Stroke is a leading cause of disability with associated hemiparesis resulting in difficulty bearing and transferring weight on to the paretic limb. Difficulties in weight bearing and weight transfer may result in impaired mobility and balance, increased fall risk, and decreased community engagement. Despite considerable efforts aimed at improving weight transfer after stroke, impairments in its neuromotor and biomechanical control remain poorly understood. In the present study, a novel experimental paradigm was used to characterize differences in weight transfer biomechanics in individuals with chronic stroke versus able-bodied controls
Fifteen participants with stroke and fifteen age-matched able-bodied controls participated in the study. Participants stood with one foot on each of two custom built platforms. One of the platforms dropped 4.3 cm vertically to induce lateral weight transfer and weight bearing. Trials involving a drop of the platform beneath the paretic lower extremity (non-dominant limb for control) were included in the analyses. Paretic lower extremity joint kinematics, vertical ground reaction forces, and center of pressure velocity were measured. All participants completed the clinical Step Test and Four-Square Step Test.
Reduced paretic ankle, knee, and hip joint angular displacement and velocity, delayed ankle and knee inter-joint timing, increased downward displacement of center of mass, and increased center of pressure (COP) velocity stabilization time were exhibited in the stroke group compared to the control group. In addition, paretic COP velocity stabilization time during induced weight transfer predicted Four-Square Step Test scores in individuals post-stroke.
The induced weight transfer approach identified stroke-related abnormalities in the control of weight transfer towards the paretic limb side compared to controls. Decreased joint flexion of the paretic ankle and knee, altered inter-joint timing, and increased COP stabilization times may reflect difficulties in neuromuscular control during weight transfer following stroke. Future work will investigate the potential of improving functional weight transfer through induced weight transfer training exercise.
Stroke is a leading cause of death and serious long-term disability in the United States [1, 2]. Individuals with hemiparesis due to stroke commonly demonstrate difficulty bearing weight on the paretic lower extremity and transferring weight from one leg to the other [3,4,5]. Reduced paretic limb weight bearing has been associated with functional deficits when rising from a chair , standing , and walking [8, 9]. The ability to transfer bodyweight between the lower limbs is related to impaired standing and stepping balance [10, 11] and gait performance [3, 12]. In particular, diminished weight transfer to the paretic limb contributes to gait asymmetries, which commonly lead to greater energy expenditure . Previously we reported the ability to transfer weight laterally to the paretic leg during single stance was associated with self-selected walking speed and the capacity to increase walking speed . This may indicate that weight transfer deficits negatively affect forward progression. Indeed, forceful weight shift towards the paretic limb enhanced paretic lower extremity kinetics and muscle activities that contribute to forward progression . Moreover, deficits in paretic limb weight-bearing contribute to lateral and vertical balance instability and are associated with risk of falling in individuals with chronic stroke . These functional limitations can affect community participation and quality of life. Consequently, restoring the capacity to load the paretic limb is an important goal for rehabilitation post-stroke [17,18,19].
Despite considerable rehabilitation efforts aimed at improving weight transfer following a stroke [10, 20], the impairments in neuromotor and biomechanical control underlying weight transfer dysfunction remain poorly understood. Functional weight transfer requires the coordination of multi-joint actions to absorb the impact force and provide support to the body. In particular, the ankle and knee joints are key contributors to shock absorption [21,22,23,24] and body weight support . Increased stiffness in the paretic limb knee and ankle joints has been reported in persons with stroke [26, 27]. Inadequate lower limb joint flexion may disrupt impact force regulation during weight acceptance and lead to instability that ultimately delays and prolongs weight transfer timing during locomotion. Alternatively, excessive ankle and knee joint flexion during loading may precipitate limb collapse and destabilize balance during weight transfer. Thus, both insufficient and excessive joint movement could affect weight transfer processes. In addition to the amplitude of paretic ankle and knee joint angular displacements, abnormalities in the relative timing of these joint motions (i.e., inter-joint coordination) may also contribute to impaired weight transfer following stroke.
Another key factor affecting functional weight transfer is the ability to regulate the center of pressure (COP) beneath the feet in relation to the body center of mass (COM). During locomotion, effective neuromotor control of the lower extremities contributes to regulating COM position and movement relative to the base of support to maintain stability and prevent falling. Compared with able-bodied adults, persons with chronic stroke have a reduced capacity to rapidly shift their COP to the stance limb during gait initiation , reflecting abnormalities in balance control during weight transfer. Because hip and ankle musculature regulates COM and COP movements , difficulties in controlling hip kinematics and hip-ankle joint coordination may contribute to delayed and reduced weight transfer after a stroke.
