Gait Rehabilitation Devices Research Articles

Social Human-Robot Interaction for Gait Rehabilitation.

Robot-assisted therapy for gait rehabilitation of patients with neurological disorders usually combines a body weight support system with a treadmill system. Lokomat is one of the most used devices for gait rehabilitation. This device allows therapists to focus on the patient and the therapy. However, this therapy session is based on multi-tasking processes, which are often difficult for a therapist to manage. In this work, a Socially Assistive Robot (SAR) was integrated into a neurorehabilitation program as a collaborator agent to promote patient engagement and performance during the therapy. This short-term study presents the effects comparing the social robot condition and control condition with a group of four neurological patients using repeated measurement design. As a remarkable result, patients improved thoracic 18.44% and cervical 32.23% posture on average with SAR assistance. This study demonstrated the feasibility of the integration of a social robot as a complement of gait rehabilitation programs.

Biomechanical differences during ascent on regular stairs and on a stairmill

Stair climbing is an intense physical activity and requires large range of motion at the joints, adequate muscle strength, and balance control. A powered stairmill, integrated with a gait rehabilitation device, can potentially be used for training those who have difficulty climbing stairs. In order to assess the effectiveness of such an approach, it is necessary to understand the similarities and differences in walking on regular stairs and on a stairmill. We have conducted an experiment to compare the differences in kinematics and muscle activations during climbing on regular stairs and a stairmill. Twelve subjects participated in this study. They first walked on regular stairs five times and then performed a one-minute continuous walking on a stairmill. The results showed several important differences. During continuous walking on a stairmill, when compared to regular stairs, there was (i) an increase in the percentage of stance phase during a walking cycle, (ii) a higher angle of plantarflexion of the ankle during the transition from stance phase to swing phase, and (iii) a decrease in muscle activation of the tibialis anterior during swing phase. These differences would provide additional insights into the design of future rehabilitation systems and to interpret human data obtained from stairmills.

Robotic orthoses for gait rehabilitation: An overview of mechanical design and control strategies.

The application of robotic devices in providing physiotherapies to post-stroke patients and people suffering from incomplete spinal cord injuries is rapidly expanding. It is crucial to provide valid rehabilitation for people who are experiencing abnormality in their gait performance; therefore, design and development of newer robotic devices for the purpose of facilitating patients' recovery is being actively researched. In order to advance the traditional gait treatment among patients, exoskeletons and orthoses were introduced over the last two decades. This article presents a thorough review of existing robotic gait rehabilitation devices. The latest advancements in the mechanical design, types of control and actuation are also covered. The study comprehends discussions on robotic rehabilitation devices developed both for the training on treadmill and over-ground training. The assist-as-needed strategy for the gait training is particularly emphasized while reviewing various control strategies applied to these robotic devices. This study further reviews experimental investigations and clinical assessments of different control strategies and mechanism designs of robotic gait rehabilitation devices using experimental and clinical trials.

Whole-body vibration on parallel bar device for gait and balance rehabilitation in stroke patients

Stroke is a condition that affects the cerebral vessels with focal or global involvement of the central nervous system. There is an increase in the use of whole-body vibrations (WBV) as a complement to neurological rehabilitation. Some studies on vibratory performance in a controlled way can improve muscle performance and balance in young adults. Therefore, this paper aims to present the design, development, and validation of a vibratory platform with unidirectional oscillation of controlled amplitude and frequency to aid in the gait and balance rehabilitation of ischemic stroke. The vibrating platform was built with 2 m length allowing mobility and diversity of gait training. It is actuated by an interchangeable eccentric mechanism that allows amplitude change. Frequency control is done by analog signal given by a potentiometer to a frequency inverter that allows real-time control. The project was submitted to Finite Elements Analysis in appropriate software. The device was built predominantly in structural steel following safety criteria and physically tested in the same project configuration, with frequency, amplitude, and applied load of 26 Hz, 4 mm, and 100 kgf, respectively positioned in three points of the platform, validated in terms of amplitude, frequency, and working load. Obtained data demonstrated reproducibility and repeatability, such as an appropriate device to aid the gait and balance treatment in stroke patients. Although the equipment has been positively analyzed in operation by a board of physiotherapists specializing in neurological rehabilitation, it is convenient to evaluate protocol in asymptomatic previously to the stroke.

Evaluation and Analysis of Push-Pull Cable Actuation System Used for Powered Orthoses.

