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Max Ortizcatalan - One of the best experts on this subject based on the ideXlab platform.

  • out of the clinic into the home the in home use of phantom Motor Execution aided by machine learning and augmented reality for the treatment of phantom limb pain
    Journal of Pain Research, 2020
    Co-Authors: Eva Lendaro, Alexandra Middleton, Shannon Brown, Max Ortizcatalan
    Abstract:

    Purpose: Phantom Motor Execution (PME) facilitated by augmented/virtual reality (AR/ VR) and serious gaming (SG) has been proposed as a treatment for phantom limb pain (PLP). Evidence of the efficacy of this approach was obtained through a clinical trial involving individuals with chronic intractable PLP affecting the upper limb, and further evidence is currently being sought with a multi-sited, international, double blind, randomized, controlled clinical trial in upper and lower limb amputees. All experiments have been conducted in a clinical setting supervised by a therapist. Here, we present a series of case studies (two upper and two lower limb amputees) on the use of PME as a self-treatment. We explore the benefits and the challenges encountered in translation from clinic to home use with a holistic, mixed-methods approach, employing both quantitative and qualitative methods from engineering, medical anthropology, and user interface design. Patients and Methods: All patients were provided with and trained to use a myoelectric pattern recognition and AR/VR device for PME. Patients took these devices home and used them independently over 12 months. Results: We found that patients were capable of conducting PME as a self-treatment and incorporated the device into their daily life routines. Use patterns and adherence to PME practice were not only driven by the presence of PLP but also influenced by patients’ perceived need and social context. The main barriers to therapy adherence were time and availability of single-use electrodes, both of which could be resolved, or attenuated, by informed design considerations. Conclusion: Our findings suggest that adherence to treatment, and thus related outcomes, could be further improved by considering disparate user types and their utilization patterns. Our study highlights the importance of understanding, from multiple disciplinary angles, the tight coupling and interplay between pain, perceived need, and use of medical devices in patient-initiated therapy.

  • real time classification of non weight bearing lower limb movements using emg to facilitate phantom Motor Execution engineering and case study application on phantom limb pain
    Frontiers in Neurology, 2017
    Co-Authors: Eva Lendaro, Enzo Mastinu, Bo Hakansson, Max Ortizcatalan
    Abstract:

    Phantom Motor Execution (PME) facilitated by Myoelectric Pattern Recognition (MPR) and Virtual Reality (VR), is positioned to be a viable option to treat Phantom Limb Pain (PLP). A recent clinical trial using PME on upper-limb amputees with chronic intractable PLP, yielded promising results. However, further work in the area of signal acquisition is needed if such technology is to be used on subjects with lower-limb amputation. We propose two alternative electrode configurations to conventional, bipolar, targeted recordings for acquiring surface electromyography (sEMG). We evaluated their performance in a real-time MPR task for non-weight-bearing, lower-limb movements. We found that monopolar recordings using a circumferential electrode of conductive fabric, performed similarly to classical bipolar recordings, but were easier to use in a clinical setting. In addition, we present the first case study of a lower-limb amputee with chronic, intractable PLP treated with Phantom Motor Execution. The patient’s Pain Rating Index dropped by 22 points (from 32 to 10, 68%) after 23 Phantom Motor Execution sessions. These results represent a methodological advancement and a positive proof-of-concept of Phantom Motor Execution in lower limbs. Further work remains to be conducted for a high-evidence level clinical validation of Phantom Motor Execution as a treatment of PLP in lower-limb amputees.

