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Gutierrez-Farewik, ElenaORCID iD iconorcid.org/0000-0001-5417-5939
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Publications (10 of 113) Show all publications
Gutierrez-Farewik, E. & Zhang, X. (2025). Biplanar Ankle Assistance for Dropfoot with a Human-in-the-Loop Optimization Approach. In: Pons; J.L.; Tornero; J.; Akay; M (Ed.), Converging Clinical and Engineering Research on Neurorehabilitation V. ICNR 2024. Biosystems & Biorobotics, vol 31: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1. Paper presented at Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain (pp. 246-250). Springer Nature, 31
Open this publication in new window or tab >>Biplanar Ankle Assistance for Dropfoot with a Human-in-the-Loop Optimization Approach
2025 (English)In: Converging Clinical and Engineering Research on Neurorehabilitation V. ICNR 2024. Biosystems & Biorobotics, vol 31: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1 / [ed] Pons; J.L.; Tornero; J.; Akay; M, Springer Nature , 2025, Vol. 31, p. 246-250Conference paper, Published paper (Refereed)
Abstract [en]

Wearable robotic exoskeletons are frequently explored for their efficacy in rehabilitation and in assistance in daily activities in people with motor disorders, yet relatively few have convincing evidence for use. Here we describe a cable-driven ankle exoskeleton that provides assistance to the ankle in sagittal and frontal planes simultaneously, aimed for persons with dropfoot and excessive inversion after e.g. stroke. In this study, we propose a multi-objective human-in-the-loop optimization that adjusts exoskeleton control parameters to improve two independent gait quality measures, specifically foot segment kinematics and step length symmetry. We illustrate how the identified solutions represent a balance between the two objectives.

Place, publisher, year, edition, pages
Springer Nature, 2025
National Category
Robotics and automation
Identifiers
urn:nbn:se:kth:diva-361727 (URN)10.1007/978-3-031-77588-8_49 (DOI)2-s2.0-86000655479 (Scopus ID)
Conference
Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain
Note

Part of ISBN 9783031775901, 9783031775888

QC 20250328

Available from: 2025-03-27 Created: 2025-03-27 Last updated: 2025-03-28Bibliographically approved
Zhang, L., Hu, Y., Zhang, M., Wang, R., Gutierrez-Farewik, E. & Ang, W. T. (2025). Editorial: Advanced technology for human movement rehabilitation and enhancement. Frontiers in Neuroscience, 19, Article ID 1581451.
Open this publication in new window or tab >>Editorial: Advanced technology for human movement rehabilitation and enhancement
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2025 (English)In: Frontiers in Neuroscience, ISSN 1662-4548, E-ISSN 1662-453X, Vol. 19, article id 1581451Article in journal, Editorial material (Other academic) Published
Keywords
advancing rehabilitation strategies, artificial intelligence, neuromuscular diseases, virtual reality, wearable exoskeletons
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-362490 (URN)10.3389/fnins.2025.1581451 (DOI)001462972800001 ()40206412 (PubMedID)2-s2.0-105002163319 (Scopus ID)
Note

QC 20250422

Available from: 2025-04-16 Created: 2025-04-16 Last updated: 2025-05-22Bibliographically approved
Gutierrez-Farewik, E., Luis, I. & Afschrift, M. (2025). Optimal Lower Limb Exoskeleton Assistance in Walking Predicted by Musculoskeletal Simulation. In: Pons, J.L., Tornero, J., Akay, M. (Ed.), Converging Clinical and Engineering Research on Neurorehabilitation V. ICNR 2024. Biosystems & Biorobotics, vol 31: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1. Paper presented at 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain (pp. 169-173). Springer Nature, 31
Open this publication in new window or tab >>Optimal Lower Limb Exoskeleton Assistance in Walking Predicted by Musculoskeletal Simulation
2025 (English)In: Converging Clinical and Engineering Research on Neurorehabilitation V. ICNR 2024. Biosystems & Biorobotics, vol 31: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain - Volume 1 / [ed] Pons, J.L., Tornero, J., Akay, M., Springer Nature , 2025, Vol. 31, p. 169-173Conference paper, Published paper (Refereed)
Abstract [en]

Breakthroughs in assistive exoskeletons have occurred in the recent decade; both active and passive devices that provide partial joint moments in the lower limbs have reduced metabolic costs during walking by assisting muscle action. Musculoskeletal simulation is highly useful in describing the interaction between assistive moments, muscle-tendon mechanics, and walking energetics. In this study, we computed optimal assistive moments in ankle plantarflexion and hip flexion that produce minimal muscle activations during walking, described the muscle energetics, and estimated the potential reduction in metabolic cost. We described with analyses of muscle-tendon mechanics and motor control how reductions in muscle activation do not always result in metabolic cost savings.

