| 1. |
- Buist, Mirka, et al.
(författare)
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Novel Wearable Device for Mindful Sensorimotor Training: Integrating Motor Decoding and Somatosensory Stimulation for Neurorehabilitation
- 2024
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Ingår i: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 1558-0210 .- 1534-4320. ; 32, s. 1515-1523
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Tidskriftsartikel (refereegranskat)abstract
- Sensorimotor impairment is a prevalent condition requiring effective rehabilitation strategies. This study introduces a novel wearable device for Mindful Sensorimotor Training (MiSMT) designed for sensory and motor rehabilitation. Our MiSMT device combines motor training using myoelectric pattern recognition along sensory training using two tactile displays. This device offers a comprehensive solution, integrating electromyography and haptic feedback, lacking in existing devices. The device features eight electromyography channels, a rechargeable battery, and wireless Bluetooth or Wi-Fi connectivity for seamless communication with a computer or mobile device. Its flexible material allows for adaptability to various body parts, ensuring ease of use in diverse patients. The two tactile displays, with 16 electromagnetic actuators each, provide touch and vibration sensations up to 250 Hz. In this proof-of-concept study, we show improved two-point discrimination after 5 training sessions in participants with intact limbs (p=0.047). We also demonstrated successful acquisition, processing, and decoding of myoelectric signals in offline and online evaluations. In conclusion, the MiSMT device presents a promising tool for sensorimotor rehabilitation by combining motor execution and sensory training benefits. Further studies are required to assess its effectiveness in individuals with sensorimotor impairments. Integrating mindful sensory and motor training with innovative technology can enhance rehabilitation outcomes and improve the quality of life for those with sensorimotor impairments.
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| 2. |
- Earley, Eric, 1989, et al.
(författare)
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Competitive motivation increased home use and improved prosthesis self-perception after Cybathlon 2020 for neuromusculoskeletal prosthesis user
- 2022
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Ingår i: Journal of NeuroEngineering and Rehabilitation. - : Springer Science and Business Media LLC. - 1743-0003. ; 19:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Assistive technologies, such as arm prostheses, are intended to improve the quality of life of individuals with physical disabilities. However, certain training and learning is usually required from the user to make these technologies more effective. Moreover, some people can be encouraged to train more through competitive motivation. Methods In this study, we investigated if the training for and participation in a competitive event (Cybathlon 2020) could promote behavioral changes in an individual with upper limb amputation (the pilot). We defined behavioral changes as the active time while his prosthesis was actuated, ratio of opposing and simultaneous movements, and the pilot's ability to finely modulate his movement speeds. The investigation was based on extensive home-use data from the period before, during and after the Cybathlon 2020 competition. Results Relevant behavioral changes were found from both quantitative and qualitative analyses. The pilot's home use of his prosthesis nearly doubled in the period before the Cybathlon, and remained 66% higher than baseline after the competition. Moreover, he improved his speed modulation when controlling his prosthesis, and he learned and routinely operated new movements in the prosthesis (wrist rotation) at home. Additionally, as confirmed by semi-structured interviews, his self-perception of the prosthetic arm and its functionality also improved. Conclusions An event like the Cybathlon may indeed promote behavioral changes in how competitive individuals with amputation use their prostheses. Provided that the prosthesis is suitable in terms of form and function for both competition and at-home daily use, daily activities can become opportunities for training, which in turn can improve prosthesis function and create further opportunities for daily use. Moreover, these changes appeared to remain even well after the event, albeit relevant only for individuals who continue using the technology employed in the competition.
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| 3. |
- Earley, Eric, 1989, et al.
(författare)
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Cutting Edge Bionics in Highly Impaired Individuals: A Case of Challenges and Opportunities
- 2024
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Ingår i: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - 1558-0210 .- 1534-4320. ; 32, s. 1013-1022
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Tidskriftsartikel (refereegranskat)abstract
- Highly impaired individuals stand to benefit greatly from cutting-edge bionic technology, however concurrent functional deficits may complicate the adaptation of such technology. Here, we present a case in which a visually impaired individual with bilateral burn injury amputation was provided with a novel transradial neuromusculoskeletal prosthesis comprising skeletal attachment via osseointegration and implanted electrodes in nerves and muscles for control and sensory feedback. Difficulties maintaining implant hygiene and donning and doffing the prosthesis arose due to his contralateral amputation, ipsilateral eye loss, and contralateral impaired vision necessitating continuous adaptations to the electromechanical interface. Despite these setbacks, the participant still demonstrated improvements in functional outcomes and the ability to control the prosthesis in various limb positions using the implanted electrodes. Our results demonstrate the importance of a multidisciplinary, iterative, and patient-centered approach to making cutting-edge technology accessible to patients with high levels of impairment.
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| 4. |
- Earley, Eric, 1989, et al.
