8 research outputs found

    Electromyography Based Human-Robot Interfaces for the Control of Artificial Hands and Wearable Devices

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    The design of robotic systems is currently facing human-inspired solutions as a road to replicate the human ability and flexibility in performing motor tasks. Especially for control and teleoperation purposes, the human-in-the-loop approach is a key element within the framework know as Human-Robot Interface. This thesis reports the research activity carried out for the design of Human-Robot Interfaces based on the detection of human motion intentions from surface electromyography. The main goal was to investigate intuitive and natural control solutions for the teleoperation of both robotic hands during grasping tasks and wearable devices during elbow assistive applications. The design solutions are based on the human motor control principles and surface electromyography interpretation, which are reviewed with emphasis on the concept of synergies. The electromyography based control strategies for the robotic hand grasping and the wearable device assistance are also reviewed. The contribution of this research for the control of artificial hands rely on the integration of different levels of the motor control synergistic organization, and on the combination of proportional control and machine learning approaches under the guideline of user-centred intuitiveness in the Human-Robot Interface design specifications. From the side of the wearable devices, the control of a novel upper limb assistive device based on the Twisted String Actuation concept is faced. The contribution regards the assistance of the elbow during load lifting tasks, exploring a simplification in the use of the surface electromyography within the design of the Human-Robot Interface. The aim is to work around complex subject-dependent algorithm calibrations required by joint torque estimation methods

    Causes of Performance Degradation in Non-invasive Electromyographic Pattern Recognition in Upper Limb Prostheses

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    Surface Electromyography (EMG)-based pattern recognition methods have been investigated over the past years as a means of controlling upper limb prostheses. Despite the very good reported performance of myoelectric controlled prosthetic hands in lab conditions, real-time performance in everyday life conditions is not as robust and reliable, explaining the limited clinical use of pattern recognition control. The main reason behind the instability of myoelectric pattern recognition control is that EMG signals are non-stationary in real-life environments and present a lot of variability over time and across subjects, hence affecting the system's performance. This can be the result of one or many combined changes, such as muscle fatigue, electrode displacement, difference in arm posture, user adaptation on the device over time and inter-subject singularity. In this paper an extensive literature review is performed to present the causes of the drift of EMG signals, ways of detecting them and possible techniques to counteract for their effects in the application of upper limb prostheses. The suggested techniques are organized in a table that can be used to recognize possible problems in the clinical application of EMG-based pattern recognition methods for upper limb prosthesis applications and state-of-the-art methods to deal with such problems

    Restoring Fine Motor Prosthetic Hand Control via Peripheral Neural Technology

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    Losing a limb can drastically alter a person’s way of life, and in some cases, brings great financial and emotional burdens. In particular, upper-limb amputations means losing the ability to do many daily activities that are normally simple with intact hands. Prosthesis technology has significantly advanced in the past decade to replicate the mechanical complexity of the human hand. However, current commercial user-to-prosthesis interfaces fail to provide users with full intuitive control over the many functionalities advanced prosthetic hands can offer. Research in developing new interfaces for better motor control has been on the rise, focusing on tapping directly into the peripheral nervous system. The aim of this work is to characterize and validate the properties of a novel peripheral interface called the Regenerative Peripheral Nerve Interface (RPNI) to improve fine motor skills for prosthetic hand control. The first study characterizes the use of RPNI signals for continuous hand control in non-human primates. In two rhesus macaques, we were able to reconstruct continuous finger movement offline with an average correlation of ρ = 0.87 and root mean squared error (RMSE) of 0.12 between actual and predicted position across both macaques. During real-time control, neural control performance was slightly slower but maintained an average target hit success rate of 96.7% compared to physical hand control. The second study presents the viability of the RPNI in humans who have suffered from upper-limb amputations. Three participants with transradial amputations, P1, P2 and P3, underwent surgical implantation of nine, three, and four RPNIs for the treatment of neuroma pain, respectively. In P1 and P2, ultrasound demonstrated strong contractions of P1 and P2’s median RPNIs during flexion of the phantom thumb, and of P1’s ulnar RPNIs during small finger flexion. In P1, the median RPNI and ulnar RPNIs produced electromyography (EMG) signals with a signal-to-noise ratio (SNR) of 4.62 and 3.80 averaged across three recording sessions, respectively. In P2, the median RPNI and ulnar RPNI had an average SNR of 107 and 35.9, respectively, while P3’s median RPNI and ulnar RPNIs had an average SNR of 22.3 and 19.4, respectively. The final study characterizes the capabilities of RPNI signals to predict continuous finger position in human subjects. Two participants, P2 and P3, successfully hit targets during a center-out target task with 92.4 ± 2.3% accuracy, controlling RPNI-driven one DOF finger movements. Comparably, non-RPNI driven finger movement had similar accuracy and performance. Without recalibrating parameter coefficients, no decreasing trend in motor performance was seen for all one DOF finger control across 300 days for P2 and 40 days for P3, suggesting that RPNIs can generate robust control signals from day to day. Lastly, using RPNI-driven control, P2 and P3 successfully manipulated a two DOF virtual and physical thumb with 96.4 ± 2.5% accuracy. These three studies demonstrated: (1) RPNIs provided robust continuous control of one DOF hand movement in non-human primates, an important step for human translation, (2) RPNIs were safely implemented in three participants, showing evidence of contraction and generation of EMG, and (3) in two participants, RPNIs can provide continuous control of one DOF finger movements and two DOF thumb movements. The results presented in this dissertation suggest RPNIs may be a viable option to advance peripheral nerve interfaces into clinical reality and enhance neuroprosthetic technology for people with limb loss.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149816/1/philipv_1.pd

