Robotic-assessment of walking in individuals with gait disorders

EMG-Centered Multisensory Based Technologies for Pattern Recognition in Rehabilitation: State of the Art and Challenges

In the field of rehabilitation, the electromyography (EMG) signal plays an important role in interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the EMG signal suffers from difficulty in recognizing slight body movements, and the detection accuracy is strongly influenced by environmental factors. To address the above issues, multisensory integration-based EMG pattern recognition (PR) techniques have been developed in recent years, and fruitful results have been demonstrated in diverse rehabilitation scenarios, such as achieving high locomotion detection and prosthesis control accuracy. Owing to the importance and rapid development of the EMG centered multisensory fusion technologies in rehabilitation, this paper reviews both theories and applications in this emerging field. The principle of EMG signal generation and the current pattern recognition process are explained in detail, including signal preprocessing, feature extraction, classification algorithms, etc. Mechanisms of collaborations between two important multisensory fusion strategies (kinetic and kinematics) and EMG information are thoroughly explained; corresponding applications are studied, and the pros and cons are discussed. Finally, the main challenges in EMG centered multisensory pattern recognition are discussed, and a future research direction of this area is prospected.

Measurement of Walking Ground Reactions in Real-Life Environments: A Systematic Review of Techniques and Technologies

Monitoring natural human gait in real-life environments is essential in many applications, including quantification of disease progression, monitoring the effects of treatment, and monitoring alteration of performance biomarkers in professional sports. Nevertheless, developing reliable and practical techniques and technologies necessary for continuous real-life monitoring of gait is still an open challenge. A systematic review of English-language articles from scientific databases including Scopus, ScienceDirect, Pubmed, IEEE Xplore, EBSCO and MEDLINE were carried out to analyse the ‘accuracy’ and ‘practicality’ of the current techniques and technologies for quantitative measurement of the tri-axial walking ground reactions outside the laboratory environment, and to highlight their strengths and shortcomings. In total, 679 relevant abstracts were identified, 54 full-text papers were included in the paper and the quantitative results of 17 papers were used for meta-analysis and comparison. Three classes of methods were reviewed: (1) methods based on measured kinematic data; (2) methods based on measured plantar pressure; and (3) methods based on direct measurement of ground reactions. It was found that all three classes of methods have competitive accuracy levels with methods based on direct measurement of the ground reactions showing highest accuracy while being least practical for long-term real-life measurement. On the other hand, methods that estimate ground reactions using measured body kinematics show highest practicality of the three classes of methods reviewed. Among the most prominent technical and technological challenges are: (1) reducing the size and price of tri-axial load-cells; (2) improving the accuracy of orientation measurement using IMUs; (3) minimizing the number and optimizing the location of required IMUs for kinematic measurement; (4) increasing the durability of pressure insole sensors, and (5) enhancing the robustness and versatility of the ground reactions estimation methods to include pathological gaits and natural variability of gait in real-life physical environment.

Robot-supported assessment of balance in standing and walking

Clinically useful and efficient assessment of balance during standing and walking is especially challenging in patients with neurological disorders. However, rehabilitation robots could facilitate assessment procedures and improve their clinical value. We present a short overview of balance assessment in clinical practice and in posturography. Based on this overview, we evaluate the potential use of robotic tools for such assessment. The novelty and assumed main benefits of using robots for assessment are their ability to assess 'severely affected' patients by providing assistance-as-needed, as well as to provide consistent perturbations during standing and walking while measuring the patient's reactions. We provide a classification of robotic devices on three aspects relevant to their potential application for balance assessment: 1) how the device interacts with the body, 2) in what sense the device is mobile, and 3) on what surface the person stands or walks when using the device. As examples, nine types of robotic devices are described, classified and evaluated for their suitability for balance assessment. Two example cases of robotic assessments based on perturbations during walking are presented. We conclude that robotic devices are promising and can become useful and relevant tools for assessment of balance in patients with neurological disorders, both in research and in clinical use. Robotic assessment holds the promise to provide increasingly detailed assessment that allows to individually tailor rehabilitation training, which may eventually improve training effectiveness.

