A Subspace Method for Dynamical Estimation of Evoked Potentials

It is a challenge in evoked potential (EP) analysis to incorporate prior physiological knowledge for estimation. In this paper, we address the problem of single-channel trial-to-trial EP characteristics estimation. Prior information about phase-locked properties of the EPs is assesed by means of estimated signal subspace and eigenvalue decomposition. Then for those situations that dynamic fluctuations from stimulus-to-stimulus could be expected, prior information can be exploited by means of state-space modeling and recursive Bayesian mean square estimation methods (Kalman filtering and smoothing). We demonstrate that a few dominant eigenvectors of the data correlation matrix are able to model trend-like changes of some component of the EPs, and that Kalman smoother algorithm is to be preferred in terms of better tracking capabilities and mean square error reduction. We also demonstrate the effect of strong artifacts, particularly eye blinks, on the quality of the signal subspace and EP estimates by means of independent component analysis applied as a prepossessing step on the multichannel measurements

Levodopa-Induced Changes in Electromyographic Patterns in Patients with Advanced Parkinson's Disease

Levodopa medication is the most efficient treatment for motor symptoms of Parkinson's disease (PD). Levodopa significantly alleviates rigidity, rest tremor, and bradykinesia in PD. The severity of motor symptoms can be graded with UPDRS-III scale. Levodopa challenge test is routinely used to assess patients' eligibility to deep-brain stimulation (DBS) in PD. Feasible and objective measurements to assess motor symptoms of PD during levodopa challenge test would be helpful in unifying the treatment. Twelve patients with advanced PD who were candidates for DBS treatment were recruited to the study. Measurements were done in four phases before and after levodopa challenge test. Rest tremor and rigidity were evaluated using UPDRS-III score. Electromyographic (EMG) signals from biceps brachii and kinematic signals from forearm were recorded with wireless measurement setup. The patients performed two different tasks: arm isometric tension and arm passive flexion-extension. The electromyographic and the kinematic signals were analyzed with parametric, principal component, and spectrum-based approaches. The principal component approach for isometric tension EMG signals showed significant decline in characteristics related to PD during levodopa challenge test. The spectral approach on passive flexion-extension EMG signals showed a significant decrease on involuntary muscle activity during the levodopa challenge test. Both effects were stronger during the levodopa challenge test compared to that of patients' personal medication. There were no significant changes in the parametric approach for EMG and kinematic signals during the measurement. The results show that a wireless and wearable measurement and analysis can be used to study the effect of levodopa medication in advanced Parkinson's disease.Peer reviewe

Signal features of surface electromyography in advanced Parkinson's disease during different settings of deep brain stimulation

Objective: Electromyography (EMG) and acceleration (ACC) measurements are potential methods for quantifying efficacy of deep brain stimulation (DBS) treatment in Parkinson's disease (PD). The treatment efficacy depends on the settings of DBS parameters (pulse amplitude, frequency and width). This study quantified, if EMG and ACC signal features differ between different DBS settings and if DBS effect is unequal between different muscles. Methods: EMGs were measured from biceps brachii (BB) and tibialis anterior (TA) muscles of 13 PD patients. ACCs were measured from wrists. Measurements were performed during seven different settings of DBS and analyzed using methods based on spectral analysis, signal morphology and nonlinear dynamics. Results: The results showed significant within-subject differences in the EMG signal kurtosis, correlation dimension, recurrence rate and EMG-ACC coherence between different DBS settings for BB but not for TA muscles. Correlations between EMG feature values and clinical rest tremor and rigidity scores were weak but significant. Conclusions: Surface EMG features differed between different DBS settings and DBS effect was unequal between upper and lower limb muscles. Significance: EMG changes pointed to previously defined optimal settings in most of patients, which should be quantified even more deeply in the upcoming studies. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.Peer reviewe

Changes in elbow flexion EMG morphology during adjustment of deep brain stimulator in advanced Parkinson's disease

