Posts Tagged gait rehabilitation

[ARTICLE] Adaptive Treadmill-Assisted Virtual Reality-Based Gait Rehabilitation for Post-Stroke Physical Reconditioning—a Feasibility Study in Low-Resource Settings – Full Text

Abstract

Objectives: Individuals with chronic stroke suffer from heterogeneous functional limitations, including cardiovascular dysfunction and gait disorders (associated with increased energy expenditure) besides psychological factors, e.g., motivation. To recondition their cardiovascular endurance and gait, rehabilitation exercises with gradually increasing exercise intensity suiting their individualized capabilities need to be offered. In principal accordance, here we (i) implemented an adaptive Virtual Reality (VR)-based treadmill-assisted platform sensitive to energy expenditure, (ii) investigated its safety and feasibility of use and (iii) examined the implications of gait exercise with this platform on cardiac and gait performance along with energy expenditure, clinical measures (to estimate physical reconditioning of subjects with stroke) and their views on community ambulation capabilities. Methods: Ten able-bodied subjects volunteered in a study to ensure its safety and feasibility of use. Nine subjects with chronic stroke underwent physical reconditioning over multiple exposures using our platform. We investigated the patients’ cardiac and gait performance prior and post exposure to our platform along with studying the clinical relevance of gait parameters in estimating their physical reconditioning. We collected the patients’ feedback. Results: We found statistical improvement in the gait parameters and reduction in energy expenditure during overground walk following ~1 month of gait exercise with our platform. They reported that the VR-based tasks were motivating. Conclusion: Results show that this platform can pave the way towards implementing home-based individualized exercise platform that can monitor one’s cardiac and gait performance capabilities while offering an adaptive and progressive gait exercise environment within safety thresholds suiting one’s exercise capabilities.
Physiological Cost Index sensitive Adaptive Response Technology (PCI-ART) for post-stroke physical reconditioning. Note: PCI- Physiological Cost Index; SST-Single Support Time; AL- Affected limb; UAL- Unaffected limb.

Physiological Cost Index sensitive Adaptive Response Technology (PCI-ART) for post-stroke physical reconditioning. Note: PCI- Physiological Cost Index; SST-Single Support Time; AL- Affected limb; UAL- Unaffected limb. 

SECTION I.

Introduction

Neurological disorders, such as stroke is a leading cause of disability with a prevalence rate of 424 in 100,000 individuals in India [1]. Often, these patients suffer from functional disabilities, heterogeneous physical deconditioning along with deteriorated cardiac functioning [2], [3] and a sedentary lifestyle immediately following stroke [4]. A deconditioned patient requires reconditioning of his/her cardiac capacity and ambulation capabilities that can be achieved through individualized rehabilitation [5]. This needs to be done under the supervision of a clinician who can monitor one’s functional capability, cardiac capacity and gait performance thereby recommending an appropriate dosage of the gait rehabilitation exercise intensity to the patient along with feedback. Such gait rehabilitation is crucial since about 80% of these patients have been reported to suffer from gait-related disorders [6] along with more energy expenditure than able-bodied individuals [7] often accompanied with reduced cardiac capacity [2], [4]. However, given the low doctor-to-patient ratio [8], lack of rehabilitation facilities and patients being released early from rehabilitation clinics followed by home-based exercise [9], particularly in developing countries like India, availing individualized rehabilitation services becomes difficult. Again, undergoing home-based exercises under clinician’s one-on-one supervision becomes difficult given the restricted healthcare resources, thereby limiting the rehabilitation outcomes [10]. Again, given the restricted healthcare resources, getting a clinician visiting the homes for delivering therapy sessions to patients is often costly causing the patients to miss the expert inputs on the exercise intensity suiting his/her exercise capability along with motivational feedback from the clinician [11]. This necessitates the use of a complementary technology-assisted rehabilitation platform that can be availed by the patient at his/her home [12] following a short stay at the rehabilitation clinic [13]. Again, it is preferred that this platform be capable of offering individualized gait exercise while varying the dosage of exercise intensity (based on the patient’s exercise capability) along with motivational feedback [14]. Additionally, exercise administered by this platform can be complemented with intermediate clinician-mediated assessments of rehabilitation outcomes, thereby reducing continuous demands on the restricted clinical resources. Thus, it is important to investigate the use of such technology-assisted gait exercise platforms that are capable of offering exercise based on one’s individualized capability along with motivational feedback.

