UNASSIGNED: Hand postural physiological tremor increases during arithmetic computation. The present work aims at investigating whether this could be attributed to a raise in stress for having to provide a correct answer within a constrained period of time, or to voice vibration for having to speak to report the answer.
UNASSIGNED: In 16 participants tremor was recorded by using a 3-axial accelerometer during 5 min of a hand postural task performed simultaneously while: 1) subtracting 13 from a 3-digit number within 4 s and with mistakes correction (intervention: math stress task), 2) same as for the \"intervention task\" but without time limit and mistakes correction (intervention: math nonstress task), 3) adding 1 to a 3-digit number (intervention: voice vibration task), and 4) only postural task while keeping quiet (control task). Electromyographic (EMG) activity from the extensor carpi radialis was measured during the hand postural task.
UNASSIGNED: Compared to control, tremor increased during both math interventions (+30.9 % p = 0.002, math stress; +15.0 % p = 0.01, math nonstress), but not during the voice vibration task (+12.2 % p = 0.239). During the math stress trial tremor was greater compared to both the voice vibration trial (+21.0 % p = 0.021), and the math nonstress trial (+13.5 % p = 0.01). EMG activity was not affected.
UNASSIGNED: The results suggest that during arithmetic computation the \"stress component\" contributes only partially to the observed increase in hand postural tremor, and that this increase cannot be attributed to voice vibrations.

Physiologic hand tremors are a critical factor affecting the aim of air pistol shooters. However, the extent of the effect of hand tremors on shooting performance is unclear. In this study, we aim to explore the relationship between hand tremors and shooting performance scores as well as investigate potential links between muscle activation and hand tremors. In this study, 17 male air pistol shooters from China\'s national team and the Air Pistol Sports Center were divided into two groups: the elite group and the sub-elite group. Each participant completed 40 shots during the experiment, with shooters\' hand tremors recorded using three-axis digital accelerometers affixed to their right hands. Muscle activation was recorded using surface electromyography on the right anterior deltoid, posterior deltoid, biceps brachii (short head), triceps brachii (long head), flexor carpi radialis, and extensor carpi radialis. Our analysis revealed weak correlations between shooting scores and hand tremor amplitude in multiple directions (middle-lateral, ML: r2 = -0.22, p < 0.001; vertical, VT: r2 = -0.25, p < 0.001), as well as between shooting scores and hand tremor complexity (ML: r2 = -0.26, p < 0.001; VT: r2 = -0.28, p < 0.001), across all participants. Notably, weak correlations between shooting scores and hand tremor amplitude (ML: r2 = -0.27, p < 0.001; VT: r2 = -0.33, p < 0.001) and complexity (ML: r2 = -0.31, p < 0.001) were observed in the elite group but not in the sub-elite group. Moderate correlation were found between the biceps brachii (short head) RMS and hand tremor amplitude in the VT and ML directions (ML: r2 = 0.49, p = 0.010; VT: r2 = 0.44, p = 0.025) in all shooters, with a moderate correlation in the ML direction in elite shooters (ML: r2 = 0.49, p = 0.034). Our results suggest that hand tremors in air pistol shooters are associated with the skill of the shooters, and muscle activation of the biceps brachii (long head) might be a factor affecting hand tremors. By balancing the agonist and antagonist muscles of the shoulder joint, shooters might potentially reduce hand tremors and improve their shooting scores.

OBJECTIVE: During a cognitive effort, an increase in cortical electrical activity, functional alterations in the anterior cingulate cortex, and modifications in cortical inputs to the active motor units have been reported. In light of this, an increase in tremor could be anticipated as result of a mental task. In the present work, we tested this hypothesis.
METHODS: In 25 individuals, tremor was measured with a three-axial accelerometer during 300 s of postural and goal-directed tasks performed simultaneously to mental calculation, or during control (same tasks without mental calculation). Hand and finger dexterity were also evaluated. Electromyographic (EMG) recordings from the extensor digitorum communis were collected during the postural task.
RESULTS: Hand and finger dexterity was negatively affected by the mental task (p = .003 and p = .00005 respectively). During mental calculation, muscle tremor increased in the hand postural (+ 29%, p = .00005) but not in the goal-directed task (- 1.5%, p > .05). The amplitude of the main frequency peak also increased exclusively in the hand postural task (p = .028), whilst no shift in the position of the main frequency peak was observed. EMG was not affected.
CONCLUSIONS: These results support the position of the contribution of a central component in the origin of physiological hand postural tremor. It is suggested that the different effect of mental calculation on hand postural and goal-directed tasks can be attributed to the different origins and characteristics of hand postural and goal-directed physiological tremor.