To further address the foregoing issues, this study examined the potential biomechanical factors that could affect lower paretic limb weight bearing and weight transfer performance following stroke. After stroke individuals often limit their use of the paretic limb by favoring the use of the less affected leg during stance and gait . An approach that forces individuals to fully load the paretic limb is warranted to reveal the performance capacity and assess the control of weight bearing and weight transfer. Accordingly, we designed a novel system that vertically displaces the support surface underneath one leg and therefore imposes weight transfer. By unilaterally introducing a perturbation that drops the standing support surface, this approach forces a rapid alteration in inter-limb weight bearing distribution and challenges medial–lateral balance control.
The primary purpose of this study was to characterize the kinematics and kinetics of the paretic lower extremity during an externally induced weight transfer towards the paretic limb in chronic stroke compared to age-matched controls. We hypothesized that, compared with able-bodied individuals, those with chronic stroke would show reduced and uncoordinated paretic limb joint angular displacements, and prolonged stabilization time of the COP velocity following an externally induced weight transfer. In addition, relationships between measurements during imposed weight transfer, motor recovery assessment (i.e. Chedoke McMaster Stroke Assessment leg and foot subscale), and clinical limb loading and balance performance (i.e. Four-Square Step Test (FSST) and Step Test (ST)) were explored. We expected that COP velocity stabilization time and CMSA scores would be associated with FSST and ST scores.[…]
Objective: To investigate the performance of the less affected upper limb in people with stroke compared with normative values. To examine less affected upper limb function in those whose prestroke dominant limb became paretic and those whose prestroke nondominant limb became paretic.
Design: Cohort study of survivors of chronic stroke (7.2±6.7y post incident).
Setting: The study was performed at a freestanding academic rehabilitation hospital.
Participants: Survivors of chronic stroke (N=40) with severe hand impairment (Chedoke-McMaster Stroke Assessment rating of 2-3 on Stage of Hand) participated in the study. In 20 participants the prestroke dominant hand (DH) was tested (nondominant hand [NH] affected by stroke), and in 20 participants the prestroke NH was tested (DH affected by stroke).
Main outcome measure: Jebsen-Taylor Hand Function Test. Data from survivors of stroke were compared with normative age- and sex-matched data from neurologically intact individuals.
Results: When combined, DH and NH groups performed significantly worse on fine motor tasks with their nonparetic hand relative to normative data (P<.007 for all measures). Even the participants who continued to use their prestroke DH as their primary hand after the stroke demonstrated reduced fine motor skills compared with normative data. In contrast, grip strength was not significantly affected in either group of survivors of stroke (P>.140).
Conclusions: Survivors of stroke with severe impairment of the paretic limb continue to present significant upper extremity impairment in their nominally nonparetic limb even years after stroke. This phenomenon was observed regardless of whether the DH or NH hand was primarily affected. Because this group of survivors of stroke is especially dependent on the nonparetic limb for performing functional tasks, our results suggest that the nonparetic upper limb should be targeted for rehabilitation.
Background: Population ageing and changes in the epidemiological profile of neurological pathologies has resulted in an increase in patients with disabilities. Rehabilitation strategies such as Modified Constraint-Induced Movement Therapy (CIMTm) play a key role in treating patients with neurologic deficiencies and motor impairments. This intervention is intended to mitigate disability, promote maximum functional independence, and optimize social and economic participation of patients with upper extremity weakness. Our goal was to assess the recovery of functional independence in patients after a stroke using to CIMTm.
Patients and method: Thirty-six subjects who had suffered stroke took part in a randomised clinical trial. The treatment was applied through either collective or individual modalities for three hours per day for a period of ten days. Participant’s functional independence was assessed using the Functional Independence Measure (FIM) scale at the before and after of the intervention.
Results: An analysis of covariance carried out on the pre-test assessments indicates that the dependent variable presents significant differences (F1.31 = 42.78, p < 0.001, η2p = 0.72) in favour of the collective intervention modality.
Conclusion: Both modalities of CIMTm intervention promote functional independence. However, the greatest improvements were observed in participants in the collective modality. Improvements in functional independence pursue a reduction in learned non-use behaviours through greater use of the paretic upper extremity in everyday activities.
Unilateral arm paralysis is a common symptom of stroke. In stroke patients, we observed that self-guided biomechanical support by the nonparetic arm unexpectedly triggered electromyographic activity with normal muscle synergies in the paretic arm. The muscle activities on the paretic arm became similar to the muscle activities on the nonparetic arm with self-supported exercises that were quantified by the similarity index (SI). Electromyogram (EMG) signals and functional near-infrared spectroscopy (fNIRS) of the patients (n=54) showed that self-supported exercise can have an immediate effect of improving the muscle activities by 40–80% according to SI quantification, and the muscle activities became much more similar to the muscle activities of the age-matched healthy subjects. Using this self-supported exercise, we investigated whether the recruitment of a patient’s contralesional nervous system could reactivate their ipsilesional neural circuits and stimulate functional recovery. We proposed biofeedback training with self-supported exercise where the muscle activities were visualized to encourage the appropriate neural pathways for activating the muscles of the paretic arm. We developed the biofeedback system and tested the recovery speed with the patients (n=27) for 2 months. The clinical tests showed that self-support-based biofeedback training improved SI approximately by 40%, Stroke Impairment Assessment Set (SIAS) by 35%, and Functional Independence Measure (FIM) by 20%.
