Continuous Description of Human 3D Motion Intent through Switching Mechanism

© 2001-2011 IEEE. Post-stroke motor recovery highly relies on voluntarily participating in active rehabilitation as early as possible for promoting the reorganization of the patient's brain. In this paper, a new method is proposed which manipulates cable-based rehabilitation robots to assist multi-joint body motions. This uses an electromyography (EMG) decoder for continuous estimation of voluntary motion intention to establish a cooperative human-machine interface for promoting the participation in rehabilitation exercises. In particular, for multi-joint complex tasks in three-dimensional space, a switching mechanism has been developed which can carve up tasks into separate simple motions. For each simple motion, a linear six-inputs and three-outputs time-invariant model is established respectively. The inputs are the processed muscle activations of six arm muscles, and the outputs are voluntary forces of participants when executing a multi-directional tracking task with visual feedback. The experiments for examining the decoder model and EMG-based controller include model training, testing and controller application phases with seven healthy participants. Experimental results demonstrate that the decoder model with the switching mechanism could effectively recognize arm movement intention and provide appropriate assistance to the participants. This study finds that the switching mechanism can improve both the model estimation accuracy and the completeness for executing complex tasks

Human motion intent description based on bumpless switching mechanism for rehabilitation robot.

This paper aims to improve the performance of an electromyography (EMG) decoder based on a switching mechanism in controlling a rehabilitation robot for assisting human-robot cooperation arm movements. For a complex arm movement, the major difficulty of the EMG decoder modeling is to decode EMG signals with high accuracy in real-time. Our recent study presented a switching mechanism for carving up a complex task into simple subtasks and trained different submodels with low nonlinearity. However, it was observed that a "bump" behavior of decoder output (i.e., the discontinuity) occurred during the switching between two submodels. The bumps might cause unexpected impacts on the affected limb and thus potentially injure patients. To improve this undesired transient behavior on decoder outputs, we attempt to maintain the continuity of the outputs during the switching between multiple submodels. A bumpless switching mechanism is proposed by parameterizing submodels with all shared states and applied in the construction of the EMG decoder. Numerical simulation and real-time experiments demonstrated that the bumpless decoder shows high estimation accuracy in both offline and online EMG decoding. Furthermore, the outputs achieved by the proposed bumpless decoder in both testing and verification phases are significantly smoother than the ones obtained by a multimodel decoder without a bumpless switching mechanism. Therefore, the bumpless switching approach can be used to provide a smooth and accurate motion intent prediction from multi-channel EMG signals. Indeed, the method can actually prevent participants from being exposed to the risk of unpredictable loads

A novel hardware approach to integrating active and passive rehabilitation in a single exoskeleton

The proposed exoskeleton is based on the elbow joint where patients can have active and passive rehabilitation in a single structure without changing its configuration. The structural formation of the exoskeleton has been designed in such a way that it offers two working regions namely; actuator based active rehabilitation in the first phase and passive rehabilitation in the second phase. The solution for integrating these two phases has been implemented using an innovative passive locking mechanism which uses a spring-based system for transformation. The stiffness of the spring is utilized to switch between active and passive rehabilitation regions. Besides this there are some other advantages this exoskeleton offers such as reduction of the actuation torque as well as ease of control. The paper is divided into three parts: the first part describes the existing designs, the second part gives an overview of the developed mechanism with structural description and the last part provides the solution with technical specification

Robot Pengetik Untuk Alat Bantu Pengoperasian Komputer Bagi Penyandang Cacat

Pada tahun 2005, UNICEF memperkirakan jumlah anak-anak penyandang cacat di bawah usia 18 tahun dari 150 juta anak. Indonesia mempunyai 11 juta pekerja penyandang cacat. Jumlah ini kurang dari 50% jumlah penderita cacat (data tahun 2010). Berbagai upaya telah dilakukan untuk membantu penyandang cacat agar dapat bekerja secara normal. Ada banyak penelitian tentang kaki palsu, tangan buatan, dan kursi roda bermotor. Dalam penelitian ini akan membangun sebuah robot pengetik. Ini dirancang untuk penyandang cacat fisik. Fungsi robot ini dapat membantu orang cacat untuk mengoperasikan computer secara normal. Robot pengetik terdiri dari 2 robot lengan. Setiap lengan mempunyai 4 derajat kebebasan (DOF). Sensor kompas dengan kompensasi kemiringan dipasang pada kaki pengguna. Ini digunakan untuk mengukur pergerakan kaki pengguna. Keyboard USB ukuran mini digunakan sebagai objek kerja robot. Sebuah rule-based dibuat untuk mengkonversi gerakan kaki pengguna menjadi gerakan robot pengetik. Pembuatan rule-based mempunyai tingkat keberhasilan 100% (untuk keseluruhan akses tombol) dan kesalahan posisi maksimum 3 mm

Elbow exoskeleton mechanism for multistage poststroke rehabilitation.

