Negro, Francesco

[["dc.bibliographiccitation.firstpage","1699"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Journal of Neurophysiology"],["dc.bibliographiccitation.lastpage","1706"],["dc.bibliographiccitation.volume","119"],["dc.contributor.author","Yavuz, Utku Ş."],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Diedrichs, Robin"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2019-02-06T11:53:32Z"],["dc.date.available","2019-02-06T11:53:32Z"],["dc.date.issued","2018"],["dc.description.abstract","Motor neurons innervating antagonist muscles receive reciprocal inhibitory afferent inputs to facilitate the joint movement in the two directions. The present study investigates the mutual transmission of reciprocal inhibitory afferent inputs between the tibialis anterior (TA) and triceps surae (soleus and medial gastrocnemius) motor units. We assessed this mutual mechanism in large populations of motor units for building a statistical distribution of the inhibition amplitudes during standardized input to the motor neuron pools to minimize the effect of modulatory pathways. Single motor unit activities were identified using high-density surface electromyography (HDsEMG) recorded from the TA, soleus (Sol), and medial gastrocnemius (GM) muscles during isometric dorsi- and plantarflexion. Reciprocal inhibition on the antagonist muscle was elicited by electrical stimulation of the tibial (TN) or common peroneal nerves (CPN). The probability density distributions of reflex strength for each muscle were estimated to examine the strength of mutual transmission of reciprocal inhibitory input. The results showed that the strength of reciprocal inhibition in the TA motor units was fourfold greater than for the GM and the Sol motor units. This suggests an asymmetric transmission of reciprocal inhibition between ankle extensor and flexor muscles. This asymmetry cannot be explained by differences in motor unit type composition between the investigated muscles since we sampled low-threshold motor units in all cases. Therefore, the differences observed for the strength of inhibition are presumably due to a differential reciprocal spindle afferent input and the relative contribution of nonreciprocal inhibitory pathways. NEW & NOTEWORTHY We investigated the mutual transmission of reciprocal inhibition in large samples of motor units using a standardized input (electrical stimulation) to the motor neurons. The results demonstrated that the disynaptic reciprocal inhibition exerted between ankle flexor and extensor muscles is asymmetric. The functional implication of asymmetric transmission may be associated with the neural strategies of postural control."],["dc.identifier.doi","10.1152/jn.00424.2017"],["dc.identifier.pmid","29384455"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/57534"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.eissn","1522-1598"],["dc.title","Reciprocal inhibition between motor neurons of the tibialis anterior and triceps surae in humans"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","37"],["dc.bibliographiccitation.journal","Acta Physiologica"],["dc.bibliographiccitation.lastpage","38"],["dc.bibliographiccitation.volume","215"],["dc.contributor.author","Yavuz, Utku Suekrue"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Sebik, Oguz"],["dc.contributor.author","Holobar, Ales"],["dc.contributor.author","Froemmel, Cornelius"],["dc.contributor.author","Turker, Kemal S."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:49:23Z"],["dc.date.available","2018-11-07T09:49:23Z"],["dc.date.issued","2015"],["dc.identifier.isi","000364786400081"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35500"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.publisher.place","Hoboken"],["dc.relation.issn","1748-1716"],["dc.relation.issn","1748-1708"],["dc.title","The new technique for accurate estimation of the spinal cord circuitry: recording reflex responses of large motor unit populations"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","189"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","198"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Stango, Antonietta"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T10:00:16Z"],["dc.date.available","2018-11-07T10:00:16Z"],["dc.date.issued","2015"],["dc.description.abstract","Research on pattern recognition for myoelectric control has usually focused on a small number of electromyography (EMG) channels because of better clinical acceptability and low computational load with respect to multi-channel EMG. However, recently, high density (HD) EMG technology has substantially improved, also in practical usability, and can thus be applied in myocontrol. HD EMG provides several closely spaced recordings in multiple locations over the skin surface. This study considered the use of HD EMG for controlling upper limb prostheses, based on pattern recognition. In general, robustness and reliability of classical pattern recognition systems are influenced by electrode shift in dons and doff, and by the presence of malfunctioning channels. The aim of this study is to propose a new approach to attenuate these issues. The HD EMG grid of electrodes is an ensemble of sensors that records data spatially correlated. The experimental variogram, which is a measure of the degree of spatial correlation, was used as