Stroke is the leading cause of long-term disability worldwide. Of more than 750,000 stroke victims in the United States each year , approximately two-thirds survive and require immediate rehabilitation to recover lost brain functions . These stroke rehabilitation programs, of which direct and indirect costs were estimated to be 73.7 billion dollars in 2010 , aim to help survivors gain physical independence and better quality of life.
Stroke damage typically interrupts blood flow within one brain hemisphere, resulting in unilateral motor deficits, sensory deficits, or both. The preservation of long-term neural and synaptic plasticity is essential for the functional reorganization and recovery of neural pathways disrupted by stroke –. Stroke survivors typically require long-term, intensive rehabilitation training due to the length of time required for these recovery processes , . The typical time course for partial recovery of arm movement after mild to moderate unilateral stroke damage is 2 to 6 months, depending on the severity of tissue damage and the latency of treatment initiation , ; however, patients with severe damage require additional months to years of rehabilitation. Given the economic burden on patients’ families and the medical system, novel rehabilitation methods that promote rapid and complete functional recovery are needed, along with a better understanding of the functional mechanisms and neural circuits that can participate in potential therapeutic processes. The identification of rehabilitation methods that can more effectively recover brain functions in the damaged hemisphere by re-engaging dormant motor functions should be a major global objective, from both economic and societal perspectives. Such an objective would require the interface of biology, medical research, and clinical practice .
Recently, candidate brain areas that become activated during stroke recovery have been identified in patients and animal models . Brain imaging studies during stroke recovery suggest that the extent of functional motor recovery is associated with an increase in neuronal activity in the sensorimotor cortex of the ipsilesional hemisphere –. Other work has suggested that repetitive sensorimotor tasks may promote cortical reorganization and functional recovery in the ipsilesional area by increasing bilateral cortical activity to enhance neuroplasticity . Activation in the contralesional hemisphere is also observed in the early stages of post-stroke patients. This activation has been explained by the emergence of communication in corticospinal projections that are silent in the healthy state , and it may also contribute to movement-related neural activity on the ipsilesional limb , . Functional brain imaging studies show that activity of the contralesional hemisphere is increased early after stroke and gradually declines as recovery progresses . The functional relevance of contralesional recruitment remains unclear , . Some reported studies have linked high abnormal activity to a high inhibitory signaling drive onto the ipsilesional cortex , which may be a major contributor to motor impairment , . Recent studies have also investigated the benefits of activating the contralesional and/or ipsilesional hemispheres in functional motor recovery using brain-computer interface (BCI) and transcranial magnetic stimulation (TMS) therapies , .
Current stroke rehabilitation approaches have largely focused on paretic limb rehabilitation interventions such as muscle strengthening and endurance training , forced-use therapy , constraint-induced exercise , robot therapy with biofeedback , nonparetic limb interventions (e.g., mirror-therapy , ), or bilateral/bimanual training , . However, to date, none have clearly investigated how the use of a patient’s unaffected neural circuits in the healthy cortical hemisphere, or in the local peripheral circuit, affect the impaired limb in terms of functional rehabilitation of the bilateral cortical sensorimotor network .
In this study, we investigated a motor recovery approach for post-stroke unilateral arm impairment that combined sensory feedback, motor control, and motor intention. While observing a patient cohort with unilateral stroke damage and arm movement impairment, we found that a specific self-guided motion, which we termed self-supported exercise, surprisingly reactivated a healthy muscles pattern in the paretic arm. The key of the self-supported exercise is use of the nonparetic arm as a support to help move the paretic arm. First, we will show the observation of appropriate muscle recruitment and reduction of abnormal muscle synergies for post-stroke patients during the self-supported exercise, which are a common problem in stroke recovery . Then, we conduct the experiments of functional imaging and electromyography recordings and characterized the neurobiology and physiology of this self-supported exercise. Based on this mechanism, we designed a rehabilitation program involving biofeedback-aided self-supported exercises that employ a patients’ self-initiated motor intention. The results of the comparative experiments between the feedback training cohorts and the control cohorts show that this method results in efficient recovery from post-stroke motion paralysis. Finally, we discuss the significance of our findings for the design of biologically-based stroke rehabilitation.[…]
Background/Objective. We investigated interhemispheric interactions in stroke survivors by measuring transcranial magnetic stimulation (TMS)–evoked cortical coherence. We tested the effect of TMS on interhemispheric coherence during rest and active muscle contraction and compared coherence in stroke and older adults. We evaluated the relationships between interhemispheric coherence, paretic motor function, and the ipsilateral cortical silent period (iSP).
