Analysis Of Tremor Research Articles

Exploiting speech tremors: machine learning for early diagnosis of amyotrophic lateral sclerosis

Abstract Neurodegenerative diseases pose significant challenges in healthcare, with Amyotrophic Lateral Sclerosis (ALS) being one such rare yet debilitating condition affecting motor neurons. Machine learning (ML) and artificial intelligence (AI) have emerged as powerful tools in healthcare, offering insights and solutions for various medical conditions. This study investigates the application of ML to enhance early ALS diagnosis through the analysis of tremors in sustained speech. By focusing on tremor detection as a diagnostic marker, the research employs ML algorithms to develop predictive models capable of distinguishing ALS patients from healthy controls. The dataset comprises 54 patients from the Republican Research and Clinical Centre of Neurology and Neurosurgery in Belarus, Minsk. The study adopts a two-faceted approach: (1) Exploratory voice analysis to identify tremors associated with ALS in speech samples. (2) Development of ML algorithms to construct predictive models for early ALS diagnosis based on the identified tremors. The ML models exhibit promising results in distinguishing ALS patients from healthy controls based on speech analysis. Tremor detection in sustained speech proves to be an effective marker for early ALS diagnosis. While initial findings are encouraging, larger-scale studies are required to validate the clinical applicability of this approach. The successful application of ML and AI in early ALS diagnosis by leveraging innovative approaches, such as tremor detection in sustained speech, we can enhance early diagnosis and improve patient outcomes in neurodegenerative diseases like ALS on a broader scale.

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions.

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

A Retrospective Study on Botulinum Toxin Injection in Patients With Multiple Sclerosis Related Tremor: A Treatment Option Worth Trying

Objectives Multiple sclerosis (MS)-related tremor remains a disabling problem that often responds poorly to medical treatments. This study aims to evaluate the effect of botulinum toxin type A on MS-related upper limb tremor. Methods This retrospective observational cohort study included 8 patients who received intramuscular injections of onabotulinum toxin type A for medically refractory MS-related tremor. Hospital records before and 4–6 weeks after treatment, including the Fahn-Tolosa-Marin Tremor rating scale (FTM-TRS), electrophysiological tremor analysis, neurological examination findings, and videos, were reviewed retrospectively. Results There was significant improvement after botulinum toxin injection in the FTM TRS part A score for tremor (P = 0.011), FTM TRS part B score for hand function (P = 0.011), FTM Part score for activities of daily living (P = 0.012), and FTM TRS total score for overall evaluation (P = 0.012). Electrophysiological tremor analysis revealed maximal tremor amplitudes between 700–2000 μV (before treatment) and between 300–1000 μV (after treatment). The mean tremor amplitudes before and after treatment were 1350 μV and 725 μV, respectively. No adverse reactions were observed after botulinum toxin treatment. Conclusions BoNT may improve upper limb tremor and functionality in MS-related tremor. The treatment involved administering BoNT under EMG guidance, with careful muscle selection based on clinical assessment and EMG findings. This approach aimed to optimize treatment efficacy while minimizing potential adverse effects. Further studies are warranted to confirm these findings.

Study of the frequency characteristics of a tremor analysis system based on a capacitive proximity sensor

The technique of tremor control using a capacitive sensor to ensure high sensitivity and stability of measurement results requires the correct selection of operating parameters of the system. Study of the influence of operating parameters, selection of the optimal antenna design and frequency-setting elements in a system for analyzing tremor of the upper limbs based on a capacitive proximity sensor. The tremor sensor being developed is based on a rectangular pulse generator, the generation frequency of which depends on the capacitance. The dependence of the generation frequency on the distance between the antenna and the limb was studied for various values of capacitance and resistance of the resistor in the generator circuit. It is proposed to use a circuit without a capacitor in the frequency-setting RC circuit, which allows for the largest frequency increment and clearly detects tremor with both large and small amplitude. An experimental study of various antenna designs was carried out. It has been shown that when using a helical antenna, the maximum sensitivity of the sensor is observed with the smallest diameter, however, the use of a small diameter reduces the area of interaction between the electric field and the tissues of the human limb. The electromagnetic method is a promising method for digitizing tremor, allowing for rapid non-contact diagnostics. The experimental results obtained make it possible to justify the choice of optimal parameters for the tremor analysis system.