Publisher Copyright: © 2022 Ruonala et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Objective Deep brain stimulation (DBS) is an effective treatment for motor symptoms of advanced Parkinson's disease (PD). Currently, DBS programming outcome is based on a clinical assessment. In an optimal situation, an objectively measurable feature would assist the operator to select the appropriate settings for DBS. Surface electromyographic (EMG) measurements have been used to characterise the motor symptoms of PD with good results; with proper methodology, these measurements could be used as an aid to program DBS. Methods Muscle activation measurements were performed for 13 patients who had advanced PD and were treated with DBS. The DBS pulse voltage, frequency, and width were changed during the measurements. The measured EMG signals were analysed with parameters that characterise the EMG signal morphology, and the results were compared to the clinical outcome of the adjustment. Results The EMG signal correlation dimension, recurrence rate, and kurtosis changed significantly when the DBS settings were changed. DBS adjustment affected the signal recurrence rate the most. Relative to the optimal settings, increased recurrence rates (median ± IQR) 1.1 ± 0.5 (-0.3 V), 1.3 ± 1.1 (+0.3 V), 1.7 ± 0.4 (-30 Hz), 1.7 ± 0.8 (+30 Hz), 2.0 ± 1.7 (+30 μs), and 1.5 ± 1.1 (DBS off) were observed. With optimal stimulation settings, the patients' Unified Parkinson's Disease Rating Scale motor part (UPDRS-III) score decreased by 35% on average compared to turning the device off. However, the changes in UPRDS-III arm tremor and rigidity scores did not differ significantly in any settings compared to the optimal stimulation settings. Conclusion Adjustment of DBS treatment alters the muscle activation patterns in PD patients. The changes in the muscle activation patterns can be observed with EMG, and the parameters calculated from the signals differ between optimal and non-optimal settings of DBS. This provides a possibility for using the EMG-based measurement to aid the clinicians to adjust the DBS.Peer reviewe

Open-source software library for real-time inertial measurement unit data-based inverse kinematics using OpenSim

Background Inertial measurements (IMUs) facilitate the measurement of human motion outside the motion laboratory. A commonly used open-source software for musculoskeletal simulation and analysis of human motion, OpenSim, includes a tool to enable kinematics analysis of IMU data. However, it only enables offline analysis, i.e., analysis after the data has been collected. Extending OpenSim’s functionality to allow real-time kinematics analysis would allow real-time feedback for the subject during the measurement session and has uses in e.g., rehabilitation, robotics, and ergonomics. Methods We developed an open-source software library for real-time inverse kinematics (IK) analysis of IMU data using OpenSim. The software library reads data from IMUs and uses multithreading for concurrent calculation of IK. Its operation delays and throughputs were measured with a varying number of IMUs and parallel computing IK threads using two different musculoskeletal models, one a lower-body and torso model and the other a full-body model. We published the code under an open-source license on GitHub. Results A standard desktop computer calculated full-body inverse kinematics from treadmill walking at 1.5 m/s with data from 12 IMUs in real-time with a mean delay below 55 ms and reached a throughput of more than 90 samples per second. A laptop computer had similar delays and reached a throughput above 60 samples per second with treadmill walking. Minimal walking kinematics, motion of lower extremities and torso, were calculated from treadmill walking data in real-time with a throughput of 130 samples per second on the laptop and 180 samples per second on the desktop computer, with approximately half the delay of full-body kinematics. Conclusions The software library enabled real-time inverse kinematical analysis with different numbers of IMUs and customizable musculoskeletal models. The performance results show that subject-specific full-body motion analysis is feasible in real-time, while a laptop computer and IMUs allowed the use of the method outside the motion laboratory

Nonlinear parameters of surface EMG in schizophrenia patients depend on kind of antipsychotic therapy

ArticleWe compared a set of surface EMG (sEMG) parameters in several groups of schizophrenia (SZ, n = 74) patients and healthy controls (n = 11) and coupled them with the clinical data. sEMG records were quantified with spectral, mutual information (MI) based and recurrence quantification analysis (RQA) parameters, and with approximate and sample entropies (ApEn and SampEn). Psychotic deterioration was estimated with Positive and Negative Syndrome Scale (PANSS) and with the positive subscale of PANSS. Neuroleptic-induced parkinsonism (NIP) motor symptoms were estimated with Simpson-Angus Scale (SAS). Dyskinesia was measured with Abnormal Involuntary Movement Scale (AIMS). We found that there was no difference in values of sEMG parameters between healthy controls and drug-naïve SZ patients. The most specific group was formed of SZ patients who were administered both typical and atypical antipsychotics (AP). Their sEMG parameters were significantly different from those of SZ patients taking either typical or atypical AP or taking no AP. This may represent a kind of synergistic effect of these two classes of AP. For the clinical data we found that PANSS, SAS, and AIMS were not correlated to any of the sEMG parameters. Conclusion: with nonlinear parameters of sEMG it is possible to reveal NIP in SZ patients, and it may help to discriminate between different clinical groups of SZ patients. Combined typical and atypical AP therapy has stronger effect on sEMG than a therapy with AP of only one class.Publisher's pdfhttp://purl.org/eprint/status/PeerReviewe

An EMG-Assisted Muscle-Force Driven Finite Element Analysis Pipeline to Investigate Joint- and Tissue-Level Mechanical Responses in Functional Activities : Towards a Rapid Assessment Toolbox

