Multimodal fusion and human-robot interaction control of an intelligent robot

Introduction: Small-scaled robotic walkers play an increasingly important role in Activity of Daily Living (ADL) assistance in the face of ever-increasing rehab requirements and existing equipment drawbacks. This paper proposes a Rehabilitation Robotic Walker (RRW) for walking assistance and body weight support (BWS) during gait rehabilitation. Methods: The walker provides the patients with weight offloading and guiding force to mimic a series of the physiotherapist's (PT's) movements, and creates a natural, comfortable, and safe environment. This system consists of an omnidirectional mobile platform, a BWS mechanism, and a pelvic brace to smooth the motions of the pelvis. To recognize the human intentions, four force sensors, two joysticks, and one depth-sensing camera were used to monitor the human-machine information, and a multimodal fusion algorithm for intention recognition was proposed to improve the accuracy. Then the system obtained the heading angle E, the pelvic pose F, and the motion vector H via the camera, the force sensors, and the joysticks respectively, classified the intentions with feature extraction and information fusion, and finally outputted the motor speed control through the robot's kinematics. Results: To validate the validity of the algorithm above, a preliminary test with three volunteers was conducted to study the motion control. The results showed that the average error of the integral square error (ISE) was 2.90 and the minimum error was 1.96. Discussion: The results demonstrated the efficiency of the proposed method, and that the system is capable of providing walking assistance.

A robotic treadmill system to mimic overground walking training with body weight support

Introduction

Body weight support overground walking training (BWSOWT) is widely used in gait rehabilitation. However, existing systems require large workspace, complex structure, and substantial installation cost for the actuator, which make those systems inappropriate for the clinical environment. For wide clinical use, the proposed system is based on a self-paced treadmill, and uses an optimized body weight support with frame-based two-wire mechanism.

Method

The Interactive treadmill was used to mimic overground walking. We opted the conventional DC motors to partially unload the body weight and modified pelvic type harness to allow natural pelvic motion. The performance of the proposed system on the measurement of anterior/posterior position, force control, and pelvic motion was evaluated with 8 healthy subjects during walking training.

Results

We verified that the proposed system was the cost/space-effective and showed the more accurate anterior/posterior position than motion sensor, comparable force control performance, and natural pelvic motion.

Discussion

The proposed system is cost/space effective, and able to mimic overground walking training with body weight support. In future work, we will improve the force control performance and optimize the training protocol for wide clinical use.

A novel Dynamic Body Weight Support overground co-walker enabling variable unloading ratio and Motion Tracking

Dynamic Body Weight Support (BWS) systems have gained attention in recent years for their potential in gait training. However, maintaining a natural gait and vertical unloading have been less explored. In our previous work, we developed a body Motion Tracking (MT) walker that can move with patients. In this study, we introduce a novel Motion Tracking Variable Body Weight Support (MTVBWS) system for overground walkers. This system utilizes Center of Mass (COM) tracking and gait phase detection to not only dynamically support the user's body weight in the vertical direction but also to facilitate movement in all directions. The system achieves this horizontal omnidirectional movement by employing active Mecanum wheels, guided by COM recognition. The validation experiments were implemented with the MT mode, passive mode, and BWS mode in "static," "fixed unloading ratio (FUR)," and "variable unloading ratio (VUR)" settings with unloading force of 20 and 30%. The result shows that, compared to other modes, the proposed system in the MTVBWS mode can reduce the dragging effect in the horizontal plane caused by the walker. Moreover, the unloading force can be adjusted automatically to minimize the fluctuations in the force experienced by each lower limb during the rehabilitation walking training process. In comparison to natural walk, this mode presents smaller force fluctuations for each lower limb.

