Technological advances in interventions to enhance poststroke gait

Eccentric training effects for patients with post-stroke hemiparesis on strength and speed gait: A randomized controlled trial

BACKGROUND

In hemiparetic patients, the skeletal muscle is mainly affected with a combination of abnormalities (denervation, remodeling, spasticity, and eventually muscular atrophy).

OBJECTIVE

This study examined the role of eccentric exercise in strengthening muscles of the lower extremity and ultimately improving autonomy in patients with post-stroke hemiparesis during gait.

METHODS

Thirty-seven patients hemiparetic adults were recruited, randomized into a control group (n = 19) and an intervention group receiving eccentric muscle strengthening (n = 18). The protocol consisted of three sets of five repetitions of eccentric contraction of the paretic limb after determining the maximum repetition (1 MRI). Evaluation of the 1RM, 10 meters and 6WMT was performed before and after the exercise for each group. Manova test was used to compare the differences between the control and intervention groups.

RESULTS

The paretic limb showed significant increase in one-repetition maximum (1RM) between before and after rehabilitation (p≤0.00003). The two groups of Patients increased their walking speed (p≤0.0005), but we observed a significant difference between groups only for the 6MWT and not on the 10 meters Test.

CONCLUSIONS

Eccentric training can be useful in strengthening the muscles of the lower limbs, and promoting gait performance. Eccentric training could complement other methods of managing patients with post-stroke hemiparesis.

Evaluation of Physical Interaction during Walker-Assisted Gait with the AGoRA Walker: Strategies Based on Virtual Mechanical Stiffness

Smart walkers are commonly used as potential gait assistance devices, to provide physical and cognitive assistance within rehabilitation and clinical scenarios. To understand such rehabilitation processes, several biomechanical studies have been conducted to assess human gait with passive and active walkers. Several sessions were conducted with 11 healthy volunteers to assess three interaction strategies based on passive, low and high mechanical stiffness values on the AGoRA Smart Walker. The trials were carried out in a motion analysis laboratory. Kinematic data were also collected from the smart walker sensory interface. The interaction force between users and the device was recorded. The force required under passive and low stiffness modes was 56.66% and 67.48% smaller than the high stiffness mode, respectively. An increase of 17.03% for the hip range of motion, as well as the highest trunk’s inclination, were obtained under the resistive mode, suggesting a compensating motion to exert a higher impulse force on the device. Kinematic and physical interaction data suggested that the high stiffness mode significantly affected the users’ gait pattern. Results suggested that users compensated their kinematics, tilting their trunk and lower limbs to exert higher impulse forces on the device.

The Actuation System of the Ankle Exoskeleton T-FLEX: First Use Experimental Validation in People with Stroke

Robotic devices can provide physical assistance to people who have suffered neurological impairments such as stroke. Neurological disorders related to this condition induce abnormal gait patterns, which impede the independence to execute different Activities of Daily Living (ADLs). From the fundamental role of the ankle in walking, Powered Ankle-Foot Orthoses (PAFOs) have been developed to enhance the users’ gait patterns, and hence their quality of life. Ten patients who suffered a stroke used the actuation system of the T-FLEX exoskeleton triggered by an inertial sensor on the foot tip. The VICONmotion capture system recorded the users’ kinematics for unassisted and assisted gait modalities. Biomechanical analysis and usability assessment measured the performance of the system actuation for the participants in overground walking. The biomechanical assessment exhibited changes in the lower joints’ range of motion for 70% of the subjects. Moreover, the ankle kinematics showed a correlation with the variation of other movements analyzed. This variation had positive effects on 70% of the participants in at least one joint. The Gait Deviation Index (GDI) presented significant changes for 30% of the paretic limbs and 40% of the non-paretic, where the tendency was to decrease. The spatiotemporal parameters did not show significant variations between modalities, although users’ cadence had a decrease of 70% of the volunteers. Lastly, the satisfaction with the device was positive, the comfort being the most user-selected aspect. This article presents the assessment of the T-FLEX actuation system in people who suffered a stroke. Biomechanical results show improvement in the ankle kinematics and variations in the other joints. In general terms, GDI does not exhibit significant increases, and the Movement Analysis Profile (MAP) registers alterations for the assisted gait with the device. Future works should focus on assessing the full T-FLEX orthosis in a larger sample of patients, including a stage of training.