Neuropathic Tremor in Guillain-Barré Syndrome.

Neuropathic Tremor (NT) is a postural/kinetic tremor of the upper extremity, often encountered in patients with chronic neuropathies such as paraprotein-associated and hereditary neuropathies. To describe the clinical and electrophysiological features of NT in a previously underrecognized setting- during recovery from Guillain-Barré Syndrome (GBS). Patients with a documented diagnosis of GBS in the past, presenting with tremor were identified from review of clinical records. Participants underwent structured, videotaped neurological examination, and electrophysiological analysis using tri-axial accelerometry-surface electromyography. Tremor severity was assessed using the Fahn-Tolosa-Marin Tremor Rating Scale. We describe the clinical and electrophysiological features of 5 patients with GBS associated NT. Our cohort had a fine, fast, and slightly jerky postural tremor of frequency ranging from 8 to 10 Hz. Dystonic posturing and overflow movements were noted in 4/5 patients. Tremor appeared 3 months-5 years after the onset of GBS, when patients had regained near normal muscle strength and deep tendon jerks were well elicitable. Electrophysiological analysis of tremor strongly suggested the presence of a central oscillator in all patients. NT is not limited to chronic inflammatory or hereditary neuropathies and may occur in the recovery phase of GBS. The tremor is characterized by a high frequency, jerky postural tremor with dystonic posturing. Electrophysiological evaluation suggests the presence of a central oscillator, hypothetically the cerebellum driven by impaired sensorimotor feedback.

Kinetic tremor analysis using wearable sensors and fuzzy inference systems in Parkinson's disease

BackgroundComputer systems for evaluating Parkinson's disease (PD) have recently increased. Many existing methods allow the quantification of tremors and extraction of some characteristics of the acquired signals by analysing manoeuvres established in the MDS-UPDRS. Some of these current methods interpret the finger-to-nose test, which includes kinetic tremors of the hands; however, an evaluation strictly based on the guidelines of the MDS Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is not performed, in addition to not using additional biomechanical indicators that make more robust and accurate monitoring of the patient's evolution. New methodThe proposed method consists of a fuzzy logic system that evaluates PD patients in a range based on the MDS-UPDRS. The system evaluates by taking biomechanical features extracted from signals recorded with inertial measurement units (IMUs), which were previously processed for obtaining meaningful characteristics according to the MDS-UPDRS and other additional ones. Comparison with existing methodsIn addition to the characteristics established by the MDS-UPDRS for the classification, this method uses other procedures that were considered necessary for the achievement of an accurate evaluation, such as the amplitude of the tremors in the different stages of the finger-to-nose manoeuvre, the tremors frequency and the voluntary movement frequency. Conclusionskinetic tremors were measured based on a sensor network formed by IMUs. A Fuzzy Logic system obtains an accurate and repeatable biomechanical assessment of PD patients. This system will permit physicians to follow up on each patient with objective assessments improving medical treatments.

Gait Function after High-Intensity Focused Ultrasound Thalamotomy for Essential Tremor: Searching for Technique Optimization