Robot-aided assessment of lower extremity functions: a review

The assessment of sensorimotor functions is extremely important to understand the health status of a patient and its change over time. Assessments are necessary to plan and adjust the therapy in order to maximize the chances of individual recovery. Nowadays, however, assessments are seldom used in clinical practice due to administrative constraints or to inadequate validity, reliability and responsiveness. In clinical trials, more sensitive and reliable measurement scales could unmask changes in physiological variables that would not be visible with existing clinical scores.In the last decades robotic devices have become available for neurorehabilitation training in clinical centers. Besides training, robotic devices can overcome some of the limitations in traditional clinical assessments by providing more objective, sensitive, reliable and time-efficient measurements. However, it is necessary to understand the clinical needs to be able to develop novel robot-aided assessment methods that can be integrated in clinical practice.This paper aims at providing researchers and developers in the field of robotic neurorehabilitation with a comprehensive review of assessment methods for the lower extremities. Among the ICF domains, we included those related to lower extremities sensorimotor functions and walking; for each chapter we present and discuss existing assessments used in routine clinical practice and contrast those to state-of-the-art instrumented and robot-aided technologies. Based on the shortcomings of current assessments, on the identified clinical needs and on the opportunities offered by robotic devices, we propose future directions for research in rehabilitation robotics. The review and recommendations provided in this paper aim to guide the design of the next generation of robot-aided functional assessments, their validation and their translation to clinical practice.

Advances in the Understanding and Treatment of Stroke Impairment Using Robotic Devices

The presence of robotic devices in rehabilitation centers is now becoming commonplace across the world, challenging heath care professionals to rethink treatment strategies for motor impairment in hemiparetic stroke patients. In this article, we will discuss some of the motivations for using these devices, review clinical outcomes following robotic-assisted training in both the upper and lower extremities, and detail how these devices can provide quantitative evaluations of function. We will also address the clinical issues that need to be considered when using robotic devices to treat stroke patients, and finally a vision of where this field is heading will be discussed.

Gait analysis using wearable sensors

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications.

Gait parameters and stride-to-stride variability during familiarization to walking on a split-belt treadmill

BACKGROUND

Subjects unfamiliar to walking on a split-belt treadmill may initially demonstrate an altered gait pattern or increased variability of gait parameters. While previous investigations have examined kinematic variables associated with familiarization time, the objective of this study was to determine the familiarization period required to obtain the most reproducible gait pattern through the assessment of kinetic, kinematic and spatio-temporal parameters during a single session of treadmill walking.

METHODS

Eleven healthy subjects participated in a single bout of treadmill walking which lasted 9 min. Kinematic and kinetic data were collected from the first 30s of each minute, beginning when the treadmill reached full speed. Means and standard deviations for knee flexion at heel strike, ground reaction forces, step width and step length were obtained to examine the changes in each variable over the 9 min. Mean r(2) values were evaluated for changes in variability from one stride to the subsequent stride for sagittal plane hip, knee and ankle joint angles and moments, as well as for vertical and horizontal ground reaction forces.

FINDINGS

Significant reductions in variability were found for vertical and horizontal ground reaction forces, knee flexion at heel strike and step length over 9 min. Only step width showed a change in the mean value across trials. There were no increases in r(2) values after the 5th min for any of the gait variables.

INTERPRETATION

The results suggest that in order to collect accurate data for gait analysis, subjects should be familiarized to the split-belt treadmill for at least 5 min prior to data collection.

Gait quality is improved by locomotor training in individuals with SCI regardless of training approach

BACKGROUND

While various body weight supported locomotor training (BWSLT) approaches are reported in the literature for individuals with spinal cord injury (SCI), none have evaluated outcomes in terms of gait quality. The purpose of this study was to compare changes in measures of gait quality associated with four different BWSLT approaches in individuals with chronic motor-incomplete SCI, and to identify how gait parameters differed from those of non-disabled (ND) individuals.

METHODS

Data were analyzed from 51 subjects with SCI who had been randomized into one of four BWSLT groups: treadmill with manual assistance (TM), treadmill with electrical stimulation (TS), overground with electrical stimulation (OG), treadmill with locomotor robot (LR). Subjects with SCI performed a 10-meter kinematic walk test before and after 12 weeks of training. Ten ND subjects performed the test under three conditions: walking at preferred speed, at speed comparable to subjects with SCI, and with a walker at comparable speed. Six kinematic gait quality parameters were calculated including: cadence, step length, stride length, symmetry index, intralimb coordination, and timing of knee extension.

RESULTS

In subjects with SCI, all training approaches were associated with improvements in gait quality. After training, subjects with SCI walked at higher cadence and had longer step and stride lengths. No significant differences were found among training groups, however there was an interaction effect indicating that step and stride length improved least in the LR group. Compared to when walking at preferred speed, gait quality of ND subjects was significantly different when walking at speeds comparable to those of the subjects with SCI (both with and without a walker). Post training, gait quality measures of subjects with SCI were more similar to those of ND subjects.