Methods. Participants with (n = 19) and without (n = 14) chronic stroke either rested or maintained a contraction of the ipsilateral hand muscle during simultaneous recordings of evoked responses to TMS of the ipsilesional/nondominant (i/ndM1) and contralesional/dominant (c/dM1) primary motor cortex with EEG and in the hand muscle with EMG. We calculated pre- and post-TMS interhemispheric beta coherence (15-30 Hz) between motor areas in both conditions and the iSP duration during the active condition.
Results. During active i/ndM1 TMS, interhemispheric coherence increased immediately following TMS in controls but not in stroke. Coherence during active cM1 TMS was greater than iM1 TMS in the stroke group. Coherence during active iM1 TMS was less in stroke participants and was negatively associated with measures of paretic arm motor function. Paretic iSP was longer compared with controls and negatively associated with clinical measures of manual dexterity. There was no relationship between coherence and. iSP for either group. No within- or between-group differences in coherence were observed at rest.
Conclusions. TMS-evoked cortical coherence during hand muscle activation can index interhemispheric interactions associated with poststroke motor function and potentially offer new insights into neural mechanisms influencing functional recovery.
Ankle exoskeletons offer a promising opportunity to offset mechanical deficits after stroke by applying the needed torque at the paretic ankle. Because joint torque is related to gait speed, it is important to consider the user’s gait speed when determining the magnitude of assistive joint torque. We developed and tested a novel exoskeleton controller for delivering propulsive assistance which modulates exoskeleton torque magnitude based on both soleus muscle activity and walking speed. The purpose of this research is to assess the impact of the resulting exoskeleton assistance on post-stroke walking performance across a range of walking speeds.
Six participants with stroke walked with and without assistance applied to a powered ankle exoskeleton on the paretic limb. Walking speed started at 60% of their comfortable overground speed and was increased each minute (n00, n01, n02, etc.). We measured lower limb joint and limb powers, metabolic cost of transport, paretic and non-paretic limb propulsion, and trailing limb angle.
Exoskeleton assistance increased with walking speed, verifying the speed-adaptive nature of the controller. Both paretic ankle joint power and total limb power increased significantly with exoskeleton assistance at six walking speeds (n00, n01, n02, n03, n04, n05). Despite these joint- and limb-level benefits associated with exoskeleton assistance, no subject averaged metabolic benefits were evident when compared to the unassisted condition. Both paretic trailing limb angle and integrated anterior paretic ground reaction forces were reduced with assistance applied as compared to no assistance at four speeds (n00, n01, n02, n03).
Our results suggest that despite appropriate scaling of ankle assistance by the exoskeleton controller, suboptimal limb posture limited the conversion of exoskeleton assistance into forward propulsion. Future studies could include biofeedback or verbal cues to guide users into limb configurations that encourage the conversion of mechanical power at the ankle to forward propulsion.
Walking after a stroke is more metabolically expensive, leading to rapid exhaustion, limited mobility, and reduced physical activity . Hemiparetic walking is slow and asymmetric compared to unimpaired gait. Preferred walking speeds following stroke range between < 0.2 m s− 1 and ~ 0.8 m s− 1  compared to ~ 1.4 m s− 1 in unimpaired adults, and large interlimb asymmetry has been documented in ankle joint power output [3, 4]. The ankle plantarflexors are responsible for up to 50% of the total positive work needed to maintain forward gait [5, 6]; therefore, weakness of the paretic plantarflexors is especially debilitating, and as a result, the paretic ankle is often a specific target of stroke rehabilitation [7, 8, 9, 10]. In recent years, ankle exoskeletons have emerged as a technology capable of improving ankle power output by applying torque at the ankle joint during walking in clinical populations [7, 8] and healthy controls [11, 12, 13, 14]. Myoelectric exoskeletons offer a user-controlled approach to stroke rehabilitation by measuring and adapting to changes in the user’s soleus electromyography (EMG) when generating torque profiles applied at the ankle . For example, a proportional myoelectric ankle exoskeleton was shown to increase the paretic plantarflexion moment for persons post-stroke walking at 75% of their comfortable overground (OVG) speed ; despite these improvements, assistance did not reduce the metabolic cost of walking or improve percent paretic propulsion. The authors suggested exoskeleton performance could be limited because the walking speed was restricted to a pace at which exoskeleton assistance was not needed.
Exoskeleton design for improved function following a stroke would benefit from understanding the interaction among exoskeleton assistance, changes in walking speed, and measured walking performance. Increases in walking speed post-stroke are associated with improvements in forward propulsion and propulsion symmetry , trailing limb posture [17, 18], step length symmetries [17, 19], and greater walking economies [17, 19]. This suggests that assistive technologies need to account for variability in walking speeds to further improve post-stroke walking outcomes. However, research to date has evaluated exoskeleton performance at only one walking speed, typically set to either the participant’s comfortable OVG speed or a speed below this value [7, 8]. At constant speeds, ankle exoskeletons have been shown to improve total ankle power in both healthy controls  and persons post-stroke , suggesting the joint powers and joint power symmetries could be improved by exoskeleton technology. Additionally, an exosuit applying assistance to the ankle was able to improve paretic propulsion and metabolic cost in persons post-stroke walking at their comfortable OVG speed . Assessing the impact of exoskeleton assistance on walking performance across a range of speeds is the next logical step toward developing exoskeleton intervention strategies targeted at improving walking performance and quality of life for millions of persons post-stroke.