feature for classification, contrary to previous approaches that are based on temporal or frequency features. The classification based on the variogram was tested on seven able-bodied subjects and one subject with amputation, for the classification of nine and seven classes, respectively. The performance of the proposed approach was comparable with the classic methods based on time-domain and autoregressive features (average classification accuracy over all methods similar to 95% for nine classes). However, the new spatial features demonstrated lower sensitivity to electrode shift (+/- 1 cm) with respect to the classic features (p<0.05). When even just one channel was noisy, the classification accuracy dropped by similar to 10% for all methods. However, the new method could be applied without any retraining to a subset of high-quality channels whereas the classic methods require retraining when some channels are omitted. In conclusion, the new spatial feature space proposed in this study improved the robustness to electrode number and shift in myocontrol with respect to previous approaches."],["dc.description.sponsorship","ERC AdvancedGrant DE-MOVE [267888]"],["dc.identifier.doi","10.1109/TNSRE.2014.2366752"],["dc.identifier.isi","000351365100005"],["dc.identifier.pmid","25389242"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/37767"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Ieee-inst Electrical Electronics Engineers Inc"],["dc.relation.issn","1558-0210"],["dc.relation.issn","1534-4320"],["dc.title","Spatial Correlation of High Density EMG Signals Provides Features Robust to Electrode Number and Shift in Pattern Recognition for Myocontrol"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","244"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","IEEE Transactions on Neural Systems and Rehabilitation Engineering"],["dc.bibliographiccitation.lastpage","251"],["dc.bibliographiccitation.volume","26"],["dc.contributor.author","Kapelner, Tamas"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Aszmann, Oskar C."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2020-12-10T18:26:21Z"],["dc.date.available","2020-12-10T18:26:21Z"],["dc.date.issued","2018"],["dc.identifier.doi","10.1109/TNSRE.2017.2766360"],["dc.identifier.eissn","1558-0210"],["dc.identifier.issn","1534-4320"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76053"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Decoding Motor Unit Activity From Forearm Muscles: Perspectives for Myoelectric Control"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","47"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of NeuroEngineering and Rehabilitation"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Kapelner, Tamás"],["dc.contributor.author","Vujaklija, Ivan"],["dc.contributor.author","Jiang, Ning"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Aszmann, Oskar C."],["dc.contributor.author","Principe, Jose"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2019-07-09T11:51:40Z"],["dc.date.available","2019-07-09T11:51:40Z"],["dc.date.issued","2019"],["dc.description.abstract","BACKGROUND: Current myoelectric control algorithms for active prostheses map time- and frequency-domain features of the interference EMG signal into prosthesis commands. With this approach, only a fraction of the available information content of the EMG is used and the resulting control fails to satisfy the majority of users. In this study, we predict joint angles of the three degrees of freedom of the wrist from motor unit discharge timings identified by decomposition of high-density surface EMG. METHODS: We recorded wrist kinematics and high-density surface EMG signals from six able-bodied individuals and one patient with limb deficiency while they performed movements of three degrees of freedom of the wrist at three different speeds. We compared the performance of linear regression to predict the observed individual wrist joint angles from, either traditional time domain features of the interference EMG or from motor unit discharge timings (which we termed neural features) obtained by EMG decomposition. In addition, we propose and test a simple model-based dimensionality reduction, based on the physiological notion that the discharge timings of motor units are partly correlated. RESULTS: The regression approach using neural features outperformed regression on classic global EMG features (average R2 for neural features 0.77 and 0.64, for able-bodied subjects and patients, respectively; for time-domain features 0.70 and 0.52). CONCLUSIONS: These results indicate that the use of neural information extracted from EMG decomposition can advance man-machine interfacing for prosthesis control."],["dc.identifier.doi","10.1186/s12984-019-0516-x"],["dc.identifier.pmid","30953528"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16168"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59987"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/267888/EU//DEMOVE"],["dc.relation","info:eu-repo/grantAgreement/EC/H2020/737570/EU//INTERSPINE"],["dc.relation","info:eu-repo/grantAgreement/EC/H2020/702491/EU//NeuralCon"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Predicting wrist kinematics from motor unit discharge timings for the control of active prostheses"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","4305"],["dc.bibliographiccitation.issue","19"],["dc.bibliographiccitation.journal","The Journal of Physiology"],["dc.bibliographiccitation.lastpage","4318"],["dc.bibliographiccitation.volume","593"],["dc.contributor.author","Yavuz, Utku Suekrue"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Sebik, Oguz"],["dc.contributor.author","Holobar, Ales"],["dc.contributor.author","Froemmel, Cornelius"],["dc.contributor.author","Turker, Kemal S."