Researchers have explored the use of technology-assisted solutions to offer rehabilitative gait exercises to these patients, along with presenting motivational feedback [15]–[16][17][18][19][20][21][22][23][24]. Specifically, investigators have used Virtual Reality (VR) coupled with a treadmill (having a limited footprint and making it suitable for home-based settings) while delivering individualized feedback [15] to the patient during exercise. Again, VR can help to project scenarios that can make the exercise engaging and interactive for a user [16]–[17][18][19]. In fact, Finley et al. have shown that the visual feedback offered by VR provides an optical flow that can induce changes in the gait performance (quantified in terms of gait parameters, e.g., Step Length, Step Symmetry, etc.) of such patients during treadmill-assisted walk [20]. Further, Jaffe et al. have reported positive implications of VR-based treadmill-assisted walking exercise on the gait performance of individuals with stroke [23], leading to improvement in their community ambulation [24]. These studies have shown the efficacy of the VR-based treadmill-assisted gait exercise platform to contribute towards gait rehabilitation of individuals suffering from stroke. Though promising, none of these platforms are sensitive to one’s individualized exercise capability and thus, in turn, could not decide an optimum dosage of exercise intensity suiting one’s capability, e.g., cardiac capacity and ambulation capability. This is particularly critical for individuals with stroke since they possess diminished exercise ability along with deteriorated cardiac functioning [2], [4].

From literature review, we find that after stroke, treadmill-assisted cardiac exercise programs can lead to one’s improved fitness and exercise capability [25]. For example, researchers have presented studies on Moderate-Intensity Continuous Exercise and High-Intensity Interval Training in which exercise protocols are individualized by a clinician based on one’s cardiac capacity while contributing to effective gait rehabilitation [26]–[27][28][29]. Though promising, these have not offered a progressive and adaptive exercise environment in which the dosage of exercise intensity is varied based on one’s cardiac capacity in real-time. Thus, the choice of optimum dosage of exercise intensity that can be individualized in real-time for a patient, still remains as inadequately explored [4]. For deciding the optimal dosage of rehabilitative exercise intensity, clinicians often refer to the guidelines recommended by the American College of Sports Medicine (ACSM) [30]. These guidelines suggest thresholds to decide the intensity of the exercise based on one’s metabolic energy consumption in terms of oxygen intake, heart rate, etc. Deciding the dosage of exercise intensity is crucial, particularly for individuals with stroke since their energy requirements have been reported to be 55-100% higher than that of their able-bodied counterparts [7]. Specifically, higher energy requirement often limits the capabilities of these patients and challenges their rehabilitation outcomes. This can be addressed if the technology-assisted gait exercise platform can offer individualized exercise (maintaining the safe exercise thresholds) based on the energy expenditure of the patients acquired in real-time during the exercise.

The energy expenditure can be defined as the cost of physical activity [4] and it is often expressed in terms of oxygen consumption or heart rate [31]. Thus, investigators have monitored the oxygen consumption and heart rate to estimate the energy expenditure of individuals with stroke during their walk [31], [32]. However, monitoring oxygen consumption during exercise requires a cumbersome setup [31], making it unsuitable for home-based rehabilitation. On the other hand, one’s heart rate (HR) can be monitored using portable solutions [33] that can be integrated with a treadmill in home-based settings. Researchers have explored treadmill-assisted gait exercise platforms that are sensitive to the user’s heart rate. For example, researchers have offered treadmill training to subjects with stroke in which some of them varied treadmill speed to achieve 45%-50% [34], while others varied speed to achieve 85% to 95% [35], [36] of one’s age-related maximum heart rate. Again, Pohl et al. have offered treadmill-assisted exercise to subjects with stroke while ensuring that the user’s heart rate settled to the respective resting-state heart rate [37]. Again of late, there had been advanced treadmills, available off-the-shelf, that can monitor one’s heart rate and vary the treadmill speed to maintain the user’s heart rate at a predefined level [38], [39]. Though one’s heart rate is an important indicator that needs to be considered during treadmill-assisted exercise, one’s walking speed while using the treadmill also offers important information on one’s exercise capability. This is because gait rehabilitation aims to improve one’s community ambulation that is related to one’s walking speed [40]. Thus, it would be interesting to explore the composite effect of one’s walking speed along with working and resting-state heart rates during treadmill-assisted gait exercise to study one’s energy expenditure, quantified in terms of a proxy index, namely Physiological Cost Index (PCI) [31].