Introduction: Essential tremor (ET) is one of the most prevalent movement disorders in adults and may be highly disabling for some. Magnetic resonance image-guided high-intensity focused ultrasound (MRIgFUS) has been shown to control tremor efficaciously and with acceptable risk. To date, paresthesia and ataxia are the most common adverse effects (AE). Nevertheless, the impact of MRIgFUS thalamotomy on balance is not well established. Methods: Thirty-two patients underwent MRIgFUS for ET and completed 6 months of follow-up. Tremor severity and functional disability were assessed using the Essential Tremor Rating Scale and the Quality of Life in Essential Tremor Questionnaire. The Berg Balance Scale (BBS) was applied to objectively measure balance status. Results: All treatments were successful. The sonication target was 1–2 mm above the depth of the intercommissural line. Procedures lasted less the 2 h, with an average of 8 sonications per patient. Twenty-four patients were included in the tremor analysis. The hand tremor score was improved by 76% after 6 months of follow-up and 87% of patients self-reported marked improvement (≥75%). Disability scores showed marked improvement (78%), leading to a significant improvement in quality of life. At the final follow-up, 48% of the patients reported no side effects. When present, AE were generally transient and were considered mild in 96% of affected patients. Paresthesia and subjective feeling of unsteadiness were the most common persistent complaints (23% and 20%, respectively). Regarding objective ataxia, BBS scores remained stable throughout follow-up for most patients. Only 2 patients suffered a mild worsening of balance although no patients experienced moderate or severe ataxia. Conclusions: Subjective feeling of unsteadiness is one of the most frequent AE after MRIgFUS, although objective ataxia is infrequent and mild. Selecting the most appropriate lesion location and procedural parameters should increase treatment benefits while reducing side effects.

Spectral Analysis and Validation of Parietal Signals for Different Arm Movements

Brain signal analysis plays a significant role in attaining data related to motor activities. The parietal region of the brain plays a vital role in muscular movements. This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements; perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm. This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease (PD). To play out this handling method, electroencephalogram (EEG) signals are gained while the subject is performing different wrist and elbow movements. Then, the frontal brain signals and just the parietal signals are separated from the obtained EEG signal by utilizing a band pass filter. Then, feature extraction is carried out using Fast Fourier Transform (FFT). Subsequently, the extraction process is done by Daubechies (db4) and Haar wavelet (db1) in MATLAB and classified using the Levenberg-Marquardt Algorithm. The results of the frequency changes that occurred during various wrist movements in the parietal region are compared with the frequency changes that occurred in frontal EEG signals. This proposed algorithm also uses the deep learning pattern analysis network to evaluate the matching sequence for each action that takes place. Maximum accuracy of 97.2% and maximum error range of 0.6684% are achieved during the analysis. Results of this research confirm that the Levenberg-Marquardt algorithm, along with the newly developed deep learning hybrid PatternNet, provides a more accurate range of frequency changes than any other classifier used in previous works of literature. Based on the analysis, the peak-to-peak value is used to define the threshold for the prototype arm, which performs all the intended degrees of freedom (DOF), verifying the results. These results would aid the specialists in their decision-making by facilitating the analysis and interpretation of brain signals in the field of neuroscience, specifically in tremor analysis in PD.

Bispectral Analysis of Parkinsonian Rest Tremor: New Characterization and Classification Insights Pre-/Post-DBS and Medication Treatment

Bispectral Analysis of Parkinsonian Rest Tremor: New Characterization and Classification Insights Pre-/Post-DBS and Medication Treatment

Method of Еmotional State Assessment Using a Complex of Psychophysiological and Tensotremorometric Methods

The object of research is emotional tension. The subject of the study is assessment of emotional tension in the process of presentation of emotionally significant stimuli in the form of images and sounds according to the parameters of physiological activity and tensotremorometry in the process of maintaining isometric effort. Particular attention is paid to the consideration of methods of determination of tremor and its connection with emotional tension. Key aspects are the consideration of the key frequency range of physiological tremor analysis 8-16 hertz, methods of tremor measurement such as accelerometry, tensotremorometry, electromyography. Studies of the relationship between tensotremorometry on the frequency range of physiological tremor and emotional tension are considered. We propose a new method for analyzing tremor according to tensotremorometry data using the sliding window method and filtering the frequencies characteristic of physiological tremor. Methods of recording physiological activity in the form of photoplethysmography and skin electrical activity were used for reliability of the results obtained. We described and confirmed the connection between emotional tension during the demonstration of meaningful stimuli and finger tremor, while holding a given force in an isometric condition. The new technique has wide possibilities for use in the psychological and clinical fields, in particular, in detection of hidden information, assessment of the stress resistance of personnel, and determination of the functional state of a person, as well as in the study of the psycho-emotional state of students.

