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Quantifying, Understanding and Improving Human-Exoskeleton Interaction

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Wearables".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 37063

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Special Issue Editors

Dr. Nevio Luigi Tagliamonte

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Guest Editor

Research Unit of Advanced Robotics and Human-Centered Technologies – Università Campus Bio-Medico di Roma, 00128 Rome, Italy
Laboratory of Robotic Neurorehabilitation – Fondazione Santa Lucia, 00179 Roma, Italy
Interests: wearable robotics; assistive and rehabilitation exoskeletons; human–robot interaction control; biomechanics of gait; exoskeleton-assisted walking

Dr. Diego Torricelli

E-Mail Website
Guest Editor

Neural Rehabilitation Group – Cajal Institute, Spanish National Research Council, 28006 Madrid, Spain
Interests: neurorehabilitation; wearable robotics; motor control; muscle synergies; human–machine interfaces; FES; eye-gaze tracking

Dr. Philipp Beckerle

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Guest Editor

Chair of Autonomous Systems and Mechatronics, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
Interests: wearable robotics; human-centered design/control; elastic actuation; human–robot interaction; body representations

Special Issue Information

Dear Colleagues,

Exoskeletons are becoming increasingly relevant to augment, train, or supplement motor functions in several application scenarios.

Using exoskeletons to exploit effective motor assistance while preserving natural, intuitive, smooth, and harmonious motion is still a great challenge in the design and control of exoskeletons.

Biomechatronic and user-centered design and control solutions are continuously evolving to improve wearability and ergonomics, functionality and effectiveness, as well as acceptability and usability. Moreover, novel sensor systems and assessment methods and protocols are currently being developed to analyze human–exoskeleton interaction from robotic, biomechanical, and physiological perspectives.

This Special Issue aims to collect current developments in the field of exoskeleton-assisted interaction, including any aspects related to the design, control, interfacing, and assessment of exoskeletons putting emphasis on sensors. Contributions from different application areas, such as orthopedic and neurological rehabilitation, personal daily life assistance, and industrial robot-aided working, are encouraged. Original studies and review papers from human-centered and industrial robotics, biomechatronics, biomechanics and bioengineering, rehabilitation, neuroscience, and other related fields will be considered.

Topics of interest include (but are not limited to):

Protocols and methods to assess exoskeleton-assisted motion;
Sensor systems for exoskeleton and interface assessment;
Algorithms for exoskeleton sensors and control;
Human–exoskeleton interaction modalities and analysis;
Biomechanical and ergonomic considerations of human–exoskeleton interaction;
Metabolic and physiological assessment of human–exoskeleton interaction;
Exoskeleton benchmarking metrics and protocols.

Dr. Nevio Luigi Tagliamonte
Dr. Diego Torricelli
Dr. Philipp Beckerle
Guest Editors

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Keywords

Exoskeletons
Wearable robotics
Human–exoskeleton interaction
Exoskeleton assessment

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Published Papers (12 papers)

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12 pages, 2088 KiB

Open AccessArticle

Human Exteroception during Object Handling with an Upper Limb Exoskeleton

by Dorine Arcangeli, Océane Dubois, Agnès Roby-Brami, Sylvain Famié, Giovanni de Marco, Gabriel Arnold, Nathanaël Jarrassé and Ross Parry

Sensors 2023, 23(11), 5158; https://doi.org/10.3390/s23115158 - 29 May 2023

Cited by 1 | Viewed by 1679

Abstract

Upper limb exoskeletons may confer significant mechanical advantages across a range of tasks. The potential consequences of the exoskeleton upon the user’s sensorimotor capacities however, remain poorly understood. The purpose of this study was to examine how the physical coupling of the user’s arm to an upper limb exoskeleton influenced the perception of handheld objects. In the experimental protocol, participants were required to estimate the length of a series of bars held in their dominant right hand, in the absence of visual feedback. Their performance in conditions with an exoskeleton fixed to the forearm and upper arm was compared to conditions without the upper limb exoskeleton. Experiment 1 was designed to verify the effects of attaching an exoskeleton to the upper limb, with object handling limited to rotations of the wrist only. Experiment 2 was designed to verify the effects of the structure, and its mass, with combined movements of the wrist, elbow, and shoulder. Statistical analysis indicated that movements performed with the exoskeleton did not significantly affect perception of the handheld object in experiment 1 (BF₀₁ = 2.3) or experiment 2 (BF₀₁ = 4.3). These findings suggest that while the integration of an exoskeleton complexifies the architecture of the upper limb effector, this does not necessarily impede transmission of the mechanical information required for human exteroception. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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22 pages, 4654 KiB