Given that there are no existing studies that have used a treadmill-assisted gait exercise platform deciding the dosage of exercise intensity based on one’s PCI estimated in real-time during exercise, it might be interesting to explore the use of such an individualized gait exercise platform for individuals with stroke. Thus, we wanted to extend a treadmill-assisted gait exercise platform by making it adaptive to one’s individualized PCI. Additionally, we wanted to augment this platform with VR-based user interface to offer visual feedback to the user undergoing gait exercise. We hypothesized that such a gait exercise platform can recondition a patient’s exercise capability in terms of cardiac and gait performance to achieve improved community ambulation. The objectives of our research were three-fold, namely to (i) implement a novel PCI-sensitive Adaptive Response Technology (PCI-ART) offering VR-based treadmill-assisted gait exercise, (ii) investigate the safety and feasibility of use of this platform among able-bodied individuals before applying it to subjects with stroke and (iii) examine implications of undergoing gait exercise with this platform on the patients’ (a) cardiac and gait performance along with energy expenditure, (b) clinical measures estimating the physical reconditioning and (c) views on their community ambulation capabilities.

The rest of the paper is organized as follows: Section II presents our system design. Section III explains the experiments and procedures of this study. Section IV discusses the results. In Section V, we summarize our findings, limitations, and scope of future research.[…]

Continue —-> Adaptive Treadmill-Assisted Virtual Reality-Based Gait Rehabilitation for Post-Stroke Physical Reconditioning—a Feasibility Study in Low-Resource Settings – IEEE Journals & Magazine

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[Abstract + References] Gait rehabilitation after stroke: review of the evidence of predictors, clinical outcomes and timing for interventions

Abstract

The recovery of walking capacity is one of the main aims in stroke rehabilitation. Being able to predict if and when a patient is going to walk after stroke is of major interest in terms of management of the patients and their family’s expectations and in terms of discharge destination and timing previsions. This article reviews the recent literature regarding the predictive factors for gait recovery and the best recommendations in terms of gait rehabilitation in stroke patients. Trunk control and lower limb motor control (e.g. hip extensor muscle force) seem to be the best predictors of gait recovery as shown by the TWIST algorithm, which is a simple tool that can be applied in clinical practice at 1 week post-stroke. In terms of walking performance, the 6-min walking test is the best predictor of community ambulation. Various techniques are available for gait rehabilitation, including treadmill training with or without body weight support, robotic-assisted therapy, virtual reality, circuit class training and self-rehabilitation programmes. These techniques should be applied at specific timing during post-stroke rehabilitation, according to patient’s functional status.

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[Abstract] Enriching footsteps sounds in gait rehabilitation in chronic stroke patients: a pilot study

Abstract

In the context of neurorehabilitation, sound is being increasingly applied for facilitating sensorimotor learning. In this study, we aimed to test the potential value of auditory stimulation for improving gait in chronic stroke patients by inducing alterations of the frequency spectra of walking sounds via a sound system that selectively amplifies and equalizes the signal in order to produce distorted auditory feedback. Twenty‐two patients with lower extremity paresis were exposed to real‐time alterations of their footstep sounds while walking. Changes in body perception, emotion, and gait were quantified. Our results suggest that by altering footsteps sounds, several gait parameters can be modified in terms of left–right foot asymmetry. We observed that augmenting low‐frequency bands or amplifying the natural walking sounds led to a reduction in the asymmetry index of stance and stride times, whereas it inverted the asymmetry pattern in heel–ground exerted force. By contrast, augmenting high‐frequency bands led to opposite results. These gait changes might be related to updating of internal forward models, signaling the need for adjustment of the motor system to reduce the perceived discrepancies between predicted–actual sensory feedbacks. Our findings may have the potential to enhance gait awareness in stroke patients and other clinical conditions, supporting gait rehabilitation.