Fatigue is defined as \"a loss of force-generating capacity\" in a muscle that can intensify tremor. Tremor quantification can facilitate early detection of fatigue onset so that preventative or corrective controls can be taken to minimize work-related injuries and improve the performance of tasks that require high-levels of accuracy. We focused on developing a system that recognizes and classifies voluntary effort and detects phases of fatigue. The experiment was designed to extract and evaluate hand-tremor data during the performance of both rest and effort tasks. The data were collected from the wrist and finger of the participant\'s dominant hand. To investigate tremor, time, frequency domain features were extracted from the accelerometer signal for segments of 45 and 90 samples/window. Analysis using advanced signal processing and machine-learning techniques such as decision tree, k-nearest neighbor, support vector machine, and ensemble classifiers were applied to discover models to classify rest and effort tasks and the phases of fatigue. Evaluation of the classifier\'s performance was assessed based on various metrics using 5-fold cross-validation. The recognition of rest and effort tasks using an ensemble classifier based on the random subspace and window length of 45 samples was deemed to be the most accurate (96.1%). The highest accuracy (~98%) that distinguished between early and late fatigue phases was achieved using the same classifier and window length.

OBJECTIVE: Although careful clinical examination and medical history are the most important steps towards a diagnostic separation between different tremors, the electro-physiological analysis of the tremor using accelerometry and electromyography (EMG) of the affected limbs are promising tools.
METHODS: A soft-decision wavelet-based decomposition technique is applied with 8 decomposition stages to estimate the power spectral density of accelerometer and surface EMG signals (sEMG) sampled at 800 Hz. A discrimination factor between physiological tremor (PH) and pathological tremor, namely, essential tremor (ET) and the tremor caused by Parkinson\'s disease (PD), is obtained by summing the power entropy in band 6 (B6: 7.8125-9.375 Hz) and band 11 (B11: 15.625-17.1875 Hz).
RESULTS: A discrimination accuracy of 93.87% is obtained between the PH group and the ET & PD group using a voting between three results obtained from the accelerometer signal and two sEMG signals.
CONCLUSIONS: Biomedical signal processing techniques based on high resolution wavelet spectral analysis of accelerometer and sEMG signals are implemented to efficiently perform classification between physiological tremor and pathological tremor.

OBJECTIVE: Assessment of physiological tremor during neurosurgical procedures may provide further insights into the composites of surgical expertise. Virtual reality platforms may provide a mechanism for the quantitative assessment of physiological tremor. In this study, a virtual reality simulator providing haptic feedback was used to study physiological tremor in a simulated tumor resection task with participants from a \"skilled\" group and a \"novice\" group.
METHODS: The task involved using a virtual ultrasonic aspirator to remove a series of virtual brain tumors with different visual and tactile characteristics without causing injury to surrounding tissue. Power spectral density analysis was employed to quantitate hand tremor during tumor resection. Statistical t test was used to determine tremor differences between the skilled and novice groups obtained from the instrument tip x, y, z coordinates, the instrument roll, pitch, yaw angles, and the instrument haptic force applied during tumor resection.
METHODS: The study was conducted at the Neurosurgical Simulation and Artificial Intelligence Learning Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.
METHODS: The skilled group comprised 23 neurosurgeons and senior residents and the novice group comprised 92 junior residents and medical students.
RESULTS: The spectral analysis allowed quantitation of physiological tremor during virtual reality tumor resection. The skilled group displayed smaller physiological tremor than the novice group in all cases. In 3 out of 7 cases the difference was statistically significant.
CONCLUSIONS: The first investigation of the application of a virtual reality platform is presented for the quantitation of physiological tremor during a virtual reality tumor resection task. The goal of introducing such methodology to assess tremor is to highlight its potential educational application in neurosurgical resident training and in helping to further define the psychomotor skill set of surgeons.

