Forskning

This case study demonstrates the feasibility for long-term sensory feedback using implanted nerve cuff electrodes, and shows that sensations elicited in the missing hand were relatively stable over the course of two years. Sensations were elicited by electrical stimulation using an implanted nerve cuff electrode for a participant with a neuromusculoskeletal prosthesis, who at best was able to distinguish between sensations delivered with only 1/2 Hz difference between them. The ability to distinguish these different sensations is paramount to usable and graded sensory feedback. With this technology, we can develop sensory feedback systems which can signal information about prosthesis movement and its interaction with the world in daily life.

Myoelectric pattern recognition (MPR) has shown promising results for controlling prosthetic limbs in clinical practice, but its effectiveness in real-life situations is less clear. In this study, we used MPR to control a prosthetic hand with four different grips. We tested the system on a person with dysmelia in daily activities. The person reported more intuitive control when performing different grips, but also experienced more uncertainty during continuous movements. This suggests that MPR may be useful for certain amputee patients.

Sensory impairment hinders a person’s ability to interact with their environment, and thus reduces their quality of life.

Bone-anchored limb prostheses allow for the direct transfer of external loads from the prosthesis to the skeleton, eliminating the need for a socket and the associated problems of poor fit, discomfort, and limited range of movement. A percutaneous implant system for direct skeletal attachment of an external limb must provide a long-term, mechanically stable interface to the bone, along with an infection barrier to the external environment. In addition, the mechanical integrity of the implant system and bone must be preserved despite constant stresses induced by the limb prosthesis. Three different percutaneous implant systems for direct skeletal attachment of external limb prostheses are currently clinically available and a few others are under investigation in human subjects. These systems employ different strategies and have undergone design changes with a view to fulfilling the aforementioned requirements. This review summarises such strategies and design changes, providing an overview of the biomechanical characteristics of current percutaneous implant systems for direct skeletal attachment of amputation limb prostheses.

Real-time evaluation of novel prosthetic control schemes is critical for translational research on artificial limbs. Recently, two computer-based, real-time evaluation tools, the target achievement control (TAC) test and the Fitts’ law test (FLT), have been proposed to assess real-time controllability. Whereas TAC tests provides an anthropomorphic visual representation of the limb at the cost of confusing visual feedback, FLT clarifies the current and target locations by simplified non-anthropomorphic representations. Here, we investigated these two approaches and quantied differences in common performance metrics that can result from the chosen method of visual feedback. Ten able-bodied and one amputee subject performed target achievement tasks corresponding to the FLT and TAC test with equivalent indices of difficulty. Ablebodied subjects exhibited significantly (p <0.05) better completion rate, path efficiency, and overshoot when performing the FLT, although no significant difference was seen in throughput performance. The amputee subject showed significantly better performance in overshoot at the FLT, but showed no significant difference in completion rate, path efficiency, and throughput. Results from the FLT showed a strong linear relationship between the movement time and the index of difficulty (R2 D 0:96), whereas TAC test results showed no apparent linear relationship (R2 D 0:19). These results suggest that in relatively similar conditions, the confusing location of virtual limb representation used in the TAC test contributed to poorer performance. Establishing an understanding of the biases of various evaluation protocols is critical to the translation of research into clinical practice.

In this assessment, a model for shoulder/elbow coordination guides a motorized elbow using movement in the residual limb. This control strategy was enabled by attaching the prosthetic limb to an abutment anchored to the skeleton (osseo-integration), allowing the residual limb to move more freely. Combined with a myoelectrical controlled hand, an improvement was seen in the form of less compensatory movements when using automatic shoulder/elbow coordination.

When measuring electric signals from the muscles of the leg to treat phantom limb pain, the placement of the electrodes which measures the signal is important, but it is not known how to place the electrodes for getting the best signals for analysing the electric signals with artificial intelligence algorithms. We tested different electrodes placements, such as putting two electrodes on a specific muscle compared to putting one electrode on several untargeted muscles. The best placement was putting one electrode on several untargeted muscles and we presented a case study who had a 68% reduction in pain after 23 sessions. Removing the need to target the muscles means that electrode placement will be easier which can make it easier to perform phantom limb pain treatments measuring electric signals from the muscles of the leg.

Depending on a pre-processing step known as feature extraction, an EMG classifier can have better or worse discrimination capabilities with respect to its classes. We explore what metrics can be used to indicate the effectiveness of different feature extraction strategies. We find that nearest neighbour separability (NNS) and separability index (SI) computed on the extracted features correlate strongly to the performance of final classification.

The use of myoelectric pattern recognition (MPR) for the control of prosthetic limbs has been limited by interfering noise and susceptibility to motion artifacts. In this article, we present a novel algorithm using wavelet transforms that can be executed in real-time and improves the robustness of MPR systems. The algorithm outperformed conventional methods and showed potential for improving the feasibility and usability of prosthetic devices in real-life situations.

Despite the technological progress in robotics achieved in the last decades, prosthetic limbs still lack functionality, reliability, and comfort. Recently, an implanted neuromusculoskeletal interface built upon osseointegration was developed and tested in humans, namely the Osseointegrated Human-Machine Gateway. Here, we present an embedded system to exploit the advantages of this technology. Our artificial limb controller allows for bioelectric signals acquisition, processing, decoding of motor intent, prosthetic control, and sensory feedback. It includes a neurostimulator to provide direct neural feedback based on sensory information. The system was validated using real-time tasks characterization, power consumption evaluation, and myoelectric pattern recognition performance. Functionality was proven in a first pilot patient from whom results of daily usage were obtained. The system was designed to be reliably used in activities of daily living, as well as a research platform to monitor prosthesis usage and training, machine-learning-based control algorithms, and neural stimulation paradigms.