Publications by authors named "Mads Jochumsen"

63 Publications

Electroencephalographic Recording of the Movement-Related Cortical Potential in Ecologically Valid Movements: A Scoping Review.

Front Neurosci 2021 28;15:721387. Epub 2021 Sep 28.

Rehabilitation Innovation Centre, Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland, New Zealand.

The movement-related cortical potential (MRCP) is a brain signal that can be recorded using surface electroencephalography (EEG) and represents the cortical processes involved in movement preparation. The MRCP has been widely researched in simple, single-joint movements, however, these movements often lack ecological validity. Ecological validity refers to the generalizability of the findings to real-world situations, such as neurological rehabilitation. This scoping review aimed to synthesize the research evidence investigating the MRCP in ecologically valid movement tasks. A search of six electronic databases identified 102 studies that investigated the MRCP during multi-joint movements; 59 of these studies investigated ecologically valid movement tasks and were included in the review. The included studies investigated 15 different movement tasks that were applicable to everyday situations, but these were largely carried out in healthy populations. The synthesized findings suggest that the recording and analysis of MRCP signals is possible in ecologically valid movements, however the characteristics of the signal appear to vary across different movement tasks (i.e., those with greater complexity, increased cognitive load, or a secondary motor task) and different populations (i.e., expert performers, people with Parkinson's Disease, and older adults). The scarcity of research in clinical populations highlights the need for further research in people with neurological and age-related conditions to progress our understanding of the MRCPs characteristics and to determine its potential as a measure of neurological recovery and intervention efficacy. MRCP-based neuromodulatory interventions applied during ecologically valid movements were only represented in one study in this review as these have been largely delivered during simple joint movements. No studies were identified that used ecologically valid movements to control BCI-driven external devices; this may reflect the technical challenges associated with accurately classifying functional movements from MRCPs. Future research investigating MRCP-based interventions should use movement tasks that are functionally relevant to everyday situations. This will facilitate the application of this knowledge into the rehabilitation setting.
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http://dx.doi.org/10.3389/fnins.2021.721387DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505671PMC
September 2021

Detection of Error-Related Potentials in Stroke Patients from EEG Using an Artificial Neural Network.

Sensors (Basel) 2021 Sep 18;21(18). Epub 2021 Sep 18.

Department of Health Science and Technology, Aalborg University, 9000 Aalborg, Denmark.

Error-related potentials (ErrPs) have been proposed as a means for improving brain-computer interface (BCI) performance by either correcting an incorrect action performed by the BCI or label data for continuous adaptation of the BCI to improve the performance. The latter approach could be relevant within stroke rehabilitation where BCI calibration time could be minimized by using a generalized classifier that is continuously being individualized throughout the rehabilitation session. This may be achieved if data are correctly labelled. Therefore, the aims of this study were: (1) classify single-trial ErrPs produced by individuals with stroke, (2) investigate test-retest reliability, and (3) compare different classifier calibration schemes with different classification methods (artificial neural network, ANN, and linear discriminant analysis, LDA) with waveform features as input for meaningful physiological interpretability. Twenty-five individuals with stroke operated a sham BCI on two separate days where they attempted to perform a movement after which they received feedback (error/correct) while continuous EEG was recorded. The EEG was divided into epochs: ErrPs and NonErrPs. The epochs were classified with a multi-layer perceptron ANN based on temporal features or the entire epoch. Additionally, the features were classified with shrinkage LDA. The features were waveforms of the ErrPs and NonErrPs from the sensorimotor cortex to improve the explainability and interpretation of the output of the classifiers. Three calibration schemes were tested: within-day, between-day, and across-participant. Using within-day calibration, 90% of the data were correctly classified with the entire epoch as input to the ANN; it decreased to 86% and 69% when using temporal features as input to ANN and LDA, respectively. There was poor test-retest reliability between the two days, and the other calibration schemes led to accuracies in the range of 63-72% with LDA performing the best. There was no association between the individuals' impairment level and classification accuracies. The results show that ErrPs can be classified in individuals with stroke, but that user- and session-specific calibration is needed for optimal ErrP decoding with this approach. The use of ErrP/NonErrP waveform features makes it possible to have a physiological meaningful interpretation of the output of the classifiers. The results may have implications for labelling data continuously in BCIs for stroke rehabilitation and thus potentially improve the BCI performance.
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http://dx.doi.org/10.3390/s21186274DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8472485PMC
September 2021

The Danish Future Patient Telerehabilitation Program for Patients With Atrial Fibrillation: Design and Pilot Study in Collaboration With Patients and Their Spouses.

JMIR Cardio 2021 Jul 19;5(2):e27321. Epub 2021 Jul 19.

Department of Cardiology, Viborg and Skive Regional Hospital, Viborg, Denmark.

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is predicted to more than double in prevalence over the next 20 years. Tailored patient education is recommended as an important aspect of AF care. Current guidelines emphasize that patients become more active participants in the management of their own disease, yet there are no rehabilitation programs for patients with AF in the Danish health care system. Through participatory design, we developed the Future Patient Telerehabilitation (TR) Programs, A and B, for patients with AF. The 2 programs are based on HeartPortal and remote monitoring, together with educational modules.

Objective: The aim of this pilot study is to evaluate and compare the feasibility of the 2 programs of TR for patients with AF.

Methods: This pilot study was conducted between December 2019 and March 2020. The pilot study consisted of testing the 2 TR programs, A and B, in two phases: (1) treatment at the AF clinic and (2) TR at home. The primary outcome of the study was the usability of technologies for self-monitoring and the context of the TR programs as seen from patients' perspectives. Secondary outcomes were the development of patients' knowledge of AF, development of clinical data, and understanding the expectations and experiences of patients and spouses. Data were collected through interviews, questionnaires, and clinical measurements from home monitoring devices. Statistical analyses were performed using the IBM SPSS Statistics version 26. Qualitative data were analyzed using NVivo 12.0.

Results: Through interviews, patients articulated the following themes about participating in a TR program: usefulness of the HeartPortal, feeling more secure living with AF, community of practice living with AF, and measuring heart rhythm makes good sense. Through interviews, the spouses of patients with AF expressed that they had gained increased knowledge about AF and how to support their spouses living with AF in everyday life. Results from the responses to the Jessa AF Knowledge Questionnaire support the qualitative data, as they showed that patients in program B acquired increased knowledge about AF at follow-up compared with baseline. No significant differences were found in the number of electrocardiography recordings between the 2 groups.

Conclusions: Patients with AF and their spouses were positive about the TR program and they found the TR program useful, especially because it created an increased sense of security, knowledge about mastering their symptoms, and a community of practice linking patients with AF and their spouses and health care personnel. To assess all the benefits of the Future Patient-TR Program for patients with AF, it needs to be tested in a comprehensive randomized controlled trial.