  • phantom Motor Execution facilitated by machine learning and augmented reality as treatment for phantom limb pain a single group clinical trial in patients with chronic intractable phantom limb pain
    The Lancet, 2016
    Co-Authors: Max Ortizcatalan, Rannveig A Guðmundsdottir, Morten Kristoffersen, Alejandra Zepedaechavarria, Kerstin Cainewinterberger, Katarzyna Kulbackaortiz, Cathrine Widehammar, Karin Eriksson, Anita Stockselius
    Abstract:

    Summary 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 amputation and known chronic intractable phantom limb pain were recruited at three clinics in Sweden and one in Slovenia. Patients received 12 sessions of phantom Motor Execution using machine learning, augmented and virtual reality, and serious gaming. Changes in intensity, frequency, duration, quality, and intrusion of phantom limb pain were assessed by the use of the numeric rating scale, the pain rating index, the weighted pain distribution scale, and a study-specific frequency scale before each session and at follow-up interviews 1, 3, and 6 months after the last session. Changes in medication and prostheses were also monitored. Results are reported using descriptive statistics and analysed by non-parametric tests. The trial is registered at ClinicalTrials.gov, number NCT02281539. Findings Between Sept 15, 2014, and April 10, 2015, 14 patients with intractable chronic phantom limb pain, for whom conventional treatments failed, were enrolled. After 12 sessions, patients showed statistically and clinically significant improvements in all metrics of phantom limb pain. Phantom limb pain decreased from pre-treatment to the last treatment session by 47% (SD 39; absolute mean change 1·0 [0·8]; p=0·001) for weighted pain distribution, 32% (38; absolute mean change 1·6 [1·8]; p=0·007) for the numeric rating scale, and 51% (33; absolute mean change 9·6 [8·1]; p=0·0001) for the pain rating index. The numeric rating scale score for intrusion of phantom limb pain in activities of daily living and sleep was reduced by 43% (SD 37; absolute mean change 2·4 [2·3]; p=0·004) and 61% (39; absolute mean change 2·3 [1·8]; p=0·001), respectively. Two of four patients who were on medication reduced their intake by 81% (absolute reduction 1300 mg, gabapentin) and 33% (absolute reduction 75 mg, pregabalin). Improvements remained 6 months after the last treatment. Interpretation Our findings suggest potential value in Motor Execution of the phantom limb as a treatment for phantom limb pain. Promotion of phantom Motor Execution aided by machine learning, augmented and virtual reality, and gaming is a non-invasive, non-pharmacological, and engaging treatment with no identified side-effects at present. Funding Promobilia Foundation, VINNOVA, Jimmy Dahlstens Fond, PicoSolve, and Innovationskontor Vast.

Jiwoong Choi - One of the best experts on this subject based on the ideXlab platform.

  • convolutional neural network for high accuracy functional near infrared spectroscopy in a brain computer interface three class classification of rest right and left hand Motor Execution
    Neurophotonics, 2017
    Co-Authors: Thanawin Trakoolwilaiwan, Bahareh Behboodi, Jiwoong Choi
    Abstract:

    The aim of this work is to develop an effective brain–computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI. In this study, the hemodynamic responses evoked by performing rest, right-, and left-hand Motor Execution tasks were measured on eight healthy subjects to compare performances. Our CNN-based method provided improvements in classification accuracy over conventional methods employing the most commonly used features of mean, peak, slope, variance, kurtosis, and skewness, classified by support vector machine (SVM) and artificial neural network (ANN). Specifically, up to 6.49% and 3.33% improvement in classification accuracy was achieved by CNN compared with SVM and ANN, respectively.

  • Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain–computer interface: three-class classification of rest, right-, and left-hand Motor Execution
    Neurophotonics, 2017
    Co-Authors: Thanawin Trakoolwilaiwan, Bahareh Behboodi, Jiwoong Choi
    Abstract:

    The aim of this work is to develop an effective brain–computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI. In this study, the hemodynamic responses evoked by performing rest, right-, and left-hand Motor Execution tasks were measured on eight healthy subjects to compare performances. Our CNN-based method provided improvements in classification accuracy over conventional methods employing the most commonly used features of mean, peak, slope, variance, kurtosis, and skewness, classified by support vector machine (SVM) and artificial neural network (ANN). Specifically, up to 6.49% and 3.33% improvement in classification accuracy was achieved by CNN compared with SVM and ANN, respectively.

John L Bradshaw - One of the best experts on this subject based on the ideXlab platform.