Hardware Development and Safety Control Strategy Design for a Mobile Rehabilitation Robot

The use of bodyweight unloading force control on a treadmill with therapist manual assistance for gait training imposes constraints on natural walking. It influences the patient’s training effect for a full range of natural walks. This study presents a prototype and a safety controller for a mobile rehabilitation robot (MRR). The prototype integrates an autonomous mobile bodyweight support system (AMBSS) with a lower-limb exoskeleton system (LES) to simultaneously achieve natural over-ground gait training and motion relearning. Human-centered rehabilitation robots must guarantee the safety of patients in the presence of significant tracking errors. It is difficult for traditional stiff controllers to ensure safety and excellent tracking accuracy concurrently, because they cannot explicitly guarantee smooth, safe, and overdamped motions without overshoot. This paper integrated a linear extended state observer (LESO) into proxy-based sliding mode control (ILESO-PSMC) to overcome this problem. The LESO was used to observe the system’s unknown states and total disturbance simultaneously, ensuring that the “proxy” tracks the reference target accurately and avoids the unsafe control of the MRR. Based on the Lyapunov theorem to prove the closed-loop system stability, the proposed safety control strategy has three advantages: (1) it provides an accurate and safe control without worsening tracking performance during regular operation, (2) it guarantees safe recoveries and overdamped properties after abnormal events, and (3) it need not identify the system model and measure unknown system states as well as external disturbance, which is quite difficult for human–robot interaction (HRI) systems. The results demonstrate the feasibility of the proposed ILESO-PSMC for MRR. The experimental comparison also indicates better safety performance for the ILESO-PSMC than for the conventional proportional–integral–derivative (PID) control.

Development of a Prototype Overground Pelvic Obliquity Support Robot for Rehabilitation of Hemiplegia Gait

In this work, we present the overground prototype gait-rehabilitation robot for using motion assistance and training for paralyzed patients. In contrast to the existing gait-rehabilitation robots, which focus on the sagittal plane motion of the hip and knee, we aim to develop a mobile-based pelvic support gait-rehabilitation system that includes a pelvic obliquity support mechanism and a lower-limb exoskeleton. To achieve this, a scissor mechanism is proposed to generate the paralyzed patient’s pelvic obliquity motion and weight support. Moreover, the lower limb exoskeleton robot is integrated with the developed system to provide the patient’s gait by correcting mechanical aids. We used computer-aided analysis to verify the performance of the prototype hardware itself. Through these methods, it was shown that our motor can sufficiently lift 100 kg of user weight through the scissor mechanism, and that the mobile driving wheel motor can operate at a speed of 1.6 m/s of human walking, showing that it can be used for gait rehabilitation of patients in need of a lower speed. In addition, we verified that the system drives the model by generating pelvic motion, and we verified the position controller of the integrated system, which supports the multi-degree motion by creating hip/knee/pelvic motion with a human dummy mannequin and systems. We believe that the proposed system can help address the complex rehabilitation motion assistance and training of paralyzed patients.

Metabolically efficient walking assistance using optimized timed forces at the waist

The metabolic rate of walking can be reduced by applying a constant forward force at the center of mass. It has been shown that the metabolically optimal constant force magnitude minimizes propulsion ground reaction force at the expense of increased braking. This led to the hypothesis that selectively assisting propulsion could lead to greater benefits. We used a robotic waist tether to evaluate the effects of forward forces with different timings and magnitudes. Here, we show that it is possible to reduce the metabolic rate of healthy participants by 48% with a greater efficiency ratio of metabolic cost reduction per unit of net aiding work compared with other assistive robots. This result was obtained using a sinusoidal force profile with peak timing during the middle of the double support. The same timing could also reduce the metabolic rate in patients with peripheral artery disease. A model explains that the optimal force profile accelerates the center of mass into the inverted pendulum movement during single support. Contrary to the hypothesis, the optimal force timing did not entirely coincide with propulsion. Within the field of wearable robotics, there is a trend to use devices to mimic biological torque or force profiles. Such bioinspired actuation can have relevant benefits; however, our results demonstrate that this is not necessarily optimal for reducing metabolic rate.

Motion Planning for Mobile Manipulators—A Systematic Review

One of the fundamental fields of research is motion planning. Mobile manipulators present a unique set of challenges for the planning algorithms, as they are usually kinematically redundant and dynamically complex owing to the different dynamic behavior of the mobile base and the manipulator. The purpose of this article is to systematically review the different planning algorithms specifically used for mobile manipulator motion planning. Depending on how the two subsystems are treated during planning, sampling-based, optimization-based, search-based, and other planning algorithms are grouped into two broad categories. Then, planning algorithms are dissected and discussed based on common components. The problem of dealing with the kinematic redundancy in calculating the goal configuration is also analyzed. While planning separately for the mobile base and the manipulator provides convenience, the results are sub-optimal. Coordinating between the mobile base and manipulator while utilizing their unique capabilities provides better solution paths. Based on the analysis, challenges faced by the current planning algorithms and future research directions are presented.