Trial Registration: ClinicalTrials.gov NCT04493437; https://clinicaltrials.gov/ct2/show/NCT04493437.
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http://dx.doi.org/10.2196/27321DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329756PMC
July 2021

Investigating the Intervention Parameters of Endogenous Paired Associative Stimulation (ePAS).

Brain Sci 2021 Feb 12;11(2). Epub 2021 Feb 12.

Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland 0627, New Zealand.

Advances in our understanding of neural plasticity have prompted the emergence of neuromodulatory interventions, which modulate corticomotor excitability (CME) and hold potential for accelerating stroke recovery. Endogenous paired associative stimulation (ePAS) involves the repeated pairing of a single pulse of peripheral electrical stimulation (PES) with endogenous movement-related cortical potentials (MRCPs), which are derived from electroencephalography. However, little is known about the optimal parameters for its delivery. A factorial design with repeated measures delivered four different versions of ePAS, in which PES intensities and movement type were manipulated. Linear mixed models were employed to assess interaction effects between PES intensity (suprathreshold (Hi) and motor threshold (Lo)) and movement type (Voluntary and Imagined) on CME. ePAS interventions significantly increased CME compared to control interventions, except in the case of Lo-Voluntary ePAS. There was an overall main effect for the Hi-Voluntary ePAS intervention immediately post-intervention ( = 0.002), with a sub-additive interaction effect at 30 min' post-intervention ( = 0.042). Hi-Imagined and Lo-Imagined ePAS significantly increased CME for 30 min post-intervention ( = 0.038 and = 0.043 respectively). The effects of the two PES intensities were not significantly different. CME was significantly greater after performing imagined movements, compared to voluntary movements, with motor threshold PES (Lo) 15 min post-intervention ( = 0.012). This study supports previous research investigating Lo-Imagined ePAS and extends those findings by illustrating that ePAS interventions that deliver suprathreshold intensities during voluntary or imagined movements (Hi-Voluntary and Hi-Imagined) also increase CME. Importantly, our findings indicate that stimulation intensity and movement type interact in ePAS interventions. Factorial designs are an efficient way to explore the effects of manipulating the parameters of neuromodulatory interventions. Further research is required to ensure that these parameters are appropriately refined to maximise intervention efficacy for people with stroke and to support translation into clinical practice.
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http://dx.doi.org/10.3390/brainsci11020224DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918620PMC
February 2021

Decoding of Ankle Joint Movements in Stroke Patients Using Surface Electromyography.

Sensors (Basel) 2021 Feb 24;21(5). Epub 2021 Feb 24.

Department of Health Science and Technology, Aalborg University, 9220 Aalborg Øst, Denmark.

Stroke is a cerebrovascular disease (CVD), which results in hemiplegia, paralysis, or death. Conventionally, a stroke patient requires prolonged sessions with physical therapists for the recovery of motor function. Various home-based rehabilitative devices are also available for upper limbs and require minimal or no assistance from a physiotherapist. However, there is no clinically proven device available for functional recovery of a lower limb. In this study, we explored the potential use of surface electromyography (sEMG) as a controlling mechanism for the development of a home-based lower limb rehabilitative device for stroke patients. In this experiment, three channels of sEMG were used to record data from 11 stroke patients while performing ankle joint movements. The movements were then decoded from the sEMG data and their correlation with the level of motor impairment was investigated. The impairment level was quantified using the Fugl-Meyer Assessment (FMA) scale. During the analysis, Hudgins time-domain features were extracted and classified using linear discriminant analysis (LDA) and artificial neural network (ANN). On average, 63.86% ± 4.3% and 67.1% ± 7.9% of the movements were accurately classified in an offline analysis by LDA and ANN, respectively. We found that in both classifiers, some motions outperformed others ( < 0.001 for LDA and = 0.014 for ANN). The Spearman correlation (ρ) was calculated between the FMA scores and classification accuracies. The results indicate that there is a moderately positive correlation (ρ = 0.75 for LDA and ρ = 0.55 for ANN) between the two of them. The findings of this study suggest that a home-based EMG system can be developed to provide customized therapy for the improvement of functional lower limb motion in stroke patients.
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http://dx.doi.org/10.3390/s21051575DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7956677PMC
February 2021

Potential synergy between PSMA uptake and tumour blood flow for prediction of human prostate cancer aggressiveness.

EJNMMI Res 2021 Feb 9;11(1):12. Epub 2021 Feb 9.

Department of Nuclear Medicine & PET-Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, 8200, Aarhus N, Denmark.

Background: Both prostate-specific membrane antigen (PSMA) uptake and tumour blood flow (TBF) correlate with International Society of Urological Pathology (ISUP) Grade Group (GG) and hence prostate cancer (PCa) aggressiveness. The aim of the present study was to evaluate the potential synergistic benefit of combining the two physiologic parameters for separating significant PCa from insignificant findings.

Methods: From previous studies of [Rb]Rb positron emission tomography (PET) TBF in PCa, the 43 patients that underwent clinical [Ga]Ga-PSMA-11 PET were selected for this retrospective study. Tumours were delineated on [Ga]Ga-PSMA-11 PET or magnetic resonance imaging. ISUP GG was recorded from 52 lesions.

Results: [Ga]Ga-PSMA-11 maximum standardized uptake value (SUVmax) and [Rb]Rb SUVmax correlated moderately with ISUP GG (rho = 0.59 and rho = 0.56, both p < 0.001) and with each other (r = 0.65, p < 0.001). A combined model of [Ga]Ga-PSMA-11 and [Rb]Rb SUVmax separated ISUP GG > 2 from ISUP GG 1-2 and benign with an area-under-the-curve of 0.85, 96% sensitivity, 74% specificity, and 95% negative predictive value. The combined model performed significantly better than either tracer alone did (p < 0.001), primarily by reducing false negatives from five or six to one (p ≤ 0.025).

Conclusion: PSMA uptake and TBF provide complementary information about tumour aggressiveness. We suggest that a combined analysis of PSMA uptake and TBF could significantly improve the negative predictive value and allow non-invasive separation of significant from insignificant PCa.
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http://dx.doi.org/10.1186/s13550-021-00757-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873172PMC
February 2021

Induction of Neural Plasticity Using a Low-Cost Open Source Brain-Computer Interface and a 3D-Printed Wrist Exoskeleton.

Sensors (Basel) 2021 Jan 15;21(2). Epub 2021 Jan 15.

Department of Health Science and Technology, Aalborg University, 9220 Aalborg, Denmark.

