Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces
Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this pap...
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Published in | IEEE transactions on neural systems and rehabilitation engineering Vol. 25; no. 9; pp. 1612 - 1621 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.09.2017
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Subjects | |
Online Access | Get full text |
ISSN | 1534-4320 1558-0210 1558-0210 |
DOI | 10.1109/TNSRE.2017.2683488 |
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Abstract | Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body. |
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AbstractList | Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body.Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body. Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body. Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this study we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed 5 healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only 3 subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this study focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body. |
Author | Saxby, David J. Modenese, Luca Ceseracciu, Elena Lloyd, David G. Pizzolato, Claudio Reggiani, Monica |
Author_xml | – sequence: 1 givenname: Claudio orcidid: 0000-0002-0292-2776 surname: Pizzolato fullname: Pizzolato, Claudio email: c.pizzolato@griffith.edu.au organization: School of Allied Health Sciences, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia – sequence: 2 givenname: Monica surname: Reggiani fullname: Reggiani, Monica organization: Department of Management and Engineering, University of Padova, Vicenza, Italy – sequence: 3 givenname: David J. surname: Saxby fullname: Saxby, David J. organization: School of Allied Health Sciences, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia – sequence: 4 givenname: Elena surname: Ceseracciu fullname: Ceseracciu, Elena organization: Department of Management and Engineering, University of Padova, Vicenza, Italy – sequence: 5 givenname: Luca orcidid: 0000-0003-1402-5359 surname: Modenese fullname: Modenese, Luca organization: Department of Mechanical Engineering, INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, U.K – sequence: 6 givenname: David G. surname: Lloyd fullname: Lloyd, David G. organization: School of Allied Health Sciences, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28436878$$D View this record in MEDLINE/PubMed |
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Snippet | Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used... Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used... |
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SubjectTerms | Adult Biofeedback, Psychology - methods Biological control systems Biological system modeling Computer Simulation Computer Systems contact force electromyography Electromyography - methods Force Gait Gait Disorders, Neurologic - physiopathology Gait Disorders, Neurologic - rehabilitation Gait modification Humans Knee knee joint Knee Joint - physiopathology Legged locomotion Male Models, Biological Muscles real-time biofeedback Real-time systems Stress, Mechanical Therapy, Computer-Assisted - methods Treatment Outcome |
Title | Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces |
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