Publisher Copyright: © 1964-2012 IEEE.Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising, MS-FE models to research applications with few participants and makes the models impractical for clinical assessments. Also, these previously developed MS-FE models have not been used to assess activities other than gait. This study introduces and verifies a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography- (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was verified by comparing the estimated muscle activations and joint mechanics to existing experimental data. To determine the importance of the EMG-assisted MS analysis approach, results were compared to those from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments compared to the static-optimization-based MS-FE pipeline. Importantly, the developed pipeline showed great potential as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA.Peer reviewe

Tooth Clenching Induces Abnormal Cerebrovascular Responses in Migraineurs

Prevalence of masticatory parafunctions, such as tooth clenching and grinding, is higher among migraineurs than non-migraineurs, and masticatory dysfunctions may aggravate migraine. Migraine predisposes to cerebrovascular disturbances, possibly due to impaired autonomic vasoregulation, and sensitization of the trigeminovascular system. The relationships between clenching, migraine, and cerebral circulation are poorly understood. We used Near-Infrared Spectroscopy to investigate bilateral relative oxy-(Þlta[O(2)Hb]), deoxy-(Þlta[HHb]), and total (Þlta[tHb]) hemoglobin concentration changes in prefrontal cortex induced by maximal tooth clenching in twelve headache-free migraineurs and fourteen control subjects. From the start of the test, migraineurs showed a greater relative increase in right-side Þlta[HHb] than controls, who showed varying reactions, and right-side increase in Þlta[tHb] was also greater in migraineurs (p < 0.001 and p < 0.05, respectively, time-group interactions, Linear mixed models). With multivariate regression model, migraine predicted the magnitude of maximal blood pressure increases, associated in migraineurs with mood scores and an intensity of both headache and painful signs of temporomandibular disorders (pTMD). Although changes in circulatory parameters predicted maximal NIRS responses, the between-group differences in the right-side NIRS findings remained significant after adjusting them for systolic blood pressure and heart rate. A family history of migraine, reported by all migraineurs and four controls, also predicted maximal increases in both Þlta[HHb]and Þlta[tHb]. Presence of pTMD, revealed in clinical oral examination in eight migraineurs and eight controls, was related to maximal Þlta[HHb] increase only in controls. To conclude, the greater prefrontal right-side increases in cerebral Þlta[HHb] and Þlta[tHb] may reflect disturbance of the tooth clenching-related cerebral (de)oxygenation based on impaired reactivity and abnormal microcirculation processes in migraineurs. This finding may have an impact in migraine pathophysiology and help to explain the deleterious effect of masticatory dysfunctions in migraine patients. However, the role of tooth clenching as a migraine trigger calls for further studies

Ability to remotely monitor atrial high-rate episodes using a single-chamber implantable cardioverter-defibrillator with a floating atrial sensing dipole

Aims To allow timely initiation of anticoagulation therapy for the prevention of stroke, the European guidelines on atrial fibrillation (AF) recommend remote monitoring (RM) of device-detected atrial high-rate episodes (AHREs) and progression of arrhythmia duration along pre-specified strata (6 min…&lt;1 h, 1 h…&lt;24 h, ≥ 24 h). We used the MATRIX registry data to assess the capability of a single-lead implantable cardioverter-defibrillator (ICD) with atrial sensing dipole (DX ICD system) to follow this recommendation in patients with standard indication for single-chamber ICD. Methods In 1841 DX ICD patients with daily automatic RM transmissions, electrograms of first device-detected AHREs per patient in and results each duration stratum were adjudicated, and the corresponding positive predictive values (PPVs) for the detections to be true atrial arrhythmia were calculated. Moreover, the incidence and progression of new-onset AF was assessed in 1451 patients with no AF history. A total of 610 AHREs ≥6 min were adjudicated. The PPV was 95.1% (271 of 285) for episodes 6min…&lt;1 h, 99.6% (253/254) for episodes 1 h…&lt;24 h, 100% (71/71) for episodes ≥24 h, or 97.5% for all episodes (595/ 610). The incidence of new-onset AF was 8.2% (119/1451), and in 31.1% of them (37/119), new-onset AF progressed to a higher duration stratum. Nearly 80% of new-onset AF patients had high CHA 2DS 2-VASc stroke risk, and 70% were not on anticoagulation therapy. Age was the only significant predictor of new-onset AF. Conclusion A 99.7% detection accuracy for AHRE ≥1 h in patients with DX ICD systems in combination with daily RM allows a reliable guideline-recommended screening for subclinical AF and monitoring of AF-duration progression.</p