Publications by authors named "Strahinja Dosen"

In a recently developed associative rehabilitative brain computer interface system, electroencephalography is used to identify the most active phase of the motor cortex during attempted movement and deliver precisely timed peripheral stimulation during training. This approach has been demonstrated to facilitate corticospinal excitability and functional recovery in patients with lower limb weakness following stroke. The current study expands those findings by investigating changes in corticospinal excitability following the associative BCI intervention in post-stroke patients with upper limb weakness.

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Article Synopsis
  • This study evaluates a new electrotactile interface designed to enhance interaction with a Supernumerary Robotic Limb (SRL) by providing 3D spatial information through feedback on the user's thigh.
  • Psychometric tests showed that participants successfully distinguished between electrode pads with an average success rate of 62.7% in static conditions, which improved to 88.1% during dynamic target-reaching tasks.
  • The interface demonstrated high-resolution spatial information transmission with an overall success rate of 78.8% in mixed spatial and frequency modulation tasks, indicating potential applications in tactile-based navigation and control systems.
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Article Synopsis
  • * Nine stroke patients participated by performing ankle and knee movements, with an algorithm determining the level of assistance needed for each repetition.
  • * Results showed that patients needed support for a significant percentage of ankle movements (44%) but much less for knee movements (5%), and the fatigue experienced was mild to moderate. The study suggests this method is feasible and encourages future clinical application research.
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Background: Although early rehabilitation is important following a stroke, severely affected patients have limited options for intensive rehabilitation as they are often bedridden. To create a system for early rehabilitation of lower extremities in these patients, we combined the robotic manipulator ROBERT® with electromyography (EMG)-triggered functional electrical stimulation (FES) and developed a novel user-driven Assist-As-Needed (AAN) control. The method is based on a state machine able to detect user movement capability, assessed by the presence of an EMG-trigger and the movement velocity, and provide different levels of assistance as required by the patient (no support, FES only, and simultaneous FES and mechanical assistance).

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Restoring tactile feedback in virtual reality can improve user experience and facilitate the feeling of embodiment. Electrotactile stimulation can be an attractive technology in this context as it is compact and allows for high-resolution spatially distributed stimulation. In the present study, a 32-channel tactile glove worn on the fingertips was used to provide tactile sensations during a virtual version of a rubber hand illusion experiment.

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Background: Lower limb amputation does not affect only physical and psychological functioning but the use of a prosthetic device can also lead to increased cognitive demands. Measuring cognitive load objectively is challenging, and therefore, most studies use questionnaires that are easy to apply but can suffer from subjective bias. Motivated by this, the present study investigated whether a mobile eye tracker can be used to objectively measure cognitive load by monitoring gaze behavior during a set of motor tasks.

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Electrotactile stimulation through matrix electrodes is a promising technology to restore high-resolution tactile feedback in extended reality applications. One of the fundamental tactile effects that should be simulated is the change in the size of the contact between the finger and a virtual object. The present study investigated how participants perceive the increase of stimulation area when stimulating the index finger using static or dynamic (moving) stimuli produced by activating 1 to 6 electrode pads.

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Closed-loop myoelectric prostheses, which combine supplementary sensory feedback and electromyography (EMG) based control, hold the potential to narrow the divide between natural and bionic hands. The use of these devices, however, requires dedicated training. Therefore, it is crucial to develop methods that quantify how users acquire skilled control over their prostheses to effectively monitor skill progression and inform the development of interfaces that optimize this process.

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Background: Restorative Brain-Computer Interfaces (BCI) that combine motor imagery with visual feedback and functional electrical stimulation (FES) may offer much-needed treatment alternatives for patients with severely impaired upper limb (UL) function after a stroke.

Objectives: This study aimed to examine if BCI-based training, combining motor imagery with FES targeting finger/wrist extensors, is more effective in improving severely impaired UL motor function than conventional therapy in the subacute phase after stroke, and if patients with preserved cortical-spinal tract (CST) integrity benefit more from BCI training.

Methods: Forty patients with severe UL paresis (< 13 on Action Research Arm Test (ARAT) were randomized to either a 12-session BCI training as part of their rehabilitation or conventional UL rehabilitation.

