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Affordable upper-limb prostheses often lack intuitive control systems, limiting functionality and accessibility for amputees in low-resource settings. This project presents a low-cost, dual-mode neuro-muscular control system integrating…
We propose, implement and evaluate a natural human-machine control interface for a variable stiffness transradial hand prosthesis that achieves tele-impedance control through surface electromyography (sEMG) signals. This interface, together…
Objective: Deep learning-based neural decoders have emerged as the prominent approach to enable dexterous and intuitive control of neuroprosthetic hands. Yet few studies have materialized the use of deep learning in clinical settings due to…
Objective: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand…
Despite decades of research and development of pattern recognition approaches, the clinical usability of myoelectriccontrolled prostheses is still limited. One of the main issues is the high inter-subject variability that necessitates long…
Clinical myoelectric prostheses lack the sensory feedback and sufficient dexterity required to complete activities of daily living efficiently and accurately. Providing haptic feedback of relevant environmental cues to the user or imbuing…
Multiarticulate bionic arms are now capable of mimicking the endogenous movements of the human hand. 3D-printing has reduced the cost of prosthetic hands themselves, but there is currently no low-cost alternative to dexterous…
The incorporation of advanced control algorithms into prosthetic hands significantly enhances their ability to replicate the intricate motions of a human hand. This work introduces a model-based controller that combines an Artificial Neural…
Prosthesis users can regain partial limb functionality, however, full natural limb mobility is rarely restored, often resulting in compensatory movements that lead to discomfort, inefficiency, and long-term physical strain. To address this…
The anthropomorphism of grasping process significantly benefits the experience and grasping efficiency of prosthetic hand wearers. Currently, prosthetic hands controlled by signals such as brain-computer interfaces (BCI) and…
Current control strategies for powered lower limb prostheses often lack awareness of the environment and the user's intended interactions with it. This limitation becomes particularly apparent in complex terrains. Obstacle negotiation, a…
Electromyography (EMG) is a measure of muscular electrical activity and is used in many clinical/biomedical disciplines and modern human computer interaction. Myo-electric prosthetics analyze and classify the electrical signals recorded…
This work presents a description of the EXOSMOOTH project, oriented to the benchmarking of lower limb exoskeletons performance. In the field of assisted walking by powered lower limb exoskeletons, the EXOSMOOTH project proposes an…
Lower extremity amputees face challenges in natural locomotion, which is partially compensated using powered assistive systems, e.g., micro-processor controlled prosthetic leg. In this paper, a radar-based perception system is proposed to…
Dexterous prosthetic hands have better grasp performance than traditional ones. However, patients still find it difficult to use these hands without a suitable control system. A new hybrid myoelectric control system, termed i-MYO, is…
Assistive devices for indivuals with upper-limb movement often lack controllability and intuitiveness, in particular for grasping function. In this work, we introduce a novel user interface for grasping movement control in which the user…
Precise and elegant coordination of a prosthesis across many degrees of freedom represents a significant challenge to efficient rehabilitation of people with limb deficiency. Processing the electrical neural signals, collected from the…
Recent advancements in prosthetic technology have increasingly focused on enhancing dexterity and autonomy through intelligent control systems. Vision-based approaches offer promising results for enabling prosthetic hands to interact more…
Partial hand amputations significantly affect the physical and psychosocial well-being of individuals, yet intuitive control of externally powered prostheses remains an open challenge. To address this gap, we developed a force-controlled…
Non-invasive myoelectric prostheses require a long training time to obtain satisfactory control dexterity. These training times could possibly be reduced by leveraging over training efforts by previous subjects. So-called domain adaptation…