joint angle θ). After a short break, the robot then moves it to a so-called distractor position. The subject was then asked to bring the joint back to the original position by using a joystick control (θ_S). The nominal value |θ ─ θ_S| is the matching error, reflecting the subject's performance. Refer to the figure above.

For the upper limb, studies mostly involved the more proximal limb, i.e. shoulder and elbow joints. A study with a bimanual protocol or two-arm matching task used two groups of subjects. In the first group, subjects moved both middle fingers to the same spatial location (extrinsic). The second group, however, was asked to move the right finger to a mirror-symmetric location of the left middle finger with respect to the body midline (intrinsic). The authors showed that bimanual accuracy is higher for tasks involving extrinsic coordinate (Iandolo, et al, 2015).

KINARM has proven to be a popular robotic tool for bimanual tasks studying sensorimotor behavior in the healthy and clinical population. Dukelow et al did a series of studies using KINARM in patients with stroke and see whether proprioception can be assessed objectively. In one study, 74 healthy subjects and 113 subjects with acute stroke (62 left-affected, 51 right-affected) performed a JPM task with vision occluded. The robot moved the most affected arm at a preset speed of 28 cm/sec, direction, and magnitude. Stroke patients were then asked to mirror-match the movement with their opposite, active arm (Semrau et al, 2013). For control subjects, both arms were tested. All subjects performed 36 total movements, for a total of 6 movements in each of 6 movement directions. See the figure below. The authors found that most stroke patients (69% of left-affected; median, 28.0°; 49% of right-affected subjects; median, 22.1°) made significantly larger directional errors than 95% of the controls (95% of range, <22.4°; median, 14.8°).

Fig-2: An example of the joint position matching task using bilateral limbs of upper extremities.

Recently, Konczak, Masia, and colleagues (2016) used a wrist robotic device and found the anisotropic nature of sensory acuity using JPM method on the dominant arm. Active matching acuity for flexion/extension was found to be 4.64 ± 0.24°; abduction/adduction: 3.68 ± 0.32°; supination/pronation: 5.15 ± 0.37°. A similar study was also performed with young children (Marini F, et al., 2017) and it was found that the anisotropic nature of sensory acuity does not change significantly across age. See the figure below for more illustration.

Fig-3: An example of the joint position matching task of the wrist (distal upper limb).

Psychophysical Threshold Method

Assessment using PTM yields a certain psychometric function with nominal value or threshold of detection in movement speed or position/angle. The method utilizes principles of Psychophysics, which is discussed in a separate blog entry on the "Human Sensory Perception". The shape of this function reflects the variability of responses about this threshold. The most common paradigm used in PTM tasks is a method of constant stimuli but one drawback of such method is the length procedure (Simo et al, 2014); and the same trial usually repeats until 3 to 5 correct judgments of the same stimulus are achieved. More recently, a revised and faster version of PTM paradigm was proposed by Mrotek et al (2017) using the "method of adjustment" during ten iterative trials. Here, subjects repeatedly adjust the magnitude of the stimulus until it is just perceptible, with an equal number of trials approaching that estimated threshold from below (i.e., starting from smaller stimulus magnitudes) and above (starting from larger magnitudes). Typical force magnitude and the threshold of detection can be found below for a hemiparetic patient (left) and normal control (right).

Fig-4: An illustration of a psychophysical method in assessing the threshold of detection.

Studies involving the lower limb have investigated the use of robotic devices in assessing knee joint proprioception. Using a custom-made device similar to the one by Biodex, Hurkmans et al. (2007) assessed the smallest detectable angular change in the knee joint. A similar method was used to find the smallest detectable passive knee movement in both sagittal as well as the frontal plane (Cammarata, et al., 2011). This method lets the subjects respond when they are just able to detect a change in joint position. In another study by Lam at UBC (Chrishold et al, 2016) in patients with spinal cord injury, Lokomat was used to test hip and joint again. Here, the joint was moved passively in 4 different movement speeds (0.5, 1.0, 2.0, and 4.0 deg/s) in both flexion and extension directions. The subject had to respond when the movement was first felt.

Assessment of proprioception in conjunction with motor adaptation has been studied by Ostry et al (2010). This study involves MIT-Manus robotic arm that produces a velocity-dependent curl field which perturbs the movement of the upper limb. Sensory acuity was assessed using an adaptive staircase method or PEST. The authors found that motor adaptation causes a shift in sensory acuity, a term called sensory recalibration (by another group, Henriques et al.). In another study, threshold detection of a wrist movement was assessed using a Wristbot by Konczak and colleagues. The authors found that the mean threshold for wrist flexion was 2.15°± 0.43° and 1.52°± 0.36° for abduction.

Conclusion
The robotic-based somatosensory assessment has gained popularity. It has great potential clinical applications in areas that involve human movements and movement disorders. Until now, there is no clinical biomarkers to predict somatosensory impairment in stroke (see: Boyd et al, 2018 for a review).


Reference: Based on a nice book chapter, "Robotic techniques for the assessment of proprioceptive deficits and for proprioceptive training" by Casadio et al., 2018. Figures are taken from the relevant individual citation therein.

Stroke Rehabilitation (I): Neurophysiology of Stroke Recovery

The topic of stroke rehabilitation is huge. In this first out of several blog posts, I will summarize the fundamental concepts of stroke. Subsequent posts will continue with more specific themes, e.g. intervention strategy, somatosensory relearning, and so on. 

