However, signal processing techniques and sensing technologies need to be properly selected in order to provide data in agreement with the clinical-functional assessment of tremor ( 5). Mobile devices, together with the advent of the Internet of Things (IoT), have dramatically changed people's lifestyles and have found newer and newer areas of application, allowing for continuous monitoring of disease symptoms and vital signs. Smartphones, smartwatches, and tablets have sufficient computing resources for performing complex calculations, such as digital signal processing and artificial intelligence (AI). Many of them can be interfaced with smartphones or tablets through wireless communication protocols (Bluetooth, Wi-Fi, etc.). Most of such devices are based on inertial sensors (accelerometers and gyroscopes), while others use a combination of inertial and electrophysiological information. #Sufficient velocity magna graecia portableIn the last decade, the large diffusion of mobile devices has fostered the development of several portable and wearable solutions for health monitoring or even for disease diagnosis. Generally, EMG is unsuitable for continuous monitoring or frequent assessment of tremor characteristics. To avoid such inconveniences, needle EMG ( 4) is the most reliable technique for a precise characterization of tremor features, but it is invasive and costly. #Sufficient velocity magna graecia skinUnfortunately, it suffers from uncertainty and errors due to bad positioning of electrodes, changes in skin conductance, and cross-talking from other muscles. Surface EMG is the gold standard technique for the diagnosis, characterization, and monitoring of tremor ( 3). When two or more antagonist muscles are involved in tremor, activation patterns are defined according to the relative timing of tremor electromyography (EMG) bursts: synchronous pattern, when muscle bursts are in phase, and alternating pattern, when bursts are phase-shifted ( 2), as shown in Figures 1A–D. Tremor features include frequency (usually in the range of 4–8 Hz) and amplitude. According to activation conditions, two kinds of tremors are generally considered: rest tremor, when the affected part is relaxed, and action tremor (kinetic, postural, or isometric), when the subject performs voluntary movements or voluntarily maintains a certain position against gravity. Tremor symptoms may affect one body region (focal tremor), two or more adjacent parts (segmental tremor), one side (hemitremor), or the whole body (generalized tremor). Pathological tremor, on the other hand, is usually visible and persistent and can severely compromise the execution of normal life tasks, like eating, dressing, writing. Such tremor is generally not visible or symptomatic unless it is enhanced by fatigue or anxiety. Limbs and head, when unsupported, may exhibit slight tremor, referred to as physiological tremor. Tremor is generally defined as an involuntary, rhythmic, oscillatory movement of a body part ( 1). 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. Such devices have proven to be useful for monitoring the efficacy of therapies or even aiding in differential diagnosis. 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. To date, electromyography (EMG) is the gold standard for the analysis and diagnosis of tremors. Some of such diseases are neurodegenerative, and tremor characterization may be of help in differential diagnosis. Tremor is an impairing symptom associated with several neurological diseases. 4Department of Medical and Surgical Sciences, Neuroscience Research Center, Magna Græcia University, Catanzaro, Italy.3Neuroimaging Unit, Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR), Catanzaro, Italy.2Department of Medical and Surgical Sciences, Institute of Neurology, Magna Græcia University, Catanzaro, Italy.1Biotecnomed S.C.aR.L., Catanzaro, Italy. Basilio Vescio 1, Andrea Quattrone 2, Rita Nisticò 3, Marianna Crasà 4 and Aldo Quattrone 3,4 *
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