Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human-Robot Interaction: A Systematic Review.

This article presents a systematic review on wearable robotic devices that use human-in-the-loop optimization (HILO) strategies to improve human-robot interaction. A total of 46 HILO studies were identified and divided into upper and lower limb robotic devices. The main aspects from HILO were identified, reviewed, and classified in four areas: 1) human-machine systems; 2) optimization methods; 3) control strategies; and 4) experimental protocols. A variety of objective functions (physiological, biomechanical, and subjective), optimization strategies, and optimized control parameters configurations used in different control strategies are presented and analyzed. An overview of experimental protocols is provided, including metrics, tasks, and conditions tested. Moreover, the relevance given to training or adaptation periods was explored. We outline an HILO framework that includes current wearable robots, optimization strategies, objective functions, control strategies, and experimental protocols. We conclude by highlighting current research gaps and defining future directions to improve the development of advanced HILO strategies in upper and lower limb wearable robots.

Passive shoulder exoskeleton support partially mitigates fatigue-induced effects in overhead work.

BACKGROUND: Despite the potential of occupational passive shoulder exoskeletons (PSEs) to relieve overhead work, limited insights in overhead work precision performance impedes large-scale adoption in industry. OBJECTIVE: To investigate the effect of PSE support on the reduction in task performance caused by physical fatigue. METHODS: This experiment consisted of a randomized, counterbalanced cross-over design comparing Exo4Work PSE support and no support, in a physically fatigued state and a control condition. Precision performance was determined using execution speed and drilling errors. Muscle activity and shoulder joint kinematics were recorded. RESULTS: Fatigue altered task performance, shoulder joint kinematics, muscle activity and subjective experience during overhead work. The PSE support mitigated the fatigue-induced changes in shoulder kinematics. Additionally, a part of the fatigue-induced co-activation of shoulder stabilizing muscles was avoided when working with the PSE. The PSE support also reduced the activity of the anterior and medial deltoid. CONCLUSION: Physical fatigue provokes compensatory movements and increased co-contraction of muscles when executing overhead work. These fatigue-induced alterations are generally believed to increase the overall musculoskeletal load. The support provided by the PSE reduced muscle activity of muscles working to elevate the arm, but also partially mitigated those fatigue-induced effects. SIGNIFICANCE: This study shows that the effect of PSE support on precision performance is limited, and suggested that, apart from the known effects of PSE support during overhead work, wearing the exoskeleton in a physically fatigued state may provide additional advantages.

Comparison of machine learning and deep learning-based methods for locomotion mode recognition using a single inertial measurement unit.

Locomotion mode recognition provides the prosthesis control with the information on when to switch between different walking modes, whereas the gait phase detection indicates where we are in the gait cycle. But powered prostheses often implement a different control strategy for each locomotion mode to improve the functionality of the prosthesis. Existing studies employed several classical machine learning methods for locomotion mode recognition. However, these methods were less effective for data with complex decision boundaries and resulted in misclassifications of motion recognition. Deep learning-based methods potentially resolve these limitations as it is a special type of machine learning method with more sophistication. Therefore, this study evaluated three deep learning-based models for locomotion mode recognition, namely recurrent neural network (RNN), long short-term memory (LSTM) neural network, and convolutional neural network (CNN), and compared the recognition performance of deep learning models to the machine learning model with random forest classifier (RFC). The models are trained from data of one inertial measurement unit (IMU) placed on the lower shanks of four able-bodied subjects to perform four walking modes, including level ground walking (LW), standing (ST), and stair ascent/stair descent (SA/SD). The results indicated that CNN and LSTM models outperformed other models, and these models were promising for applying locomotion mode recognition in real-time for robotic prostheses.

An Occupational Shoulder Exoskeleton Reduces Muscle Activity and Fatigue During Overhead Work.