Stroke can be classified into either hemorrhagic or ischemic stroke. Hemorrhagic stroke is caused by a rupture or internal bleeding in any of the cerebral arteries. On the other hand, ischemic stroke is due to blockage of blood supply to the brain, causing cell death due to lack of oxygen (infarct). This type of stroke is much more common to occur in either large arteries (atherosclerosis) or small penetrating arteries (lacunar infarct), or cardioembolism (the heart pumps blocking materials up to the brain). Neuroimaging has been useful as a diagnostic tool.

As most patients survive the initial injury, the next biggest challenge is the management of long-term impairment, limitation of daily activities or disability, and reduced participation or handicap. The main focus of the rehabilitation post-stroke is the recovery of the impaired movement (by physiotherapists), and the associated functions in daily living (by occupational therapists). Technically, we have to understand the difference between the recovery of function ("I am able to use the hand and arm in daily activities again") and resolution of impairment ("I can gain back my strength and movement"). Regardless of which, motor recovery after stroke is confusing. The term cannot be separated from compensatory mechanisms, where a new type of movement is produced to achieve the natural way prior to the stroke. Often during the assessment, clinicians do not separate motor compensation and recovery. In doing a prognosis, it has been known that there is a large inter-individual variability, patient heterogeneity. While clinical assessment has been very crucial in the early phase, there also exists a degree of inter-rater variability of the clinicians.

Stroke recovery in the early phase correlates to the resolution of dying tissue, edema, and inflammation (Furlan et al., 1996; Stinear and Byblow, 2014), while later recovery relates mainly to disinhibition of redundant neural circuits, recruitment of functionally homologous pathways, and the creation of neural connections to overtake the previous functions of the damaged neurons (Rossini et al., 2007; Murphy and Corbett, 2009; Ackerley et al., 2011). Interestingly, such processes may occur on the ipsilesional and contralesional hemispheres and are not completely understood (Hoyer and Celnik, 2011; Buetefisch, 2015).

Several studies have shown that patients commonly demonstrate increased M1 excitability on the contralesional hemisphere (equivalent to the ipsilateral hemisphere for healthy patients) for movements with the affected side (e.g. Shimizu et al., 2002; Butefisch et al., 2008; Murase et al., 2004; Ward and Cohen, 2004). Such theory, known as the interhemispheric competition model, says that an interhemispheric imbalance occurs in patients where the ipsilesional M1 no longer inhibits the contralesional hemisphere and the contralesional side appears to inhibit the ipsilesional, possibly through the transcallosal fibers. The magnitude of such an imbalance appears to positively correlate with the degree of motor impairment (Murase et al., 2004), and the interhemispheric imbalance in other functional networks may also contribute toward other cortical functional disruptions including neglect and aphasia.

Neuroimaging studies have shown that bilateral activation of the motor cortex leads to poorer motor recovery in most stroke patients. Conversely, studies by Nick Ward and colleagues show that a shift from bilateral activation to unilateral activation is a sign of good recovery. In other studies, it has been shown that this statement may have a limitation, i.e. significant mirror movements of the unaffected hand, causing an increase in contralesional activity.




In 2008, Krakauer's team studied the recovery of motor impairment using improvement in the Fugl-Meyer scale (FM) of the upper limb (UL). They defined recovery of impairment as the difference between FM score in the few days after stroke and at a later time point (3 months) (Prabakharan S. et al, 2008). They pointed to the idea of the proportional recovery rule which reflects spontaneous recovery. The maximum FM score for UL = 66. The proportional recovery rule states that, at 3 months, patients should get approximately 70% of their maximum potential recovery back. Example: a patient with moderate hemiparesis of 46 will recover (66-46) x 0.7 = 60. This rule has been validated in subsequent studies. Interestingly, some severe patients do not follow this rule while some other severe patients do. Such a categorical phenomenon bears two consequences. First, perhaps the current rehab therapy has little or, if it does, limited impact on the recovery within 3 months after the onset of stroke. Second, there are some underlying neurophysiological mechanisms unique to those non-fitter severe patients (see Krakauer et al, 2015).

TMS may provide a valuable assessment tool early in stroke. It can be used to test the functional integrity and excitability of the descending corticospinal pathways. Studies have shown that the ability to elicit MEP (motor evoked potential) within 2 weeks after stroke indicates a good corticospinal tract (CST) and it serves as a good predictor for recovery. However, most of these studies only targeted the upper limb, not the lower limb (LL), to the difficulty in accessing the "leg" area in the medial wall of the central sulcus. See Bembenek J.P, et al, (2012) for a review. Byblow et al (2015) did an important study using TMS very early in stroke, where they show that non-fitter patients do not follow the proportional recovery rule because they do not have intact CST useful for recovery. Patients who have their posterior limb of the internal capsule above 0.15, a threshold or point of no return, do not recover at later assessments. The resting motor threshold (RMT) also displays the proportional recovery rule. Interestingly, the authors show that adding regular therapy session does not yield significant results, suggesting that a more intensive behavioral intervention (e.g. using robots) may be needed. Feng W, et al (2015) did another relevant study where they formulated a neuroimaging biomarker of stroke. The authors used a weighted CST load, a method to better estimate the integrity of the CST in the ipsilesional hemisphere. An initial assessment using such measure, instead of an initial FM score, would be a more graded and sensitive predictor of recovery.