Brain-computer interfaces (BCIs) have been proven to be useful for stroke rehabilitation, but there are a number of factors that impede the use of this technology in rehabilitation clinics and in home-use, the major factors including the usability and costs of the BCI system. The aims of this study were to develop a cheap 3D-printed wrist exoskeleton that can be controlled by a cheap open source BCI (OpenViBE), and to determine if training with such a setup could induce neural plasticity. Eleven healthy volunteers imagined wrist extensions, which were detected from single-trial electroencephalography (EEG), and in response to this, the wrist exoskeleton replicated the intended movement. Motor-evoked potentials (MEPs) elicited using transcranial magnetic stimulation were measured before, immediately after, and 30 min after BCI training with the exoskeleton. The BCI system had a true positive rate of 86 ± 12% with 1.20 ± 0.57 false detections per minute. Compared to the measurement before the BCI training, the MEPs increased by 35 ± 60% immediately after and 67 ± 60% 30 min after the BCI training. There was no association between the BCI performance and the induction of plasticity. In conclusion, it is possible to detect imaginary movements using an open-source BCI setup and control a cheap 3D-printed exoskeleton that when combined with the BCI can induce neural plasticity. These findings may promote the availability of BCI technology for rehabilitation clinics and home-use. However, the usability must be improved, and further tests are needed with stroke patients.
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http://dx.doi.org/10.3390/s21020572DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830618PMC
January 2021

Decoding Attempted Hand Movements in Stroke Patients Using Surface Electromyography.

Sensors (Basel) 2020 Nov 26;20(23). Epub 2020 Nov 26.

Department of Biomedical Engineering & Sciences, School of Mechanical & Manufacturing Engineering, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.

Brain- and muscle-triggered exoskeletons have been proposed as a means for motor training after a stroke. With the possibility of performing different movement types with an exoskeleton, it is possible to introduce task variability in training. It is difficult to decode different movement types simultaneously from brain activity, but it may be possible from residual muscle activity that many patients have or quickly regain. This study investigates whether nine different motion classes of the hand and forearm could be decoded from forearm EMG in 15 stroke patients. This study also evaluates the test-retest reliability of a classical, but simple, classifier (linear discriminant analysis) and advanced, but more computationally intensive, classifiers (autoencoders and convolutional neural networks). Moreover, the association between the level of motor impairment and classification accuracy was tested. Three channels of surface EMG were recorded during the following motion classes: Hand Close, Hand Open, Wrist Extension, Wrist Flexion, Supination, Pronation, Lateral Grasp, Pinch Grasp, and Rest. Six repetitions of each motion class were performed on two different days. Hudgins time-domain features were extracted and classified using linear discriminant analysis and autoencoders, and raw EMG was classified with convolutional neural networks. On average, 79 ± 12% and 80 ± 12% (autoencoders) of the movements were correctly classified for days 1 and 2, respectively, with an intraclass correlation coefficient of 0.88. No association was found between the level of motor impairment and classification accuracy (Spearman correlation: 0.24). It was shown that nine motion classes could be decoded from residual EMG, with autoencoders being the best classification approach, and that the results were reliable across days; this may have implications for the development of EMG-controlled exoskeletons for training in the patient's home.
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http://dx.doi.org/10.3390/s20236763DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7730601PMC
November 2020

Evaluation of windowing techniques for intramuscular EMG-based diagnostic, rehabilitative and assistive devices.

J Neural Eng 2020 Nov 20. Epub 2020 Nov 20.

Department of Centre for chiropractic researchHealth Science and Technology, New Zealand College of Chiropractic, Auckland, NEW ZEALAND.

Objective: Intramuscular electromyography (iEMG) signals, non-invasively recorded, directly from the muscles are used to diagnose various neuromuscular disorders/diseases, also to control rehabilitative and assistive robotic devices. iEMG signals are being potentially used in neurology, kinesiology, rehabilitation, and ergonomics, to detect/diagnose various diseases/ disorders. Electromyography (EMG) based classification systems are being designed and tested for classification of various neuromuscular disorders and to control rehabilitative and assistive robotic devices. Many studies have explored parameters, such as pre-processing, feature extraction and selection of classifier that can affect the performance and efficacy of iEMG-based classification systems. Pre-processing stage includes removal of any unwanted noise from original signal and windowing of the signal.

Approach: This study investigated and presented optimum windowing configurations for robust control and better classification results of iEMG-based classification system. Both, disjoint and overlap, windowing techniques with varying window and overlap sizes have been investigated using a machine learning (ML) based classification algorithm called linear discriminant analysis (LDA).

Main Results: The optimum window size ranges are from 200ms to 300ms for disjoint and 225ms to 300ms for overlap windowing technique, respectively. The inferred results show that for overlap windowing technique the optimum range of overlap size is from 10% to 40% of the length of a window size. Mean classification accuracy (MCA) was found to be lower in disjoint windowing technique as compared to overlap windowing at all investigated overlap sizes. Statistical analysis (two-way analysis of variance test) showed that MCA of overlap windowing technique was significantly different at overlap sizes of 10% to 40% (p-values < 0.05).

Significance: These results can be used to achieve best possible classification performance for any iEMG based real-time diagnosis, detection, and control system.
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http://dx.doi.org/10.1088/1741-2552/abcc7fDOI Listing
November 2020

Avid 68Ga-PSMA Uptake in Periappendicular Abscess.

Clin Nucl Med 2020 Nov;45(11):929-930

From the Department of Nuclear Medicine & PET-Centre, Aarhus University Hospital, Aarhus, Denmark.

Ga-prostate-specific membrane antigen (PSMA) PET/CT for primary staging of high-risk prostate cancer revealed increased Ga-PSMA uptake in a known periappendicular abscess in a patient, who had undergone surgical drainage of the abscess 1 month earlier. The case presents another example of Ga-PSMA uptake in a benign infectious and inflammatory condition.
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http://dx.doi.org/10.1097/RLU.0000000000003290DOI Listing
November 2020

Classification of error-related potentials from single-trial EEG in association with executed and imagined movements: a feature and classifier investigation.

Med Biol Eng Comput 2020 Nov 30;58(11):2699-2710. Epub 2020 Aug 30.

Department of Health Science and Technology, Aalborg University, Fredrik Bajers Vej 7D, 9220, Aalborg, Denmark.