Cable-based actuation systems are preferred in rehabilitation robotics due to their adequate force transmission and the possibility of safely locating the motors away from the patient. In such applications, the cable dynamics represents the prescribing component for the system operating loads and control. A good understanding of the actuation, based on cable-conduit transmission, is therefore becoming mandatory. There are several types of cable-conduit configurations used for the actuation. Currently, there is lack of information in literature with regard to the push-pull cable type. Therefore, the main focus of this contribution is to evaluate push-pull cable-based actuation used within wearable robotic devices. This study includes working principle description of push-pull cable actuation with its characteristic advantages and drawbacks. The use of push-pull cables in bidirectional force transfer with remote actuation is investigated being integrated in a test-stand setup of a novel gait rehabilitation device. The experimental results and close analysis of the push-pull cable-based actuation system outline its performance, the overall dynamic behavior and the transmission efficiency of push-pull cables used for powered orthoses.

A wearable somatosensory teaching device with adjustable operating force for gait rehabilitation training robot

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.

Automated stand-up and sit-down detection for robot-assisted body-weight support training with the FLOAT.

Patients with impaired walking function are often dependent on assistive devices to retrain gait and regain independence in life. To provide adequate support, gait rehabilitation devices have to be manually set to the correct support mode or have to recognize the type and starting point of a certain motion automatically. For automated motion type detection, machine learning-based classification algorithms using sensor signals from different body parts can achieve robust performance. However, until today, there is only little work available to detect motion onset. In this paper, we investigate task onset detection of sit-to-stand and stand-to-sit transitions. The focus of the current study is twofold: First, the optimal window size for the online classification algorithm shall be found. Second, the ideal sensor placement in a single sensor-setup, to detect movement onset with shortest detection delays possible is of interest. For our investigations a linear discriminant analysis classifier, basic kinematic features, and a leave-one-subject-out cross validation are used. As a result, an average detection time of 56 milliseconds (SD 111) for sit-to-stand and 48 milliseconds (SD 137) for stand-to-sit were achieved with a window size of 15 and 35 milliseconds respectively at a data rate of 200 hertz. For sit-to-stand transitions, a sensor close to the tenth vertebra and for stand-to-sit transitions close to the posterior pelvis provided the smallest detection times.

MIT-Skywalker: On the use of a markerless system.

This paper describes our efforts to employ the Microsoft Kinect as a low cost vision control system for the MIT-Skywalker, a robotic gait rehabilitation device. The Kinect enables an alternative markerless solution to control the MIT-Skywalker and allows a more user-friendly set-up. A study involving eight healthy subjects and two stroke survivors using the MIT-Skywalker device demonstrates the advantages and challenges of this new proposed approach.

Real-time biofeedback device for gait rehabilitation of post-stroke patients.

In this work, we develop a device, called 'Walk-Even', that can provide real-time feedback to correct gait asymmetry commonly exhibited in post-stroke survivors and persons with certain neurological disorders. The device computes gait parameters, including gait time, swing time, and stance time of each leg, to detect gait asymmetry and provide corresponding real-time biofeedback by means of auditory and electrotactile stimulation to actively correct the user's gait. The system consists of customized force-sensor-embedded insoles adjustable to fit any shoe size, electrotactile and auditory feedback circuits, microcontroller, and wireless XBee transceivers. The device also offers data saving capability. To validate its accuracy and reliability, we compared the gait measurements from our device with a commercial gait and balance assessment device, Zeno Walkway. The results show good correlation and agreement in a validity study with six healthy subjects and reliability study with seventeen healthy subjects. In addition, preliminary testing on six post-stroke patients after an 8-week training shows that the Walk-Even device helps to improve gait symmetry, foot pressure and forefoot loading of the affected side. Thus, initial testing indicates that the device is accurate in measuring the gait parameters and effective in improving gait symmetry using real-time feedback. The device is portable and low cost and has the potential for use in a non-clinical setting for patients that can walk independently without assistance. A more extensive testing with stroke patients is still ongoing.

Multi-Axis Force Sensor for Human-Robot Interaction Sensing in a Rehabilitation Robotic Device.

Human–robot interaction sensing is a compulsory feature in modern robotic systems where direct contact or close collaboration is desired. Rehabilitation and assistive robotics are fields where interaction forces are required for both safety and increased control performance of the device with a more comfortable experience for the user. In order to provide an efficient interaction feedback between the user and rehabilitation device, high performance sensing units are demanded. This work introduces a novel design of a multi-axis force sensor dedicated for measuring pelvis interaction forces in a rehabilitation exoskeleton device. The sensor is conceived such that it has different sensitivity characteristics for the three axes of interest having also movable parts in order to allow free rotations and limit crosstalk errors. Integrated sensor electronics make it easy to acquire and process data for a real-time distributed system architecture. Two of the developed sensors are integrated and tested in a complex gait rehabilitation device for safe and compliant control.