Open AccessArticle

Benchmarking the Effects on Human–Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control

by Camila Rodrigues-Carvalho, Marvin Fernández-García, David Pinto-Fernández, Clara Sanz-Morere, Filipe Oliveira Barroso, Susana Borromeo, Cristina Rodríguez-Sánchez, Juan C. Moreno and Antonio J. del-Ama

Sensors 2023, 23(2), 791; https://doi.org/10.3390/s23020791 - 10 Jan 2023

Cited by 8 | Viewed by 2903

Abstract

Nowadays, robotic technology for gait training is becoming a common tool in rehabilitation hospitals. However, its effectiveness is still controversial. Traditional control strategies do not adequately integrate human intention and interaction and little is known regarding the impact of exoskeleton control strategies on muscle coordination, physical effort, and user acceptance. In this article, we benchmarked three types of exoskeleton control strategies in a sample of seven healthy volunteers: trajectory assistance (TC), compliant assistance (AC), and compliant assistance with EMG-Onset stepping control (OC), which allows the user to decide when to take a step during the walking cycle. This exploratory study was conducted within the EUROBENCH project facility. Experimental procedures and data analysis were conducted following EUROBENCH’s protocols. Specifically, exoskeleton kinematics, muscle activation, heart and breathing rates, skin conductance, as well as user-perceived effort were analyzed. Our results show that the OC controller showed robust performance in detecting stepping intention even using a corrupt EMG acquisition channel. The AC and OC controllers resulted in similar kinematic alterations compared to the TC controller. Muscle synergies remained similar to the synergies found in the literature, although some changes in muscle contribution were found, as well as an overall increase in agonist-antagonist co-contraction. The OC condition led to the decreased mean duration of activation of synergies. These differences were not reflected in the overall physiological impact of walking or subjective perception. We conclude that, although the AC and OC walking conditions allowed the users to modulate their walking pattern, the application of these two controllers did not translate into significant changes in the overall physiological cost of walking nor the perceived experience of use. Nonetheless, results suggest that both AC and OC controllers are potentially interesting approaches that can be explored as gait rehabilitation tools. Furthermore, the INTENTION project is, to our knowledge, the first study to benchmark the effects on human–exoskeleton interaction of three different exoskeleton controllers, including a new EMG-based controller designed by us and never tested in previous studies, which has made it possible to provide valuable third-party feedback on the use of the EUROBENCH facility and testbed, enriching the apprenticeship of the project consortium and contributing to the scientific community. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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18 pages, 2097 KiB

Open AccessArticle

How Do Joint Kinematics and Kinetics Change When Walking Overground with Added Mass on the Lower Body?

by Shanpu Fang, Vinayak Vijayan, Megan E. Reissman, Allison L. Kinney and Timothy Reissman