Error-related potentials (ErrPs) have been proposed for designing adaptive brain-computer interfaces (BCIs). Therefore, ErrPs must be decoded. The aim of this study was to evaluate ErrP decoding using combinations of different feature types and classifiers in BCI paradigms involving motor execution (ME) and imagination (MI). Fifteen healthy subjects performed 510 (ME) and 390 (MI) trials of right/left wrist extensions and foot dorsiflexions. Sham BCI feedback was delivered with an accuracy of 80% (ME) and 70% (MI). Continuous EEG was recorded and divided into ErrP and NonErrP epochs. Temporal, spectral, and discrete wavelet transform (DWT) marginals and template matching features were extracted, and all combinations of feature types were classified using linear discriminant analysis, support vector machine, and random forest classifiers. ErrPs were elicited for both ME and MI paradigms, and the average classification accuracies were significantly higher than the chance level. The highest average classification accuracy was obtained using temporal features and a combination of temporal + DWT features classified with random forest; 89 ± 9% and 83 ± 9% for ME and MI, respectively. These results generally indicate that temporal features should be used when detecting ErrPs, but there is great inter-subject variability, which means that user-specific features should be derived to maximize the performance. Graphical abstract.
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http://dx.doi.org/10.1007/s11517-020-02253-2DOI Listing
November 2020

Tumour blood flow for prediction of human prostate cancer aggressiveness: a study with Rubidium-82 PET, MRI and Na/K-ATPase-density.

Eur J Nucl Med Mol Imaging 2021 02 18;48(2):532-542. Epub 2020 Aug 18.

Department of Nuclear Medicine and PET-Centre, Aarhus University Hospital, Aarhus, Denmark.

Purpose: Tumour blood flow (TBF) is a crucial determinant of cancer growth. Recently, we validated Rubidium-82 (Rb) positron emission tomography (PET) for TBF measurement in prostate cancer (PCa) and found TBF and cancer aggressiveness positively correlated. The aims of the present study were to determine the ability of TBF for separating significant from insignificant PCa and to examine the relation to underlying Na/K-ATPase density, which is relevant as Rb is transported intracellularly via the Na/K-ATPase.

Methods: One hundred and two patients were included for pelvic Rb PET scan prior to magnetic resonance imaging (MRI)-guided prostate biopsy. Findings constituted 100 PCa lesions (86 patients) and 25 benign lesions (16 patients). Tumours were defined on MRI and transferred to Rb PET for TBF measurement. Immunohistochemical Na/K-ATPase staining was subsequently performed on biopsies.

Results: TBF was the superior predictor (rho = 0.68, p < 0.0001, inflammatory lesions excluded) of MRI-guided biopsy grade group (GG) over lowest apparent diffusion coefficient (ADC) value (rho = -0.23, p = 0.01), independent of ADC value and tumour volume (p < 0.0001). PET could separate GG-2-5 from GG-1 and benign lesions with an area under the curve (AUC), sensitivity, and specificity of 0.79, 96%, and 59%, respectively. For separating GG-3-5 from GG-1-2 and benign lesions the AUC, sensitivity, and specificity were 0.82, 95%, and 63%, respectively. Na/K-ATPase density per PCa cell profile was 38% lower compared with that of the benign prostate cell profiles. Neither cell density nor Na/K-ATPase density determined tumour Rb uptake.

Conclusion: TBF is an independent predictor of PCa aggressiveness and deserves more attention, as it may be valuable in separating clinically significant from insignificant PCa.
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http://dx.doi.org/10.1007/s00259-020-04998-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835182PMC
February 2021

Decoding kinetic features of hand motor preparation from single-trial EEG using convolutional neural networks.

Eur J Neurosci 2021 01 25;53(2):556-570. Epub 2020 Aug 25.

Institute for Research and Development in Bioengineering and Bioinformatics (IBB), CONICET-UNER, Oro Verde, Argentina.

Building accurate movement decoding models from brain signals is crucial for many biomedical applications. Predicting specific movement features, such as speed and force, before movement execution may provide additional useful information at the expense of increasing the complexity of the decoding problem. Recent attempts to predict movement speed and force from the electroencephalogram (EEG) achieved classification accuracies at or slightly above chance levels, highlighting the need for more accurate prediction strategies. Thus, the aims of this study were to accurately predict hand movement speed and force from single-trial EEG signals and to decode neurophysiological information of motor preparation from the prediction strategies. To these ends, a decoding model based on convolutional neural networks (ConvNets) was implemented and compared against other state-of-the-art prediction strategies, such as support vector machines and decision trees. ConvNets outperformed the other prediction strategies, achieving an overall accuracy of 84% in the classification of two different levels of speed and force (four-class classification) from pre-movement single-trial EEG (100 ms and up to 1,600 ms prior to movement execution). Furthermore, an analysis of the ConvNet architectures suggests that the network performs a complex spatiotemporal integration of EEG data to optimize classification accuracy. These results show that movement speed and force can be accurately predicted from single-trial EEG, and that the prediction strategies may provide useful neurophysiological information about motor preparation.
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http://dx.doi.org/10.1111/ejn.14936DOI Listing
January 2021

A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN.

Sensors (Basel) 2020 Jun 15;20(12). Epub 2020 Jun 15.

Centre for Robotics Research, Department of Informatics, King's College London, London WC2R 2LS, UK.

Recent developments in implantable technology, such as high-density recordings, wireless transmission of signals to a prosthetic hand, may pave the way for intramuscular electromyography (iEMG)-based myoelectric control in the future. This study aimed to investigate the real-time control performance of iEMG over time. A novel protocol was developed to quantify the robustness of the real-time performance parameters. Intramuscular wires were used to record EMG signals, which were kept inside the muscles for five consecutive days. Tests were performed on multiple days using Fitts' law. Throughput, completion rate, path efficiency and overshoot were evaluated as performance metrics using three train/test strategies. Each train/test scheme was categorized on the basis of data quantity and the time difference between training and testing data. An artificial neural network (ANN) classifier was trained and tested on (i) data from the same day (WDT), (ii) data collected from the previous day and tested on present-day (BDT) and (iii) trained on all previous days including the present day and tested on present-day (CDT). It was found that the completion rate (91.6 ± 3.6%) of CDT was significantly better ( < 0.01) than BDT (74.02 ± 5.8%) and WDT (88.16 ± 3.6%). For BDT, on average, the first session of each day was significantly better ( < 0.01) than the second and third sessions for completion rate (77.9 ± 14.0%) and path efficiency (88.9 ± 16.9%). Subjects demonstrated the ability to achieve targets successfully with wire electrodes. Results also suggest that time variations in the iEMG signal can be catered by concatenating the data over several days. This scheme can be helpful in attaining stable and robust performance.
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http://dx.doi.org/10.3390/s20123385DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349229PMC
June 2020

Detection and classification of single-trial movement-related cortical potentials associated with functional lower limb movements.

J Neural Eng 2020 07 3;17(3):035009. Epub 2020 Jul 3.

SMI, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. Author to whom any correspondence should be addressed.

Objective: Brain-computer interfaces that activate exoskeletons based on decoded movement-related activity have been shown to be useful for stroke rehabilitation. With the advances in the development of exoskeletons it is possible to replicate a number of different functional movements that are relevant to rehabilitate after stroke. In this study, the aim is to detect and classify six different movement tasks of the lower extremities that are used in the activities of daily living.