 

via Enriching footsteps sounds in gait rehabilitation in chronic stroke patients: a pilot study – Gomez‐Andres – – Annals of the New York Academy of Sciences – Wiley Online Library

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[ARTICLE] State-of-the-art research in robotic hip exoskeletons: A general review – Full Text

Abstract

Ageing population is now a global challenge, where physical deterioration is the common feature in elderly people. In addition, the diseases, such as spinal cord injury, stroke, and injury, could cause a partial or total loss of the ability of human locomotion. Thus, assistance is necessary for them to perform safe activities of daily living. Robotic hip exoskeletons are able to support ambulatory functions in elderly people and provide rehabilitation for the patients with gait impairments. They can also augment human performance during normal walking, loaded walking, and manual handling of heavy-duty tasks by providing assistive force/torque. In this article, a systematic review of robotic hip exoskeletons is presented, where biomechanics of the human hip joint, pathological gait pattern, and common approaches to the design of robotic hip exoskeletons are described. Finally, limitations of the available robotic hip exoskeletons and their possible future directions are discussed, which could serve a useful reference for the engineers and researchers to develop robotic hip exoskeletons with practical and plausible applications in geriatric orthopaedics.

Introduction

Most countries are reported with rising life expectancy and therefore a rapid increase in ageing population worldwide. Elderly people normally have physical deterioration and frailty, which imposes a heavy burden on the social health care system. The decreased physical capabilities owing to deterioration of neuromusculoskeletal system makes elderly people walking with a changed gait pattern and more cautious [1]. They generally have increased step variability and metabolic cost of walking, lower walking speed, shorter step-length, and reduced range of motion of the ankle, knee, and hip joints [2,3]. In addition, the elderly people have difficulties in maintaining trunk stability and have a risk of falls [4]. The lower limbs dysfunction and gait impairments are also common in elderly people, which could cause unnatural gait patterns [5,6]. Nearly three-quarters of all strokes occur in people over the age of 65 years. All those could reduce the mobility of elderly people and lead them to fewer independent lives and poor quality of life.

In addition, the patients with neurological disorders caused by diseases or injuries such as a stroke and spinal cord injury generally have muscle weakness, which could lead to insufficient force/torque at the hip joints during human locomotion [7]. These individuals often have decreased capacities of self-balancing and increased falling risk [8]. Therefore, approaches that can help elderly people and these patients to maintain a good walking pattern are desirable [9]. The past decade has witnessed a remarkable progress in research and development (R&D) of wearable medical devices for the patients with gait impairments [10]. The use of wearable medical devices such as robotic exoskeletons [11] and active orthoses [12] have become one of the most promising approaches to assist the individuals with gait disorders. It is predicted by a researcher that robotic exoskeletons would be commonly used in the community by 2024 [13].

Robotic hip exoskeletons integrate the robot power and human intelligence, and they can provide controllable assistive force/torque at the wearers’ hip joints with an anthropomorphic configuration. One application of robotic hip exoskeletons is on gait rehabilitation. They are able to train the wearers’ muscles and assist their movements for therapeutic exercise. The robot-assisted rehabilitation can release therapists from the heavy burden of rehabilitation training and provide long training sessions for the patients with good consistency. Human regular walking is able to reduce the risk of strokes and coronary heart disease, and hence to improve the physical and mental health [14]. Thus, it is promising to make human walking more efficient. Human effort is related to metabolic expenditure, and the other application of robotic hip exoskeletons is to augment human performance such as increasing the human strength and endurance.