Sensors 2022, 22(23), 9177; https://doi.org/10.3390/s22239177 - 25 Nov 2022

Cited by 6 | Viewed by 2150

Abstract

Lower-limb exoskeletons, regardless of their control strategies, have been shown to alter a user’s gait just by the exoskeleton’s own mass and inertia. The characterization of these differences in joint kinematics and kinetics under exoskeleton-like added mass is important for the design of such devices and their control strategies. In this study, 19 young, healthy participants walked overground at self-selected speeds with six added mass conditions and one zero-added-mass condition. The added mass conditions included +2/+4 lb on each shank or thigh or +8/+16 lb on the pelvis. OpenSim-derived lower-limb sagittal-plane kinematics and kinetics were evaluated statistically with both peak analysis and statistical parametric mapping (SPM). The results showed that adding smaller masses (+2/+8 lb) altered some kinematic and kinetic peaks but did not result in many changes across the regions of the gait cycle identified by SPM. In contrast, adding larger masses (+4/+16 lb) showed significant changes within both the peak and SPM analyses. In general, adding larger masses led to kinematic differences at the ankle and knee during early swing, and at the hip throughout the gait cycle, as well as kinetic differences at the ankle during stance. Future exoskeleton designs may implement these characterizations to inform exoskeleton hardware structure and cooperative control strategies. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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27 pages, 9507 KiB

Open AccessArticle

How Does Added Mass Affect the Gait of Middle-Aged Adults? An Assessment Using Statistical Parametric Mapping

by Vinayak Vijayan, Shanpu Fang, Timothy Reissman, Megan E. Reissman and Allison L. Kinney

Sensors 2022, 22(16), 6154; https://doi.org/10.3390/s22166154 - 17 Aug 2022

Cited by 5 | Viewed by 1817

Abstract

To improve exoskeleton designs, it is crucial to understand the effects of the placement of such added mass on a broad spectrum of users. Most prior studies on the effects of added mass on gait have analyzed young adults using discrete point analysis. This study quantifies the changes in gait characteristics of young and middle-aged adults in response to added mass across the whole gait cycle using statistical parametric mapping. Fourteen middle-aged and fourteen younger adults walked during 60 s treadmill trials under nine different loading conditions. The conditions represented full-factorial combinations of low (+3.6 lb), medium (+5.4 lb), and high (+10.8 lb) mass amounts at the thighs and pelvis. Joint kinematics, kinetics and muscle activations were evaluated. The young and middle-aged adults had different responses to added mass. Under pelvis loading, middle-aged adults did not adopt the same kinematic responses as younger adults. With thigh loading, middle-aged adults generally increased knee joint muscle activity around heel strike, which could have a negative impact on joint loading. Overall, as age may impact the user’s response to an exoskeleton, designers should aim to include sensors to directly monitor user response and adaptive control approaches that account for these differences. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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19 pages, 2998 KiB

Open AccessArticle

Evaluation of Spatiotemporal Patterns of the Spinal Muscle Coordination Output during Walking in the Exoskeleton

by Dmitry S. Zhvansky, Francesca Sylos-Labini, Arthur Dewolf, Germana Cappellini, Andrea d’Avella, Francesco Lacquaniti and Yury Ivanenko

Sensors 2022, 22(15), 5708; https://doi.org/10.3390/s22155708 - 30 Jul 2022

Cited by 9 | Viewed by 1985

Abstract

Recent advances in the performance and evaluation of walking in exoskeletons use various assessments based on kinematic/kinetic measurements. While such variables provide general characteristics of gait performance, only limited conclusions can be made about the neural control strategies. Moreover, some kinematic or kinetic parameters are a consequence of the control implemented on the exoskeleton. Therefore, standard indicators based on kinematic variables have limitations and need to be complemented by performance measures of muscle coordination and control strategy. Knowledge about what happens at the spinal cord output level might also be critical for rehabilitation since an abnormal spatiotemporal integration of activity in specific spinal segments may result in a risk for abnormalities in gait recovery. Here we present the PEPATO software, which is a benchmarking solution to assess changes in the spinal locomotor output during walking in the exoskeleton with respect to reference data on normal walking. In particular, functional and structural changes at the spinal cord level can be mapped into muscle synergies and spinal maps of motoneuron activity. A user-friendly software interface guides the user through several data processing steps leading to a set of performance indicators as output. We present an example of the usage of this software for evaluating walking in an unloading exoskeleton that allows a person to step in simulated reduced (the Moon’s) gravity. By analyzing the EMG activity from lower limb muscles, the algorithms detected several performance indicators demonstrating differential adaptation (shifts in the center of activity, prolonged activation) of specific muscle activation modules and spinal motor pools and increased coactivation of lumbar and sacral segments. The software is integrated at EUROBENCH facilities to benchmark the performance of walking in the exoskeleton from the point of view of changes in the spinal locomotor output. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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10 pages, 2788 KiB