    Automated instability detection for interactive myocontrol of prosthetic hands

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    Myocontrol is control of a prosthetic device using data obtained from (residual) muscle activity. In most myocontrol prosthetic systems, such biological data also denote the subject\u2019s intent: reliably interpreting what the user wants to do, exactly and only when she wants, is paramount to avoid instability, which can potentially lead to accidents, humiliation and trauma. Indeed, instability manifests itself as a failure of the myocontrol in interpreting the subject\u2019s intent, and the automated detection of such failures can be a specific step to improve myocontrol of prostheses\u2014e.g., enabling the possibility of self-adaptation of the system via on-demand model updates for incremental learning, i.e., the interactive myocontrol paradigm. In this work we engaged six expert myocontrol users (five able-bodied subjects and one trans-radial amputee) in a simple, clear grasp-carry-release task, in which the subject\u2019s intent was reasonably determined by the task itself. We then manually ascertained when the intent would not coincide with the behavior of the prosthetic device, i.e., we labeled the failures of the myocontrol system. Lastly, we trained and tested a classifier to automatically detect such failures. Our results show that a standard classifier is able to detect myocontrol failures with a mean balanced error rate of 18.86% over all subjects. If confirmed in the large, this approach could pave the way to self-detection and correction of myocontrol errors, a tighter man-machine co-adaptation, and in the end the improvement of the reliability of myocontrol

    Evidence Synthesis of Shoulder Pain Among Canadian Firefighters

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    Injury or degeneration of rotator cuff tendon leads to rotator cuff disease (subacromial impingement syndrome and rotator cuff tears). Shoulder pain – pain in the upper arm close to the deltoid muscle insertion has been reported as the most common symptom for subacromial impingement syndrome and rotator cuff tears. However, the current state of evidence on treatment effectiveness of rotator cuff disease is indeterminate. The shoulder function is essential for many of the physically demanding tasks that firefighters perform on the fire ground. For fire services and firefighters, the preservation of active duty is critical for their continued service to their communities. However, the prevalence of shoulder pain among Canadian firefighters has not been synthesized. Further, high quality randomized clinical trials (RCTs) provide the highest level of evidence and assist in clinical decision making. The International Committee of Medical Journal Editors (ICMJE) recommendation of RCT trial registration in public trials registry has been made to improve the reporting, transparency, rigor and reproducibility in RCTs. However, there is a paucity of evidence on the proportion of RCTs with proper trial registrations in the field of rehabilitation therapy. Therefore, the purposes of this thesis were 1) to assess the effects of arthroscopic versus mini-open rotator cuff repair surgery on function, pain and range of motion at in patients with rotator cuff tears; 2) to quantify the effects of surgical vs conservative interventions on clinical outcomes of pain and function in patients with subacromial impingement syndrome; 3) to assess the prevalence of musculoskeletal disorders (MSDs) among Canadian firefighters, 4) to examine the proportion of RCTs that were reported to have been prospectively, retrospectively registered or not registered in the field of rehabilitation therapy, and 5) to use the synthesized evidence to inform the design of a single center (fire-station), investigator-blinded, randomized, 12-month, parallel-group, superiority trial for the evaluation of the efficacy of a shoulder exercises on clinical outcomes in firefighters with shoulder pain. From the existing literature, we found evidence that both arthroscopic and mini-open techniques to rotator cuff repairs with post-operative rehabilitation exercises were effective in improving clinical outcomes of function, pain and shoulder range of motion in patients with rotator cuff tears. However, the between-group differences in outcomes were too small to be clinically important. The effects of surgery plus physiotherapy (exercises) vs physiotherapy (exercises) alone on pain and function were too small to be clinically important at 3-, 6-months, 1-, 2-, 5- and ≄ 10-years follow up. This further highlighted that rehabilitation exercises be considered as the first treatment approach in patients with shoulder pain. We also identified high point-prevalence estimates (1 in 4 firefighters) of shoulder-, back-, and knee-related MSDs among Canadian firefighters (shoulder pain was 23%). Our review study indicated that fifteen years after the introduction of standards for RCT registration by ICMJE, only one-third of the RCTs in the field of rehabilitation therapy were prospectively registered. Subsequently, the emergence of further evidence (observational studies in firefighters and RCTs in active-duty military personnel) indicating the clinical effectiveness of occupation-specific rehabilitation exercises along with our evidence syntheses provided the rationale for the design and conduct of an RCT to assess the effectiveness of firefighter-specific rehabilitation exercises among Canadian firefighter with shoulder pain
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