Publications by authors named "Victor H Duenas"

Article Synopsis
  • The study aimed to evaluate the validity of the Fitbit Inspire 3 for tracking daily steps in adults with transtibial amputation, using activPAL 3 accelerometers as a benchmark.
  • 79 participants wore both devices for a week, revealing that the Fitbit averaged significantly higher daily step counts (5,768) compared to the activPAL (4,674), despite a high correlation (0.93) between the two.
  • The findings indicate that while the two devices both track physical activity effectively, they are not interchangeable due to significant differences in step counts, though they may rank individuals similarly based on their results.
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Restoring and improving the ability to walk is a top priority for individuals with movement impairments due to neurological injuries. Powered exoskeletons coupled with functional electrical stimulation (FES), called hybrid exoskeletons, exploit the benefits of activating muscles and robotic assistance for locomotion. In this paper, a cable-driven lower-limb exoskeleton is integrated with FES for treadmill walking at a constant speed.

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Objective: The objective of this paper was to develop and test a novel control algorithm that enables stroke survivors to pedal a cycle in a desired cadence range despite varying levels of functional abilities after stroke.

Methods: A novel algorithm was developed which automatically adjusts 1) the intensity of functional electrical stimulation (FES) delivered to the leg muscles, and 2) the current delivered to an electric motor. The algorithm automatically switches between assistive, uncontrolled, and resistive modes to accommodate for differences in functional impairment, based on the mismatch between the desired and actual cadence.

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For an individual suffering from a neurological condition, such as spinal cord injury, traumatic brain injury, or stroke, motorized functional electrical stimulation (FES) cycling is a rehabilitation strategy, which offers numerous health benefits. Motorized FES cycling is an example of physical human-robot interaction in which both systems must be controlled; the human is actuated by applying neuromuscular electrical stimulation to the large leg muscle groups, and the cycle is actuated through its onboard electric motor. While the rider is stimulated using a robust sliding-mode controller, the cycle utilizes an admittance controller to preserve rider safety.

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Closed-loop control of functional electrical stimulation coupled with motorized assistance to induce cycling is a rehabilitative strategy that can improve the mobility of people with neurological conditions (NCs). However, robust control methods, which are currently pervasive in the cycling literature, have limited effectiveness due to the use of high stimulation intensity leading to accelerated fatigue during cycling protocols. This paper examines the design of a distributed repetitive learning controller (RLC) that commands an independent learning feedforward term to each of the six stimulated lower-limb muscle groups and an electric motor during the tracking of a periodic cadence trajectory.

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Two common rehabilitation therapies for individuals possessing neurological conditions are functional electrical stimulation (FES) and robotic assistance. This paper focuses on combining the two rehabilitation strategies for use on the biceps brachii muscle group. FES is used to elicit muscle contractions to actuate the forearm and a rehabilitation robot is used to challenge the muscle group in its efforts.

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