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Background: Electrotactile systems are compact interfaces that can be used to convey information through the skin by producing a range of haptic sensations. In many applications, however, the user needs to perceive and interpret haptic stimulation while being engaged in parallel activities. Developing methods that ensure reliable recognition of electrotactile messages despite additional cognitive load is, therefore, an important step for the practical application of electrotactile displays.

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Reliable force control is especially important when using myoelectric upper-limb prostheses as the force defines whether an object will be firmly grasped, damaged, or dropped. It is known from human motor control that the grasping of non-disabled subjects is based on a combination of anticipation and feedback correction. Inspired by this insight, the present study proposes a novel approach to provide artificial sensory feedback to the user of a myoelectric prosthesis using vibrotactile stimulation to facilitate both predictive and corrective processes characteristic of grasping in non-disabled people.

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Surgical neural engineering and human-machine interfacing enable bionic limbs with dexterous control and sensory feedback.

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Electrotactile stimulation can be an attractive technology to restore tactile feedback in different application scenarios (e.g., virtual and augmented reality, tele-manipulation).

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Background: Closing the control loop in myoelectric prostheses by providing artificial somatosensory feedback is recognized as an important goal. However, designing a feedback interface that is effective in realistic conditions is still a challenge. Namely, in some situations, feedback can be redundant, as the information it provides can be readily obtained through hearing or vision (e.

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Background: One of the drawbacks of lower-limb prostheses is that they do not provide explicit somatosensory feedback to their users. Electrotactile stimulation is an attractive technology to restore such feedback because it enables compact solutions with multiple stimulation points. This allows stimulating a larger skin area to provide more information concurrently and modulate parameters spatially as well as in amplitude.

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Bidirectional human-machine interfaces involve commands from the central nervous system to an external device and feedback characterizing device state. Such feedback may be elicited by electrical stimulation of somatosensory nerves, where a task-relevant variable is encoded in stimulation amplitude or frequency. Recently, concurrent modulation in amplitude and frequency (multimodal encoding) was proposed.

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When using EMG biofeedback to control the grasping force of a myoelectric prosthesis, subjects need to activate their muscles and maintain the myoelectric signal within an appropriate interval. However, their performance decreases for higher forces, because the myoelectric signal is more variable for stronger contractions. Therefore, the present study proposes to implement EMG biofeedback using nonlinear mapping, in which EMG intervals of increasing size are mapped to equal-sized intervals of the prosthesis velocity.

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Objective: The bidirectional communication between the user and the prosthesis is an important requirement when developing prosthetic hands. Proprioceptive feedback is fundamental to perceiving prosthesis movement without the need for constant visual attention. We propose a novel solution to encode wrist rotation using a vibromotor array and Gaussian interpolation of vibration intensity.

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Background: Biomechanical gait analyses are typically performed in laboratory settings, and are associated with limitations due to space, marker placement, and tasks that are not representative of the real-world usage of lower limb prostheses. Therefore, the purpose of this study was to investigate the possibility of accurately measuring gait parameters using embedded sensors in a microprocessor-controlled knee joint.

Methods: Ten participants were recruited for this study and equipped with a Genium X3 prosthetic knee joint.

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Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands.

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State-of-the-art myoelectric hand prostheses provide multi-functional control but lack somatosensory feedback. To accommodate the full functionality of a dexterous prosthesis, the artificial sensory feedback needs to convey several degrees of freedom (DoF) simultaneously. However, this is a challenge with current methods as they are characterized by a low information bandwidth.

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This study proposes a bioinspired exotendon routing configuration for a tendon-based mechanism to provide finger flexion and extension that utilizes a single motor to reduce the complexity of the system. The configuration was primarily inspired by the extrinsic muscle-tendon units of the human musculoskeletal system. The function of the intrinsic muscle-tendon units was partially compensated by adding a minor modification to the configuration of the extrinsic units.

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Recording electrical muscle activity using a dense matrix of detection points (high-density electromyography, EMG) is of interest in a range of different applications, from human-machine interfacing to rehabilitation and clinical assessment. The wider application of high-density EMG is, however, limited as the clinical interfaces are not convenient for practical use (e.g.

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Background: The development of bionic legs has seen substantial improvements in the past years but people with lower-limb amputation still suffer from impairments in mobility (e.g., altered balance and gait control) due to significant limitations of the contemporary prostheses.

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