Approach: Thirteen healthy subjects performed six movement tasks (1) Stand-to-sit, (2) Sit-to-stand, (3) Walking, (4) Step up, (5) Side step, and (6) Back step. Each movement task was performed 50 times while continuous EEG was recorded. The continuous EEG was divided into epochs containing the movement intention associated with the movements, and idle activity was obtained from recordings during rest. Temporal, spectral and template matching features were extracted from the EEG channels covering the motor cortex and classified using Random Forest in two ways: (1) movement intention vs. idle activity (estimate of movement intention detection), and (2) classification of movement types.

Main Results: The classification accuracies associated with movement intention detection were in the range of 80%-90%, while 54 ± 3% of all movement types were classified correctly. The stand-to-sit and sit-to-stand tasks were easiest to classify, while step up often was classified as walking.

Significance: The results indicate that it is possible to detect and classify functional movements of the lower extremities from single-trial EEG. This may be implemented in a brain-computer interface that can control an exoskeleton and be used for neurorehabilitation.
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http://dx.doi.org/10.1088/1741-2552/ab9a99DOI Listing
July 2020

Peripheral Electrical Stimulation Paired With Movement-Related Cortical Potentials Improves Isometric Muscle Strength and Voluntary Activation Following Stroke.

Front Hum Neurosci 2020 15;14:156. Epub 2020 May 15.

Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland, New Zealand.

Background: Endogenous paired associative stimulation (ePAS) is a neuromodulatory intervention that has potential to aid stroke recovery. ePAS involves pairing endogenous electroencephalography (EEG) signals known as movement-related cortical potentials (MRCPs), with peripheral electrical stimulation. Previous studies have used transcranial magnetic stimulation (TMS) to demonstrate changes in corticomotor excitability following ePAS. However, the use of TMS as a measure in stroke research is limited by safety precautions, intolerance, and difficulty generating a measurable response in more severely affected individuals. We were interested in evaluating the effect of ePAS using more feasible measures in people with stroke. This study asks whether ePAS produces immediate improvements in the primary outcomes of maximal voluntary isometric contraction (MVIC) and total neuromuscular fatigue of the dorsiflexor muscles, and in the secondary outcomes of muscle power, voluntary activation (VA), central fatigue, peripheral fatigue, and electromyography activity.

Method: In this repeated-measures cross-over study, 15 participants with chronic stroke completed two interventions, ePAS and sham, in a randomized order. During ePAS, 50 repetitions of visually cued dorsiflexion were completed, while single pulses of electrical stimulation were delivered to the deep branch of the common peroneal nerve. Each somatosensory volley was timed to arrive in the primary motor cortex at the peak negativity of the MRCP. Univariate and multivariate linear mixed models were used to analyze the primary and secondary data, respectively.

Results: There was a statistically significant increase in dorsiflexor MVIC immediately following the ePAS intervention (mean increase 7 N), compared to the sham intervention (mean change 0 N) (univariate between-condition analysis = 0.047). The multivariate analysis revealed a statistically significant effect of ePAS on VA of the tibialis anterior muscle, such that ePAS increased VA by 7 percentage units (95% confidence interval 1.3-12.7%). There was no statistically significant effect on total neuromuscular fatigue, muscle power, or other secondary measures.

Conclusion: A single session of ePAS can significantly increase isometric muscle strength and VA in people with chronic stroke. The findings confirm that ePAS has a central neuromodulatory mechanism and support further exploration of its potential as an adjunct to stroke rehabilitation. In addition, the findings offer alternative, feasible outcome measures for future research.

Clinical Trial Registration: Australia New Zealand Clinical Trials Registry ACTRN12617000838314 (www.anzctr.org.au), Universal Trial Number U111111953714.
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http://dx.doi.org/10.3389/fnhum.2020.00156DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242792PMC
May 2020

Ga-PSMA PET/CT for Primary Lymph Node and Distant Metastasis NM Staging of High-Risk Prostate Cancer.

J Nucl Med 2021 02 22;62(2):214-220. Epub 2020 May 22.

Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark.

With the largest high-risk prostate cancer (PCa) cohort to date undergoing Ga-prostate-specific membrane antigen (PSMA) PET/CT primary staging, we aimed to, first, characterize the metastatic spread of PCa in relation to tumor Ga-PSMA uptake and the D'Amico classification and, second, compare Ga-PSMA PET/CT findings with radical prostatectomy and pelvic lymph node dissection (PLND) histopathology findings. The study included 691 consecutive newly diagnosed, biopsy-proven, treatment-naïve, D'Amico high-risk PCa patients primary-staged by Ga-PSMA PET/CT. PSMA SUV and metastatic findings were compared with prostate-specific antigen level, International Society of Urological Pathology (ISUP) grade, and clinical stage as traditional risk stratification parameters. Moreover, Ga-PSMA PET/CT findings were compared with histology findings in radical prostatectomy patients undergoing PLND. Undetected lymph node metastases (LNMs) underwent immunohistochemical PSMA staining. Advanced disease (N1/M1) was observed in 35.3% of patients (244/691) and was associated with increasing prostate-specific antigen level, ISUP grade, and clinical stage. LNMs (N1/M1a) were detected in 31.4% (217/691) and bone metastases (M1b) in 16.8% (116/691). Advanced disease frequencies in patients with ISUP grades 2 and 3 were 10.8% (11/102) and 37.1% (33/89), respectively. Risk of advanced disease for cT2a, cT2b, and cT2c tumors was almost equal (24.2%, 27.9%, and 22.4%, respectively). We observed a weak correlation between SUV and biopsy ISUP grade (ρ = 0.21; < 0.001) and a modest correlation between SUV and postprostatectomy ISUP grade (ρ = 0.38; < 0.001). Sensitivity, specificity, positive and negative predictive value, and accuracy for LNM detection on Ga-PSMA PET/CT in the PLND cohort were 30.6%, 96.5%, 68.8%, 84.5%, and 83.1%, respectively. Undetected LNMs either were micrometastases located in the lymph node border or were without PSMA expression. In this high-risk PCa cohort, we identified advanced disease in about one third at diagnosis. ISUP grade was the superior predictor for advanced disease at diagnosis. We found a significant difference in frequency of advanced disease between ISUP grades 2 and 3, as supports the Gleason score 7 subdivision. Interestingly, we observed no significant differences in risk of advanced disease when comparing the different cT2 stages. The undetected LNMs were either PSMA-negative or micrometastases.
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http://dx.doi.org/10.2967/jnumed.120.245605DOI Listing
February 2021

EEG Headset Evaluation for Detection of Single-Trial Movement Intention for Brain-Computer Interfaces.

Sensors (Basel) 2020 May 14;20(10). Epub 2020 May 14.