In order to assess the impact of exoskeleton assistance across a range of walking speeds in persons post-stroke, we developed a novel, speed-adaptive exoskeleton controller that automatically modulates the magnitude of ankle torque with changes in walking speed and soleus EMG. We hypothesized that: 1) Our novel speed-adaptive controller will scale exoskeleton assistance with increases in walking speed as intended. 2) Exoskeleton assistance will lead to increases in total average net paretic ankle power and limb power at all walking speeds. 3) Exoskeleton assistance will lead to metabolic benefits associated with improved paretic average net ankle and limb powers.
We implemented an exoskeleton emulator comprised of a powerful off-board actuation and control system, a flexible Bowden cable transmission, and a lightweight exoskeleton end effector . The exoskeleton end effector includes shank and foot carbon fiber components custom fitted to participants and hinged at the ankle. The desired exoskeleton torque profile was applied by a benchtop motor (Baldor Electric Co, USA) to the carbon-fiber ankle exoskeleton through a Bowden-cable transmission system. An inline tensile load cell (DCE-2500 N, LCM Systems, Newport, UK) was used to confirm the force transmitted by the exoskeleton emulator during exoskeleton assistance.
Our exoskeleton controller alters the timing and magnitude of assistance with the user’s soleus EMG signal and walking speed (Fig. 1). The exoskeleton torque is determined from Eq. 1, in which participant mass (mparticipant) is constant across speeds, treadmill speed (V) is measured in real-time, the speed gain (Gspeed) is constant for all subjects and across speeds, the adaptive gain (Gadp) is constant for a gait cycle and calculated anew for each gait cycle, and the force-gated and normalized EMG (EMGGRFgated) is a continuously changing variable.
Background. High-intensity, variable stepping training can improve walking speed in individuals poststroke, although neuromuscular strategies used to achieve faster speeds are unclear. We evaluated changes in joint kinetics and neuromuscular coordination following such training; movement strategies consistent with intact individuals were considered evidence of recovery and abnormal strategies indicative of compensation.
Methods. A total of 15 individuals with stroke (duration: 23 ± 30 months) received ≤40 sessions of high-intensity stepping in variable contexts (tasks and environments). Lower-extremity kinetics and electromyographic (EMG) activity were collected prior to (BSL) and following (POST) training at peak treadmill speeds and speeds matched to peak BSL (MATCH). Primary measures included positive (concentric) joint and total limb powers, measures of interlimb (paretic/nonparetic powers) and intralimb compensation (hip/ankle or knee/ankle powers), and muscle synergies calculated using nonnegative matrix factorization.
Results. Gains in most positive paretic and nonparetic joint powers were observed at higher speeds at POST, with decreased interlimb compensation and limited changes in intralimb compensation. There were very few differences in kinetic measures between BSL to MATCH conditions. However, the number of neuromuscular synergies increased significantly following training at both POST and MATCH conditions, indicating gains from training rather than altered speeds. Despite these results, speed improvements were associated primarily with changes in nonparetic versus paretic powers.
Conclusion. Gains in locomotor function were accomplished by movement strategies consistent with both recovery and compensation. These and other data indicate that both strategies may be necessary to maximize walking function in patients poststroke.
After a stroke, during seated reaching with their paretic upper limb, many patients spontaneously replace the use of their arm by trunk compensation movements, even though they are able to use their arm when forced to do so. We previously quantified this proximal arm non-use (PANU) with a motion capture system (Zebris, CMS20s). The aim of this study was to validate a low-cost Microsoft Kinect-based system against the CMS20s reference system to diagnose PANU.
In 19 hemiparetic stroke individuals, the PANU score, reach length, trunk length, and proximal arm use (PAU) were measured during seated reaching simultaneously by the Kinect (v2) and the CMS20s over two testing sessions separated by two hours.
Intraclass correlation coefficients (ICC) and linear regression analysis showed that the PANU score (ICC = 0.96, r2 = 0.92), reach length (ICC = 0.81, r2 = 0.68), trunk length (ICC = 0.97, r2 = 0.94) and PAU (ICC = 0.97, r2 = 0.94) measured using the Kinect were strongly related to those measured using the CMS20s. The PANU scores showed good test-retest reliability for both the Kinect (ICC = 0.76) and CMS20s (ICC = 0.72). Bland and Altman plots showed slightly reduced PANU scores in the re-test session for both systems (Kinect: − 4.25 ± 6.76; CMS20s: − 4.71 ± 7.88), which suggests a practice effect.