Place, publisher, year, edition, pages
Springer Nature, 2025
National Category
Robotics and automation Physiology and Anatomy Physiotherapy
Identifiers
urn:nbn:se:kth:diva-361726 (URN)10.1007/978-3-031-77588-8_33 (DOI)2-s2.0-86000518527 (Scopus ID)
Conference
6th International Conference on Neurorehabilitation (ICNR 2024), November 5–8, 2024, La Granja, Spain
Note

Part of ISBN 9783031775901, 9783031775888

QC 20250328

Available from: 2025-03-27 Created: 2025-03-27 Last updated: 2025-03-28Bibliographically approved
Forslund, E. B., Truong, M. T., Wang, R., Seiger, Å. & Gutierrez-Farewik, E. (2024). A Protocol for Comprehensive Analysis of Gait in Individuals with Incomplete Spinal Cord Injury. Methods and Protocols, 7(3), Article ID 39.
Open this publication in new window or tab >>A Protocol for Comprehensive Analysis of Gait in Individuals with Incomplete Spinal Cord Injury
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2024 (English)In: Methods and Protocols, ISSN 2409-9279, Vol. 7, no 3, article id 39Article in journal (Refereed) Published
Abstract [en]

This is a protocol for comprehensive analysis of gait and affecting factors in individuals with incomplete paraplegia due to spinal cord injury (SCI). A SCI is a devastating event affecting both sensory and motor functions. Due to better care, the SCI population is changing, with a greater proportion retaining impaired ambulatory function. Optimizing ambulatory function after SCI remains challenging. To investigate factors influencing optimal ambulation, a multi-professional research project was grounded with expertise from clinical rehabilitation, neurophysiology, and biomechanical engineering from Karolinska Institutet, the Spinalis Unit at Aleris Rehab Station (Sweden's largest center for specialized neurorehabilitation), and the Promobilia MoveAbility Lab at KTH Royal Institute of Technology. Ambulatory adults with paraplegia will be consecutively invited to participate. Muscle strength, sensitivity, and spasticity will be assessed, and energy expenditure, 3D movements, and muscle function (EMG) during gait and submaximal contractions will be analyzed. Innovative computational modeling and data-driven analyses will be performed, including the identification of clusters of similar movement patterns among the heterogeneous population and analyses that study the link between complex sensorimotor function and movement performance. These results may help optimize ambulatory function for persons with SCI and decrease the risk of secondary conditions during gait with a life-long perspective.

Place, publisher, year, edition, pages
MDPI AG, 2024
Keywords
paraplegia, gait, ambulation, movement analysis, machine learning, EMG, predictive modeling
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:kth:diva-350118 (URN)10.3390/mps7030039 (DOI)001256315700001 ()38804333 (PubMedID)2-s2.0-85197173750 (Scopus ID)
Note

QC 20240708

Available from: 2024-07-08 Created: 2024-07-08 Last updated: 2024-07-08Bibliographically approved
Luis, I., Afschrift, M. & Gutierrez Farewik, E. (2024). Experiment-guided tuning of muscle–tendon parameters to estimate muscle fiber lengths and passive forces. Scientific Reports, 14(1), Article ID 14652.
Open this publication in new window or tab >>Experiment-guided tuning of muscle–tendon parameters to estimate muscle fiber lengths and passive forces
2024 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 14, no 1, article id 14652Article in journal (Refereed) Published
Abstract [en]

The workflow to simulate motion with recorded data usually starts with selecting a generic musculoskeletal model and scaling it to represent subject-specific characteristics. Simulating muscle dynamics with muscle–tendon parameters computed from existing scaling methods in literature, however, yields some inconsistencies compared to measurable outcomes. For instance, simulating fiber lengths and muscle excitations during walking with linearly scaled parameters does not resemble established patterns in the literature. This study presents a tool that leverages reported in vivo experimental observations to tune muscle–tendon parameters and evaluates their influence in estimating muscle excitations and metabolic costs during walking. From a scaled generic musculoskeletal model, we tuned optimal fiber length, tendon slack length, and tendon stiffness to match reported fiber lengths from ultrasound imaging and muscle passive force–length relationships to match reported in vivo joint moment–angle relationships. With tuned parameters, muscle contracted more isometrically, and soleus’s operating range was better estimated than with linearly scaled parameters. Also, with tuned parameters, on/off timing of nearly all muscles’ excitations in the model agreed with reported electromyographic signals, and metabolic rate trajectories varied significantly throughout the gait cycle compared to linearly scaled parameters. Our tool, freely available online, can customize muscle–tendon parameters easily and be adapted to incorporate more experimental data.

