Biology subjects

Dyson, M.

Publications and source records attributed to Dyson, M..

4 recordsLinked to original sources

bioRxiv2025

Successful transfer of myoelectric skill from virtual interface to prosthesis control

ObjectiveProsthesis control can be seen as a new skill to be learned. To enhance learning, both internal and augmented feedback are exploited. The latter represents external feedback sources that can be designed to enhance learning, e.g. biofeedback. Previous research has shown that augmented feedback protocols can be designed to induce retention by adhering to the guidance hypothesis, but it is not clear yet if that also results in transfer of those skills to prosthesis control. In this study, we test if a training paradigm optimised for retention allows for the transfer of myoelectric skill to prosthesis control. ApproachTwelve limb-intact participants learned a novel myoelectric skill during five one-hour training sessions. To induce retention of the novel myoelectric skill, we used a delayed feedback paradigm. Prosthesis transfer was tested through pre-and post-tests with a prosthesis. Prosthesis control tests included a grasp matching task, the modified box and blocks test, and an object manipulation task, requiring five grasps in total ( power, tripod, pointer, lateral grip, and hand open). Main resultsWe found that prosthesis control improved significantly following five days of training. Importantly, the prosthesis control metrics were significantly related to the retention metrics during training, but not to the prosthesis performance during the pre-test. SignificanceThis study shows that transfer of novel, abstract myoelectric control from a computer interface to prosthetic control is possible if the training paradigm is designed to induce retention. These results highlight the importance of approaching myoelectric and prosthetic skills from a skill acquisition standpoint, and open up new avenues for the design of prosthetic training protocols.

neuroscience↗

bioRxiv2023

Reducing Motor Variability Enhances Myoelectric Control Robustness Across Limb Positions

BackgroundThe limb position effect is a multi-faceted problem, associated with decreased upper-limb prosthesis control acuity following a change in arm position. The many factors contributing to this problem can arise from distinct environmental or physiological sources. Despite their differences in origin, the effect of each factor manifests similarly as increased variability in the detected control signal. This variability can cause incorrect decoding of user intent, leading to dropped items or inability to use the prosthesis during activities of daily living. The general approach of previous research has attempted to limit the impact of the factors or better capture the variability with data abundance. In this paper we take an alternative approach and investigate the effect of reducing the variability of the control signal by improving the consistency of muscle activity with user training. MethodsParticipants underwent 4 days of myoelectric training with either concurrent or delayed feedback in a single arm position. During this time, they were trained to control a two-dimensional cursor using muscles in the forearm. At the end of training participants underwent a zero feedback retention test in multiple limb positions. In doing so, we tested how well the skill learned in a single limb position generalized to untrained positions. ResultsWe found that delayed feedback training led to more consistent muscle activity across both the trained and untrained limb positions. Analysis of patterns of activation in the delayed feedback group suggest a structured change in muscle activity occurs across arm positions. The structured changes allowed us to quantify the limb position effect by comparing trained to untrained arm positions. Different limb positions changed mean ECR and FCR muscle activity in the range of -4.3% to +18.7%. All participants were able to counter the limb position effect if given concurrent feedback, confirming our results align with existing findings. ConclusionsOur results demonstrate that myoelectric user-training can lead to the retention of motor skills that are more robust to limb position changes. This work highlights the importance of reducing motor variability with practice, prior to examining the underlying structure of muscle changes associated with limb position. These findings will be useful for the majority of myoelectric prosthesis control systems and will create better quality input data leading to more robust machine-learning based prosthesis control systems.

neuroscience↗

bioRxiv2022

Gba1 deletion causes immune hyperactivation and microbial dysbiosis through autophagic defects

Mutations in the GBA1 gene cause the lysosomal storage disorder Gaucher disease (GD) and are the greatest genetic risk factor for Parkinsons disease (PD). Communication between gut and brain and immune dysregulation are increasingly being implicated in neurodegenerative disorders such as PD. Here, we show that flies lacking the Gba1b gene, the main fly orthologue of GBA1, display widespread innate immune up-regulation, including gut inflammation and brain glial activation. We also demonstrate gut dysfunction in flies lacking Gba1b, with increased intestinal transit time, gut barrier permeability and microbiome dysbiosis. Remarkably, modulating the microbiome of Gba1b knockout flies, by raising them under germ-free conditions, can partially ameliorate lifespan, locomotor and some neuropathological phenotypes. Lastly, direct stimulation of autophagy by rapamycin treatment achieves similar beneficial effects. Overall, our data reveal that the gut microbiome drives systemic immune activation in Gba1b knockout flies and that reducing innate immune response activation either by eliminating the microbiota or clearance of immunogens by autophagy may represent potential therapeutic avenues for GBA1-associated neurodegenerative disease.

neuroscience↗

bioRxiv2020

3D-Printing and upper-limb prosthetic sockets; promises and pitfalls

Modernising the way upper-limb prosthetic sockets are made has seen limited progress. The casting techniques that are employed in clinics today resemble those developed over 50 years ago and there is still a heavy reliance on manual labour. Modern manufacturing methods such as 3D scanning and printing are often presented as ready-to-use solutions for producing low-cost functional devices, with public perceptions being largely shaped by the superficial media representation and advertising. The promise is that modern socket manufacturing methods can improve patient satisfaction, decrease manufacturing times and reduce the workload in the clinic. However, the perception in the clinical community is that total conversion to digital methods in a clinical environment is not straightforward. Anecdotally, there is currently a disconnect between those developing technology to produce prosthetic devices and the actual needs of clinicians and people with limb difference. In this paper, we demonstrate strengths and drawbacks of a fully digitised, low-cost trans-radial diagnostic socket making process, informed by clinical expertise. We present volunteer feedback on the digitally created sockets and provide expert commentary on the use of digital tools in upper-limb socket manufacturing. We show that it is possible to utilise 3D scanning and printing, but only if the process is informed by expert knowledge. We bring examples to demonstrate how and why the process may go wrong. Finally, we provide discussion on why progress in modernising the manufacturing of upper-limb sockets has been slow yet it is still too early to rule out digital methods.

bioengineering↗