Department of Engineering-Electrical and Computer Engineering, Aarhus University, 8200 Aarhus, Denmark.

Brain-computer interfaces (BCIs) can be used in neurorehabilitation; however, the literature about transferring the technology to rehabilitation clinics is limited. A key component of a BCI is the headset, for which several options are available. The aim of this study was to test four commercially available headsets' ability to record and classify movement intentions (movement-related cortical potentials-MRCPs). Twelve healthy participants performed 100 movements, while continuous EEG was recorded from the headsets on two different days to establish the reliability of the measures: classification accuracies of single-trials, number of rejected epochs, and signal-to-noise ratio. MRCPs could be recorded with the headsets covering the motor cortex, and they obtained the best classification accuracies (73%-77%). The reliability was moderate to good for the best headset (a gel-based headset covering the motor cortex). The results demonstrate that, among the evaluated headsets, reliable recordings of MRCPs require channels located close to the motor cortex and potentially a gel-based headset.
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http://dx.doi.org/10.3390/s20102804DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7287803PMC
May 2020

Renal Potassium Excretion Visualized on Rubidium PET/CT.

Nucl Med Mol Imaging 2020 Apr 15;54(2):120-122. Epub 2020 Apr 15.

1Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, 8200 Aarhus N, Denmark.

The positron emission tomography (PET) flow tracer Rubidium is a known potassium analogue. During our studies of tumor blood flow in prostate cancer, we found that approximately 10% of the patients had high urinary Rubidium activity. In roughly half of these patients, the increased renal rubidium/potassium excretion was either causing hypokalemia or explained by Thiazide treatment. In the other half, there was no obvious explanation or clinical consequence of the renal rubidium/potassium excretion. This is the first time enhanced renal potassium excretion is visualized on Rubidium PET/CT.
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http://dx.doi.org/10.1007/s13139-020-00637-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198679PMC
April 2020

Deep Breathing Increases Heart Rate Variability in Patients With Rheumatoid Arthritis and Systemic Lupus Erythematosus.

J Clin Rheumatol 2021 Oct;27(7):261-266

From the SMI, Department of Health Science and Technology, Aalborg University.

Background/objective: Autoimmune diseases such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) have been associated with an impaired function of the autonomic nervous system and reduced vagus nerve (VN) tone measured through lower heart rate variability (HRV). Targeting the VN through electrical stimulation has been proposed as a treatment strategy with promising results in patients with RA. Moreover, it has been suggested that the VN can be stimulated physiologically through deep breathing. In this study, the aim was to investigate if the VN can be stimulated through deep breathing in patients with RA and SLE, as measured by HRV.

Methods: Fifty-seven patients with RA and SLE performed deep breathing exercises for 30 minutes in this explorative study. Before the breathing exercise, 2 electrocardiogram recordings were obtained to determine the patient's baseline HRV during rest. After the 30-minute breathing exercise, 5 minutes of electrocardiogram recordings were obtained to determine postintervention HRV and used as a measure of vagal activity.

Results: No change was observed in the HRV between the 2 recordings prior the exercise, but the heart rate and HRV significantly decreased and increased, respectively, after the deep breathing exercise.

Conclusions: HRV can be modulated in patients with RA and SLE; this may have implications for future treatment with medications in conjunction with deep breathing. However, the biological and clinical effect of deep breathing must be investigated in future studies.
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http://dx.doi.org/10.1097/RHU.0000000000001300DOI Listing
October 2021

Evaluation of EEG Headset Mounting for Brain-Computer Interface-Based Stroke Rehabilitation by Patients, Therapists, and Relatives.

Front Hum Neurosci 2020 14;14:13. Epub 2020 Feb 14.

Laboratory of Welfare Technologies, Telehealth and Telerehabilitation, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.

Brain-computer interfaces (BCIs) have successfully been used for motor recovery training in stroke patients. However, the setup of BCI systems is complex and may be divided into (1) mounting the headset and (2) calibration of the BCI. One of the major problems is mounting the headset for recording brain activity in a stroke rehabilitation context, and usability testing of this is limited. In this study, the aim was to compare the translational aspects of mounting five different commercially available headsets from a user perspective and investigate the design considerations associated with technology transfer to rehabilitation clinics and home use. No EEG signals were recorded, so the effectiveness of the systems have not been evaluated. Three out of five headsets covered the motor cortex which is needed to pick up movement intentions of attempted movements. The other two were as control and reference for potential design considerations. As primary stakeholders, nine stroke patients, eight therapists and two relatives participated; the stroke patients mounted the headsets themselves. The setup time was recorded, and participants filled in questionnaires related to comfort, aesthetics, setup complexity, overall satisfaction, and general design considerations. The patients had difficulties in mounting all headsets except for a headband with a dry electrode located on the forehead (control). The therapists and relatives were able to mount all headsets. The fastest headset to mount was the headband, and the most preferred headsets were the headband and a behind-ear headset (control). The most preferred headset that covered the motor cortex used water-based electrodes. The patients reported that it was important that they could mount the headset themselves for them to use it every day at home. These results have implications for design considerations for the development of BCI systems to be used in rehabilitation clinics and in the patient's home.
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http://dx.doi.org/10.3389/fnhum.2020.00013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033449PMC
February 2020

Upper limb complex movements decoding from pre-movement EEG signals using wavelet common spatial patterns.

Comput Methods Programs Biomed 2020 Jan 9;183:105076. Epub 2019 Sep 9.

Centre for Chiropractic Research, New Zealand College of Chiropractic, Auckland, New Zealand; Faculty of Health & Environmental Sciences, Health & Rehabilitation Research Institute, AUT University, Auckland, New Zealand; Centre for Sensory-Motor Interactions (SMI), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. Electronic address:

Background And Objective: Decoding functional movements from electroencephalographic (EEG) activity for motor disability rehabilitation is essential to develop home-use brain-computer interface systems. In this paper, the classification of five complex functional upper limb movements is studied by using only the pre-movement planning and preparation recordings of EEG data.

Methods: Nine healthy volunteers performed five different upper limb movements. Different frequency bands of the EEG signal are extracted by the stationary wavelet transform. Common spatial patterns are used as spatial filters to enhance separation of the five movements in each frequency band. In order to increase the efficiency of the system, a mutual information-based feature selection algorithm is applied. The selected features are classified using the k-nearest neighbor, support vector machine, and linear discriminant analysis methods.

Results: K-nearest neighbor method outperformed the other classifiers and resulted in an average classification accuracy of 94.0 ± 2.7% for five classes of movements across subjects. Further analysis of each frequency band's contribution in the optimal feature set, showed that the gamma and beta frequency bands had the most contribution in the classification. To reduce the complexity of the EEG recording system setup, we selected a subset of the 10 most effective EEG channels from 64 channels, by which we could reach an accuracy of 70%. Those EEG channels were mostly distributed over the prefrontal and frontal areas.

