Posts Tagged Lokomat
[ARTICLE] Immediate affective responses of gait training in neurological rehabilitation: A randomized crossover trial – Full Text HTML
Objective: To examine the immediate effects of physical therapy and robotic-assisted gait training on affective responses of gait training in neurological rehabilitation.
Design: Randomized crossover trial with blinded observers.
Patients: Sixteen patients with neurological disorders (stroke, traumatic brain injury, spinal cord injury, multiple sclerosis).
Methods: All patients underwent 2 single treatment sessions: physical therapy and robotic-assisted gait training. Both before and after the treatment sessions, the self-report Mood Survey Scale was used to assess the effects of the treatment on distinct affective states. The subscales of the Mood Survey Scale were tested for pre–post changes and differences in effects between treatments, using non-parametric tests.
Results: Fourteen participants completed the study. Patients showed a significant increase in activation (r = 0.55), elation (r = 0.79), and calmness (r = 0.72), and a significant decrease in anger (r = 0.64) after robotic-assisted gait training compared with physical therapy.
Conclusion: Affective responses might be positively influenced by robotic-assisted gait training, which may help to overcome motivational problems during the rehabilitation process in neurological patients.
Patients with neurological impairment are known to have reduced quality of life and increased risk for depressive symptoms, which may hinder their ability to perform daily rehabilitation programmes, such as physical therapy (PT) or robotic-assisted gait training (RAGT) (1). During the continuum of rehabilitation it is necessary to consider factors such as choice and enjoyment in order to determine specifically how an individual would participate in rehabilitation programmes. The inclusion of participation scales is recommended when assessing the outcome of rehabilitation programmes (2). According to Self-Determination Theory (3), positive affective responses (e.g. activation, elation, or calmness) are connected with high intrinsic motivation and are an important regulation process in human behaviour. Therefore affective responses to the treatment sessions, as defined by Ekkekakis & Petruzello (4), might be important predictors of motivation, adoption, and maintenance of treatment regimes in the rehabilitation process.
Fatigue is a common and distressing complaint among people with neurological impairment (5). Patients often are afraid that engagement in exercise may increase fatigue (6). In patients with traumatic brain injury, “lack of energy” was rated as 1 of the top 5 problems for participation (7). Therefore it is important to emphasize that it is more likely that a higher level of energy will be achieved after exercise (8, 9). Although not yet a widely recognized determinant of exercise behaviour, affective valence is viewed in psychology and behavioural economics as one of the major factors in human decision-making (10). Findings from exercise psychology have demonstrated that the affective components of pleasure and activation might be crucial for bridging the intention–behaviour gap at the beginning of engagement in exercise (10). Regular participation in physical activity, in the long-term, may be mediated by an individual’s belief in the exercise–psychological wellbeing association. It may also lead to anti-depressive effects (11). Both PT and RAGT can be considered as forms of physical activity; therefore one might speculate that the effects mentioned above could be transferred to neurological patients. While increases in energy and mood in response to a single bout of moderate intensity exercise have been shown in healthy people and several risk-groups (6, 8, 9), no such study has been carried out involving neurological patients.
To our knowledge, only 2 studies concerning RAGT and psychological effects have been published. Koenig et al. (12) described a method to observe mental engagement during RAGT. Recently, Calabro et al. (13) reported positive long-term effects of RAGT on mood and coping strategies in a case study. To our knowledge, apart from these studies, affective responses have not been researched in PT or RAGT.
Thus, the aim of this study was to determine, for patients with neurological impairment: (i) whether a single session of PT and RAGT has immediate effects on affective responses (e.g. activation, elation, or calmness) and; (ii) whether possible affective responses differ between PT and RAGT.
[ARTICLE] Feasibility of using Lokomat combined with functional electrical stimulation for the rehabilitation of foot drop. – Full Text PDF
This study investigated the clinical feasibility of combining the electromechanical gait trainer Lokomat with functional electrical therapy (LokoFET), stimulating the common peroneal nerve during the swing phase of the gait cycle to correct foot drop as an integrated part of gait therapy.
Five patients with different acquired brain injuries trained with LokoFET 2-3 times a week for 3-4 weeks. Pre- and post-intervention evaluations were performed to quantify neurophysiological changes related to the patients’ foot drop impairment during the swing phase of the gait cycle. A semi-structured interview was used to investigate the therapists’ acceptance of LokoFET in clinical practice. The patients showed a significant increase in the level of activation of the tibialis anterior muscle and the maximal dorsiflexion during the swing phase, when comparing the pre- and post-intervention evaluations.
This showed an improvement of function related to the foot drop impairment. The interview revealed that the therapists perceived the combined system as a useful tool in the rehabilitation of gait. However, lack of muscle selectivity relating to the FES element of LokoFET was assessed to be critical for acceptance in clinical practice.