Development of algorithm for different programmable modes for a prototype of orthotic ambulatory device for gait rehabilitation

Development of algorithm for different programmable modes for a prototype of orthotic ambulatory device for gait rehabilitation

Development of algorithm for different programmable modes for a prototype of orthotic ambulatory device for gait rehabilitation

Presently available orthotic devices have many limitations in their mechanical design, sensor mechanism and real-time control to achieve stable, efficient and human like bipedal walking. User adaptive control algorithm with different programmable modes for developed prototype of an orthotic device is implemented. Gait postures like sit, stand, walk, stair walk, user defined exercise mode, etc., are basic human mobility functions. These activities are part of rehabilitation therapy for a locomotive disabled. With emerging trend of robotic rehabilitation, orthotic devices with good control strategy that helps in early recovery and more effective in gait rehabilitation are required. Control strategy is based on gait parameters like lower limb joint angles and ground reaction force. Software algorithm is developed in LabVIEW platform for different modes like sit, stand, walk and stair climbing. Implemented control strategy is verified based on the trajectory error estimated of hip, knee and ankle of the device are analysed. These trajectories are compared with the standard available data.

Design, Analysis, and Optimization of an Acute Stroke Gait Rehabilitation Device

Stroke is one of the leading causes of adult physical disability, and rehabilitation and hospitalization costs for stroke are among the highest for all injuries. Current rehabilitation techniques are labor intensive and time consuming for therapists and difficult to perform effectively. Research suggests that starting rehabilitation during the acute or subacute stage of recovery results in better outcomes than therapy delivered in the chronic stage. To improve the gait rehabilitation process, robot-assisted gait rehabilitation has gained much interest over the past years. However, many robot-assisted rehabilitation devices have limitations; one of which is being bulky and complex to handle. Large and expensive devices that require special training to operate are less attractive to clinics and therapists, and ultimately less likely to be available to patients especially at the early stage of stroke. To address these limitations, this research proposes a new gait rehabilitation device called the linkage design gait trainer (LGT). The device is based on a walking frame design with a simple four-bar linkage “end-effector” mechanism to generate normal gait trajectories during general walking and exercise. The design of the four-bar linkage mechanism was optimized for a particular gait pattern. A prototype of the device was developed and tested. The kinematics of the device itself and gait kinematics with and without assistance from the device were recorded and analyzed using an optical motion capture system. The results show the linkage mechanism is able to guide the leg of the user during over ground walking. There were some differences in the hip (20.5 deg RMS) and knee (14.8 deg RMS) trajectory between the person walking with and without the device assistance. The study demonstrated the concept and feasibility of this novel gait training device.

Development and pilot clinical evaluation of a haptic-based perception-empathy biofeedback device for gait rehabilitation.

Recent studies have shown that haptic feedback on the body, either at or away from the desired gait parameter to be changed, can improve gait performance. Here we introduced a haptic-based biofeedback device to supplement the foot pressure information of a paretic foot with a wearable vibrotactile biofeedback device attached to the back. This system provides information regarding a patient's foot pressure pattern to the patient and physical therapist. Therefore, the biofeedback system can share information regarding abnormal gait patterns between patients and therapists. This pilot study showed that the device immediately improved the stride length during walking, but not walking speed. Furthermore, subjective reports indicated that synchronizing foot pressure pattern information between the patient and therapist induced higher patient motivation for gait rehabilitation.

Robotic gait rehabilitation and substitution devices in neurological disorders: where are we now?

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.

Decoding Sensorimotor Rhythms during Robotic-Assisted Treadmill Walking for Brain Computer Interface (BCI) Applications.