Analysis of physiological tremors during different intensities of armcurl exercises using wearable three-axis accelerometers in healthy young men: a pilot study.

The purpose of this pilot study was to determine whether physiological tremors (PTs) assessed using an accelerometer could be used to evaluate resistance exercise intensity. Twenty healthy young men with no prior experience of resistance exercise were recruited. Different intensities (resting, 30%, 50%, and 70% of their predetermined one-repetition maximum (1-RM)) of arm-curl exercise were used to elicit PT. The total work was held equally by varying the number of repetitions, with five sets for each intensity. Sessions of varying intensities were performed randomly with a washout period of at least a week. PT responses were recorded during exercise using accelerometers (3-axis) attached to the wrist and ear. Electromyography (EMG) data were obtained from the biceps brachii muscle during exercise. PT and EMG data were expressed as the average root mean square index. The EMG amplitude increased significantly as exercise intensity increased. Furthermore, PT amplitude significantly increased as exercise intensity increased. Moreover, the Borg rating of perceived exertion (RPE) and lactic acid levels increased significantly. The wrist PT was related to ear PT, EMG, RPE, and lactic acid levels. Additionally, ear PT was associated with EMG, RPE, and lactic acid levels. This pilot study identified changes in PT during resistance exercise at different intensities. We suggest that the use of PT analyses during these exercises provides a more intuitive delineation of resistance exercise intensity and fatigue.

Markerless Radio Frequency Indoor Monitoring for Telemedicine: Gait Analysis, Indoor Positioning, Fall Detection, Tremor Analysis, Vital Signs and Sleep Monitoring.

Quantitative indoor monitoring, in a low-invasive and accurate way, is still an unmet need in clinical practice. Indoor environments are more challenging than outdoor environments, and are where patients experience difficulty in performing activities of daily living (ADLs). In line with the recent trends of telemedicine, there is an ongoing positive impulse in moving medical assistance and management from hospitals to home settings. Different technologies have been proposed for indoor monitoring over the past decades, with different degrees of invasiveness, complexity, and capabilities in full-body monitoring. The major classes of devices proposed are inertial-based sensors (IMU), vision-based devices, and geomagnetic and radiofrequency (RF) based sensors. In recent years, among all available technologies, there has been an increasing interest in using RF-based technology because it can provide a more accurate and reliable method of tracking patients' movements compared to other methods, such as camera-based systems or wearable sensors. Indeed, RF technology compared to the other two techniques has higher compliance, low energy consumption, does not need to be worn, is less susceptible to noise, is not affected by lighting or other physical obstacles, has a high temporal resolution without a limited angle of view, and fewer privacy issues. The aim of the present narrative review was to describe the potential applications of RF-based indoor monitoring techniques and highlight their differences compared to other monitoring technologies.

Zonisamide add-on in tremor-dominant Parkinson's disease- A randomized controlled clinical trial

Introductionand objective: Tremor is a disabling symptom of PD that usually responds poorly to available standard pharmacological agents. This study aimed to assess the effect of Zonisamide 25 mg on tremor in tremor-dominant PD patients as compared to placebo. MethodsThis was a randomized, placebo-controlled, double-blind study. Parkinson's disease patients were allocated either to the intervention group (standard treatment along with Zonisamide 25 mg add-on) or the placebo group (standard treatment along with placebo). Baseline Unified Parkinson's Disease Rating Scale (UPDRS) and Tremor Research Group Essential Tremor Rating Scale (TETRAS) scores, as well as accelerometric tremor analysis were done and follow-up assessments of the same were done after 12 weeks of intervention. Percentage change from baseline in the UPDRS tremor score was the primary outcome whereas percentage change from baseline of total UPDRS score, UPDRS rigidity and bradykinesia scores, TETRAS score, and accelerometric tremor analysis values were the secondary outcomes. ResultsThere was no significant difference in the percentage change from baseline UPDRS tremor scores between the two groups (placebo: 8.33 [-19.89–23.86] vs drug: 26.14 [-35.58 to −16.07], p-value: 0.164, CI: 0.157–0.171). Best-case analysis for missing values showed a significant improvement in the drug group, compared to the placebo group (p-value: < 0.001, CI: <0.001 - <0.001). ConclusionZonisamide at a dose of 25 mg per day did not improve tremor in tremor-dominant PD patients, however, a positive trend was seen as compared to Placebo in the UPDRS tremor score. Larger studies are required to confirm this finding.