We showed that the Kinect could accurately and reliably assess PANU, reach length, trunk length and PAU during seated reaching in post stroke individuals. We conclude that the Kinect can offer a low-cost and widely available solution to clinically assess PANU for individualised rehabilitation and to monitor the progress of paretic arm recovery.
A large proportion of post-stroke individuals develop upper limb (UL) disabilities that result in difficulties in performing daily activities such as reaching for objects, which impacts their quality of life . Stroke survivors often compensate for these impairments by adapting their movement patterns to incorporate additional degrees of freedom at new joints and body segments. One of the most common compensatory behaviours following a stroke is when patients replace the use of the paretic UL with the use of the less impaired UL. When such compensation persists even if the paretic UL recovered enough to be used, this is called learned non-use. However, the learned non-use phenomenon is more general than this specific case: it applies to any cases when individuals “forget” how to use their affected body parts and instead overuse compensations . Here, our reasoning is that the learned non-use phenomenon explains why some patients “forget” how to use the proximal joints of their paretic UL and instead overuse trunk compensation during reaching . Long-term non-use of shoulder-elbow movements is suspected to be detrimental to optimal upper limb functional recovery, due the “Use it or lose it” principle of use-dependent neural plasticity [4, 5]. Long-term overuse of trunk compensation may lead to suboptimal motor recovery of the paretic UL and secondary complications such as muscle contractures [6, 7, 8].
In our previous study , the non-use of shoulder-elbow joints during reaching has been termed “proximal arm non-use” and was assessed with the PANU score. The PANU score was derived by the substraction of the spontaneous proximal arm-use (SPAU) from the maximal proximal arm-use (MPAU). MPAU was recorded when patients were asked to voluntarily maximise proximal arm-use (or constrained not to use trunk movement). SPAU was recorded when patients were free to spontaneously balance their use of trunk and their use of proximal arm joints during hand reaching while seated. We showed that the PANU score had very good test-retest reliability. The PANU score did not depend on time since stroke. Higher PANU scores were moderately related to higher UL impairment (Fugl Meyer Assessment of the upper extremity-FM-UE) and to lower UL function (Box & Block Test-BBT). Moreover, 61% of patients with lower impairment (FM-UE proximal > 28/42) exhibited proximal arm non-use (PANU score > 6.5%) . The PANU score provides information about the remaining functional motor reserve of the paretic arm (at the level of shoulder and elbow movements), which is not used by the post-stroke individual. Consequently, the PANU score potentially enables a clinician to select patients for specific rehabilitation programs focusing on the “maximal-use” of shoulder and elbow movements as well as to monitor the paretic arm recovery/compensation post-stroke. Therefore, PANU assessment is complementary with routine clinical measures of arm impairment (e.g., FM-UE) and function (e.g., BBT).
In our previous study , the PANU measurement using the ultrasound 3D motion capture system (CMS20s, Zebris) required to position markers on the hands and on the trunk of the patient during the seated reaching task. Although most clinical motion analysis devices use a marker-based system , recent developments in computer gaming technology brought forward marker-less infrared sensors such as the Microsoft’s Kinect (v2 for Xbox One) that captures the users’ body movement and allows them to interact within video games [10, 11, 12, 13, 14]. The Kinect sensor is low cost and reliably tracks body joints in real-time without requiring markers attached to the body . Moreover, the official Microsoft software development kit (SDK) release permitted the Kinect sensor to be used not only as a gaming device, but also as a measurement system. The Kinect sensor showed comparable results in measuring shoulder movements during validity assessment with an established highly accurate 3D motion capture (6-camera Vicon) system [16, 17]. However, very few studies are available on the validity of the Kinect to accurately track trunk and hand motions in a reaching task , which is essential for quantifying the PANU score in post-stroke individuals.
Therefore, the purpose of this study was to validate a Kinect-based system to accurately and reliably quantify PANU scores and related kinematic parameters in individuals who sustained a stroke. Our clinical question was whether the Kinect sensor could replace the existing CMS20s sensor for PANU assessment. We hypothesised that the Kinect will provide similar measurements of PANU score and related kinematic variables as those determined by the reference CMS20s system.[…]
Fig. 1 Experimental setup. The quantification of the proximal arm non-use (PANU) score was simultaneously determined by the Kinect (blue encircled) and CMS20s (red encircled) movement recording systems. The CMS20s recorded the position of 3 markers placed on the manubrium, right dorsal hand, left dorsal hand (blue spots). The Kinect provided a skeleton of the person (orange) out of which we retained 3 “joints” corresponding best to the position of CMS20s markers on the body: Spine-Shoulder, WristRight, WristLeft
The purpose of the study is to assess poststroke muscle structural alterations by examining muscular electrical conductivity and inherent electrophysiological properties. In particular, muscle impedance and compound muscle action potentials (CMAP) were measured from the hypothenar muscle bilaterally using the electrical impedance myography and the electrophysiological techniques, respectively. Significant changes of muscle impedance were observed in the paretic muscle compared with the contralateral side (resistance: paretic: 27.54 ± 0.97 Ω, contralateral: 25.46 ± 0.91 Ω, p < 0.05; phase angle: paretic: 8.81 ± 0.61°, contralateral: 10.79 ± 0.69°, p< 0.05). In addition, impedance changes correlated moderately with the CMAP amplitude in the paretic hand (phase angle: r = 0.66, p < 0.05; reactance: r = 0.58, p < 0.05). The study discloses significant muscle rearrangements as a result of fiber loss or atrophy, fat infiltration or impaired membrane integrity in chronic stroke.