Towards self-learning based hypotheses generation in biomedical text domain

Motivation

The overwhelming amount of research articles in the domain of bio-medicine might cause important connections to remain unnoticed. Literature Based Discovery is a sub-field within biomedical text mining that peruses these articles to formulate high confident hypotheses on possible connections between medical concepts. Although many alternate methodologies have been proposed over the last decade, they still suffer from scalability issues. The primary reason, apart from the dense inter-connections between biological concepts, is the absence of information on the factors that lead to the edge-formation. In this work, we formulate this problem as a collaborative filtering task and leverage a relatively new concept of word-vectors to learn and mimic the implicit edge-formation process. Along with single-class classifier, we prune the search-space of redundant and irrelevant hypotheses to increase the efficiency of the system and at the same time maintaining and in some cases even boosting the overall accuracy.

Results

We show that our proposed framework is able to prune up to 90% of the hypotheses while still retaining high recall in top-K results. This level of efficiency enables the discovery algorithm to look for higher-order hypotheses, something that was infeasible until now. Furthermore, the generic formulation allows our approach to be agile to perform both open and closed discovery. We also experimentally validate that the core data-structures upon which the system bases its decision has a high concordance with the opinion of the experts.This coupled with the ability to understand the edge formation process provides us with interpretable results without any manual intervention.

Availability and implementation

The relevant JAVA codes are available at: https://github.com/vishrawas/Medline-Code_v2.

Supplementary information

Supplementary data are available at Bioinformatics online.

A soft robotic exosuit improves walking in patients after stroke

Stroke-induced hemiparetic gait is characteristically slow and metabolically expensive. Passive assistive devices such as ankle-foot orthoses are often prescribed to increase function and independence after stroke; however, walking remains highly impaired despite-and perhaps because of-their use. We sought to determine whether a soft wearable robot (exosuit) designed to supplement the paretic limb's residual ability to generate both forward propulsion and ground clearance could facilitate more normal walking after stroke. Exosuits transmit mechanical power generated by actuators to a wearer through the interaction of garment-like, functional textile anchors and cable-based transmissions. We evaluated the immediate effects of an exosuit actively assisting the paretic limb of individuals in the chronic phase of stroke recovery during treadmill and overground walking. Using controlled, treadmill-based biomechanical investigation, we demonstrate that exosuits can function in synchrony with a wearer's paretic limb to facilitate an immediate 5.33 ± 0.91° increase in the paretic ankle's swing phase dorsiflexion and 11 ± 3% increase in the paretic limb's generation of forward propulsion (P < 0.05). These improvements in paretic limb function contributed to a 20 ± 4% reduction in forward propulsion interlimb asymmetry and a 10 ± 3% reduction in the energy cost of walking, which is equivalent to a 32 ± 9% reduction in the metabolic burden associated with poststroke walking. Relatively low assistance (~12% of biological torques) delivered with a lightweight and nonrestrictive exosuit was sufficient to facilitate more normal walking in ambulatory individuals after stroke. Future work will focus on understanding how exosuit-induced improvements in walking performance may be leveraged to improve mobility after stroke.

Reducing The Cost of Transport and Increasing Walking Distance After Stroke: A Randomized Controlled Trial on Fast Locomotor Training Combined With Functional Electrical Stimulation

Background Neurorehabilitation efforts have been limited in their ability to restore walking function after stroke. Recent work has demonstrated proof-of-concept for a functional electrical stimulation (FES)-based combination therapy designed to improve poststroke walking by targeting deficits in paretic propulsion. Objectives To determine the effects on the energy cost of walking (EC) and long-distance walking ability of locomotor training that combines fast walking with FES to the paretic ankle musculature (FastFES). Methods Fifty participants >6 months poststroke were randomized to 12 weeks of gait training at self-selected speeds (SS), fast speeds (Fast), or FastFES. Participants' 6-minute walk test (6MWT) distance and EC at comfortable (EC-CWS) and fast (EC-Fast) walking speeds were measured pretraining, posttraining, and at a 3-month follow-up. A reduction in EC-CWS, independent of changes in speed, was the primary outcome. Group differences in the number of 6MWT responders and moderation by baseline speed were also evaluated. Results When compared with SS and Fast, FastFES produced larger reductions in EC (Ps ≤.03). FastFES produced reductions of 24% and 19% in EC-CWS and EC-Fast (Ps <.001), respectively, whereas neither Fast nor SS influenced EC. Between-group 6MWT differences were not observed; however, 73% of FastFES and 68% of Fast participants were responders, in contrast to 35% of SS participants. Conclusions Combining fast locomotor training with FES is an effective approach to reducing the high EC of persons poststroke. Surprisingly, differences in 6MWT gains were not observed between groups. Closer inspection of the 6MWT and EC relationship and elucidation of how reduced EC may influence walking-related disability is warranted.