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:50:51Z"],["dc.date.available","2018-11-07T09:50:51Z"],["dc.date.issued","2015"],["dc.description.abstract","We propose and validate a non-invasive method that enables accurate detection of the discharge times of a relatively large number of motor units during excitatory and inhibitory reflex stimulations. High-density surface electromyography (HDsEMG) and intramuscular EMG (iEMG) were recorded from the tibialis anterior muscle during ankle dorsiflexions performed at 5%, 10% and 20% of the maximum voluntary contraction (MVC) force, in nine healthy subjects. The tibial nerve (inhibitory reflex) and the peroneal nerve (excitatory reflex) were stimulated with constant current stimuli. In total, 416 motor units were identified from the automatic decomposition of the HDsEMG. The iEMG was decomposed using a state-of-the-art decomposition tool and provided 84 motor units (average of two recording sites). The reflex responses of the detected motor units were analysed using the peri-stimulus time histogram (PSTH) and the peri-stimulus frequencygram (PSF). The reflex responses of the common motor units identified concurrently from the HDsEMG and the iEMG signals showed an average disagreement (the difference between number of observed spikes in each bin relative to the mean) of 8.2 +/- 2.2% (5% MVC), 6.8 +/- 1.0% (10% MVC) and 7.5 +/- 2.2% (20% MVC), for reflex inhibition, and 6.5 +/- 4.1%, 12.0 +/- 1.8% and 13.9 +/- 2.4%, for reflex excitation. There was no significant difference between the characteristics of the reflex responses, such as latency, amplitude and duration, for the motor units identified by both techniques. Finally, reflex responses could be identified at higher force (4 of the 9 subjects performed contraction up to 50% MVC) using HDsEMG but not iEMG, because of the difficulty in decomposing the iEMG at high forces. In conclusion, single motor unit reflex responses can be estimated accurately and non-invasively in relatively large populations of motor units using HDsEMG. This non-invasive approach may enable a more thorough investigation of the synaptic input distribution on active motor units at various force levels."],["dc.description.sponsorship","European Research Council (ERC) [267888]"],["dc.identifier.doi","10.1113/JP270635"],["dc.identifier.isi","000363090500002"],["dc.identifier.pmid","26115007"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35792"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1469-7793"],["dc.relation.issn","0022-3751"],["dc.title","Estimating reflex responses in large populations of motor units by decomposition of the high-density surface electromyogram"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e92390"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Yavuz, Utku Suekrue"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:42:26Z"],["dc.date.available","2018-11-07T09:42:26Z"],["dc.date.issued","2014"],["dc.description.abstract","Contractile properties of human motor units provide information on the force capacity and fatigability of muscles. The spike-triggered averaging technique (STA) is a conventional method used to estimate the twitch waveform of single motor units in vivo by averaging the joint force signal. Several limitations of this technique have been previously discussed in an empirical way, using simulated and experimental data. In this study, we provide a theoretical analysis of this technique in the frequency domain and describe its intrinsic limitations. By analyzing the analytical expression of STA, first we show that a certain degree of correlation between the motor unit activities prevents an accurate estimation of the twitch force, even from relatively long recordings. Second, we show that the quality of the twitch estimates by STA is highly related to the relative variability of the inter-spike intervals of motor unit action potentials. Interestingly, if this variability is extremely high, correct estimates could be obtained even for high discharge rates. However, for physiological inter-spike interval variability and discharge rate, the technique performs with relatively low estimation accuracy and high estimation variance. Finally, we show that the selection of the triggers that are most distant from the previous and next, which is often suggested, is not an effective way for improving STA estimates and in some cases can even be detrimental. These results show the intrinsic limitations of the STA technique and provide a theoretical framework for the design of new methods for the measurement of motor unit force twitch."],["dc.description.sponsorship","European Research Council Advanced Grant DEMOVE [267888]"],["dc.identifier.doi","10.1371/journal.pone.0092390"],["dc.identifier.isi","000333675600035"],["dc.identifier.pmid","24667744"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10062"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/33952"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Limitations