Muscle weakness is a remarkable symptom in stroke and contributes significantly to impaired motor functions. To understand mechanisms underlying weakness, studies can focus on assessing changes in neural control and muscular properties. In particular, intramuscular electromyography (EMG) and morphological techniques have been applied to examine muscle structural rearrangements poststroke. Increased motor unit fiber density, larger and complex motor unit action potentials (1–3), small angular fibers, as well as fiber type grouping (4, 5) have been observed in the acute and chronic stages of stroke suggesting the process of muscle denervation and reinnervation. While these studies characterize structural alterations in the paretic muscles, most approaches involve invasive recording and are limited by sampling only small selective areas of the muscle.
Electrical impedance myography (EIM) is an emerging technique for noninvasive evaluation of muscle electrical conductive properties. It applies weak, high-frequency alternating current to the muscles and produces raw bio-impedance data without causing neuronal and muscular depolarization (6, 7). EIM measures three impedance parameters in terms of resistance (R), reactance (X), and phase angle [θ = arctan (X/R)] (7, 8), which represent the inherent resistivity of skeletal muscle relative to extracellular and intracellular fluid, the integrity of cell membranes, tissue interfaces and non-ionic substances, and membrane oscillation properties of the muscle respectively (9–12).
Electrical impedance myography has been used to examine muscle structural alterations in a number of neuromuscular diseases including amyotrophic lateral sclerosis (ALS), muscular dystrophy, and spinal muscular atrophy (6, 7, 13–19). It is sensitive to muscle structural modifications in terms of atrophy, increased fat infiltration or connective tissue growth (20–22). In addition, the technique demonstrates strong correlations with standard measures of ALS including ALS functional rating scale-revised, handheld dynamometry, and motor unit number estimation in tracking the progression of the disease (13, 17, 23).
Applications of EIM to assess poststroke muscle conditions are relatively limited in the literature. In a previous study, we examined muscle impedance properties in the biceps brachii and found significant changes of muscle structural properties in the paretic side (24). Since proximal muscles demonstrate different extents of impairment from distal muscles (25), it remains unknown whether findings from biceps brachii are applicable to hand muscles. In this study, we applied EIM technique to examine impedance changes in the hypothenar muscle poststroke. In addition, we measured the compound muscle action potentials (CMAP) of the muscle, to assess inherent electrical properties. CMAP is evoked by electrical activation of all functioning motor units and represents summation of all action potentials in spatial distribution. Application of the two different techniques to the same muscle may disclose different features of the muscle and improve current knowledge on structural changes in the paretic hand muscle.[…]
The human hand comprises complex sensorimotor functions that can be impaired by neurological diseases and traumatic injuries. Effective rehabilitation can bring the impaired hand back to a functional state because of the plasticity of the central nervous system to relearn and remodel the lost synapses in the brain. Current rehabilitation therapies focus on strengthening motor skills, such as grasping, employ multiple objects of varying stiffness so that affected persons can experience a wide range of strength training. These devices have limited range of stiffness due to the rigid mechanisms employed in their variable stiffness actuators. This paper presents a novel soft robotic haptic device for neuromuscular rehabilitation of the hand, which is designed to offer adjustable stiffness and can be utilized in both clinical and home settings. The device eliminates the need for multiple objects by employing a pneumatic soft structure made with highly compliant materials that act as the actuator of the haptic interface. It is made with interchangeable sleeves that can be customized to include materials of varying stiffness to increase the upper limit of the stiffness range. The device is fabricated using existing 3D printing technologies, and polymer molding and casting techniques, thus keeping the cost low and throughput high. The haptic interface is linked to either an open-loop system that allows for an increased pressure during usage or closed-loop system that provides pressure regulation in accordance to the stiffness the user specifies. Preliminary evaluation is performed to characterize the effective controllable region of variance in stiffness. It was found that the region of controllable stiffness was between points 3 and 7, where the stiffness appeared to plateau with each increase in pressure. The two control systems are tested to derive relationships between internal pressure, grasping force exertion on the surface, and displacement using multiple probing points on the haptic device. Additional quantitative evaluation is performed with study participants and juxtaposed to a qualitative analysis to ensure adequate perception in compliance variance. The qualitative evaluation showed that greater than 60% of the trials resulted in the correct perception of stiffness in the haptic device.