[Abstract] Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now? – Springer
Gait abnormalities following neurological disorders are often disabling, negatively affecting patients’ quality of life. Therefore, regaining of walking is considered one of the primary objectives of the rehabilitation process. To overcome problems related to conventional physical therapy, in the last years there has been an intense technological development of robotic devices, and robotic rehabilitation has proved to play a major role in improving one’s ability to walk.
The robotic rehabilitation systems can be classified into stationary and overground walking systems, and several studies have demonstrated their usefulness in patients after severe acquired brain injury, spinal cord injury and other neurological diseases, including Parkinson’s disease, multiple sclerosis and cerebral palsy.
In this review, we want to highlight which are the most widely used devices today for gait neurological rehabilitation, focusing on their functioning, effectiveness and challenges.
Novel and promising rehabilitation tools, including the use of virtual reality, are also discussed.
Robotic support has gained more and more interest in rehabilitation of human haptic behavior, e.g. after stroke. First types of rehabilitation robots were intended to replace repetitive movements performed by a physiotherapist by guiding the patient along a physiological reference trajectory. The robot has the advantage of an accurate and repetitive movement while being resistant to any type of fatigue.
New understanding of motor learning shows that active participation of the patient is an essential element of rehabilitation success. A rehabilitation robot should therefore be just as cooperative as the physiotherapist and enhance the patient’s activity. That means that they should only support the patient if needed. It has also been shown that perturbations such as increasing the error in the patient’s movement can progress the rehabilitation procedure more quickly than only “guiding” the patient to perform the correct movement. This form of therapy has some limitations however, if the patient is not able to apply the necessary forces for the movement. In this case the robot should give appropriate support, for example by providing partial weight support of the patient’s arm if the patient is not able to support their own weight. This simulated weightlessness is able to compensate for muscle disabilities and increase the range of motion during training sessions.
Furthermore, a rehabilitation robot can support the patient during specific tasks by recognizing movement deficiencies and disabilities. The robot supports as much as needed and as little as possible. Such a controller has been implemented in the armrobot ARMin (Figure 1, left). While the user is playing a ping-pong game, the robot is able to support the user as much as needed. In human gait rehabilitation, controller design is more restricted for the sake of security. In the Lokomat (Figure 1, right), path controlling is employed to ensure safe and still self-motivated walking. The path controlling method provides a tunnel for joint angles within which the patient can move. As soon as the patient exceeds the pre-set path trajectory limits, the robot pushes the patient back into the right direction. Figure 2 illustrates and explains the concept of path controlling. Another concept is employed in virtual model control (VMC) which aims at maximum patient activity and only supports selectively chosen characteristics such as length or height of the patient’s stride.
All of those control strategies require the robot to assist-as-needed. The assistance can be interpreted as a virtual helping hand. These virtually created worlds are able to display different forms, from free user-performed movements (no help) to resistance against “wrong” user movements (support), or even guiding the patient through their movement completely. In case of the patient being able to self-perform movements correctly, ideally, the robot should not be felt. This behavior is called transparency.
In addition to movement support, a rehabilitation robot is able to display a virtual world which the user can interact with. This is used for simulating activities if daily living (ADL) such as cooking. The representation of a virtual environment requires the possibility of displaying different virtual objects. Especially hard objects are important. Such requirements for the control of a hard environment differ a lot from those for the control of a free, transparent environment. Two different actuator and controller concepts are optimal to be employed to display a hard or soft environment respectively. The two strategies are called impedance and admittance control and will be the central part of this exercise.
Furthermore, we have to make sure that the human-robot-interaction is safe and secure, i.e. the robot should also be able to navigate a totally passive patient. Therefore, the actuators must fulfill some requirements on power and torque. This includes high transmission ratios, which additionally increase the reflected inertia of the drives. High robot inertia lowers the reachable transparency of the robot. Another important point is backdriveability, which makes the robot movable when the robot is not powered at all. This is an important fact e.g. for the case of an emergency stop.
To sum up, the design and choice of the hardware as well as the software implementation should balance each other. The robot has to bring enough forces and moments to support the patient. A strong (therefore heavy) robot arm is well able to display a hard virtual object such as a wall. On the other hand, the robot should be backdriveable and therefore be as lightweight as possible to easily display transparency. Inertia and mass of a strong (heavy) motor in the system make it difficult to display free environment such as air. Besides the choice of the hardware, the choice of the control strategy is an important fact, too. We will focus on two different strategies of how to display a virtual environment and discuss the concepts of impedance and admittance control.
[ARTICLE] Robot-assisted gait training improves motor performances and modifies Motor Unit firing in poststroke patients.