By comparing with the human ankle joint, the hip joint needs higher metabolic cost for the generation of similar mechanical joint power owing to the differences in muscle characteristics [15]. Therefore, in addition to the robotic ankle exoskeletons developed for metabolic benefit [16], the hip joint actuating is also a promising strategy because large positive torque is provided by the human hip during the activities of daily living [17]. Robotic hip exoskeletons also have the potential to integrate into the factories. In warehouses and manufacturing environments, the workers often have to handle heavy goods, which could load their lumbar spine and increase the risk of physical injury such as low back pain and other work-related musculoskeletal disorders [18,19]. The work-related injuries could have a serious impact on the quality of life of these individuals. Robotic hip exoskeletons are able to assist these workers during manual handling of heavy-duty tasks.

The aim of this article is to review the aspects of engineering design and control strategies of robotic hip exoskeletons for the two applications, i.e., gait rehabilitation and human performance augmentation, and to discuss some possible future directions to improve the currently available robotic hip exoskeletons. We hope this review would provide useful information for the engineers and researchers to design desirable robotic hip exoskeletons, especially for those new to this field and would like to make contributions to this important multidisciplinary biomedical engineering and orthopaedic rehabilitation filed.

In this article, the biomechanics of the human hip joint and pathological gait of individuals with hip dysfunction are first presented before reviewing the mechanical structure, actuators, sensors, and control strategies of the existing robotic hip exoskeletons. Finally, this article discusses the limitations of the available robotic hip exoskeletons and their possible R&D directions with respect to clinical applications.

Biomechanics of human hip and pathological gait

To increase adaptability and achieve minimal interference, bioinspired design of robotic hip exoskeletons is required. This section presents a brief description of biomechanics of the human hip joint and the pathological gait pattern of individuals with hip dysfunction, which provides a basis for the design and control of robotic hip exoskeletons.

Biomechanics of normal human hip joint

The human hip joint is a ball-and-socket joint and joins the pelvis to the femur. It is composed of the cup-shaped acetabulum and femoral head, which are connected and supported by several tissues and muscles [20,21]. In human locomotion analysis, the human hip behaves as a spherical joint with three degrees of freedom (DOFs), i.e., flexion/extension, abduction/adduction, and internal/external rotation. A human gait cycle is defined as a sequence of movements during walking and is basically composed of the alternating stance phase and swing phase [22], as shown in Fig. 1. According to the gait analysis of people with a normal gait pattern [23], the human hip joint will generate positive work to bear the body weight, propel the body forward, and stabilize the trunk during the period of 0–35% of a gait cycle. After this phase, the hip joint angle will cross the zero degree and the leg will become vertical.

Fig. 1

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Fig. 1. Normal gait cycle. The green lines represent the right leg, and the blue lines represent the left leg. The gait cycle is composed of the alternating stance phase and swing phase, and it starts when one foot contacts the ground and ends when the same foot contacts the ground again.

[…]

Continue —->  State-of-the-art research in robotic hip exoskeletons: A general review – ScienceDirect

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[Abstract + References] A Wireless BCI-FES Based on Motor Intent for Lower Limb Rehabilitation

Abstract

Recent investigations have proposed brain computer interfaces combined with functional electrical stimulation as a novel approach for upper limb motor recovery. These systems could detect motor intention movement as a power decrease of the sensorimotor rhythms in the electroencephalography signal, even in people with damaged brain cortex. However, these systems use a large number of electrodes and wired communication to be employed for gait rehabilitation. In this paper, the design and development of a wireless brain computer interface combined with functional electrical stimulation aimed at lower limb motor recovery is presented. The design requirements also account the dynamic of a rehabilitation therapy by allowing the therapist to adapt the system during the session. A preliminary evaluation of the system in a subject with right lower limb motor impairment due to multiple sclerosis was conducted and as a performance metric, the true positive rate was computed. The developed system evidenced a robust wireless communication and was able to detect lower limb motor intention. The mean of the performance metric was 75%. The results encouraged the possibility of testing the developed system in a gait rehabilitation clinical study.