CONCLUSION

BWSLT leads to improvements in gait quality (values closer to ND subjects) regardless of training approach. We hypothesize that the smaller changes in the LR group were due to the passive settings used for the robotic device. Compared to walking at preferred speed, gait quality values of ND individuals walking at a slower speed and while using a walker were more similar to those of individuals with SCI.

Ankle load modulates hip kinetics and EMG during human locomotion

The purpose of this research was to examine the role of isolated ankle-foot load in regulating locomotor patterns in humans with and without spinal cord injury (SCI). We used a powered ankle-foot orthosis to unilaterally load the ankle and foot during robotically assisted airstepping. The load perturbation consisted of an applied dorsiflexion torque designed to stimulate physiological load sensors originating from the ankle plantar flexor muscles and pressure receptors on the sole of the foot. We hypothesized that 1) the response to load would be phase specific with enhanced ipsilateral extensor muscle activity and joint torque occurring when unilateral ankle-foot load was provided during the stance phase of walking and 2) that the phasing of subject produced hip moments would be modulated by varying the timing of the applied ankle-foot load within the gait cycle. As expected, both SCI and nondisabled subjects demonstrated a significant increase (P < 0.05) in peak hip extension moments (142 and 43% increase, respectively) when given ankle-foot load during the stance phase compared with no ankle-foot load. In SCI subjects, this enhanced hip extension response was accompanied by significant increases (P < 0.05) in stance phase gluteus maximus activity (27% increase). In addition, when ankle-foot load was applied either 200 ms earlier or later within the gait cycle, SCI subjects demonstrated significant phase shifts ( approximately 100 ms) in hip moment profile (P < 0.05; i.e., the onset of hip extension moments occurred earlier when ankle-foot load was applied earlier). This study provides new insights into how individuals with spinal cord injury use sensory feedback from ankle-foot load afferents to regulate hip joint moments and muscle activity during gait.

Validation of a speed-based classification system using quantitative measures of walking performance poststroke

BACKGROUND

For clinical trials in stroke rehabilitation, self-selected walking speed has been used to stratify persons to predict functional walking status and to define clinical meaningfulness of changes. However, this stratification was validated primarily using self-report questionnaires.

OBJECTIVE

This study aims to validate the speed-based classification system with quantitative measures of walking performance.

METHODS

A total of 59 individuals who had hemiparesis for more than 6 months after stroke participated in this study. Spatiotemporal and kinetic measures included the percentage of total propulsion generated by the paretic leg (Pp), the percentage of the stride length accounted for by the paretic leg step length (PSR), and the percentage of the gait cycle spent in paretic preswing (PPS). Additional measures included the synergy portion of the Fugl-Meyer Assessment and the average number of steps/day in the home and community measured with a step activity monitor. Participants were stratified by self-selected gait speed into 3 groups: household (<0.4 m/s), limited community (0.4-0.8 m/s), and community (>0.8 m/s) ambulators. Group differences were analyzed using a Kruskal-Wallis H test with rank sums test post hoc analyses.

RESULTS

Analyses demonstrated a main effect in all measures, but only steps/day and PPS demonstrated a significant difference between all 3 groups.

CONCLUSIONS

Classifying individuals poststroke by self-selected walking speed is associated with home and community-based walking behavior as quantified by daily step counts. In addition, PPS distinguishes all 3 groups. Pp differentiates the moderate from the fast groups and may represent a contribution to mechanisms of increasing walking speed. Speed classification presents a useful yet simple mechanism to stratify subjects poststroke and may be mechanically linked to changes in PPS.

Quantification of the dynamic properties of EMG patterns during gait

A technique for analyzing and comparing the dynamic properties of electromyographic (EMG) patterns collected during gait is presented. A gait metric is computed, consisting of both magnitude (amplitude) and phase (timing) components. For the magnitude component, the processed EMG pattern is compared to a normative EMG pattern obtained under similar walking conditions, where the metric is incremented if the muscle is firing during expected active regions or is silent during expected inactive regions. The magnitude metric is penalized when the EMG is silent during phases of expected activity or when the EMG is active in regions of expected inactivity. The phase component of the metric computes the percentage of the gait cycle when the muscle is firing appropriately, that is, active in expected active regions and silent in expected inactive regions. The magnitude and phase components of the metric are normalized and combined to yield the EMG pattern that demonstrates the closest characteristics compared to normative gait data collected under similar walking conditions. Using experimental data, the proposed gait metric was tested and accurately reflects the observed changes in the EMG patterns. Clinical uses for the gait metric are discussed in relation to gait therapies, such as determining optimal gait training conditions in individuals following stroke and spinal cord injury.