  • Motor preparation Motor Execution attention and executive functions in attention deficit hyperactivity disorder adhd
    Child Neuropsychology, 2005
    Co-Authors: Ester Ivonne Klimkeit, Jason B Mattingley, Dianne Melinda Sheppard, John L Bradshaw
    Abstract:

    Attention and executive functions were investigated in medicated and unmedicated children with ADHD combined type using a novel selective reaching task. This task involved responding as rapidly as possible to a target while at times having to ignore a distractor. Results indicated that unmedicated children with ADHD showed slow and inaccurate responding. Slow responding reflected problems at the stage of movement preparation but not movement Execution. An attentional impairment, rather than a Motor planning problem per se, appeared to underlie the slow movement preparation. Inaccurate responding reflected problems with response inhibition and selective attention, impulsivity, set-shifting, and difficulties in maintaining vigilance. Although medicated children with ADHD did not show slow movement preparation, they did show some response inaccuracy, resulting especially from impulsive responding.These findings suggest that ADHD is characterized by slow Motor preparation (but not Motor Execution), and defici...

  • Motor PREPARATION, Motor Execution, ATTENTION, AND EXECUTIVE FUNCTIONS IN ATTENTION DEFICIT/HYPERACTIVITY DISORDER (ADHD)
    Child Neuropsychology, 2005
    Co-Authors: Ester Ivonne Klimkeit, Jason B Mattingley, Dianne Melinda Sheppard, John L Bradshaw
    Abstract:

    Attention and executive functions were investigated in medicated and unmedicated children with ADHD combined type using a novel selective reaching task. This task involved responding as rapidly as possible to a target while at times having to ignore a distractor. Results indicated that unmedicated children with ADHD showed slow and inaccurate responding. Slow responding reflected problems at the stage of movement preparation but not movement Execution. An attentional impairment, rather than a Motor planning problem per se, appeared to underlie the slow movement preparation. Inaccurate responding reflected problems with response inhibition and selective attention, impulsivity, set-shifting, and difficulties in maintaining vigilance. Although medicated children with ADHD did not show slow movement preparation, they did show some response inaccuracy, resulting especially from impulsive responding.These findings suggest that ADHD is characterized by slow Motor preparation (but not Motor Execution), and defici...

Mukesh Dhamala - One of the best experts on this subject based on the ideXlab platform.

  • functional organization and restoration of the brain Motor Execution network after stroke and rehabilitation
    Frontiers in Human Neuroscience, 2015
    Co-Authors: Sahil Bajaj, Andrew J Butler, Daniel Drake, Mukesh Dhamala
    Abstract:

    Multiple cortical areas of the human brain Motor system interact coherently in the low frequency range (< 0.1 Hz), even in the absence of explicit tasks. Following stroke, cortical interactions are functionally disturbed. How these interactions are affected and how the functional organization is regained from rehabilitative treatments as people begin to recover Motor behaviors has not been systematically studied. We recorded the intrinsic functional magnetic resonance imaging (fMRI) signals from 30 participants: 17 young healthy controls and 13 aged stroke survivors. Stroke participants underwent mental practice (MP) or both mental practice and physical therapy (MP + PT) within 14-51 days following stroke. We investigated the network activity of five core areas in the Motor-Execution network, consisting of the left primary Motor area (LM1), the right primary Motor area (RM1), the left pre-Motor cortex (LPMC), the right pre-Motor cortex (RPMC) and the supplementary Motor area (SMA). We discovered that (i) the network activity dominated in the frequency range 0.06 Hz – 0.08 Hz for all the regions, and for both able-bodied and stroke participants (ii) the causal information flow between the regions: LM1 and SMA, RPMC and SMA, RPMC and LM1, SMA and RM1, SMA and LPMC, was reduced significantly for stroke survivors (iii) the flow did not increase significantly after MP alone and (iv) the flow among the regions during MP+PT increased significantly. We also found that sensation and Motor scores were significantly higher and correlated with directed functional connectivity measures when the stroke-survivors underwent MP+PT but not MP alone. The findings provide evidence that a combination of mental practice and physical therapy can be an effective means of treatment for stroke survivors to recover or regain the strength of Motor behaviors, and that the spectra of causal information flow can be used as a reliable biomarker for evaluating rehabilitation in stroke survivors.