More than three million people are suffering from stroke in England. The process of post-stroke rehabilitation consists of a series of biomechanical exercises- controlled joint movement in acute phase; external assistance in the mid phase; and variable levels of resistance in the last phase. Post-stroke rehabilitation performed by physiotherapist has many limitations including cost, time, repeatability and intensity of exercises. Although a large variety of arm exoskeletons have been developed in the last two decades to substitute the conventional exercises provided by physiotherapist, most of these systems have limitations with structural configuration, sensory data acquisition and control architecture. It is still difficult to facilitate multistage post-stroke rehabilitation to patients sited around hospital bed without expert intervention. To support this, a framework for elbow exoskeleton has been developed that is portable and has the potential to offer all three types of exercises (external force, assistive and resistive) in a single structure. The design enhances torque to weight ratio compared to joint based actuation systems. The structural lengths of the exoskeleton are determined based on the mean anthropometric parameters of healthy users and the lengths of upperarm and forearm are determined to fit a wide range of users. The operation of the exoskeleton is divided into three regions where each type of exercise can be served in a specific way depending on the requirements of users. Electric motor provides power in the first region of operation whereas spring based assistive force is used in the second region and spring based resistive force is applied in the third region. This design concept provides an engineering solution of integrating three phases of post-stroke exercises in a single device. With this strategy, the energy source is only used in the first region to power the motor whereas the other two modes of exercise can work on the stored energy of springs. All these operations are controlled by a single motor and the maximum torque of the motor required is only 5 Nm. However, due to mechanical advantage, the exoskeleton can provide the joint torque up to 10 Nm. To remove the dependency on biosensor, the exoskeleton has been designed with a hardware-based mechanism that can provide assistive and resistive force. All exoskeleton components are integrated into a microcontroller-based circuit for measuring three joint parameters (angle, velocity and torque) and for controlling exercises. A user-friendly, multi-purpose graphical interface has been developed for participants to control the mode of exercise and it can be managed manually or in automatic mode. To validate the conceptual design, a prototype of the exoskeleton has been developed and it has been tested with healthy subjects. The generated assistive torque can be varied up to 0.037 Nm whereas resistive torque can be varied up to 0.057 Nm. The mass of the exoskeleton is approximately 1.8 kg. Two comparative studies have been performed to assess the measurement accuracy of the exoskeleton. In the first study, data collected from two healthy participants after using the exoskeleton and Kinect sensor by keeping Kinect sensor as reference. The mean measurement errors in joint angle are within 5.18 % for participant 1 and 1.66% for participant 2; the errors in torque measurement are within 8.48% and 7.93% respectively. In the next study, the repeatability of joint measurement by exoskeleton is analysed. The exoskeleton has been used by three healthy users in two rotation cycles. It shows a strong correction (correlation coefficient: 0.99) between two consecutive joint angle measurements and standard deviation is calculated to determine the error margin which comes under acceptable range (maximum: 8.897). The research embodied in this thesis presents a design framework of a portable exoskeleton model for providing three modes of exercises, which could provide a potential solution for all stages of post- stroke rehabilitation

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

Enhanced teleoperation performance using hybrid control and virtual fixture

To develop secure, natural and effective teleoperation, the perception of the slave plays a key role for the interaction of a human operator with the environment. By sensing slave information, the human operator can choose the correct operation in a process during the human–robot interaction.This paper develops an integrated scheme based on a hybrid control and virtual fixture approach for the telerobot. The human operator can sense the slave interaction condition and adjust the master device via the surface electromyographic signal. This hybrid control method integrates the proportional-derivative control and the variable stiffness control, and involves the muscle activation at the same time. It is proposed to quantitatively analyse the human operator’s control demand to enhance the control performance of the teleoperation system. In addition, due to unskilful operation and muscle physiological tremor of the human operator, a virtual fixture method is developed to ensure accuracy of operation and to reduce the operation pressure on the human operator. Experimental results demonstrated the effectiveness of the proposed method for the teleoperated robot