Place, publisher, year, edition, pages
Springer Nature, 2024
Keywords
Metabolic energy cost, Muscle fiber length, Muscle–tendon mechanics, Musculoskeletal parameter, Scaling method
National Category
Applied Mechanics
Identifiers
urn:nbn:se:kth:diva-349928 (URN)10.1038/s41598-024-65183-1 (DOI)001255006800034 ()38918538 (PubMedID)2-s2.0-85196777490 (Scopus ID)
Note

QC 20240708

Available from: 2024-07-03 Created: 2024-07-03 Last updated: 2024-07-15Bibliographically approved
Luis, I., Afschrift, M., De Groote, F. & Gutierrez-Farewik, E. M. (2024). Insights into muscle metabolic energetics: modelling muscle-tendon mechanics and metabolic rates during walking across speeds. PloS Computational Biology, 20(9), Article ID e1012411.
Open this publication in new window or tab >>Insights into muscle metabolic energetics: modelling muscle-tendon mechanics and metabolic rates during walking across speeds
2024 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 20, no 9, article id e1012411Article in journal (Refereed) Published
Abstract [en]

The metabolic energy rate of individual muscles is impossible to measure without invasive procedures. Prior studies have produced models to predict metabolic rates based on experimental observations of isolated muscle contraction from various species. Such models can provide reliable predictions of metabolic rates in humans if muscle properties and control are accurately modeled. This study aimed to examine how muscle-tendon model individualization and metabolic energy models influenced estimation of muscle-tendon states and time-series metabolic rates, to evaluate the agreement with empirical data, and to provide predictions of the metabolic rate of muscle groups and gait phases across walking speeds. Three-dimensional musculoskeletal simulations with prescribed kinematics and dynamics were performed. An optimal control formulation was used to compute muscle-tendon states with four levels of individualization, ranging from a scaled generic model and muscle controls based on minimal activations, inclusion of calibrated muscle passive forces, personalization of Achilles and quadriceps tendon stiffnesses, to finally informing muscle controls with electromyography. We computed metabolic rates based on existing models. Simulations with calibrated passive forces and personalized tendon stiffness most accurately estimate muscle excitations and fiber lengths. Interestingly, the inclusion of electromyography did not improve our estimates. The whole-body average metabolic cost was better estimated with a subset of metabolic energy models. We estimated metabolic rate peaks near early stance, pre-swing, and initial swing at all walking speeds. Plantarflexors accounted for the highest cost among muscle groups at the preferred speed and were similar to the cost of hip adductors and abductors combined. Also, the swing phase accounted for slightly more than one-quarter of the total cost in a gait cycle, and its relative cost decreased with walking speed. Our prediction might inform the design of assistive devices and rehabilitation treatment. The code and experimental data are available online.

Place, publisher, year, edition, pages
Public Library of Science (PLoS), 2024
National Category
Physiotherapy
Identifiers
urn:nbn:se:kth:diva-353917 (URN)10.1371/journal.pcbi.1012411 (DOI)001312585800002 ()39269982 (PubMedID)2-s2.0-85203879764 (Scopus ID)
Note

QC 20240927

Available from: 2024-09-25 Created: 2024-09-25 Last updated: 2025-02-11Bibliographically approved
Zhang, X., Liu, Y., Wang, R. & Gutierrez-Farewik, E. (2024). Soft ankle exoskeleton to counteract dropfoot and excessive inversion. Frontiers in Neurorobotics, 18, Article ID 1372763.
Open this publication in new window or tab >>Soft ankle exoskeleton to counteract dropfoot and excessive inversion
2024 (English)In: Frontiers in Neurorobotics, ISSN 1662-5218, Vol. 18, article id 1372763Article in journal (Refereed) Published
Abstract [en]