of the Spike-Triggered Averaging for Estimating Motor Unit Twitch Force: A Theoretical Analysis"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3789"],["dc.bibliographiccitation.issue","17"],["dc.bibliographiccitation.journal","The Journal of Physiology"],["dc.bibliographiccitation.lastpage","3804"],["dc.bibliographiccitation.volume","593"],["dc.contributor.author","Muceli, Silvia"],["dc.contributor.author","Poppendieck, Wigand"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Yoshida, Ken"],["dc.contributor.author","Hoffmann, Klaus P."],["dc.contributor.author","Butler, Jane E."],["dc.contributor.author","Gandevia, Simon C."],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2018-11-07T09:52:40Z"],["dc.date.available","2018-11-07T09:52:40Z"],["dc.date.issued","2015"],["dc.description.abstract","We describe the design, fabrication and testing of a novel multi-channel thin-film electrode for detection of the output of motoneurones in vivo and in humans, through muscle signals. The structure includes a linear array of 16 detection sites that can sample intramuscular electromyographic activity from the entire muscle cross-section. The structure was tested in two superficial muscles (the abductor digiti minimi (ADM) and the tibialis anterior (TA)) and a deep muscle (the genioglossus (GG)) during contractions at various forces. Moreover, surface electromyogram (EMG) signals were concurrently detected from the TA muscle with a grid of 64 electrodes. Surface and intramuscular signals were decomposed into the constituent motor unit (MU) action potential trains. With the intramuscular electrode, up to 31 MUs were identified from the ADM muscle during an isometric contraction at 15% of the maximal force (MVC) and 50 MUs were identified for a 30% MVC contraction of TA. The new electrode detects different sources from a surface EMG system, as only one MU spike train was found to be common in the decomposition of the intramuscular and surface signals acquired from the TA. The system also allowed access to the GG muscle, which cannot be analysed with surface EMG, with successful identification of MU activity. With respect to classic detection systems, the presented thin-film structure enables recording from large populations of active MUs of deep and superficial muscles and thus can provide a faithful representation of the neural drive sent to a muscle."],["dc.identifier.doi","10.1113/JP270902"],["dc.identifier.isi","000360769900009"],["dc.identifier.pmid","26174910"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/36177"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","1469-7793"],["dc.relation.issn","0022-3751"],["dc.title","Accurate and representative decoding of the neural drive to muscles in humans with multi-channel intramuscular thin-film electrodes"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Nature Biomedical Engineering"],["dc.bibliographiccitation.volume","1"],["dc.contributor.author","Farina, Dario"],["dc.contributor.author","Vujaklija, Ivan"],["dc.contributor.author","Sartori, Massimo"],["dc.contributor.author","Kapelner, Tamás"],["dc.contributor.author","Negro, Francesco"],["dc.contributor.author","Jiang, Ning"],["dc.contributor.author","Bergmeister, Konstantin"],["dc.contributor.author","Andalib, Arash"],["dc.contributor.author","Principe, Jose"],["dc.contributor.author","Aszmann, Oskar C."],["dc.date.accessioned","2020-12-10T18:09:54Z"],["dc.date.available","2020-12-10T18:09:54Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1038/s41551-016-0025"],["dc.identifier.eissn","2157-846X"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73794"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1479"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","The Journal of Physiology"],["dc.bibliographiccitation.lastpage","1496"],["dc.bibliographiccitation.volume","595"],["dc.contributor.author","Negro, F."],["dc.contributor.author","Laine, C. M."],["dc.contributor.author","Mayer, F."],["dc.contributor.author","Martinez-Valdes, Eduardo"],["dc.contributor.author","Falla, Deborah"],["dc.contributor.author","Farina, Dario"],["dc.date.accessioned","2020-12-10T18:36:34Z"],["dc.date.available","2020-12-10T18:36:34Z"],["dc.date.issued","2017"],["dc.description.abstract","A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high-density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre-post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra-class correlation coefficients ranged between 0.63-0.99 and 0.39-0.95, respectively). In Experiment II, similar to 40% of the MUs could be tracked before and after the training intervention and training-induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders."],["dc.identifier.doi","10.1113/JP273662"],["dc.identifier.isi","000398112300016"],["dc.identifier.issn","0022-3751"],["dc.identifier.pmid","28032343"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76674"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Wiley"],["dc.relation.issn","1469-7793"],["dc.relation.issn","0022-3751"],["dc.title","Tracking motor units longitudinally across experimental sessions with high-density surface electromyography"],["dc.title.alternative","Motor unit tracking with high-density EMG"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]