Open AccessArticle

Kinematic Analysis of Exoskeleton-Assisted Community Ambulation: An Observational Study in Outdoor Real-Life Scenarios

by Michela Goffredo, Paola Romano, Francesco Infarinato, Matteo Cioeta, Marco Franceschini, Daniele Galafate, Rebecca Iacopini, Sanaz Pournajaf and Marco Ottaviani

Sensors 2022, 22(12), 4533; https://doi.org/10.3390/s22124533 - 16 Jun 2022

Cited by 1 | Viewed by 2648

Abstract

(1) Background: In neurorehabilitation, Wearable Powered Exoskeletons (WPEs) enable intensive gait training even in individuals who are unable to maintain an upright position. The importance of WPEs is not only related to their impact on walking recovery, but also to the possibility of using them as assistive technology; however, WPE-assisted community ambulation has rarely been studied in terms of walking performance in real-life scenarios. (2) Methods: This study proposes the integration of an Inertial Measurement Unit (IMU) system to analyze gait kinematics during real-life outdoor scenarios (regular, irregular terrains, and slopes) by comparing the ecological gait (no-WPE condition) and WPE-assisted gait in five able-bodied volunteers. The temporal parameters of gait and joint angles were calculated from data collected by a network of seven IMUs. (3) Results: The results showed that the WPE-assisted gait had less knee flexion in the stance phase and greater hip flexion in the swing phase. The different scenarios did not change the human–exoskeleton interaction: only the low-speed WPE-assisted gait was characterized by a longer double support phase. (4) Conclusions: The proposed IMU-based gait assessment protocol enabled quantification of the human–exoskeleton interaction in terms of gait kinematics and paved the way for the study of WPE-assisted community ambulation in stroke patients. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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13 pages, 1965 KiB

Open AccessArticle

Force and Torque Characterization in the Actuation of a Walking-Assistance, Cable-Driven Exosuit

by Daniel Rodríguez Jorge, Javier Bermejo García, Ashwin Jayakumar, Rafael Lorente Moreno, Rafael Agujetas Ortiz and Francisco Romero Sánchez

Sensors 2022, 22(11), 4309; https://doi.org/10.3390/s22114309 - 6 Jun 2022

Cited by 8 | Viewed by 2849

Abstract

Soft exosuits stand out when it comes to the development of walking-assistance devices thanks to both their higher degree of wearability, lower weight, and price compared to the bulkier equivalent rigid exoskeletons. In cable-driven exosuits, the acting force is driven by cables from the actuation system to the anchor points; thus, the user’s movement is not restricted by a rigid structure. In this paper, a 3D inverse dynamics model is proposed and integrated with a model for a cable-driven actuation to predict the required motor torque and traction force in cables for a walking-assistance exosuit during gait. Joint torques are to be shared between the user and the exosuit for different design configurations, focusing on both hip and ankle assistance. The model is expected to guide the design of the exosuit regarding aspects such as the location of the anchor points, the cable system design, and the actuation units. An inverse dynamics analysis is performed using gait kinematic data from a public dataset to predict the cable forces and position of the exosuit during gait. The obtained joint reactions and cable forces are compared with those in the literature, and prove the model to be accurate and ready to be implemented in an exosuit control scheme. The results obtained in this study are similar to those found in the literature regarding the walking study itself as well as the forces under which cables operate during gait and the cable position cycle. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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18 pages, 5089 KiB

Open AccessArticle

Development and Evaluation of BenchBalance: A System for Benchmarking Balance Capabilities of Wearable Robots and Their Users

by Cristina Bayón, Gabriel Delgado-Oleas, Leticia Avellar, Francesca Bentivoglio, Francesco Di Tommaso, Nevio L. Tagliamonte, Eduardo Rocon and Edwin H. F. van Asseldonk