Introduction Wearable exoskeletons are emerging technologies for providing movement assistance and rehabilitation for people with motor disorders. In this study, we focus on the specific gait pathology dropfoot, which is common after a stroke. Dropfoot makes it difficult to achieve foot clearance during swing and heel contact at early stance and often necessitates compensatory movements. Methods We developed a soft ankle exoskeleton consisting of actuation and transmission systems to assist two degrees of freedom simultaneously: dorsiflexion and eversion, then performed several proof-of-concept experiments on non-disabled persons. The actuation system consists of two motors worn on a waist belt. The transmission system provides assistive force to the medial and lateral sides of the forefoot via Bowden cables. The coupling design enables variable assistance of dorsiflexion and inversion at the same time, and a force-free controller is proposed to compensate for device resistance. We first evaluated the performance of the exoskeleton in three seated movement tests: assisting dorsiflexion and eversion, controlling plantarflexion, and compensating for device resistance, then during walking tests. In all proof-of-concept experiments, dropfoot tendency was simulated by fastening a weight to the shoe over the lateral forefoot. Results In the first two seated tests, errors between the target and the achieved ankle joint angles in two planes were low; errors of <1.5 degrees were achieved in assisting dorsiflexion and/or controlling plantarflexion and of <1.4 degrees in assisting ankle eversion. The force-free controller in test three significantly compensated for the device resistance during ankle joint plantarflexion. In the gait tests, the exoskeleton was able to normalize ankle joint and foot segment kinematics, specifically foot inclination angle and ankle inversion angle at initial contact and ankle angle and clearance height during swing. Discussion Our findings support the feasibility of the new ankle exoskeleton design in assisting two degrees of freedom at the ankle simultaneously and show its potential to assist people with dropfoot and excessive inversion.

Place, publisher, year, edition, pages
Frontiers Media SA, 2024
Keywords
assistive device, biomechanics, gait impairment, gait analysis, soft robotics
National Category
Physiotherapy Mechanical Engineering
Identifiers
urn:nbn:se:kth:diva-353000 (URN)10.3389/fnbot.2024.1372763 (DOI)001304932800001 ()39234442 (PubMedID)2-s2.0-85203189202 (Scopus ID)
Note

QC 20240912

Available from: 2024-09-12 Created: 2024-09-12 Last updated: 2025-05-08Bibliographically approved
Luis, I., Afschrift, M. & Gutierrez-Farewik, E. M. (2024). Springs vs. motors: ideal assistance in the lower limbs during walking at different speeds. PloS Computational Biology, 20(9), Article ID e1011837.
Open this publication in new window or tab >>Springs vs. motors: ideal assistance in the lower limbs during walking at different speeds
2024 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 20, no 9, article id e1011837Article in journal (Refereed) Published
Abstract [en]

Recent years have witnessed breakthroughs in assistive exoskeletons; both passive and active devices have reduced metabolic costs near preferred walking speed by assisting muscle actions. Metabolic reductions at multiple speeds should thus also be attainable. Musculoskeletal simulation can potentially predict the interaction between assistive moments, muscle-tendon mechanics, and walking energetics. In this study, we simulated devices’ optimal assistive moments based on minimal muscle activations during walking with prescribed kinematics and dynamics. We used a generic musculoskeletal model with tuned muscle-tendon parameters and computed metabolic rates from muscle actions. We then simulated walking across multiple speeds and with two ideal actuation modes–motor-based and spring-based–to assist ankle plantarflexion, knee extension, hip flexion, and hip abduction and compared computed metabolic rates. We found that both actuation modes considerably reduced physiological joint moments but did not always reduce metabolic rates. Compared to unassisted conditions, motor-based ankle plantarflexion and hip flexion assistance reduced metabolic rates, and this effect was more pronounced as walking speed increased. Spring-based hip flexion and abduction assistance increased metabolic rates at some walking speeds despite a moderate decrease in some muscle activations. Both modes of knee extension assistance reduced metabolic rates to a small extent, even though the actuation contributed with practically the entire net knee extension moment during stance. Motor-based hip abduction assistance reduced metabolic rates more than spring-based assistance, though this reduction was relatively small. Our study also suggests that an assistive strategy based on minimal muscle activations might result in a suboptimal reduction of metabolic rates. Future work should experimentally validate the effects of assistive moments and refine modeling assumptions accordingly. Our computational workflow is freely available online.

Place, publisher, year, edition, pages
Public Library of Science (PLoS), 2024
National Category
Robotics and automation
Identifiers
urn:nbn:se:kth:diva-353422 (URN)10.1371/journal.pcbi.1011837 (DOI)001307022400001 ()39231195 (PubMedID)2-s2.0-85203499208 (Scopus ID)
Note

