Physiological tremor is suppressed and force steadiness is enhanced with increased availability of serotonin regardless of muscle fatigue

Although there is evidence that 5-HT acts as an excitatory neuromodulator to enhance maximal force generation, it is largely unknown how 5-HT activity influences the ability to sustain a constant force during steady-state contractions. A total of 22 healthy individuals participated in the study, where elbow flexion force was assessed during brief isometric contractions at 10% maximal voluntary contraction (MVC), 60% MVC, MVC, and during a sustained MVC. The selective serotonin reuptake inhibitor, paroxetine, suppressed physiological tremor and increased force steadiness when performing the isometric contractions. In particular, a main effect of drug was detected for peak power of force within the 8-12 Hz range (p = 0.004) and the coefficient of variation (CV) of force (p < 0.001). A second experiment was performed where intermittent isometric elbow flexions (20% MVC sustained for 2 min) were repeatedly performed so that serotonergic effects on physiological tremor and force steadiness could be assessed during the development of fatigue. Main effects of drug were once again detected for peak power of force in the 8-12 Hz range (p = 0.002) and CV of force (p = 0.003), where paroxetine suppressed physiological tremor and increased force steadiness when the elbow flexors were fatigued. The findings of this study suggest that enhanced availability of 5-HT in humans has a profound influence of maintaining constant force during steady state contractions. The action of 5-HT appears to suppress fluctuations in force regardless of the fatigue state of the muscle.

MO204CHRONIC KIDNEY DISEASE, SLEEPINESS, MILD COGNITIVE IMPAIRMENT AND FINE MOTOR CONTROL

Background and Aims Chronic kidney disease (CKD) is a systemic condition because it modifies all organs' function due to an imbalance in plasma volume, electrolytes, hormones, and proteins. Indeed, at the nervous system level, mild cognitive impairment (MCI), sleep disorders and depression often accompany CKD. MCI partially explains the low quality of life of CKD patients, comparable to that of metastatic cancer patients. Mild Cognitive Impairment (MCI) has a high prevalence in this cohort (27-62%). Nevertheless, scattered literature data suggest that CKD patients can also have poor motor control, evidenced by a higher risk of falls, postural instability, reduced gait speed. In this cohort, few data are available regarding the motor circuits called central pattern generators, which control physiological tremor. Specifically, uraemic encephalopathy accentuates physiological tremor, which is regulated by central and peripheral oscillators. Overall, subtle changes in motor control often accompany other forms of MCI. Therefore, this study aimed at evaluating the effects of chronic kidney disease on cognitive and motor functions using up-to-date technologies to record physiological tremor and innovative data analysis. Method This retrospective case-control study enrolled 313 patients (139 controls, 79 CKD patients stage III-IV, 35 kidney transplant (Tx), 60 dialysis (HD) patients). These groups were comparable for age and weight. Creatininemia, azotemia, LDL, HDL, hemoglobin, and proteinuria were used for correlative analyses. We evaluated the chronotype using the Morningness-Eveningness Questionnaire (MEQ) and the degree of sleepiness using the Epworth Sleepiness Scale (ESS). Cognitive impairment was assessed by the Montreal Cognitive Assessment test (MoCA). Cognitive domains of the MoCA score were projected onto brain regions using CerebroViz library in R and a new transformation matrix derived from fMRI literature data. UMAP algorithm was used to identify patients' subgroups. The physiological tremor was recorded on patients maintaining the dominant arm extended using the smartphone App Phyphox. The tremor frequency spectrum was extracted by Fourier analysis. Results The sleepiness score (ESS) was significantly increased in HD (ESS = 5±0.4) compared to the healthy controls (ESS= 4±0.41) whereas was not significantly modified in CKD patients (3.24± 0.32). The chronotype was also not significantly different among the various groups. The mean score of the MoCA test was significantly lower in CKD, Tx, and HD groups (CKD MoCA =24.5±0.3; Tx MoCA =25.4±0.6; HD MoCA =24.6±0.7) than controls (MoCA score=28±0.1). A different pattern of impairment in the cognitive domains of MoCA was evidenced in the various groups using the CerebroViz projection and UMAP tools. MoCA score was inversely correlated with proteinuria (Pearson coefficient=-0.47; p&lt;0.05). The higher frequencies of the physiological tremor (11-13 Hz) were significantly more represented in Tx patients compared to controls (p&lt;0.05). Conversely, the lower frequencies (1-4 Hz) were significantly less represented in the HD group compared to controls (p&lt;0.05). The peak frequency was inversely correlated with age in all patients (Pearson coefficient= -0.45; p&lt;0.05) and inversely associated with azotemia levels, particularly in HD patients (Pearson coefficient=0.43; p&lt;0.05). Conclusion Our results suggest that CKD patients present altered cognitive and motor control patterns, linked in part to the proteinuria level, suggesting a pathogenetic role of endothelial dysfunction. The characteristic motor, sleepiness and cognitive patterns of HD patients might be due to the arteriovenous fistula or the other peculiarities of these patients. These results might help identify new early markers of brain dysfunction in these patients, with the possibility of delaying or reversing cognitive decay.

Discrimination of physiological tremor from pathological tremor using accelerometer and surface EMG signals

BACKGROUND AND 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. CONCLUSION: 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.

Visualisation of Parkinsonian, essential and physiological tremor planes in 3Dspace

Based on the fact that tremors display some distinct 3D spatial characteristics, we decided to visualise tremor planes in 3D space. We obtained 3-axial linear accelerometer signals of hand tremors from 58 patients with Parkinson´s disease (PD), 37 with isolated resting tremor (iRT), 75 with essential tremor (ET), and 44 healthy volunteers with physiological tremor (Ph). For each group analysis was done with subsequent spatial 3D regression of the input data i.e. along the x, y and z axes; the projected vector lengths in the individual (vertical transversal XY, vertical longitudinal XZ and horizontal YZ) reference frame planes and their angles. Most meaningful and statistically significant differences were found in the analyses of the 3D vector lengths. The tremor of the PD and the iRT group was oriented mainly in the horizontal YZ plane. The tremors of the patients with ET and Ph were oriented approximately in the midway between the all three referential planes with less tilt toward the vertical longitudinal XZ plane.

Tremor

Tremor is broadly classified into physiological tremor and pathological tremor. Depending on the clinical features and the predominant pattern of production, tremor is classified into resting tremor, postural tremor, and kinetic tremor. Tremor is associated with rhythmic contraction of agonist and antagonist muscles, either alternately or simultaneously. Tremor involving muscles in the resting condition is called resting tremor and is seen most commonly in Parkinson disease. Tremor involving muscles during isometric contraction is called postural tremor, and it is most commonly seen in essential tremor. Tremor involving muscles during intended movements (isotonic contraction) is called kinetic tremor, and it is most commonly seen in a lesion of the cerebellar efferent pathway.