OBJECTIVE: This paper assesses the effect of a passive shoulder exoskeleton prototype, Exo4Work, on muscle activity, muscle fatigue and subjective experience during simulated occupational overhead and non-overhead work. METHODS: Twenty-two healthy males performed six simulated industrial tasks with and without Exo4Work exoskeleton in a randomized counterbalanced cross-over design. During these tasks electromyography, heart rate, metabolic cost, subjective parameters and performance parameters were acquired. The effect of the exoskeleton and the body side on these parameters was investigated. RESULTS: Anterior deltoid activity and fatigue reduced up to 16% and 41%, respectively, during isometric overhead work, and minimized hindrance of the device during non-overhead tasks. Wearing the exoskeleton increased feelings of frustration and increased discomfort in the areas where the exoskeleton and the body interfaced. The assistive effect of the exoskeleton was less prominent during dynamic tasks. CONCLUSION: This exoskeleton may reduce muscle activity and delay development of muscle fatigue in an overhead working scenario. For dynamic applications, the exoskeleton's assistive profile, which mimics the gravitational torque of the arm, is potentially sub-optimal. SIGNIFICANCE: This evaluation paper is the first to report reduced muscle fatigue and activity when working with an occupational shoulder exoskeleton providing one third of the gravitational torque of the arm during overhead work. These results stress the potential of occupational shoulder exoskeletons in overhead working situations and may direct towards longitudinal field experiments. Additionally, this experiment may stimulate future work to further investigate the effect of different assistive profiles.

Benchmarking occupational exoskeletons: An evidence mapping systematic review.

OBJECTIVES: To provide an overview of protocols assessing the effect of occupational exoskeletons on users and to formulate recommendations towards a literature-based assessment framework to benchmark the effect of occupational exoskeletons on the user. METHODS: PubMed (MEDLINE), Web of Science database and Scopus were searched (March 2, 2021). Studies were included if they investigated the effect of one or more occupational exoskeletons on the user. RESULTS: In total, 139 eligible studies were identified, encompassing 33, 25 and 18 unique back, shoulder and other exoskeletons, respectively. Device validation was most frequently conducted using controlled tasks while collecting muscle activity and biomechanical data. As the exoskeleton concept matures, tasks became more applied and the experimental design more representative. With that change towards realistic testing environments came a trade-off with experimental control, and user experience data became more valuable. DISCUSSION: This evidence mapping systematic review reveals that the assessment of occupational exoskeletons is a dynamic process, and provides literature-based assessment recommendations. The homogeneity and repeatability of future exoskeleton assessment experiments will increase following these recommendations. The current review recognises the value of variability in evaluation protocols in order to obtain an overall overview of the effect of exoskeletons on the users, but the presented framework strives to facilitate benchmarking the effect of occupational exoskeletons on the users across this variety of assessment protocols.

Improved Motion Classification With an Integrated Multimodal Exoskeleton Interface.

Human motion intention detection is an essential part of the control of upper-body exoskeletons. While surface electromyography (sEMG)-based systems may be able to provide anticipatory control, they typically require exact placement of the electrodes on the muscle bodies which limits the practical use and donning of the technology. In this study, we propose a novel physical interface for exoskeletons with integrated sEMG- and pressure sensors. The sensors are 3D-printed with flexible, conductive materials and allow multi-modal information to be obtained during operation. A K-Nearest Neighbours classifier is implemented in an off-line manner to detect reaching movements and lifting tasks that represent daily activities of industrial workers. The performance of the classifier is validated through repeated experiments and compared to a unimodal EMG-based classifier. The results indicate that excellent prediction performance can be obtained, even with a minimal amount of sEMG electrodes and without specific placement of the electrode.

Passive Shoulder Exoskeletons: More Effective in the Lab Than in the Field?

Shoulder exoskeletons potentially reduce overuse injuries in industrial settings including overhead work or lifting tasks. Previous studies evaluated these devices primarily in laboratory setting, but evidence of their effectiveness outside the lab is lacking. The present study aimed to evaluate the effectiveness of two passive shoulder exoskeletons and explore the transfer of laboratory-based results to the field. Four industrial workers performed controlled and in-field evaluations without and with two exoskeletons, ShoulderX and Skelex in a randomized order. The exoskeletons decreased upper trapezius activity (up to 46%) and heart rate in isolated tasks. In the field, the effects of both exoskeletons were less prominent (up to 26% upper trapezius activity reduction) while lifting windscreens weighing 13.1 and 17.0 kg. ShoulderX received high discomfort scores in the shoulder region and usability of both exoskeletons was moderate. Overall, both exoskeletons positively affected the isolated tasks, but in the field the support of both exoskeletons was limited. Skelex, which performed worse in the isolated tasks compared to ShoulderX, seemed to provide the most support during the in-field situations. Exoskeleton interface improvements are required to improve comfort and usability. Laboratory-based evaluations of exoskeletons should be interpreted with caution, since the effect of an exoskeleton is task specific and not all in-field situations with high-level lifting will equally benefit from the use of an exoskeleton. Before considering passive exoskeleton implementation, we recommend analyzing joint angles in the field, because the support is inherently dependent on these angles, and to perform in-field pilot tests. This paper is the first thorough evaluation of two shoulder exoskeletons in a controlled and in-field situation.