Physiological hand tremor seriously influences the surgical instrument\'s tip positioning accuracy during microsurgery. To solve this problem, hand-held active tremor compensation instruments are developed to improve tip positioning accuracy during microsurgery. This paper presents the design and performance of a new hand-held instrument that aims to stabilize hand tremors and increase accuracy in microsurgery. The key components are a three degrees of freedom (DOF) integrated parallel manipulator and a high-performance inertial measurement unit (IMU). The IMU was developed to sense the 3-DOF motion of the instrument tip. A customized filter was applied to extract specific hand tremor motion. Then, the instrument was employed to generate the reverse motion simultaneously to reduce tremor motion. Experimental results show that the tremor compensation mechanism is effective. The average RMS reduction ratio of bench test is 56.5% that is a significant tremor reduction ratio. For hand-held test, it has an average RMS reduction ratio of 41.0%. Hence, it could reduce hand tremor magnitudes by 31.7% RMS in 2-DOF.

Tremor is one of the commonest movement disorders and can be disabling. There are many causes and treatment options include medications, adaptations, botulinum toxin injections and functional neurosurgery.
Pubmed.gov peer-reviewed journal articles and reviews.
A new tremor classification has been published. Axis 1 of this classification highlights the clinical characteristics of tremor and axis 2 is dedicated to aetiology. The cerebello-thalamo-cortical network and connections to other brain areas is emerging as pivotal to many types of tremor.
There has been ongoing debate around the clinical entity of essential tremor and its pathophysiological basis.
Increasing understanding of the pathophysiology underpinning tremor is helping to improve classification and is pushing forward trials of new treatment options, particularly surgical options.
With deeper phenotyping from the new classification, genetics of common forms of tremor are ripe for discovery. New pharmacological therapeutic options are needed to complement the better understanding of the basis of tremor.

To investigate the effect of octanoic acid (OA) on the peripheral component of tremor, as well as OA\'s differential effects on the central and peripheral tremor component in essential tremor (ET) patients.
We analyzed postural tremor accelerometry data from a double-blind placebo-controlled cross-over study evaluating the effect of 4 mg/kg OA in ET. The weighted condition was used to identify tremor power for both the central and peripheral tremor components. Exploratory non-parametric statistical analyses were used to describe the relation between the central and peripheral component of tremor power.
A peripheral tremor component was identified in 4 out of 18 subjects. Tremor power was reduced after OA administration in both the central and the peripheral tremor component. There was a positive correlation of tremor power between the central and peripheral component, both after placebo and OA.
When present, the peripheral component was closely related to the central tremor component. We hypothesize that the magnitude of the peripheral mechanical component of tremor is determined by that of the central component.
Both central and peripheral component of tremor are reduced after OA, with the central component providing the energy driving the peripheral component.

Humans are surrounded by sources of daily exposure to power-frequency (60 Hz in North America) magnetic fields (MFs). Such time-varying MFs induce electric fields and currents in living structures which possibly lead to biological effects. The present pilot study examined possible extremely low frequency (ELF) MF effects on human neuromotor control in general, and physiological postural tremor and electroencephalography (EEG) in particular. Since the EEG cortical mu-rhythm (8-12 Hz) from the primary motor cortex and physiological tremor are related, it was hypothesized that a 60 Hz MF exposure focused on this cortical region could acutely modulate human physiological tremor. Ten healthy volunteers (age: 23.8 ± 4 SD) were fitted with a MRI-compatible EEG cap while exposed to 11 MF conditions (60 Hz, 0 to 50 mTrms, 5 mTrms increments). Simultaneously, physiological tremor (recorded from the contralateral index finger) and EEG (from associated motor and somatosensory brain regions) were measured. Results showed no significant main effect of MF exposure conditions on any of the analyzed physiological tremor characteristics. In terms of EEG, no significant effects of the MF were observed for C1, C3, C5 and CP1 electrodes. However, a significant main effect was found for CP3 and CP5 electrodes, both suggesting a decreased mu-rhythm spectral power with increasing MF flux density. This is however not confirmed by Bonferroni corrected pairwise comparisons. Considering both EEG and tremor findings, no effect of the MF exposure on human motor control was observed. However, MF exposure had a subtle effect on the mu-rhythm amplitude in the brain region involved in tactile perception. Current findings are to be considered with caution due to the small size of this pilot work, but they provide preliminary insights to international agencies establishing guidelines regarding electromagnetic field exposure with new experimental data acquired in humans exposed to high mT-range MFs.