The human hand is a complex sensorimotor apparatus that consists of many joints, muscles, and sensory receptors. Such complexity allows for skillful and dexterous manual actions in activities of daily living (ADL). When the sensorimotor function of hand is impaired by neurological diseases or traumatic injuries, the quality of life of the affected individual could be severely impacted. For example, stroke is a condition that is broadly defined as a loss in brain function due to necrotic cell death stemming from a sudden loss in blood supply within the cranium (Hankey, 2017). This event can lead to a multitude of repercussions on sensorimotor function, one of which being impaired hand control such as weakened grip strength (Foulkes et al., 1988; Duncan et al., 1994; Nakayama et al., 1994; Jørgensen et al., 1995; Wilkinson et al., 1997; Winstein et al., 2004; Legg et al., 2007). Other potential causes of impaired hand function include cerebral palsy, multiple sclerosis, and amputation. Therefore, effective rehabilitation to help patients regain functional hand control is critically important in clinical practice. It has been shown that recovery of sensory motor function relies on the plasticity of the central nervous system to relearn and remodel the brain (Warraich and Kleim, 2010). Specifically, there are several factors that are known to contribute to neuroplasticity (Kleim and Jones, 2008): specificity, number of repetition, training intensity, time, and salience. However, existing physical therapy of hand is limited by the resource and accessibility, leading to inadequate dosage and lack of patients’ motivation. Robot-assisted hand rehabilitation has recently attracted a lot of attention because robotic devices have the advantage to provide (1) enriched environment to strengthen motivation, (2) increase number of repetition through automated control, and (3) progressive intensity levels that adapts to patient’s need (for review, see Balasubramanian et al., 2010).
Specifically, haptic interfaces and variable stiffness mechanisms are usually incorporated into robotic rehabilitation devices to provide varying difficulties by adjusting force output or stiffness. For example, the LINarm++ is a rehabilitative device that appropriates variable stiffness actuators with multimodal sensors to provide changing resistance in a physical environment in which users performs arm movement (Malosio et al., 2016; Spagnuolo et al., 2017). This device also encompasses a functional electrical stimulation system which has been shown to promote motor recovery in upper limb rehabilitation (Popović and Popović, 2006). The Haptic Knob is a device that trains stroke patients’ grasping movements, and wrist pronation and supination motions by rotating a dial that is able to produce forces and torques up to 50 N and 1.5 Nm, respectively, depending on the patient’s level of impairment (Lambercy et al., 2009). The GripAble is a handheld rehabilitative device that allows the patient to squeeze, lift, and rotate to play a video game with increasing difficulty and gives feedback through vibration in response to the patient’s performance (Mace et al., 2015, 2017). The MIT-MANUS, a planar rehabilitation robot, also has a hand-module that converts rotary motions to linear motions, and in turn allows for controllable impedance in the device (Masia et al., 2006). In addition, pneumatic particle jamming systems have been designed to provide users with haptic feedback by changing the stiffness and geometry of the surface the user presses on with their fingertips (Stanley et al., 2013; Genecov et al., 2014). These devices and systems, however, are either costly and bulky due to complex mechanical design or have limited range of stiffness due to passive mechanical components.
To overcome these limitations, this paper proposes the design of a novel pneumatically actuated soft robotics-based variable stiffness haptic interface to support rehabilitation of sensorimotor function of hands (Figure 1). Soft robotics is a rapidly growing field that utilizes highly compliant materials that are fluidic actuated to effectively adapt to shapes and constraints that traditionally rigid machines are unable to Majidi (2014) and Polygerinos et al. (2017). Several soft-robotics devices have been developed to provide assistance to stroke patients, but none of these has been designed as resistive training devices. An example of an existing device includes the use of soft actuators that bend, twist, and extend through finger-like motions in a rehabilitative exoglove to be worn by stroke patients (Polygerinos et al., 2015a,b; Yap et al., 2017). A variable stiffness device that employs soft-robotics allows a greater range of stiffness to be implemented since there is minimal or no impedance to the initial stiffness of the device. In addition, soft robotics methods allow devices to be manufactured with lowered cost and have much less complexity, thus suitable to be used not only inpatient but also outpatient hand rehabilitative services (Taylor et al., 1996; Godwin et al., 2011).
Figure 1. The prototyped soft haptic variable stiffness interface with a hand grasping it.
In Section “Materials and Methods” of this paper, the materials and methods employed in designing and fabricating the soft robotic haptic interface are described, including the design criteria of the prototype. This section also describes the methodology for a stiffness perception test on healthy participant with the proposed device. In addition, the overall closed-loop control system of the device to provide pressure regulation is presented in this section. Section “Results” describes the preliminary results obtained from characterization of the device’s varying stiffness in response to changing pressure inputs, and the subjective evaluation of perceived stiffness obtained from test participants. Finally, Section “Discussion” includes an overall discussion of open question and future research directions.