The Study Of Key Techniques For Hand Tremor Suppression Based On The Wearable Exoskeleton Roblt Techniques

Tremor is an involuntary, approximately rhythmic muscular contraction characterized by oscillations of a part of the body due to alternating or simultaneous contractions of antagonistic muscle groups. Tremor is a kind of the most common movement disorder, often expressed as a symptom of various neurological diseases. Although tremor is a disorder without life-threatening, it can be responsible for functional disability and social inconvenience. The standard and most effective treatment of tremor is medication. Although the most common types of tremor were subject to numerous studies, their mechanisms and origins are still unknown. In this case, if success in reducing tremor using drug therapy treatment is found, it must be weighed against side effects and the potential for addiction. One of the main problems is that drugs are typically prescribed on a trial-and-error basis in order of decreasing expected effectiveness because the clinical phenomenological tremor classifications are not perfectly predictive of their success. On the whole, a great deal of effort has mostly been devoted in the origins and drug therapy of tremor management in the past decades. For the aim of tremor suppression,the dissertation will do the deep investigations and research on the theory and methods of "Non-Medication" tremor treatment as the following aspects:1). tremor recognition and real-time modelling,2). tremor signal extraction and processing,3). control strategies for tremor suppression, 4). Wearable Exoskeleton Robot for tremor suppression. The main work of the full dissertation is generalized as follows:At first, a deep investigations of the theory and methods of "Non-Medication" tremor treatment. The paper introduces a comprehensive review of research work in this generic field during the last decades. In particular special focus has been put on the tremor recognition, real-time modeling and tremor signal extraction and processing and thus a specific section on control strategies for tremor suppression has been included. Aspects related to wearable Exoskeleton Robot for tremor suppression are reviewed in detail with the aim of drawing a theoretical guidance for the subsequent chapters.Secondly, tremor signals detection, analysis and processing. A wearable dection equipment for tremor signal detection included MEMS Inertial Sensors, accelerometers and EMG sensors for recoding muscle activity at flexors and extensors.In addition, a novel method for tremor processing and analysis is proposed based on Hilbert-Huang Transform. The background, involved concepts, theoretical arid computational theory of the HHT method is proposed. Study on the tremor signal processing method using Empirical Mode Decomposition (EMD) and the construction process of the Hilbert Spectrum (HS). Study on the HHT recognition method and steps of the tremor signals. The HHT method can overcome the problem effectively that the conventional Fourier Transform completely loses time resolution and therefore loosing accuracy of tremor treatments. The HHT method is able to obtain the knowledge from its amplitude and frequency at any given time incident. Study on the self-limitation of the method:End Swing, Mode Mixing and Real-time problem.Thirdly, the performance requirements of robot for the hand tremor suppression are analyzed. A three-freedom Wearable Exoskeleton Robot for Hand Tremor Suppression (WERHTS) has been designed. Study on the physiological characteristics of human arm to build a practical biomechanical model of human arm. Study on the architecture and models of the WERHTS.The design of the exoskeleton system and detection system are proposed in detail. The feasibility of its application in the hand tremor suppression is discussed. The simulation of kinematics and dynamics for the WERHTS are conducted based on the Adams Virtual Prototyping Technology.Fourthly, two different control strategies for hand tremor suppression are proposed based on adaptive biomechanical technology:1) the passive control strategies based on the impedance control; 2) the active control strategies based on the compensatory technology. The control theory of the two hand suppression strategies are detailed proposed. The interaction of the human arm and the WERHTS is discussed and the human-robot model is built. At last, study on the evaluation of tremor suppression strategies and considering the ratio of the conditioned tremor power spectral density before and after the tremor suppression as the evaluation criteria of the control strategies.Finally, it has been validated that the WERHTS is effective and efficient in human arm tremor suppression by the experiments. A novel robot platform for of hand tremor simulation has been designed to simulate the two DOFs tremor in the range of 0-20Hz. The architecture of the tremor simulation platform and the control system based dSPACE is proposed. The experimental protocol,users and procedure are proposed and the data analysis has also been carried out. Experimental results have showed that WERHTS can suppress the tremor in the range of 0-20Hz. In addition, the related power spectral density diagrams before and after the tremor suppression can also indicate the feasibility of ambulatory mechanical tremor suppression of tremor.