Not duplicate with DiVA 1833101

QC 20240927

Available from: 2024-09-19 Created: 2024-09-19 Last updated: 2025-02-09Bibliographically approved
Liu, Y., Wan, Z.-Y., Wang, R. & Gutierrez-Farewik, E. (2023). A method of detecting human movement intentions in real environments. In: 2023 international conference on rehabilitation robotics, ICORR: . Paper presented at International Conference on Rehabilitation Robotics (ICORR), SEP 24-28, 2023, Singapore, Singapore. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>A method of detecting human movement intentions in real environments
2023 (English)In: 2023 international conference on rehabilitation robotics, ICORR, Institute of Electrical and Electronics Engineers (IEEE) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Accurate and timely movement intention detection can facilitate exoskeleton control during transitions between different locomotion modes. Detecting movement intentions in real environments remains a challenge due to unavoidable environmental uncertainties. False movement intention detection may also induce risks of falling and general danger for exoskeleton users. To this end, in this study, we developed a method for detecting human movement intentions in real environments. The proposed method is capable of online self-correcting by implementing a decision fusion layer. Gaze data from an eye tracker and inertial measurement unit (IMU) signals were fused at the feature extraction level and used to predict movement intentions using 2 different methods. Images from the scene camera embedded on the eye tracker were used to identify terrains using a convolutional neural network. The decision fusion was made based on the predicted movement intentions and identified terrains. Four able-bodied participants wearing the eye tracker and 7 IMU sensors took part in the experiments to complete the tasks of level ground walking, ramp ascending, ramp descending, stairs ascending, and stair descending. The recorded experimental data were used to test the feasibility of the proposed method. An overall accuracy of 93.4% was achieved when both feature fusion and decision fusion were used. Fusing gaze data with IMU signals improved the prediction accuracy.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Series
International Conference on Rehabilitation Robotics ICORR, ISSN 1945-7898
Keywords
Robotic exoskeletons, movement intention prediction, eye tracker, wearable sensor
National Category
Computer graphics and computer vision
Identifiers
urn:nbn:se:kth:diva-341996 (URN)10.1109/ICORR58425.2023.10304774 (DOI)001103260000102 ()37941205 (PubMedID)2-s2.0-85176437253 (Scopus ID)
Conference
International Conference on Rehabilitation Robotics (ICORR), SEP 24-28, 2023, Singapore, Singapore
Note

Part of proceedings ISBN: 979-8-3503-4275-8

QC 20240109

Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2025-02-07Bibliographically approved
Zhang, L., Soselia, D., Wang, R. & Gutierrez-Farewik, E. (2023). Estimation of Joint Torque by EMG-Driven Neuromusculoskeletal Models and LSTM Networks. IEEE transactions on neural systems and rehabilitation engineering, 31, 3722-3731
Open this publication in new window or tab >>Estimation of Joint Torque by EMG-Driven Neuromusculoskeletal Models and LSTM Networks
2023 (English)In: IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320, E-ISSN 1558-0210, Vol. 31, p. 3722-3731Article in journal (Refereed) Published
Abstract [en]

Accurately predicting joint torque using wearable sensors is crucial for designing assist-as-needed exoskeleton controllers to assist muscle-generated torque and ensure successful task performance. In this paper, we estimated ankle dorsiflexion/plantarflexion, knee flexion/extension, hip flexion/extension, and hip abduction/adduction torques from electromyography (EMG) and kinematics during daily activities using neuromusculoskeletal (NMS) models and long short-term memory (LSTM) networks. The joint torque ground truth for model calibrating and training was obtained through inverse dynamics of captured motion data. A cluster approach that grouped movements based on characteristic similarity was implemented, and its ability to improve the estimation accuracy of both NMS and LSTM models was evaluated. We compared torque estimation accuracy of NMS and LSTM models in three cases: Pooled, Individual, and Clustered models. Pooled models used data from all 10 movements to calibrate or train one model, Individual models used data from each individual movement, and Clustered models used data from each cluster. Individual, Clustered and Pooled LSTM models all had relatively high joint torque estimation accuracy. Individual and Clustered NMS models had similarly good estimation performance whereas the Pooled model may be too generic to satisfy all movement patterns. While the cluster approach improved the estimation accuracy in NMS models in some movements, it made relatively little difference in the LSTM neural networks, which already had high estimation accuracy. Our study provides practical implications for designing assist-as-needed exoskeleton controllers by offering guidelines for selecting the appropriate model for different scenarios, and has potential to enhance the functionality of wearable exoskeletons and improve rehabilitation and assistance for individuals with motor disorders.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Torque, Muscles, Predictive models, Electromyography, Estimation, Dynamics, Computational modeling, Neural networks, joint torque prediction, neuromusculoskeletal modeling, cluster analysis, data-driven biomechanical models
National Category
Bioinformatics and Computational Biology
Identifiers
urn:nbn:se:kth:diva-338181 (URN)10.1109/TNSRE.2023.3315373 (DOI)001071744200003 ()37708013 (PubMedID)2-s2.0-85171796999 (Scopus ID)
Note

QC 20231016

Available from: 2023-10-16 Created: 2023-10-16 Last updated: 2025-02-07Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-5417-5939

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