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via A Wireless BCI-FES Based on Motor Intent for Lower Limb Rehabilitation | SpringerLink

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[Abstract] A Dual-Learning Paradigm Simultaneously Improves Multiple Features of Gait Post-Stroke

Background. Gait impairments after stroke arise from dysfunction of one or several features of the walking pattern. Traditional rehabilitation practice focuses on improving one component at a time, which may leave certain features unaddressed or prolong rehabilitation time. Recent work shows that neurologically intact adults can learn multiple movement components simultaneously.

Objective. To determine whether a dual-learning paradigm, incorporating 2 distinct motor tasks, can simultaneously improve 2 impaired components of the gait pattern in people posttroke.

Methods. Twelve individuals with stroke participated. Participants completed 2 sessions during which they received visual feedback reflecting paretic knee flexion during walking. During the learning phase of the experiment, an unseen offset was applied to this feedback, promoting increased paretic knee flexion. During the first session, this task was performed while walking on a split-belt treadmill intended to improve step length asymmetry. During the second session, it was performed during tied-belt walking.

Results. The dual-learning task simultaneously increased paretic knee flexion and decreased step length asymmetry in the majority of people post-stroke. Split-belt treadmill walking did not significantly interfere with joint-angle learning: participants had similar rates and magnitudes of joint-angle learning during both single and dual-learning conditions. Participants also had significant changes in the amount of paretic hip flexion in both single and dual-learning conditions.

Conclusions. People with stroke can perform a dual-learning paradigm and change 2 clinically relevant gait impairments in a single session. Long-term studies are needed to determine if this strategy can be used to efficiently and permanently alter multiple gait impairments.

via A Dual-Learning Paradigm Simultaneously Improves Multiple Features of Gait Post-Stroke – Kendra M. Cherry-Allen, Matthew A. Statton, Pablo A. Celnik, Amy J. Bastian, 2018

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[Abstract] A Dual-Learning Paradigm Simultaneously Improves Multiple Features of Gait Post-Stroke

Background. Gait impairments after stroke arise from dysfunction of one or several features of the walking pattern. Traditional rehabilitation practice focuses on improving one component at a time, which may leave certain features unaddressed or prolong rehabilitation time. Recent work shows that neurologically intact adults can learn multiple movement components simultaneously.

Objective. To determine whether a dual-learning paradigm, incorporating 2 distinct motor tasks, can simultaneously improve 2 impaired components of the gait pattern in people posttroke.

Methods. Twelve individuals with stroke participated. Participants completed 2 sessions during which they received visual feedback reflecting paretic knee flexion during walking. During the learning phase of the experiment, an unseen offset was applied to this feedback, promoting increased paretic knee flexion. During the first session, this task was performed while walking on a split-belt treadmill intended to improve step length asymmetry. During the second session, it was performed during tied-belt walking.

Results. The dual-learning task simultaneously increased paretic knee flexion and decreased step length asymmetry in the majority of people post-stroke. Split-belt treadmill walking did not significantly interfere with joint-angle learning: participants had similar rates and magnitudes of joint-angle learning during both single and dual-learning conditions. Participants also had significant changes in the amount of paretic hip flexion in both single and dual-learning conditions.

Conclusions. People with stroke can perform a dual-learning paradigm and change 2 clinically relevant gait impairments in a single session. Long-term studies are needed to determine if this strategy can be used to efficiently and permanently alter multiple gait impairments.

via A Dual-Learning Paradigm Simultaneously Improves Multiple Features of Gait Post-Stroke – Kendra M. Cherry-Allen, Matthew A. Statton, Pablo A. Celnik, Amy J. Bastian, 2018

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[Abstract] What does best evidence tell us about robotic gait rehabilitation in stroke patients: A systematic review and meta-analysis

Highlights

  • Recovery of walking function is one of the main goals of patients after stroke.
  • RAGT may be considered a valuable tool in improving gait abnormalities.
  • The earlier the gait training starts, the better the motor recovery.

Abstract

Background

Studies about electromechanical-assisted devices proved the validity and effectiveness of these tools in gait rehabilitation, especially if used in association with conventional physiotherapy in stroke patients.

Objective

The aim of this study was to compare the effects of different robotic devices in improving post-stroke gait abnormalities.