BACKGROUND: Robotics and related technologies are realizing their promise to improve the delivery of rehabilitation therapy but the mechanism by which they enhance recovery is still unknown. The electromechanical-driven gait orthosis Lokomat has demonstrated its utility for gait rehabilitation after stroke.
AIM: To test the efficacy of Lokomat in gait retraining and to investigate the neurophysiological mechanisms underlying the recovery process.
DESIGN: Case series study.
SETTING: Unit of Neurorehabilitation of a University Hospital.
POPULATION: Fifteen patients with post-stroke hemiparesis.
METHODS: Patients underwent a six weeks rehabilitative treatment provided by Lokomat.
The outcome measures were: Fugl-Meyer Motor Scale (FMMS), Berg Balance Scale (BBS), 10 metres Walking Test (10mWT), Timed Up and Go test (TUG), 6 Minute Walking Test (6MWT). Strength and Motor Unit firing rate of vastus medialis (VM) were analyzed during isometric knee extension through an isokinetic dynamometer and surface EMG recording.
RESULTS: An increase of duration and covered distance, a decrease of body weight support and guidance force on the paretic side along the sessions were observed. The FMMS, the BBS, the TUG and the 6MWT demonstrated a significant improvement after the training. No increase of force was observed whereas a significant increase of firing rate of VM was recorded.
CONCLUSION: The evidence that the improvement of walking ability observed in our study determines a significant increase of firing rate of VM not accompanied by an increase of force could suggest an effect of training on motorneuronal firing rate that thus contributes to improve motor control.
CLINICAL REHABILITATION IMPACT: Given the current wide use of robotics in gait retraining after stroke, our approach can contribute to clarify the mechanisms underlying its rehabilitative impact so as to incorporate the findings of evidence-based practice into appropriate treatment plans for persons poststroke.
[ARTICLE] Robotic neurorehabilitation in patients with chronic stroke: psychological well-being beyond motor improvement.
Although gait abnormality is one of the most disabling events following stroke, cognitive, and psychological impairments can be devastating. The Lokomat is a robotic that has been used widely for gait rehabilitation in several movement disorders, especially in the acute and subacute phases.
The aim of this study was to evaluate the effectiveness of gait robotic rehabilitation in patients affected by chronic stroke. Psychological impact was also taken into consideration.
Thirty patients (13 women and 17 men) affected by chronic stroke entered the study. All participants underwent neurological examination with respect to ambulation, Ashworth, Functional Independence Measure, and Tinetti scales to assess their physical status, and Hamilton Rating Scale for Depression, Psychological General Well-being Index, and Coping Orientation to Problem Experienced to evaluate the Lokomat-related psychological impact before and after either a conventional treatment or the robotic training.
During each rehabilitation period (separated by a no-treatment period), patients underwent a total of 40 1 h training sessions (i.e. five times a week for 8 weeks). After the conventional treatment, the patients did not achieve a significant improvement in the functional status, except balance (P<0.001) and walking ability (P<0.01), as per the Tinetti scale. Indeed, after the robotic rehabilitation, significant improvements were detected in almost all the motor and psychological scales that we investigated, particularly for Psychological General Well-being Index and Coping Orientation to Problem Experienced. Manual and robotic-assisted body weight-supported treadmill training optimizes the sensory inputs relevant to step training, repeated practice, as well as neuroplasticity.
Several controlled trials have shown a superior effect of Lokomat treatment in stroke patients’ walking ability and velocity in particular. Therefore, our preliminary results proved that active robotic training not only facilitates gait and physical function but also the psychological status, even in patients affected by chronic stroke.
We have conducted a critical review on the development of rehabilitation robots to identify the limitations of existing studies and clarify some promising research directions in this field. This paper is presented to summarize our findings and understanding. The demands for assistive technologies for elderly and disabled population have been discussed, the advantages and disadvantages of rehabilitation robots as assistive technologies have been explored, the issues involved in the development of rehabilitation robots are investigated, some representative robots in this field by leading research institutes have been introduced, and a few of critical challenges in developing advanced rehabilitation robots have been identified. Finally to meet the challenges of developing practical rehabilitation robots, reconfigurable and modular systems have been proposed to meet the identified challenges, and a few of critical areas leading to the potential success of rehabilitation robots have been discussed.
The progress on the studies of rehabilitating robots has been significantly lagged in contrast to the emerging society needs. On the one hand, the population who needs assistance and rehabilitation is consistently increasing; on the other hand, the existing rehabilitation robots have the limited capabilities of personalization and yet they are too expensive for the majority of patients. The performances of existing robots have been proven unsatisfactory [1, 2]. The innovations in the development of the next-generation rehabilitation robots can lead to significant benefits to human beings. In this paper, a critical literature review is conducted to identify the limitations of existing works and clarify the prosperous research directions in the development of assistive robots. In the next sections, the needs of assistive technologies in the healthcare industry are introduced…
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