Video-Based Hand Movement Analysis of Parkinson Patients before and after Medication Using High-Frame-Rate Videos and MediaPipe.

Tremor is one of the common symptoms of Parkinson’s disease (PD). Thanks to the recent evolution of digital technologies, monitoring of PD patients’ hand movements employing contactless methods gained momentum. Objective: We aimed to quantitatively assess hand movements in patients suffering from PD using the artificial intelligence (AI)-based hand-tracking technologies of MediaPipe. Method: High-frame-rate videos and accelerometer data were recorded from 11 PD patients, two of whom showed classical Parkinsonian-type tremor. In the OFF-state and 30 Minutes after taking their standard oral medication (ON-state), video recordings were obtained. First, we investigated the frequency and amplitude relationship between the video and accelerometer data. Then, we focused on quantifying the effect of taking standard oral treatments. Results: The data extracted from the video correlated well with the accelerometer-based measurement system. Our video-based approach identified the tremor frequency with a small error rate (mean absolute error 0.229 (±0.174) Hz) and an amplitude with a high correlation. The frequency and amplitude of the hand movement before and after medication in PD patients undergoing medication differ. PD Patients experienced a decrease in the mean value for frequency from 2.012 (±1.385) Hz to 1.526 (±1.007) Hz and in the mean value for amplitude from 8.167 (±15.687) a.u. to 4.033 (±5.671) a.u. Conclusions: Our work achieved an automatic estimation of the movement frequency, including the tremor frequency with a low error rate, and to the best of our knowledge, this is the first paper that presents automated tremor analysis before/after medication in PD, in particular using high-frame-rate video data.

A standardized accelerometry method for characterizing tremor: Application and validation in an ageing population with postural and action tremor.

BackgroundOrdinal scales based on qualitative observation are the mainstay in the clinical assessment of tremor, but are limited by inter-rater reliability, measurement precision, range, and ceiling effects. Quantitative tremor evaluation is well-developed in research, but clinical application has lagged, in part due to cumbersome mathematical application and lack of established standards.ObjectivesTo develop a novel method for evaluating tremor that integrates a standardized clinical exam, wrist-watch accelerometers, and a software framework for data analysis that does not require advanced mathematical or computing skills. The utility of the method was tested in a sequential cohort of patients with predominant postural and action tremor presenting to a specialized surgical clinic with the presumptive diagnosis of Essential Tremor (ET).MethodsWristwatch accelerometry was integrated with a standardized clinical exam. A MATLAB application was developed for automated data analysis and graphical representation of tremor. Measures from the power spectrum of acceleration of tremor in different upper limb postures were derived in 25 consecutive patients. The linear results from accelerometry were correlated with the commonly used non-linear Clinical Rating Scale for Tremor (CRST).ResultsThe acceleration power spectrum was reliably produced in all consecutive patients. Tremor frequency was stable in different postures and across patients. Both total and peak power of acceleration during postural conditions correlated well with the CRST. The standardized clinical examination with integrated accelerometry measures was therefore effective at characterizing tremor in a population with predominant postural and action tremor. The protocol is also illustrated on repeated measures in an ET patient who underwent Magnetic Resonance-Guided Focused Ultrasound thalamotomy.ConclusionQuantitative assessment of tremor as a continuous variable using wristwatch accelerometry is readily applicable as a clinical tool when integrated with a standardized clinical exam and a user-friendly software framework for analysis. The method is validated for patients with predominant postural and action tremor, and can be adopted for characterizing tremor of different etiologies with dissemination in a wide variety of clinical and research contexts in ageing populations.