Locomotor malfunction represents a major problem in some neurological disorders like stroke and spinal cord injury. Robot-assisted walking devices have been used during rehabilitation of patients with these ailments for regaining and improving walking ability. Previous studies showed the advantage of brain-computer interface (BCI) based robot-assisted training combined with physical therapy in the rehabilitation of the upper limb after stroke. Therefore, stroke patients with walking disorders might also benefit from using BCI robot-assisted training protocols. In order to develop such BCI, it is necessary to evaluate the feasibility to decode walking intention from cortical patterns during robot-assisted gait training. Spectral patterns in the electroencephalogram (EEG) related to robot-assisted active and passive walking were investigated in 10 healthy volunteers (mean age 32.3±10.8, six female) and in three acute stroke patients (all male, mean age 46.7±16.9, Berg Balance Scale 20±12.8). A logistic regression classifier was used to distinguish walking from baseline in these spectral EEG patterns. Mean classification accuracies of 94.0±5.4% and 93.1±7.9%, respectively, were reached when active and passive walking were compared against baseline. The classification performance between passive and active walking was 83.4±7.4%. A classification accuracy of 89.9±5.7% was achieved in the stroke patients when comparing walking and baseline. Furthermore, in the healthy volunteers modulation of low gamma activity in central midline areas was found to be associated with the gait cycle phases, but not in the stroke patients. Our results demonstrate the feasibility of BCI-based robotic-assisted training devices for gait rehabilitation.

Minimizing Human Tracking Error for Robotic Rehabilitation Device

This paper explores the design of a novel robotic device for gait training and rehabilitation, a method to estimate a human's orientation within the rehabilitation device, as well as an optimal state space controller to actuate the rehabilitation device. The robotic parallel bars (RPBs) were designed to address the shortcomings of currently available assistive devices. The RPB device moves in response to a human occupant to maintain a constant distance and orientation to the human. To minimize the error in tracking the human, a complementary filter was optimized to estimate the human's orientation within the device using a magnetometer and gyroscope. Experimental measurements of complementary filter performance on a test platform show that the filter estimates orientation with an average error of 0.62 deg over a range of angular velocities from 22.5 deg/s to 180 deg/s. The RPB device response was simulated, and an optimal state space controller was implemented using a linear quadratic regulator (LQR). The controller has an average position error of 14.1 cm and an average orientation error of 14.3 deg when tracking a human, while the simulation predicted an average error of 10.5 cm and 5.6 deg. The achieved level of accuracy in following a human user is sufficiently sensitive for the RPB device to conduct more advanced, realistic gait training and rehabilitation techniques for mobility impaired patients able to safely support their body weight with their legs and arms.

Design of small-size pouch motors for rat gait rehabilitation device.

Recent studies have demonstrated that active gait training can recover voluntary locomotive ability of paralyzed rats. Rehabilitation devices used for studying spinal cord injury to date are usually fixed on a treadmill, but they have been used only slightly for active training. To process active rehabilitation, a wearable, lightweight device with adequate output is needed. Pouch motors, soft pneumatic actuators, are extremely light and have other benefits such as low cost, easy fabrication, and highly customizable design. They can be used to develop active gait rehabilitation devices. However, performance details of different motor designs have not been examined. As described herein, to build a wearable gait assistive device for rat study, we specifically examine how to design small pouch motors with a good contraction ratio and force output. Results show that pouch performance decreases dramatically with size, but better output is obtainable by separation into small 0.8 length-to-width ratio rooms. We used this knowledge to produce an assistive robot suit for gait rehabilitation and to test it with paralyzed rats. Results show that these small pouches can produce sufficient power to control hip joint movements during gait training. They can reveal the potential for new pouch motor applications for spinal cord injury studies.

Tuning of robotic therapy controllers for stroke gait: Using isometrically constrained EMG modular structures.

The development of EMG based controllers for automated gait orthosis is a promising intervention for post-stroke gait rehabilitation and assistive device applications. However, the integration of stroke specific modular neuromuscular patterns for the design of active gait assistance controller is largely unexplored. To this end, this work presents preliminary evidence of the associated variability between lower limb muscle activation patterns underlying discrete isometric control objectives and the analogous dynamic subtask during treadmill gait using matrix factorization algorithms. We find that common muscle coordination patterns underlying both isometric and dynamic gait submovements can be used to reconstruct relevant spatio-temporal patterns for healthy locomotion. We propose that synergies extracted isometrically may be sufficient to tune adaptive controller assistance for disruptive linkages in the EMG control signal to impact gait dysfunction.

Gait training with a new exoskeleton robot Hybrid Assistive Limb improves gait and balance performances in chronic stroke subjects

Background: New robotic locomotion devices have been developed for facilitation of gait training, and there is several evidence of a beneficial effect of the electromechanical devices for gait rehabilitation after stroke. A newly developed exoskeleton robot suit Hybrid Assistive Limb (HAL) has demonstrated its utility for gait rehabilitation after stroke. However, there is still insufficient knowledge about the efficacy of the training with HAL in chronic stroke subjects.