The objective of this research is to develop a wearable device that could harvest waste mechanical energy of the human hand movement and utilize this energy to suppress wrist tremors. Piezoelectric material is used to measure the hand movement signals, and the signal of wrist tremor is filtered to be utilized to suppress the tremor. In order to conduct the experiment of energy harvesting and tremor suppression, an experimental rig was fabricated. Two types of piezoelectric materials, PVDF (polyvinylidene fluoride) films and MFC (macro fiber composite) films, are used to harvest mechanical energy and used as actuators to suppress hand tremors. However, due to some shortages of the materials, these two types of materials are not used as actuators to suppress the wrist tremors. Thus, we use Matlab Simulink to simulate the tremor suppression with AVC (active vibration control) algorithm.

Although tremor is the most common movement disorder, there exist few effective tremor-suppressing devices, in part because the characteristics of tremor throughout the upper limb are unknown. To clarify, optimally suppressing tremor requires a knowledge of the mechanical origin, propagation, and distribution of tremor throughout the upper limb. Here we present the first systematic investigation of how tremor propagates between the shoulder, elbow, forearm, and wrist. We simulated tremor propagation using a linear, time-invariant, lumped-parameter musculoskeletal model relating joint torques and the resulting joint displacements. The model focused on the seven main degrees of freedom (DOF) from the shoulder to the wrist and included coupled joint inertia, damping, and stiffness. We deliberately implemented a simple model to focus first on the most basic effects. Simulating tremorogenic joint torque as a sinusoidal input, we used the model to establish fundamental principles describing how input parameters (torque location and frequency) and joint impedance (inertia, damping, and stiffness) affect tremor propagation. We expect that the methods and principles presented here will serve as the groundwork for future refining studies to understand the origin, propagation, and distribution of tremor throughout the upper limb in order to enable the future development of optimal tremor-suppressing devices.