The Electrophysiological Perspectives of Essential, Enhanced Physiological, and Physiological Tremors

Abstract: Background: The most frequent movement issue seen in clinical practice is tremors. It is known as repetitive, involuntary oscillations. The diagnostic process for tremor patients can be time-consuming and complicated, as the identification of “Essential Tremor” and its distinction from other types of tremor. Objectives: This study aimed to describe the electrophysiological findings of essential, enhanced physiological, and physiological tremors, using surface electromyography and an accelerometer. Patients and Methods: The study included 24 patients with essential tremors, 10 patients with enhanced physiological tremors, and 10 patients with physiological tremors. We assessed the frequency, amplitude, and muscular contraction pattern of tremors during rest, posture, and a 1 kg load. Results: The tremor frequency of essential tremor patients was about 4.2-10.1 Hertz, while enhanced physiological tremor and physiological tremor were increased to 6.1–12.7 Hertz and 5.1-10.2 Hertz, respectively. The essential tremor group muscle contraction pattern was predominantly synchronous, as do all enhanced physiological, and physiological tremor patients, but with more fine low amplitude muscle bursts. By varying the tremor frequency and the weight load effect, tremor analysis could discriminate essential from enhanced physiological, and physiological tremors. Conclusions: The tremor analysis using surface electromyography and an accelerometer is sufficient to differentiate between essential tremors, enhanced physiological tremors, and physiological tremors.

P 57 Markerless, video-based kinematic Tremor Analysis: machine vision in movement disorders

Introduction: Clinimetrics of movement disorders relies on scales such as the Fahn-Tolosa-Marin Tremor Rating Scale for Essential Tremor (ET). However, these rating scales are prone to rater bias. Quantitative measurements of tremor kinematics, which are proxy measures of clinical outcome, can be achieved with gold standard tremor analyses using reflective markers and several special cameras. Due to their resource-intensiveness, broad availability is lacking. We therefore asked whether new developments in the field of machine vision can close the gap between granular clinimetrics and simplicity. Patients & Methods: Using the open-source software DeepLabCut (DLC), we tuned a recurrent convolutional neural network (RCNN) to track anatomic landmarks of the upper body by annotating a total of 1.878 frames from 234 videos of 51 ET patients who had undergone deep brain stimulation for ET and 10 healthy subjects. In a retrospective subcohort of 43 patients, tremor amplitudes were derived using the RCNN predictions. We probed the influence of DBS condition on tremor kinematics and expert annotated tremor rating scores (TRS) using repeated measures (rm-)ANOVA and Wilcoxon signed-ranked tests. Then, we assessed correlation of tremor metrics with TRS. To prospectively validate the method, we calculated the correlation of tremor metrics derived from both the video-based RCNN and the marker-based gold standard approach in 7 patients. The videos for validation were not used for training and were unknown to the network. To test for precision, we assessed relative errors and equivalence of both methods using two one sided T-Tests (TOST). Results: The RCNN achieved a mean Euclidean train/test error of 3.56/10.74 pixels corresponding to the average pixel size of a fingertip. In the retrospective analysis, DBS exerted a significant effect on the mean tremor amplitudes (Friedman test: χ2(3)=45.3, p<.001) and TRS (right: W=7.0, p<.001; left: W=37.5, p<.001). RCNN-derived maximum amplitudes correlated strongly with TRS (right: rs=.789, p<.001; left: rs=.640, p<.001). In the prospective analysis, mean amplitudes derived from both methods were strongly correlated (DBS off: rs=.982, p<.001; DBS on: rs=.824, p<.001). Relative errors of RCNN-derived mean amplitudes from goldstandard measurements did not significantly deviate from zero (p>.06). TOST revealed RCNN-derived measurements to be partially (DBS off: upper bound T(13)=0.5, p=.7; lower bound T(13)=3.9, p<.001) and fully (DBS on: T(13)=-15.2, p<.001; T(13)=14.52, p<.001) located within 90% CI equivalence bounds. Conclusion: We demonstrate the utility of video-based markerless tremor analysis using an RCNN for both retrospective and prospective settings. Our method allows sufficiently accurate measurements of tremor characteristics to assess the severity of the disease and to map individual disease progression.

