Morten Bak Kristoffersen

University of Gothenburg | GU · Institute of Clinical Sciences

Background: Phantom limb pain is a debilitating condition for which no effective treatment has been found. We hypothesised that re-engagement of central and peripheral circuitry involved in motor execution could reduce phantom limb pain via competitive plasticity and reversal of cortical reorganisation. Methods: Patients with upper limb amputati...

Human-machine interfaces have not yet advanced to enable intuitive control of multiple degrees of freedom as offered by modern myoelectric prosthetic hands. Pattern Recognition (PR) control has been proposed to make human-machine interfaces in myoelectric prosthetic hands more intuitive, but it requires the user to generate high-quality, i.e., cons...

Background Upper limb prosthetics with multiple degrees of freedom (DoFs) are still mostly operated through the clinical standard Direct Control scheme. Machine learning control, on the other hand, allows controlling multiple DoFs although it requires separable and consistent electromyogram (EMG) patterns. Whereas user training can improve EMG patt...

Objective: When evaluating methods for machine-learning controlled prosthetic hands, able-bodied participants are often recruited, for practical reasons, instead of participants with upper limb absence (ULA). However, able-bodied participants have been shown to often perform myoelectric control tasks better than participants with ULA. It has been...

Background: A thorough assessment of upper limb prostheses could help facilitate their transfer from scientific developments into the daily lives of users. Ideally, routine clinical testing would include assessments of upper limb function using motion-capturing technology. This is particularly relevant for the state-of-the-art upper limb prostheses...

Background: Upper limb impairment is common after stroke, and many will not regain full upper limb function. Different technologies based on surface electromyography (sEMG) have been used in stroke rehabilitation, but there is no collated evidence on the different sEMG-driven interventions and their effect on upper limb function in people with str...

When one thinks about electrodes, especially ones meant for humans, they typically think of some kind of metal. Whether on the skin or in the brain, metal electrodes are characteristically expensive, stiff, non-efficient in electron-ion transduction, and prone to toxic metal ion by-products during stimulation. In order to circumvent these disadvant...

Objective: We show that state-of-the-art deep neural networks achieve superior results in regression-based multi-class proportional myoelectric hand prosthesis control than two common baseline approaches, and we analyze the neural network mapping to explain why this is the case. Methods: Feedforward neural networks and baseline systems are train...

In myoelectric machine learning (ML) based control, it has been demonstrated that control performance usually increases with training, but it remains largely unknown which underlying factors govern these improvements. It has been suggested that the increase in performance originates from changes in characteristics of the Electromyography (EMG) patt...

Pattern-Recognition (PR) control of upper-limb prosthetics has shown inconsistent results outside lab settings, which might be due to the inadequacy of users’ electromyogram (EMG) patterns. To improve the separability and consistency of their EMG, users can receive training. Conventional training uses an internal focus of attention as prosthesis us...

Objective: To describe users' and therapists' opinions on multi-function myoelectric upper limb prostheses with conventional control and pattern recognition control. Design: Qualitative interview study. Settings: Two rehabilitation institutions in the Netherlands and one in Austria. Subjects: The study cohort consisted of 15 prosthesis users...

In myocontrol of upper limb prostheses using machine learning techniques, a basic requirement is the user’s ability to generate sufficiently distinct surface electromyography (sEMG) signals for different movement intents, over a wide range of arm orientations. Experiments with regard to training this ability are often conducted on able bodied, but...

Machine learning techniques have been proposed for the control of upper-limb prosthetics. Electromyography (EMG) signals from able-bodied participants are often used to test new algorithms and techniques. Restricting the unaffected hand has been suggested to best mimic the EMG features of the affected limb. It remains unclear whether this results i...

PURPOSE: Literature suggests that improvements in control of a pattern-recognition based myoelectric device are governed by increased distinctness of surface EMG patterns (dEMG). We investigated the relation between control ability and dEMG. METHODS: Able-bodied participants learned to control a pattern-recognition based myoelectric device over 5...

A variety of treatments have been historically used to alleviate phantom limb pain (PLP) with varying efficacy. Recently, virtual reality (VR) has been employed as a more sophisticated mirror therapy. Despite the advantages of VR over a conventional mirror, this approach has retained the use of the contralateral limb and is therefore restricted to...

We show that the autostereoscopic display of stereoscopic images using a static parallax barrier can be improved by adapting the rendering to the angle under which the user is looking at a mobile display; thus, ghosting artifacts and depth reversals can often be avoided even if the user tilts the mobile device. Instead of moving the barrier itself...