  • brain effective connectivity during Motor imagery and Execution following stroke and rehabilitation
    NeuroImage: Clinical, 2015
    Co-Authors: Sahil Bajaj, Andrew J Butler, Daniel Drake, Mukesh Dhamala
    Abstract:

    Brain areas within the Motor system interact directly or indirectly during Motor-imagery and Motor-Execution tasks. These interactions and their functionality can change following stroke and recovery. How brain network interactions reorganize and recover their functionality during recovery and treatment following stroke are not well understood. To contribute to answering these questions, we recorded blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) signals from 10 stroke survivors and evaluated dynamical causal modeling (DCM)-based effective connectivity among three Motor areas: primary Motor cortex (M1), pre-Motor cortex (PMC) and supplementary Motor area (SMA), during Motor-imagery and Motor-Execution tasks. We compared the connectivity between affected and unaffected hemispheres before and after mental practice and combined mental practice and physical therapy as treatments. The treatment (intervention) period varied in length between 14 to 51 days but all patients received the same dose of 60 h of treatment. Using Bayesian model selection (BMS) approach in the DCM approach, we found that, after intervention, the same network dominated during Motor-imagery and Motor-Execution tasks but modulatory parameters suggested a suppressive influence of SM A on M1 during the Motor-imagery task whereas the influence of SM A on M1 was unrestricted during the Motor-Execution task. We found that the intervention caused a reorganization of the network during both tasks for unaffected as well as for the affected hemisphere. Using Bayesian model averaging (BMA) approach, we found that the intervention improved the regional connectivity among the Motor areas during both the tasks. The connectivity between PMC and M1 was stronger in Motor-imagery tasks whereas the connectivity from PMC to M1, SM A to M1 dominated in Motor-Execution tasks. There was significant behavioral improvement (p = 0.001) in sensation and Motor movements because of the intervention as reflected by behavioral Fugl-Meyer (FMA) measures, which were significantly correlated (p = 0.05) with a subset of connectivity. These findings suggest that PMC and M1 play a crucial role during Motor-imagery as well as during Motor-Execution task. In addition, M1 causes more exchange of causal information among Motor areas during a Motor-Execution task than during a Motor-imagery task due to its interaction with SM A. This study expands our understanding of Motor network involved during two different tasks, which are commonly used during rehabilitation following stroke. A clear understanding of the effective connectivity networks leads to a better treatment in helping stroke survivors regain Motor ability.

Karen T Reilly - One of the best experts on this subject based on the ideXlab platform.

  • Disentangling Motor Execution from Motor imagery with the phantom limb.
    Brain : a journal of neurology, 2020
    Co-Authors: Estelle Raffin, Karen T Reilly, Jeremie Mattout, Pascal Giraux
    Abstract:

    Amputees can move their phantom limb at will. These 'movements without movements' have generally been considered as Motor imagery rather than Motor Execution, but amputees can in fact perform both executed and imagined movements with their phantom and they report distinct perceptions during each task. Behavioural evidence for this dual ability comes from the fact that executed movements are associated with stump muscle contractions whereas imagined movements are not, and that phantom executed movements are slower than intact hand executed movements whereas the speed of imagined movements is identical for both hands. Since neither Execution nor imagination produces any visible movement, we hypothesized that the perceptual difference between these two Motor tasks relies on the activation of distinct cerebral networks. Using functional magnetic resonance imaging and changes in functional connectivity (dynamic causal modelling), we examined the activity associated with imagined and executed movements of the intact and phantom hands of 14 upper-limb amputees. Distinct but partially overlapping cerebral networks were active during both executed and imagined phantom limb movements (both performed at the same speed). A region of interest analysis revealed a 'switch' between Execution and imagination; during Execution there was more activity in the primary somatosensory cortex, the primary Motor cortex and the anterior lobe of the cerebellum, while during imagination there was more activity in the parietal and occipital lobes, and the posterior lobe of the cerebellum. In overlapping areas, task-related differences were detected in the location of activation peaks. The dynamic causal modelling analysis further confirmed the presence of a clear neurophysiological distinction between imagination and Execution, as Motor imagery and Motor Execution had opposite effects on the supplementary Motor area-primary Motor cortex network. This is the first imaging evidence that the neurophysiological network activated during phantom limb movements is similar to that of executed movements of intact limbs and differs from the phantom limb imagination network. The dual ability of amputees to execute and imagine movements of their phantom limb and the fact that these two tasks activate distinct cortical networks are important factors to consider when designing rehabilitation programmes for the treatment of phantom limb pain.