(författare)
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Neurostimulation artifact removal for implantable sensors improves signal clarity and decoding of motor volition
- 2022
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Ingår i: Frontiers in Human Neuroscience. - : Frontiers Media SA. - 1662-5161. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- As the demand for prosthetic limbs with reliable and multi-functional control increases, recent advances in myoelectric pattern recognition and implanted sensors have proven considerably advantageous. Additionally, sensory feedback from the prosthesis can be achieved via stimulation of the residual nerves, enabling closed-loop control over the prosthesis. However, this stimulation can cause interfering artifacts in the electromyographic (EMG) signals which deteriorate the reliability and function of the prosthesis. Here, we implement two real-time stimulation artifact removal algorithms, Template Subtraction (TS) and epsilon-Normalized Least Mean Squares (epsilon-NLMS), and investigate their performance in offline and real-time myoelectric pattern recognition in two transhumeral amputees implanted with nerve cuff and EMG electrodes. We show that both algorithms are capable of significantly improving signal-to-noise ratio (SNR) and offline pattern recognition accuracy of artifact-corrupted EMG signals. Furthermore, both algorithms improved real-time decoding of motor intention during active neurostimulation. Although these outcomes are dependent on the user-specific sensor locations and neurostimulation settings, they nonetheless represent progress toward bi-directional neuromusculoskeletal prostheses capable of multifunction control and simultaneous sensory feedback.
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| 5. |
- Just, Fabian, 1990, et al.
(författare)
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Deployment of Machine Learning Algorithms on Resource-Constrained Hardware Platforms for Prosthetics
- 2024
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Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 12, s. 40439-40449
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Tidskriftsartikel (refereegranskat)abstract
- Motion intent recognition for controlling prosthetic systems has long relied on machine learning algorithms. Artificial neural networks have shown great promise for solving such nonlinear classification tasks, making them a viable method for this purpose. To bring these advanced methods and algorithms beyond the confines of the laboratory and into the daily lives of prosthetic users, self-contained embedded systems are essential. However, embedded systems face constraints in size, computational power, memory footprint, and power consumption, as they must be non-intrusive and discreetly integrated into commercial prosthetic components. One promising approach to tackle these challenges is to use network quantization, which allows complying with limitations without significant loss in accuracy. Here, we compare network quantization performance for self-contained systems using TensorFlow Lite and the recently developed QKeras platform. Due to internal libraries, the use of TensorFlow Lite led to a 8 times higher flash memory usage than that of the unquantized reference network, disadvantageous for self-contained prosthetic systems. In response, we offer open-source code solutions that leverage the QKeras platform, effectively reducing flash memory requirements by 24 times compared to Tensorflow Lite. Additionally, we conducted a comprehensive comparison of state-of-The-Art microcontrollers. Our results reveal that the adoption of new architectures offers substantial reductions in inference time and power consumption. These improvements pave the way for real-Time decoding of motor intent using more advanced machine learning algorithms for daily life usage, possibly enabling more reliable and precise control for prosthetic users.
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| 6. |
- Lang, Victoria Ashley, et al.
(författare)
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Hand Temperature Is Not Consistent With Illusory Strength During the Rubber Hand Illusion.
- 2021
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Ingår i: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. - 2694-0604. ; 2021, s. 1416-1418
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Tidskriftsartikel (refereegranskat)abstract
- The rubber hand illusion is known to invoke a sense of ownership of a rubber hand when a person watches the stroking of the rubber hand in synchrony with their own hidden hand. Quantification of the sense of ownership is traditionally performed with the rubber hand illusion questionnaire, but the search for reliable physiological measurements persists. Skin temperature has been previously suggested and debated as a biomarker for ownership. We investigated hand temperature as a measure of rubber hand illusory strength via thermal imaging of the hand during the rubber hand experiment. No relationship was found between reported illusory strength and skin temperature.Clinical Relevance- Our results indicate that skin temperature is not a suitable biomarker for rubber hand illusory strength.
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| 7. |
- Ortiz Catalan, Max Jair, 1982, et al.
(författare)
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A highly integrated bionic hand with neural control and feedback for use in daily life
- 2023
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Ingår i: Science Robotics. - 2470-9476. ; 8:83
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Tidskriftsartikel (refereegranskat)abstract
- Restoration of sensorimotor function after amputation has remained challenging because of the lack of human-machine interfaces that provide reliable control, feedback, and attachment. Here, we present the clinical implementation of a transradial neuromusculoskeletal prosthesis-a bionic hand connected directly to the user's nervous and skeletal systems. In one person with unilateral below-elbow amputation, titanium implants were placed intramedullary in the radius and ulna bones, and electromuscular constructs were created surgically by transferring the severed nerves to free muscle grafts. The native muscles, free muscle grafts, and ulnar nerve were implanted with electrodes. Percutaneous extensions from the titanium implants provided direct skeletal attachment and bidirectional communication between the implanted electrodes and a prosthetic hand. Operation of the bionic hand in daily life resulted in improved prosthetic function, reduced postamputation, and increased quality of life. Sensations elicited via direct neural stimulation were consistently perceived on the phantom hand throughout the study. To date, the patient continues using the prosthesis in daily life. The functionality of conventional artificial limbs is hindered by discomfort and limited and unreliable control. Neuromusculoskeletal interfaces can overcome these hurdles and provide the means for the everyday use of a prosthesis with reliable neural control fixated into the skeleton.