Conclusions: Overall, the results indicate that it is possible to classify complex movements before the movement onset by using spatially selected EEG data.
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http://dx.doi.org/10.1016/j.cmpb.2019.105076DOI Listing
January 2020

EMG- Versus EEG-Triggered Electrical Stimulation for Inducing Corticospinal Plasticity.

IEEE Trans Neural Syst Rehabil Eng 2019 09 31;27(9):1901-1908. Epub 2019 Jul 31.

Brain-computer interfaces have been proposed for stroke rehabilitation. Motor cortical activity derived from the electroencephalography (EEG) can trigger external devices that provide congruent sensory feedback. However, many stroke patients regain residual muscle (EMG: electromyography) control due to spontaneous recovery and rehabilitation; therefore, EEG may not be necessary as a control signal. In this paper, a direct comparison was made between the induction of corticospinal plasticity using either EEG- or EMG-controlled electrical nerve stimulation. Twenty healthy participants participated in two intervention sessions consisting of EEG- and EMG-controlled electrical stimulation. The sessions consisted of 50 pairings between foot dorsiflexion movements (decoded through either EEG or EMG) and electrical stimulation of the common peroneal nerve. Before, immediately after and 30 minutes after the intervention, 15 motor evoked potentials (MEPs) were elicited in tibialis anterior through transcranial magnetic stimulation. Increased MEPs were observed immediately after (62 ± 26%, 73 ± 27% for EEG- and EMG-triggered electrical stimulation, respectively) and 30 minutes after each of the two interventions (79 ± 26% and 72 ± 27%) compared to the pre-intervention measurement. There was no difference between the interventions. Both EEG- and EMG-controlled electrical stimulation can induce corticospinal plasticity which suggests that stroke patients with residual EMG can use that modality instead of EEG to trigger stimulation.
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http://dx.doi.org/10.1109/TNSRE.2019.2932104DOI Listing
September 2019

68Ga-PSMA Uptake in Escherichia coli Spondylodiscitis.

Clin Nucl Med 2019 Nov;44(11):916-919

From the Departments of Nuclear Medicine & PET-Centre.

In a patient with recently diagnosed intermediate-risk prostate cancer, Ga-prostate-specific-membrane-antigen (PSMA) PET/CT for primary staging discovered increased Ga-PSMA uptake in spondylodiscitis in the thoracic spine. The bacteria Escherichia coli was found both in blood cultures and bone biopsies from the thoracic lesion. This case presents spondylodiscitis as a potential benign pitfall to be aware of when interpreting PSMA PET/CT in prostate cancer patients.
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http://dx.doi.org/10.1097/RLU.0000000000002752DOI Listing
November 2019

Repeatability of tumor blood flow quantification with Rubidium PET/CT in prostate cancer - a test-retest study.

EJNMMI Res 2019 Jul 4;9(1):58. Epub 2019 Jul 4.

Department of Nuclear Medicine and PET-Centre, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, 8200, Aarhus N, Denmark.

Background: Non-invasive tumor blood flow (TBF) quantification is a candidate approach for risk stratification and monitoring of prostate cancer patients. Validation data have recently been published on prostate TBF measurement with the widely used positron emission tomography (PET) flow tracer Rubidium (Rb). However, no test-retest data is available for TBF measurement with Rb PET in prostate cancer. Such information is important to determine the potential clinical usefulness of the technique. The aim of the present study was to determine the test-retest repeatability of TBF measurement with both dynamic and static Rb PET.

Methods: We recruited 10 low-to-high-risk prostate cancer patients scheduled for clinical prostate-specific membrane antigen (PSMA) PET/computed tomography (CT) or magnetic resonance imaging. Pelvic and cardiac static and dynamic Rb PET/CT were performed at baseline and repeated on a different day within 1 week. In total, 11 primary lesions were analyzed.

Results: For K1, standardized uptake values (SUV)max, SUVmean, and SUVpeak, prostate cancer Rb PET TBF has a repeatability of 32%, 51%, 53%, and 58% and an intraclass correlation of 0.98, 0.89, 0.88, and 0.88, respectively.

Conclusion: Dynamic Rb PET/CT with kinetic modeling measures TBF in prostate cancer with high repeatability, which allows identification of blood flow changes of 32%. Static late-uptake Rb PET/CT is inferior, and only intra-individual blood flow changes above 51% can hence be recognized.
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http://dx.doi.org/10.1186/s13550-019-0529-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609677PMC
July 2019

Self-Paced Online vs. Cue-Based Offline Brain-Computer Interfaces for Inducing Neural Plasticity.

Brain Sci 2019 Jun 1;9(6). Epub 2019 Jun 1.

SMI, Department of Health Science and Technology, Aalborg University, Aalborg, 9220, Denmark.

Brain-computer interfaces (BCIs), operated in a cue-based (offline) or self-paced (online) mode, can be used for inducing cortical plasticity for stroke rehabilitation by the pairing of movement-related brain activity with peripheral electrical stimulation. The aim of this study was to compare the difference in cortical plasticity induced by the two BCI modes. Fifteen healthy participants participated in two experimental sessions: cue-based BCI and self-paced BCI. In both sessions, imagined dorsiflexions were extracted from continuous electroencephalogram (EEG) and paired 50 times with the electrical stimulation of the common peroneal nerve. Before, immediately after, and 30 minutes after each intervention, the cortical excitability was measured through the motor-evoked potentials (MEPs) of tibialis anterior elicited through transcranial magnetic stimulation. Linear mixed regression models showed that the MEP amplitudes increased significantly ( < 0.05) from pre- to post- and 30-minutes post-intervention in terms of both the absolute and relative units, regardless of the intervention type. Compared to pre-interventions, the absolute MEP size increased by 79% in post- and 68% in 30-minutes post-intervention in the self-paced mode (with a true positive rate of ~75%), and by 37% in post- and 55% in 30-minutes post-intervention in the cue-based mode. The two modes were significantly different ( = 0.03) at post-intervention (relative units) but were similar at both post timepoints (absolute units). These findings suggest that immediate changes in cortical excitability may have implications for stroke rehabilitation, where it could be used as a priming protocol in conjunction with another intervention; however, the findings need to be validated in studies involving stroke patients.
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http://dx.doi.org/10.3390/brainsci9060127DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6627467PMC
June 2019

No Added Value of F-Sodium Fluoride PET/CT for the Detection of Bone Metastases in Patients with Newly Diagnosed Prostate Cancer with Normal Bone Scintigraphy.

J Nucl Med 2019 12 30;60(12):1713-1716. Epub 2019 May 30.