Performance of the CYBERLEGs motorized lower limb prosthetic device during simulated daily activities.

Background: The CYBERLEGs-gamma (CLs-É£) prosthesis has been developed to investigate the possibilities of powerful active prosthetics in restoring human gait capabilities after lower limb amputation. Objective: The objective of this study was to determine the performance of the CLs-É£ prosthesis during simulated daily activities. Methods: Eight participants with a transfemoral amputation (age: 55 ± 15 years, K-level 3, registered under: NCT03376919) performed a familiarization session, an experimental session with their current prosthesis, three training sessions with the CLs-É£ prosthesis and another experimental session with the CLs-É£ prosthesis. Participants completed a stair-climbing-test, a timed-up-and-go-test, a sit-to stand-test, a 2-min dual-task and a 6-min treadmill walk test. Results: Comparisons between the two experimental sessions showed that stride length significantly increased during walking with the CLs-É£ prosthesis (p = .012) due to a greater step length of the amputated leg (p = .035). Although a training period with the prototype was included, preferred walking speed was significantly slower (p = .018), the metabolic cost of transport was significantly higher (p = .028) and reaction times significantly worsened (p = .012) when walking with the CLs-É£ compared to the current prosthesis. Conclusions: It can be stated that a higher physical and cognitive effort were required when wearing the CLs-É£ prosthesis. Positive outcomes were observed regarding stride length and stair ambulation. Future prosthetics development should minimize the weight of the device and integrate customized control systems. A recommendation for future research is to include several shorter training periods or a prolonged adaptation period.

A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses.

Fast and accurate gait phase detection is essential to achieve effective powered lower-limb prostheses and exoskeletons. As the versatility but also the complexity of these robotic devices increases, the research on how to make gait detection algorithms more performant and their sensing devices smaller and more wearable gains interest. A functional gait detection algorithm will improve the precision, stability, and safety of prostheses, and other rehabilitation devices. In the past years the state-of-the-art has advanced significantly in terms of sensors, signal processing, and gait detection algorithms. In this review, we investigate studies and developments in the field of gait event detection methods, more precisely applied to prosthetic devices. We compared advantages and limitations between all the proposed methods and extracted the relevant questions and recommendations about gait detection methods for future developments.

Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements.

BACKGROUND: Currently, control of exoskeletons in rehabilitation focuses on imposing desired trajectories to promote relearning of motions. Furthermore, assistance is often provided by imposing these desired trajectories using impedance controllers. However, lower-limb exoskeletons are also a promising solution for mobility problems of individuals in daily life. To develop an assistive exoskeleton which allows the user to be autonomous, i.e. in control of his motions, remains a challenge. This paper presents a model-based control method to tackle this challenge. METHODS: The model-based control method utilizes a dynamic model of the exoskeleton to compensate for its own dynamics. After this compensation of the exoskeleton dynamics, the exoskeleton can provide a desired assistance to the user. While dynamic models of exoskeletons used in the literature focus on gravity compensation only, the need for modelling and monitoring of the ground contact impedes their widespread use. The control strategy proposed here relies on modelling of the full exoskeleton dynamics and of the contacts with the environment. A modelling strategy and general control scheme are introduced. RESULTS: Validation of the control method on 15 non-disabled adults performing sit-to-stand motions shows that muscle effort and joint torques are similar in the conditions with dynamically compensated exoskeleton and without exoskeleton. The condition with exoskeleton in which the compensating controller was not active showed a significant increase in human joint torques and muscle effort at the knee and hip. Motor saturation occurred during the assisted condition, which limited the assistance the exoskeleton could deliver. CONCLUSIONS: This work presents the modelling steps and controller design to compensate the exoskeleton dynamics. The validation seems to indicate that the presented model-based controller is able to compensate the exoskeleton.

The Challenges and Achievements of Experimental Implementation of an Active Transfemoral Prosthesis Based on Biological Quasi-Stiffness: The CYBERLEGs Beta-Prosthesis.

The CYBERLEGs Beta-Prosthesis is an active transfemoral prosthesis that can provide the full torque required for reproducing average level ground walking at both the knee and ankle in the sagittal plane. The prosthesis attempts to produce a natural level ground walking gait that approximates the joint torques and kinematics of a non-amputee while maintaining passively compliant joints, the stiffnesses of which were derived from biological quasi-stiffness measurements. The ankle of the prosthesis consists of a series elastic actuator with a parallel spring and the knee is composed of three different systems that must compliment each other to generate the correct joint behavior: a series elastic actuator, a lockable parallel spring and an energy transfer mechanism. Bench testing of this new prosthesis was completed and demonstrated that the device was able to create the expected torque-angle characteristics for a normal walker under ideal conditions. The experimental trials with four amputees walking on a treadmill to validate the behavior of the prosthesis proved that although the prosthesis could be controlled in a way that allowed all subjects to walk, the accurate timing and kinematic requirements of the output of the device limited the efficacy of using springs with quasi-static stiffnesses. Modification of the control and stiffness of the series springs could provide better performance in future work.