A Review of Robot-Assisted Lower-Limb Stroke Therapy: Unexplored Paths and Future Directions in Gait Rehabilitation

Stroke affects one out of every six people on Earth. Approximately 90% of stroke survivors have some functional disability with mobility being a major impairment, which not only affects important daily activities but also increases the likelihood of falling. Originally intended to supplement traditional post-stroke gait rehabilitation, robotic systems have gained remarkable attention in recent years as a tool to decrease the strain on physical therapists while increasing the precision and repeatability of the therapy. While some of the current methods for robot-assisted rehabilitation have had many positive and promising outcomes, there is moderate evidence of improvement in walking and motor recovery using robotic devices compared to traditional practice. In order to better understand how and where robot-assisted rehabilitation has been effective, it is imperative to identify the main schools of thought that have prevailed. This review intends to observe those perspectives through three different lenses: the goal and type of interaction, the physical implementation, and the sensorimotor pathways targeted by robotic devices. The ways that researchers approach the problem of restoring gait function are grouped together in an intuitive way. Seeing robot-assisted rehabilitation in this unique light can naturally provoke the development of new directions to potentially fill the current research gaps and eventually discover more effective ways to provide therapy. In particular, the idea of utilizing the human inter-limb coordination mechanisms is brought up as an especially promising area for rehabilitation and is extensively discussed.

High mobility control of an omnidirectional platform for gait rehabilitation after stroke

We present a novel control method for an omnidirectional robotic platform for gait training. This mobile platform or "walker" provides trunk support and allows unrestricted motion of the pelvis simultaneously. In addition to helping the user maintain balance and preventing falls, the walker combines two types of therapeutic intervention: forward propulsion of the trunk and partial body weight support (BWS). The core of the walker's control is an admittance controller that maximizes the platform's horizontal mobility by optimizing the virtual mass of the admittance model. Said mass represents the best tradeoff between a low-frequency oscillation mode that becomes more damped as the virtual mass decreases, and a high-frequency mode that becomes less damped simultaneously and hence could destabilize the system. Forward propulsion of the trunk is aided by a horizontal force that is modulated with the patient's gait speed and turning rate to ensure easy adaptation. BWS is provided by a second, independent admittance controller that generates a spring-like upward force. In an initial study, a stroke patient was able to walk stably in the platform, as evidenced by the absence of oscillations associated with an excessively low virtual mass. A progressive increase in the patient's self-selected speed, along with greater uniformity in the instantaneous velocity, suggest that forward propulsion was effective in compensating the patient's own propulsion deficit.

Robotics for Lower Limb Rehabilitation

Improving walking function is a desirable outcome in rehabilitation and of high importance for social and vocational reintegration for persons with neurologic-related gait impairment. Robots for lower limb gait rehabilitation are designed principally to help automate repetitive labor-intensive training during neurorehabilitation. These include tethered exoskeletons, end-effector devices, untethered exoskeletons, and patient-guided suspension systems. This article reviews the first 3 categories and briefly mentions the fourth. Research is needed to further define the therapeutic applications of these devices. Additional technical improvements are expected regarding device size, controls, and battery life for untethered devices.

Toward Standardizing the Classification of Robotic Gait Rehabilitation Systems

With the existence of numerous rehabilitation systems, classification and comparison becomes difficult, especially due to the many factors involved. Moreover, most current reviews are descriptive and do not provide systematic methods for the visual comparison of systems. This review proposes a method for classifying systems and representing them graphically to easily visualize various characteristics of the different systems at the same time. This method could be an introduction for standardizing the evaluation of gait rehabilitation systems. It evaluates four main modules (body weight support, reciprocal stepping mechanism, pelvis mechanism, and environment module) of 27 different gait systems based on a set of characteristics. The combination of these modular evaluations provides a description of the system "in the space of rehabilitation." The evaluation of each robotic module, based on specific characteristics, showed diverse tendencies. While there is an augmented interest in developing more sophisticated reciprocal stepping mechanisms, few researchers are dedicated to enhance the properties of pelvis mechanisms.