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| 8. |
- Zbinden, Jan, 1994, et al.
(författare)
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A multi-dimensional framework for prosthetic embodiment: a perspective for translational research
- 2022
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Ingår i: Journal of NeuroEngineering and Rehabilitation. - : Springer Science and Business Media LLC. - 1743-0003. ; 19:1
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Forskningsöversikt (refereegranskat)abstract
- The concept of embodiment has gained widespread popularity within prosthetics research. Embodiment has been claimed to be an indicator of the efficacy of sensory feedback and control strategies. Moreover, it has even been claimed to be necessary for prosthesis acceptance, albeit unfoundedly. Despite the popularity of the term, an actual consensus on how prosthetic embodiment should be used in an experimental framework has yet to be reached. The lack of consensus is in part due to terminological ambiguity and the lack of an exact definition of prosthetic embodiment itself. In a review published parallel to this article, we summarized the definitions of embodiment used in prosthetics literature and concluded that treating prosthetic embodiment as a combination of ownership and agency allows for embodiment to be quantified, and thus useful in translational research. Here, we review the potential mechanisms that give rise to ownership and agency considering temporal, spatial, and anatomical constraints. We then use this to propose a multi-dimensional framework where prosthetic embodiment arises within a spectrum dependent on the integration of volition and multi-sensory information as demanded by the degree of interaction with the environment. This framework allows for the different experimental paradigms on sensory feedback and prosthetic control to be placed in a common perspective. By considering that embodiment lays along a spectrum tied to the interactions with the environment, one can conclude that the embodiment of prosthetic devices should be assessed while operating in environments as close to daily life as possible for it to become relevant.
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| 9. |
- Zbinden, Jan, 1994, et al.
(författare)
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Deep Learning for Enhanced Prosthetic Control: Real-Time Motor Intent Decoding for Simultaneous Control of Artificial Limbs
- 2024
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Ingår i: IEEE Transactions on Neural Systems and Rehabilitation Engineering. - 1558-0210 .- 1534-4320. ; 32, s. 1177-1186
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Tidskriftsartikel (refereegranskat)abstract
- The development of advanced prosthetic devices that can be seamlessly used during an individual's daily life remains a significant challenge in the field of rehabilitation engineering. This study compares the performance of deep learning architectures to shallow networks in decoding motor intent for prosthetic control using electromyography (EMG) signals. Four neural network architectures, including a feedforward neural network with one hidden layer, a feedforward neural network with multiple hidden layers, a temporal convolutional network, and a convolutional neural network with squeeze-and-excitation operations were evaluated in real-time, human-in-the-loop experiments with able-bodied participants and an individual with an amputation. Our results demonstrate that deep learning architectures outperform shallow networks in decoding motor intent, with representation learning effectively extracting underlying motor control information from EMG signals. Furthermore, the observed performance improvements by using deep neural networks were consistent across both able-bodied and amputee participants. By employing deep neural networks instead of a shallow network, more reliable and precise control of a prosthesis can be achieved, which has the potential to significantly enhance prosthetic functionality and improve the quality of life for individuals with amputations.
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| 10. |
- Zbinden, Jan, 1994, et al.
(författare)
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Improved control of a prosthetic limb by surgically creating electro-neuromuscular constructs with implanted electrodes
- 2023
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Ingår i: Science translational medicine. - 1946-6234 .- 1946-6242. ; 15:704
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Tidskriftsartikel (refereegranskat)abstract
- Remnant muscles in the residual limb after amputation are the most common source of control signals for prosthetic hands, because myoelectric signals can be generated by the user at will. However, for individuals with amputation higher up the arm, such as an above-elbow (transhumeral) amputation, insufficient muscles remain to generate myoelectric signals to enable control of the lost arm and hand joints, thus making intuitive control of wrist and finger prosthetic joints unattainable. We show that severed nerves can be divided along their fascicles and redistributed to concurrently innervate different types of muscle targets, particularly native denervated muscles and nonvascularized free muscle grafts. We engineered these neuromuscular constructs with implanted electrodes that were accessible via a permanent osseointegrated interface, allowing for bidirectional communication with the prosthesis while also providing direct skeletal attachment. We found that the transferred nerves effectively innervated their new targets as shown by a gradual increase in myoelectric signal strength. This allowed for individual flexion and extension of all five fingers of a prosthetic hand by a patient with a transhumeral amputation. Improved prosthetic function in tasks representative of daily life was also observed. This proof-of-concept study indicates that motor neural commands can be increased by creating electro-neuromuscular constructs using distributed nerve transfers to different muscle targets with implanted electrodes, enabling improved control of a limb prosthesis.
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