VUB-CYBERLEGs CYBATHLON 2016 Beta-Prosthesis: case study in control of an active two degree of freedom transfemoral prosthesis.

BACKGROUND: Here we present how the CYBERLEGs Beta-Prosthesis was modified with a new control system to participate in the Powered Leg Prosthesis event, and to report on our experience at the CYBATHLON 2016 which was held in Zurich, Switzerland in October 2016. The prosthesis has two active degrees of freedom which assist the user with extra joint power at the knee and ankle to complete tasks. The CYBATHLON is a championship for people with disabilities competing in six disciplines, using advanced assistive devices. Tasks for CYBATHLON 2016 were chosen to reflect everyday normal task such as sitting and standing from a chair, obstacle avoidance, stepping stones, slope walking and descent, and stair climbing and descent. METHODS: The control schemata were presented along with the description of each of the six tasks. The participant of the competition, the pilot, ran through each of the trials under lab conditions and representative behaviors were recorded. RESULTS: The VUB CYBERLEGs prosthesis was able to accomplish, to some degree, five of the six tasks and here the torque and angle behaviors of the device while accomplishing these tasks are presented. The relatively simple control methods were able to provide assistive torque during many of the events, particularly sit to stand and stair climbing. For example, the prosthesis was able to consistently provide over 30 Nm in arresting knee torque in the sitting task, and over 20 Nm while standing. Peak torque of the device was not sufficient for unassisted stair climbing, but was able to provide around 60 Nm of assistance in both ascent and descent. Use of the passive behaviors of the device were shown to be able to trigger state machine events reliably for certain tasks. CONCLUSIONS: Although the performance of the CYBERLEGs prosthesis during CYBATHLON 2016 did not compare to the other top of the market designs with regards to speed, the device performed all of the tasks that were deemed possible by the start of the competition. Moreover, the Pilot was able to accomplish tasks in ways the Pilot's personal microcontrolled prosthesis could not, with limited powered prosthesis training. Future studies will focus on decreasing weight, increasing reliability, incorporating better control, and increasing the velocity of the device. This is only a case study and actual benefits to clinical outcomes are not yet understood and need to be further investigated. This competition was a unique experience to illuminate problems that future versions of the device will be able to solve.

Whole Body Awareness for Controlling a Robotic Transfemoral Prosthesis.

Restoring locomotion functionality of transfemoral amputees is essential for early rehabilitation treatment and for preserving mobility and independence in daily life. Research in wearable robotics fostered the development of innovative active mechatronic lower-limb prostheses designed with the goal to reduce the cognitive and physical effort of lower-limb amputees in rehabilitation and daily life activities. To ensure benefits to the users, active mechatronic prostheses are expected to be aware of the user intention and properly interact in a closed human-in-the-loop paradigm. In the state of the art various cognitive interfaces have been proposed to online decode the user's intention. Electromyography in combination with mechanical sensing such as inertial or pressure sensors is a widely adopted solution for driving active mechatronic prostheses. In this framework, researchers also explored targeted muscles re-innervation for an objective-oriented surgical amputation promoting wider usability of active prostheses. However, information kept by the neural component of the cognitive interface deteriorates in a prolonged use scenario due to electrodes-related issues, thereby undermining the correct functionality of the active prosthesis. The objective of this work is to present a novel controller for an active transfemoral prosthesis based on whole body awareness relying on a wireless distributed non-invasive sensory apparatus acting as cognitive interface. A finite-state machine controller based on signals monitored from the wearable interface performs subject-independent intention detection of functional tasks such as ground level walking, stair ascent, and sit-to-stand maneuvres and their main sub-phases. Experimental activities carried out with four transfemoral amputees (among them one dysvascular) demonstrated high reliability of the controller capable of providing 100% accuracy rate in treadmill walking even for weak subjects and low walking speeds. The minimum success rate was of 94.8% in performing sit-to-stand tasks. All the participants showed high confidence in using the transfemoral active prosthesis even without training period thanks to intuitiveness of the whole body awareness controller.