A novel protocol to evaluate ankle movements during reaching tasks using pediAnklebot

The aim of the study is to design a novel protocol to characterize the ankle movements during dorsal and plantar flexion reaching tasks using the pediAnklebot. Five healthy children were instructed to control a pointer and hit targets appearing on the monitor, by moving their ankle alternatively up and down. The protocol consisted of 60 targets, 30 up and 30 down, reachable via dorsiflexion and plantarflexion movements, respectively. Ankle angular displacements and torques were gathered by encoders and load cells embedded in the robot. Ankle motor performance was evaluated by means of kinematic, submovements and dynamic indices. Results suggest that (i) plantarflexion movements are faster and more accurate than the dorsiflexion ones, but children are able to perform with a higher level of smoothness the latter ones; (ii) children are able to stop the ankle movement more easily at the end of dorsiflexion rather than plantarflexion; (iii) the central nervous system plans plantarflexion and dorsiflexion movements with the same efficiency; (iv) children apply different torque levels during the two motor tasks and they cannot balance the inversion and eversion moments during dorsiflexion. These findings provide an important starting point for the assessment of a reference baseline of motor indices for the ankle joint.

Smart walkers: an application-oriented review

In this paper, a development method for smart walker prototypes is proposed. Development of such prototypes is based on technological choices and device evaluations. The method is aimed at guiding technological choices in a modular fashion. First, the method for choosing modules to be integrated in a smart walker is presented. Application-specific modules are then studied. Finally, the issues of evaluation are investigated. In order to work out this method, more than 50 smart walkers and their pros and cons with respect to the different studied applications are reviewed.

Automated detection of instantaneous gait events using time frequency analysis and manifold embedding

Accelerometry is a widely used sensing modality in human biomechanics due to its portability, non-invasiveness, and accuracy. However, difficulties lie in signal variability and interpretation in relation to biomechanical events. In walking, heel strike and toe off are primary gait events where robust and accurate detection is essential for gait-related applications. This paper describes a novel and generic event detection algorithm applicable to signals from tri-axial accelerometers placed on the foot, ankle, shank or waist. Data from healthy subjects undergoing multiple walking trials on flat and inclined, as well as smooth and tactile paving surfaces is acquired for experimentation. The benchmark timings at which heel strike and toe off occur, are determined using kinematic data recorded from a motion capture system. The algorithm extracts features from each of the acceleration signals using a continuous wavelet transform over a wide range of scales. A locality preserving embedding method is then applied to reduce the high dimensionality caused by the multiple scales while preserving salient features for classification. A simple Gaussian mixture model is then trained to classify each of the time samples into heel strike, toe off or no event categories. Results show good detection and temporal accuracies for different sensor locations and different walking terrains.

Gait Rehabilitation Device in Central Nervous System Disease: A Review

Central nervous system diseases cause the gait disorder. Early rehabilitation of a patient with central nervous system disease is shown to be benefit. However, early gait training is difficult because of muscular weakness and those elderly patients who lose of leg muscular power. In the patient's walking training, therapists assist the movement of patient's lower limbs and control the movement of patient's lower limbs. However the assistance for the movement of the lower limbs is a serious hard labor for therapists. Therefore, research into and development of various gait rehabilitation devices is currently underway to identify methods to alleviate the physical burden on therapists. In this paper, we introduced the about gait rehabilitation devices in central nervous system disease.

Lower-Limb Robotic Rehabilitation: Literature Review and Challenges

This paper presents a survey of existing robotic systems for lower-limb rehabilitation. It is a general assumption that robotics will play an important role in therapy activities within rehabilitation treatment. In the last decade, the interest in the field has grown exponentially mainly due to the initial success of the early systems and the growing demand caused by increasing numbers of stroke patients and their associate rehabilitation costs. As a result, robot therapy systems have been developed worldwide for training of both the upper and lower extremities. This work reviews all current robotic systems to date for lower-limb rehabilitation, as well as main clinical tests performed with them, with the aim of showing a clear starting point in the field. It also remarks some challenges that current systems still have to meet in order to obtain a broad clinical and market acceptance.

Empowering and Assisting Natural Human Mobility: The Simbiosis Walker

This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staff.