Methods

A computerized literature research of articles was conducted in the databases MEDLINE, PEDro, COCHRANE, besides a search for the same items in the Library System of the University of Parma (Italy). We selected 13 randomized controlled trials, and the results were divided into sub-acute stroke patients and chronic stroke patients. We selected studies including at least one of the following test: 10-Meter Walking Test, 6-Minute Walk Test, Timed-Up-and-Go, 5-Meter Walk Test, and Functional Ambulation Categories.

Results

Stroke patients who received physiotherapy treatment in combination with robotic devices, such as Lokomat or Gait Trainer, were more likely to reach better results, compared to patients who receive conventional gait training alone. Moreover, electromechanical-assisted gait training in association with Functional Electrical Stimulations produced more benefits than the only robotic treatment (−0.80 [−1.14; −0.46], p > .05).

Conclusions

The evaluation of the results confirm that the use of robotics can positively affect the outcome of a gait rehabilitation in patients with stroke. The effects of different devices seems to be similar on the most commonly outcome evaluated by this review.

 

via What does best evidence tell us about robotic gait rehabilitation in stroke patients: A systematic review and meta-analysis – Journal of Clinical Neuroscience

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[ARTICLE] A wearable somatosensory teaching device with adjustable operating force for gait rehabilitation training robot – Full Text

A novel wearable multi-joint teaching device for lower-limb gait rehabilitation is presented, intended to facilitate the adjustment of training modes in unique requirements of patients. A physiotherapist manipulates this active teaching device to plan the personalized gait trajectory and to construct the individual training mode. A haptic interaction joint module that stems from the friction braking principle is outlined here, with an adjustable operating force exerted by pneumatic film cylinders. With dual functions of somatosensory perception and teaching, it provides physiotherapist with a smooth and comfortable operation and a kind of force telepresence. The main contents are elaborated including the structural design and pneumatic proportional servo system of the teaching device and the joint module, operating force control principle, and gravity compensation method. Through performance tests of the prototype, the adjustable operating force has been demonstrated with the characteristics of good linearity and response speed. The results of master–slave control experiments preliminarily verified the effectiveness of the control approach. The research on the novel somatosensory teaching device with master–slave teaching mode has provided a concise, convenient, and efficient means for the clinical application of lower-limb rehabilitation robots, presumably as a new idea and technical supports for the future design.

Based on the neuroplasticity principle,1 a lower-limb rehabilitation training robot is a kind of automatic equipment that can recover or rebuild neural pathways2,3 for patients with motor dysfunction. The clinical presentation of a spinal cord injury (SCI) or a stroke comprises motor weakness or complete paresis, complete or partial loss of sensory function. The Swedish therapist Brunnstrom proposed the famous six-recovery-stage theory. Based on this theory, the training has different aims in the early stage of rehabilitation (flaccid paralysis stage), middle stage of rehabilitation (spasm stage), and later stage of rehabilitation (recovery stage). One major principle of neurological rehabilitation is that of motor learning. According to the principle of neural plasticity, repetitive and specific training tasks, which make the cerebral cortex learn and store the correct movement patterns, are important and effective. During rehabilitation, patients have to relearn motor tasks in order to overcome disability and limitations in the completion of daily activities. This is the theoretical basis of rehabilitation treatment. For a robot, the control strategy is provided diversely in different stages of rehabilitation to eliminate abnormal movement patterns. In the early rehabilitation, the passive training mode is usually adopted to help patients according to the predetermined trajectory and improve exercise capacity and reduce muscle atrophy. Then the active assist training mode begins for the patients of the middle recovery stage with moderate strength and relieving muscle spasm. In the later rehabilitation stage, the active resist training mode can be used to encourage patients to participate initiatively. The effect and importance of rehabilitation robots have been internationally recognized.48

Giving different state of an illness exhibited by hemiparetic individuals and the different training modes as mentioned above, the gait rehabilitation training robot primarily entails customized designing the parameters including movement trajectory, training speed and strength, and real-time perceiving, adjusting, and controlling. Lower-limb exoskeleton mechanism features of many degrees of freedom, together with the individual and condition differences of patients, so the problems are highlighted about how to accurately plan the correct gait trajectory and how to adjust training modes on time according to the progression. These issues become one of the research foci and technical difficulties of rehabilitation robot.