Sensors 2022, 22(1), 119; https://doi.org/10.3390/s22010119 - 24 Dec 2021

Cited by 4 | Viewed by 3981

Abstract

Recent advances in the control of overground exoskeletons are being centered on improving balance support and decreasing the reliance on crutches. However, appropriate methods to quantify the stability of these exoskeletons (and their users) are still under development. A reliable and reproducible balance assessment is critical to enrich exoskeletons’ performance and their interaction with humans. In this work, we present the BenchBalance system, which is a benchmarking solution to conduct reproducible balance assessments of exoskeletons and their users. Integrating two key elements, i.e., a hand-held perturbator and a smart garment, BenchBalance is a portable and low-cost system that provides a quantitative assessment related to the reaction and capacity of wearable exoskeletons and their users to respond to controlled external perturbations. A software interface is used to guide the experimenter throughout a predefined protocol of measurable perturbations, taking into account antero-posterior and mediolateral responses. In total, the protocol is composed of sixteen perturbation conditions, which vary in magnitude and location while still controlling their orientation. The data acquired by the interface are classified and saved for a subsequent analysis based on synthetic metrics. In this paper, we present a proof of principle of the BenchBalance system with a healthy user in two scenarios: subject not wearing and subject wearing the H2 lower-limb exoskeleton. After a brief training period, the experimenter was able to provide the manual perturbations of the protocol in a consistent and reproducible way. The balance metrics defined within the BenchBalance framework were able to detect differences in performance depending on the perturbation magnitude, location, and the presence or not of the exoskeleton. The BenchBalance system will be integrated at EUROBENCH facilities to benchmark the balance capabilities of wearable exoskeletons and their users. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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14 pages, 3205 KiB

Open AccessArticle

Optimizing Calibration Procedure to Train a Regression-Based Prediction Model of Actively Generated Lumbar Muscle Moments for Exoskeleton Control

by Ali Tabasi, Maria Lazzaroni, Niels P. Brouwer, Idsart Kingma, Wietse van Dijk, Michiel P. de Looze, Stefano Toxiri, Jesús Ortiz and Jaap H. van Dieën

Sensors 2022, 22(1), 87; https://doi.org/10.3390/s22010087 - 23 Dec 2021

Cited by 3 | Viewed by 3194

Abstract

The risk of low-back pain in manual material handling could potentially be reduced by back-support exoskeletons. Preferably, the level of exoskeleton support relates to the required muscular effort, and therefore should be proportional to the moment generated by trunk muscle activities. To this end, a regression-based prediction model of this moment could be implemented in exoskeleton control. Such a model must be calibrated to each user according to subject-specific musculoskeletal properties and lifting technique variability through several calibration tasks. Given that an extensive calibration limits the practical feasibility of implementing this approach in the workspace, we aimed to optimize the calibration for obtaining appropriate predictive accuracy during work-related tasks, i.e., symmetric lifting from the ground, box stacking, lifting from a shelf, and pulling/pushing. The root-mean-square error (RMSE) of prediction for the extensive calibration was 21.9 nm (9% of peak moment) and increased up to 35.0 nm for limited calibrations. The results suggest that a set of three optimally selected calibration trials suffice to approach the extensive calibration accuracy. An optimal calibration set should cover each extreme of the relevant lifting characteristics, i.e., mass lifted, lifting technique, and lifting velocity. The RMSEs for the optimal calibration sets were below 24.8 nm (10% of peak moment), and not substantially different than that of the extensive calibration. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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19 pages, 1711 KiB

Open AccessReview

Characterization and Evaluation of Human–Exoskeleton Interaction Dynamics: A Review

by Stefano Massardi, David Rodriguez-Cianca, David Pinto-Fernandez, Juan C. Moreno, Matteo Lancini and Diego Torricelli