  • the moving phantom Motor Execution or Motor imagery
    Cortex, 2012
    Co-Authors: Estelle Raffin, Pascal Giraux, Karen T Reilly
    Abstract:

    Abstract Amputees who have a phantom limb often report the ability to move this phantom voluntarily. In the literature, phantom limb movements are generally considered to reflect Motor imagery rather than Motor Execution. The aim of this study was to investigate whether amputees distinguish between executing a movement of the phantom limb and imagining moving the missing limb. We examined the capacity of 19 upper-limb amputees to execute and imagine movements of both their phantom and intact limbs. Their behaviour was compared with that of 18 age-matched normal controls. A global questionnaire-based assessment of imagery ability and timed tests showed that amputees can indeed distinguish between Motor Execution and Motor imagery with the phantom limb, and that the former is associated with activity in stump muscles while the latter is not. Amputation reduced the speed of voluntary movements with the phantom limb but did not change the speed of imagined movements, suggesting that the absence of the limb specifically affects the ability to voluntarily move the phantom but does not change the ability to imagine moving the missing limb. These results suggest that under some conditions, for example amputation, the predicted sensory consequences of a Motor command are sufficient to evoke the sensation of voluntary movement. They also suggest that the distinction between imagined and executed movements should be taken into consideration when designing research protocols to investigate the analgesic effects of sensoriMotor feedback.

  • disentangling Motor Execution from Motor imagery with the phantom limb
    Brain, 2012
    Co-Authors: Estelle Raffin, Karen T Reilly, Jeremie Mattout, Pascal Giraux
    Abstract:

    Amputees can move their phantom limb at will. These ‘movements without movements’ have generally been considered as Motor imagery rather than Motor Execution, but amputees can in fact perform both executed and imagined movements with their phantom and they report distinct perceptions during each task. Behavioural evidence for this dual ability comes from the fact that executed movements are associated with stump muscle contractions whereas imagined movements are not, and that phantom executed movements are slower than intact hand executed movements whereas the speed of imagined movements is identical for both hands. Since neither Execution nor imagination produces any visible movement, we hypothesized that the perceptual difference between these two Motor tasks relies on the activation of distinct cerebral networks. Using functional magnetic resonance imaging and changes in functional connectivity (dynamic causal modelling), we examined the activity associated with imagined and executed movements of the intact and phantom hands of 14 upper-limb amputees. Distinct but partially overlapping cerebral networks were active during both executed and imagined phantom limb movements (both performed at the same speed). A region of interest analysis revealed a ‘switch’ between Execution and imagination; during Execution there was more activity in the primary somatosensory cortex, the primary Motor cortex and the anterior lobe of the cerebellum, while during imagination there was more activity in the parietal and occipital lobes, and the posterior lobe of the cerebellum. In overlapping areas, task-related differences were detected in the location of activation peaks. The dynamic causal modelling analysis further confirmed the presence of a clear neurophysiological distinction between imagination and Execution, as Motor imagery and Motor Execution had opposite effects on the supplementary Motor area–primary Motor cortex network. This is the first imaging evidence that the neurophysiological network activated during phantom limb movements is similar to that of executed movements of intact limbs and differs from the phantom limb imagination network. The dual ability of amputees to execute and imagine movements of their phantom limb and the fact that these two tasks activate distinct cortical networks are important factors to consider when designing rehabilitation programmes for the treatment of phantom limb pain. * Abbreviations : M1 : primary Motor cortex SMA : supplementary Motor area