Origin and Periodic Behavior of Short Duration Signals Recorded by Seismometers at Vestnesa Ridge, an Active Seepage Site on the West-Svalbard Continental Margin

Short duration events (SDEs) are reported worldwide from ocean-bottom seismometers (OBSs). Due to their high frequency (4–30 Hz) and short duration, they are commonly attributed to aseismic sources, such as fluid migration related processes from cold seeps, biological signals, or noise. We present the results of a passive seismic experiment that deployed an OBS network for 10-month (October 2015–July 2016) at an active seepage site on Vestnesa Ridge, West Svalbard continental margin. We characterize SDEs and their temporal occurrence using the conventional short-time-average over long-time-average approach. Signal periodograms show that SDEs have periodic patterns related to solar and lunar cycles. A monthly correlation between SDE occurrences and modelled tides for the area indicates that tides have a partial control on SDEs recorded over 10 months. The numbers of SDEs increase close to the tidal minima and maxima, although a correlation with tidal highs appears more robust. Large bursts of SDEs are separated by interim quiet cycles. In contrast, the periodicity analysis of tremors shows a different pattern, likely caused by the effect of tidally controlled underwater currents on the instrumentation. We suggest that SDEs at Vestnesa Ridge may be related to the dynamics of the methane seepage system which is characterized by a complex interaction between migration of deep sourced fluids, gas hydrate formation and seafloor gas advection through cracks. Our observation from this investigated area offshore west-Svalbard, is in line with the documentation of SDEs from other continental margins, where micro-seismicity and gas release into the water column are seemingly connected.

Changes in Cortical Excitability and Parkinson Tremor After Botulinum Toxin Therapy.

To investigate the relationship between botulinum toxin type A (BoNT-A) administration, tremor amplitude, and modulation of intracortical excitability and sensorimotor processing using paired-pulse transcranial magnetic stimulation (pp-TMS) in patients with early, tremor-dominant Parkinson disease (PD). Twelve de novo (naive to anti-PD medications) and 7 l-dopa (optimized on levodopa) participants with PD with tremor affecting one arm were recruited. All participants received 4 serial BoNT-A treatments for tremor every 12 weeks and peak effect was assessed 6 weeks posttreatment, totaling 8 visits over 42 weeks. Injection measures were based on kinematic tremor analysis. Short interval intracortical inhibition (SICI), intracortical facilitation (ICF), long interval intracortical inhibition (LICI), and measures of sensorimotor interaction (short-latency afferent [SAI] and long-latency afferent [LAI] stimulation) were assessed in both hemispheres using pp-TMS paradigms at each time point. Linear mixed models analyzed the effect of each pp-TMS measure and tremor severity within each cohort and the association between pp-TMS and tremor severity in the de novo cohort over 42 weeks. t Tests compared pp-TMS measures between hemispheres per time point. Baseline SICI, LICI, and SAI was reduced (higher motor evoked potential [MEP] ratio) on the tremulous/treated side compared to the nontremulous side in de novo participants. On the treated side in the de novo cohort, BoNT-A treatment significantly reduced ICF and increased LICI, SAI, and LAI (lower MEP ratio) at peak BoNT-A time points. The change in tremor severity was significantly associated with changes in SICI, LICI, and LAI. Our findings suggest that tremor severity in early PD may be related to impaired intracortical inhibition and defective sensorimotor integration.

Wearable Devices for Assessment of Tremor.

Tremor is an impairing symptom associated with several neurological diseases. Some of such diseases are neurodegenerative, and tremor characterization may be of help in differential diagnosis. To date, electromyography (EMG) is the gold standard for the analysis and diagnosis of tremors. In the last decade, however, several studies have been conducted for the validation of different techniques and new, non-invasive, portable, or even wearable devices have been recently proposed as complementary tools to EMG for a better characterization of tremors. Such devices have proven to be useful for monitoring the efficacy of therapies or even aiding in differential diagnosis. The aim of this review is to present systematically such new solutions, trying to highlight their potentialities and limitations, with a hint to future developments.