Sensors 2022, 22(11), 3993; https://doi.org/10.3390/s22113993 - 25 May 2022

Cited by 35 | Viewed by 5315

Abstract

Exoskeletons and exosuits have witnessed unprecedented growth in recent years, especially in the medical and industrial sectors. In order to be successfully integrated into the current society, these devices must comply with several commercialization rules and safety standards. Due to their intrinsic coupling with human limbs, one of the main challenges is to test and prove the quality of physical interaction with humans. However, the study of physical human–exoskeleton interactions (pHEI) has been poorly addressed in the literature. Understanding and identifying the technological ways to assess pHEI is necessary for the future acceptance and large-scale use of these devices. The harmonization of these evaluation processes represents a key factor in building a still missing accepted framework to inform human–device contact safety. In this review, we identify, analyze, and discuss the metrics, testing procedures, and measurement devices used to assess pHEI in the last ten years. Furthermore, we discuss the role of pHEI in safety contact evaluation. We found a very heterogeneous panorama in terms of sensors and testing methods, which are still far from considering realistic conditions and use-cases. We identified the main gaps and drawbacks of current approaches, pointing towards a number of promising research directions. This review aspires to help the wearable robotics community find agreements on interaction quality and safety assessment testing procedures. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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Other

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40 pages, 1560 KiB

Open AccessSystematic Review

Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review

by Tobias Moeller, Felix Moehler, Janina Krell-Roesch, Miha Dežman, Charlotte Marquardt, Tamim Asfour, Thorsten Stein and Alexander Woll

Sensors 2023, 23(6), 3032; https://doi.org/10.3390/s23063032 - 10 Mar 2023

Cited by 8 | Viewed by 3441

Abstract

Exoskeletons are a promising tool to support individuals with a decreased level of motor performance. Due to their built-in sensors, exoskeletons offer the possibility of continuously recording and assessing user data, for example, related to motor performance. The aim of this article is to provide an overview of studies that rely on using exoskeletons to measure motor performance. Therefore, we conducted a systematic literature review, following the PRISMA Statement guidelines. A total of 49 studies using lower limb exoskeletons for the assessment of human motor performance were included. Of these, 19 studies were validity studies, and six were reliability studies. We found 33 different exoskeletons; seven can be considered stationary, and 26 were mobile exoskeletons. The majority of the studies measured parameters such as range of motion, muscle strength, gait parameters, spasticity, and proprioception. We conclude that exoskeletons can be used to measure a wide range of motor performance parameters through built-in sensors, and seem to be more objective and specific than manual test procedures. However, since these parameters are usually estimated from built-in sensor data, the quality and specificity of an exoskeleton to assess certain motor performance parameters must be examined before an exoskeleton can be used, for example, in a research or clinical setting. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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18 pages, 363 KiB

Open AccessSystematic Review

A Systematic Review of Sensor Fusion Methods Using Peripheral Bio-Signals for Human Intention Decoding

by Anany Dwivedi, Helen Groll and Philipp Beckerle

Sensors 2022, 22(17), 6319; https://doi.org/10.3390/s22176319 - 23 Aug 2022

Cited by 9 | Viewed by 2974

Abstract

Humans learn about the environment by interacting with it. With an increasing use of computer and virtual applications as well as robotic and prosthetic devices, there is a need for intuitive interfaces that allow the user to have an embodied interaction with the devices they are controlling. Muscle–machine interfaces can provide an intuitive solution by decoding human intentions utilizing myoelectric activations. There are several different methods that can be utilized to develop MuMIs, such as electromyography, ultrasonography, mechanomyography, and near-infrared spectroscopy. In this paper, we analyze the advantages and disadvantages of different myography methods by reviewing myography fusion methods. In a systematic review following the PRISMA guidelines, we identify and analyze studies that employ the fusion of different sensors and myography techniques, while also considering interface wearability. We also explore the properties of different fusion techniques in decoding user intentions. The fusion of electromyography, ultrasonography, mechanomyography, and near-infrared spectroscopy as well as other sensing such as inertial measurement units and optical sensing methods has been of continuous interest over the last decade with the main focus decoding the user intention for the upper limb. From the systematic review, it can be concluded that the fusion of two or more myography methods leads to a better performance for the decoding of a user’s intention. Furthermore, promising sensor fusion techniques for different applications were also identified based on the existing literature. Full article

(This article belongs to the Special Issue Quantifying, Understanding and Improving Human-Exoskeleton Interaction)

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