Most of the typical lower-limb rehabilitation robots in the world are autonomously controlled. The gait training mode planning for them is summarized in two methods, that is, preselected by a physiotherapist and dynamically adjusted by the algorithm. For some representative examples, the horizontal rehabilitation training robot Motion Maker9 can automatically guide patients along a preselected trajectory to perform passive flexion movement training on hip, knee, and ankle joints. The Lokomat1012 is a kind of body-weight-supported treadmill training (BWSTT) robot that adjusts the assisted power or reference trajectory by the impedance algorithm according to the patient interaction force. Patients can be made available to active and passive training mode. In the case of the lower extremity powered exoskeleton (LOPES) gait rehabilitation robot,13,14 limb reference trajectory is generated by instantaneous mapping with the healthy limb movement. The feasibility and functional improvements achieved in response to the emergence of such self-control rehabilitation robot; however, the existing technological bottleneck is obvious, that is, the limited adaptability of training mode.

The objective of this research is to develop a gait trajectory teaching device, with which the physiotherapist can directly and professionally teach to the robot and therefore present complex actions and adjust training modes as needed. Through master–slave teaching method, such system may provide the adaptability of the robot-mediated training and improve the treatment quality and efficiency, and decrease the difficulties in control algorithm study and the contradiction between the complex algorithms and real-time control.

Because of the more elaborate actions of the upper extremity and hand, teaching and playback technology is first applied to upper-limb rehabilitation training robot, for example, the flexible force feedback master–slave exoskeleton manipulator developed by America General Electric Company,15 the wearable master–slave training equipment of upper limbs driven by pneumatic artificial muscles in Okayama University in Japan,16 and the remotely operated upper-limb training robot of Southeast University in China.17 But there are fewer applications for lower-limb rehabilitation training. A single-joint ankle-foot orthoses designed by Canada, the Centre for Interdisciplinary Research in Rehabilitation and Social Integration is introduced in the literature.18The main cylinder driven by a motor controlled the slave cylinder to drive the orthoses. As described in a literature,19 a wearable master–slave lower-limb training robot driven by pneumatic artificial muscle achieves the teaching and training for the knee and ankle rehabilitation by sensors feeding back the trainer joint torque to the main control mechanism. In most of the studies mentioned above, the limitations existing in master–slave teaching for the lower-limb rehabilitation training robot can be summarized as follows: (1) the teaching device has the characteristics of complex structure, large quality and high inertia, so the physiotherapist is laborious and feels fatigue quickly, (2) the coordinate of the multi joints is demanded highly which may lead to the insufficient operating smoothness of the device, and (3) the feedback joint torque cannot be directly perceived by the physiotherapist but only as the control signal for the device.

In light of the above limitations, a novel multi-joint wearable teaching device is developed with adjustable operating force, which is exerted by light film cylinders. Based on the gravity compensation control method, a physiotherapist operates the teaching device to plan training trajectory smoothly and comfortably while also perceive the scene interaction force came from patients. In this manner, our research solved the existing problems, namely, the weight, the difficult manipulation of the teaching and the less force feedback to the physiotherapist. He operates the teaching device with the master–slave mode may provide various training modes fast and intuitively. The force telepresence from patients makes physiotherapist better controlling the training intensity and realizing the individual rehabilitation training consultation.

In this article, we elaborate five major contents that have been derived from this research as follows: master–slave teaching system solution, structural design of the multi-joint wearable master teaching device, operating force regulation principle and gravity compensation method, operating force regulation performance experiments, and master–slave control experiments.

Figure 1. System overall scheme.

Continue —> A wearable somatosensory teaching device with adjustable operating force for gait rehabilitation training robotAdvances in Mechanical Engineering – Bingjing Guo, Jianhai Han, Xiangpan Li, Peng Wu, Yanbin Zhang, Aimin You, 2017

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