Peripheral electrical stimulation to reduce pathological tremor: a review

Interventions to reduce tremor in essential tremor (ET) and Parkinson’s disease (PD) clinical populations often utilize pharmacological or surgical therapies. However, there can be significant side effects, decline in effectiveness over time, or clinical contraindications for these interventions. Therefore, alternative approaches must be considered and developed. Some non-pharmacological strategies include assistive devices, orthoses and mechanical loading of the tremorgenic limb, while others propose peripheral electrical stimulation. Specifically, peripheral electrical stimulation encompasses strategies that activate motor and sensory pathways to evoke muscle contractions and impact sensorimotor function. Numerous studies report the efficacy of peripheral electrical stimulation to alter tremor generation, thereby opening new perspectives for both short- and long-term tremor reduction. Therefore, it is timely to explore this promising modality in a comprehensive review. In this review, we analyzed 27 studies that reported the use of peripheral electrical stimulation to reduce tremor and discuss various considerations regarding peripheral electrical stimulation: the stimulation strategies and parameters, electrodes, experimental designs, results, and mechanisms hypothesized to reduce tremor. From our review, we identified a high degree of disparity across studies with regard to stimulation patterns, experimental designs and methods of assessing tremor. Having standardized experimental methodology is a critical step in the field and is needed in order to accurately compare results across studies. With this review, we explore peripheral electrical stimulation as an intervention for tremor reduction, identify the limitations and benefits of the current state-of-the-art studies, and provide ideas to guide the development of novel approaches based on the neural circuitries and mechanical properties implied in tremor generation.

Quantitative Evidence of Pathological Tremor Suppression After Functional Electrical Stimulation

The article's abstract is not available.

Learning fine-grained estimation of physiological states from coarse-grained labels by distribution restoration

Due to its importance in clinical science, the estimation of physiological states (e.g., the severity of pathological tremor) has aroused growing interest in machine learning community. While the physiological state is a continuous variable, its continuity is lost when the physiological state is quantized into a few discrete classes during recording and labeling. The discreteness introduces misalignment between the true value and its label, meaning that these labels are unfortunately imprecise and coarse-grained. Most previous work did not consider the inaccuracy and directly utilized the coarse labels to train the machine learning algorithms, whose predictions are also coarse-grained. In this work, we propose to learn a precise, fine-grained estimation of physiological states using these coarse-grained ground truths. Established on mathematical rigorous proof, we utilize imprecise labels to restore the probabilistic distribution of precise labels in an approximate order-preserving fashion, then the deep neural network learns from this distribution and offers fine-grained estimation. We demonstrate the effectiveness of our approach in assessing the pathological tremor in Parkinson’s Disease and estimating the systolic blood pressure from bioelectrical signals.

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.

Tremorography in the clinical practice

Tremor is the most common type of movement disorders. In practice this differential diagnosis of hyperkinesis is diagnosed clinically and the use of additional methods of objective assessment of tremor increases the accuracy of diagnosis. The use of paraclinical methods of objective assessment of tremor improves the accuracy of diagnosis. Comparison of the neurophysiological parameters of tremor with clinical characteristics has a high diagnostic value, which justifies its use in the routine practice of neurologists. The purpose of the review is to analysis basic electrophysiological characteristics of pathological tremor, as well as the presentation of the material of its own observation.

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.