Department of Nuclear Medicine, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.

The aim of this study was to determine if additional F-sodium fluoride PET/CT (NaF PET/CT) improves the prognostic accuracy in the initial staging of prostate cancer patients with normal bone scintigraphy undergoing prostatectomy. A prospective cohort study examined NaF PET/CT in intermediate- or high-risk prostate cancer with negative bone scintigraphy who were scheduled for prostatectomy. Biochemical response: PSA levels < 0.2 ng/mL at 6 wk and 6 mo postoperatively, PSA level ≥ 0.2 ng/mL was biochemical failure. Eighty-one patients were included in the study; 75 patients (93%) achieved biochemical responses, 6 patients had biochemical failure. NaF PET/CT indicated bone metastasis in 1 patient (1.2%), was equivocal in 7 patients (8.6%), without bone metastases in 73 patients (90.1%). Eight patients with bone metastases or equivocal results on NaF PET/CT exhibited biochemical responses. All patients with biochemical failure had negative NaF PET/CT and bone scintigraphy for bone metastases. NaF PET/CT has no added value for bone staging in intermediate- and high-risk prostate cancer patients with normal bone scintigraphy results undergoing prostatectomy.
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http://dx.doi.org/10.2967/jnumed.119.229062DOI Listing
December 2019

Continuous 2D control via state-machine triggered by endogenous sensory discrimination and a fast brain switch.

J Neural Eng 2019 07 23;16(5):056001. Epub 2019 Jul 23.

Department of Neurorehabilitation Engineering, Bernstein Center for Computational Neuroscience, University Medical Center, Göttingen, Germany. Guger Technologies OG, Graz, Austria.

Objective: Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, therefore, we implemented and evaluated a novel approach for online closed-loop control using the proposed BCI.

Approach: Eleven healthy subjects used the novel method to move a cursor in a 2D space. To assure robust control with properly timed commands, the BCI was integrated within a state machine allowing the subject to start the cursor movement in the selected direction and asynchronously stop the cursor. The brain switch was controlled using motor execution (ME) or imagery (MI) and the menu implemented four (straight movements) or eight commands (straight and diagonal movements).

Main Results: The results showed a high completion rate of a target hitting task (~97% and ~92% for ME and MI, respectively), with a small number of collisions, when four-channel control was used. There was no significant difference in outcome measures between MI and ME, and performance was similar for four and eight commands.

Significance: These results demonstrate that the novel state-based scheme driven by a robust BCI can be successfully utilized for online control. Therefore, it can be an attractive solution for providing the user an online-control interface with many commands, which is difficult to achieve using classic BCI solutions.
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http://dx.doi.org/10.1088/1741-2552/ab20e5DOI Listing
July 2019

Automated Labeling of Movement- Related Cortical Potentials Using Segmented Regression.

IEEE Trans Neural Syst Rehabil Eng 2019 06 7;27(6):1282-1291. Epub 2019 May 7.

The movement-related cortical potential (MRCP) is a brain signal related to planning and execution of motor tasks. From an MRCP, three notable features can be identified: the early Bereitschaftspotential (BP1), the late Bereitschaftspotential (BP2), and the negative peak (PN). These features have been used in past studies to quantify neurophysiological changes in response to motor training. Currently, either manual labeling or a priori specification of time points is used to extract these features. The limitation of these methods is the inability to fully model the features. This paper proposes the segmented regression along with a local peak method for automated labeling of the features. The proposed method derives the onsets, amplitudes at onsets, and slopes of BP1 and BP2 along with time and amplitude of the PN in a typical average MRCP. To choose the most suitable regression technique a bounded segmented regression method, a change point method and multivariate adaptive regression splines were evaluated using the root-mean-square error on a dataset of 6000 simulated MRCPs. The best-performing regression technique combined with the local peak method was then applied to a smaller set of 123 simulated MRCPs. Error in onsets of BP1 and BP2 and time of PN were compared with the errors in manual labeling by an expert. The performance of the proposed method was also evaluated on an experimental dataset of MRCPs derived from electroencephalography (EEG) recorded across two sessions from 22 healthy participants during a lower limb task. The Bland-Altman plots were used to evaluate the absolute reliability of the proposed method. On experimental data, the proposed method was also compared with manual labeling by an expert. Bounded segmented regression produced the smallest error on the simulation data. For the experimental data, our proposed method did not exhibit statistically significant bias in any of the modeled features. Furthermore, its performance was comparable to manual labeling by experts. We conclude that the proposed method can be used to automatically obtain robust estimates for the MRCP features with known measurement error.
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http://dx.doi.org/10.1109/TNSRE.2019.2913880DOI Listing
June 2019

Therapeutic effects of aerobic exercise on EEG parameters and higher cognitive functions in mild cognitive impairment patients.

Int J Neurosci 2019 Jun;129(6):551-562

a Neurobiology Laboratory, Department of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences , National University of Sciences and Technology , Islamabad , Pakistan.

Background: Mild cognitive impairment (MCI) is becoming an emerging problem for developing countries where there is an increase in expected age. There is no specific curative therapeutic treatment available for these patients.

Objective: The objective of this study was to evaluate short and long-term changes in the electroencephalogram (EEG) parameters and cognition of MCI patients with aerobic exercises.

Methods: A randomized controlled trial was conducted on 40 patients which were randomly divided into two groups, 'aerobic exercise treatment group (n = 21)' and 'no-aerobic control group (n = 19)'. Short-term effects of exercise were measured after single session of exercise and long-term effects were measured after an 18 sessions (6 weeks) treatment. The outcomes which were measured were, electroenphelogram paramaters (slowness and complexity of the EEG) and cognitive functions (using mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), and trail making test (TMT) A and B).

Results: After one session of aerobic exercise there were significant improvements in slowness (delta waves; 0.678 ± 0.035 vs 0.791 ± 0.033; p = .015) and complexity (0.601 ± 0.051 vs 0.470 ± 0.042; p = .027) of the EEG in aerobic exercise treated group as compared to no-aerobic exercise group. After six weeks there were significant improvements in slowness (delta waves; 0.581 ± 0.036 vs 0.815 ± 0.025; p = .005) and complexity (0.751 ± 0.045 vs 0.533 ± 0.046; p = .001) of the EEG in the aerobic group as compared to no-aerobic group. Moreover, significant improvements were observed in the MMSE (p = .032), MoCA (p = .036), TMT-A (p = .005), and TMT-B (p = .007) in aerobic exercise group as compared to no-aerobic group.

Conclusion: Aerobic exercise showed improvement in cognition after short and long-term treatment in MCI subjects and can be used as potential therapeutic candidate.
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http://dx.doi.org/10.1080/00207454.2018.1551894DOI Listing
June 2019
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