2017
DOI: 10.1051/matecconf/201713500061
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Pneumatic Muscles Actuated Lower-Limb Orthosis Model Verification with Actual Human Muscle Activation Patterns

Abstract: Abstract.A review study was conducted on existing lower-limb orthosis systems for rehabilitation which implemented pneumatic muscle type of actuators with the aim to clarify the current and on-going research in this field. The implementation of pneumatic artificial muscle will play an important role for the development of the advanced robotic system. In this research a derivation model for the antagonistic mono-and bi-articular muscles using pneumatic artificial muscles of a lower limb orthosis will be verifie… Show more

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Cited by 2 publications
(1 citation statement)
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“…For example, in [19][20][21], lower limb exoskeletons are controlled based on the use of electromyography (EMG) signals to assist the patient according to an intention detection. e controllers used in these studies are proportional to the EMG signals, but the muscles working around the ankle joint could work in synergy by cocontracting at speci c moments of the gait cycle, as reported in [22], thus requiring to consider more complex controllers for EMG-based applications. However, in practice, EMG-based approaches are usually very complex to implement as EMG signals are largely a ected by sensor position, skin impedance changes, and muscular fatigue [23].…”
Section: Introductionmentioning
confidence: 99%
“…For example, in [19][20][21], lower limb exoskeletons are controlled based on the use of electromyography (EMG) signals to assist the patient according to an intention detection. e controllers used in these studies are proportional to the EMG signals, but the muscles working around the ankle joint could work in synergy by cocontracting at speci c moments of the gait cycle, as reported in [22], thus requiring to consider more complex controllers for EMG-based applications. However, in practice, EMG-based approaches are usually very complex to implement as EMG signals are largely a ected by sensor position, skin impedance changes, and muscular fatigue [23].…”
Section: Introductionmentioning
confidence: 99%