There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

/pdf/review-of-control-strategies-for-robotic-movement-training-e0fqcpvct3.pdf

Review of control strategies for robotic movement training after neurologic injury

The existing shortage of therapists and caregivers assisting physically disabled individuals at home is expected to increase and become serious problem in the near future The patient population needing physical rehabilitation of the upper extremity is also constantly increasing Robotic devices have the potential to address this problem as noted by the results of recent research studies However, the availability of these devices in clinical settings is limited, leaving plenty of room for improvement The purpose of this paper is to document a review of robotic devices for upper limb rehabilitation including those in developing phase in order to provide a comprehensive reference about existing solutions and facilitate the development of new and improved devices In particular the following issues are discussed: application field, target group, type of assistance, mechanical design, control strategy and clinical evaluation This paper also includes a comprehensive, tabulated comparison of technical solutions implemented in various systems

/pdf/a-survey-on-robotic-devices-for-upper-limb-rehabilitation-3ykq953s17.pdf

A survey on robotic devices for upper limb rehabilitation

The existing shortage of therapists and caregivers assisting physically disabled individuals at home is expected to increase and become serious problem in the near future. The patient population needing physical rehabilitation of the upper extremity is also constantly increasing. Robotic devices have the potential to address this problem as noted by the results of recent research studies. However, the availability of these devices in clinical settings is limited, leaving plenty of room for improvement. The purpose of this paper is to document a review of robotic devices for upper limb rehabilitation including those in developing phase in order to provide a comprehensive reference about existing solutions and facilitate the development of new and improved devices. In particular the following issues are discussed: application field, target group, type of assistance, mechanical design, control strategy and clinical evaluation. This paper also includes a comprehensive, tabulated comparison of technical solutions implemented in various systems.

A survey on robotic devices for upper limb

Orientation estimation using low cost sensors is an important task for Micro Aerial Vehicles (MAVs) in order to obtain a good feedback for the attitude controller. The challenges come from the low accuracy and noisy data of the MicroElectroMechanical System (MEMS) technology, which is the basis of modern, miniaturized inertial sensors. In this article, we describe a novel approach to obtain an estimation of the orientation in quaternion form from the observations of gravity and magnetic field. Our approach provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. We separate the problems of finding the "tilt" quaternion and the heading quaternion in two sub-parts of our system. This procedure is the key for avoiding the impact of the magnetic disturbances on the roll and pitch components of the orientation when the sensor is surrounded by unwanted magnetic flux. We demonstrate the validity of our method first analytically and then empirically using simulated data. We propose a novel complementary filter for MAVs that fuses together gyroscope data with accelerometer and magnetic field readings. The correction part of the filter is based on the method described above and works for both IMU (Inertial Measurement Unit) and MARG (Magnetic, Angular Rate, and Gravity) sensors. We evaluate the effectiveness of the filter and show that it significantly outperforms other common methods, using publicly available datasets with ground-truth data recorded during a real flight experiment of a micro quadrotor helicopter.

/pdf/keeping-a-good-attitude-a-quaternion-based-orientation-2uoi13loy2.pdf

Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs

The design and control of a therapeutic exercise robot for lower limb rehabilitation: Physiotherabot

This paper presents a viable quaternion-based complementary observer (CO) that is designed for rigid body attitude estimation. We claim that this approach is an alternative one to overcome the limitations of the extended Kalman filter. The CO processes data from a small inertial/magnetic sensor module containing triaxial angular rate sensors, accelerometers, and magnetometers, without resorting to GPS data. The proposed algorithm incorporates a motion kinematic model and adopts a two-layer filter architecture. In the latter, the Levenberg Marquardt algorithm preprocesses acceleration and local magnetic field measurements, to produce what will be called the system's output. The system's output together with the angular rate measurements will become measurement signals for the CO. In this way, the overall CO design is greatly simplified. The efficiency of the CO is experimentally investigated through an industrial robot and a commercial IMU during human segment motion exercises. These results are promising for human motion applications, in particular future ambulatory monitoring.

/pdf/complementary-observer-for-body-segments-motion-capturing-by-57xy5qfbqw.pdf

Complementary Observer for Body Segments Motion Capturing by Inertial and Magnetic Sensors

This paper addresses the problem of rigid body orientation and Dynamic Body Acceleration (DBA) estimation This work is applied in bio-logging, an interdisciplinary research area at the intersection of animal behavior and bioengineering The proposed approach combines a quaternion-based nonlinear filter with the Levenberg Marquardt Algorithm (LMA) The algorithm has a complementary structure design that exploits measurements from a three-axis accelerometer, a three-axis magnetometer, and a three-axis gyroscope Attitude information is necessary to calculate the animal's DBA in order to evaluate its energy expenditure Some numerical simulations illustrate the nonlinear filter performance Some quantitative assessments prove this efficiency such as the time constant of the filter ( ) and the rms magnitude of the quaternion error ( ) Moreover, the effectiveness of the algorithm is experimentally demonstrated In the experiments a domestic animal is equipped with an Inertial Measurement Unit (MTi-G), which provides a truth attitude for comparison with the complementary nonlinear filter The rms difference between the filter and MTi-G outputs in the free movement experiments is within 0392 rms on roll, 0577 rms on pitch, and 2521 rms on yaw

/pdf/a-nonlinear-filtering-approach-for-the-attitude-and-dynamic-3we92ysntp.pdf

A Nonlinear Filtering Approach for the Attitude and Dynamic Body Acceleration Estimation Based on Inertial and Magnetic Sensors: Bio-Logging Application

Control system design of a 3-DOF upper limbs rehabilitation robot

A system approach for control development of lower-limbs training machines

https://hal.archives-ouvertes.fr/hal-00642357/document

Lissan Afilal

Papers

Complementary Observer for Body Segments Motion Capturing by Inertial and Magnetic Sensors

A Nonlinear Filtering Approach for the Attitude and Dynamic Body Acceleration Estimation Based on Inertial and Magnetic Sensors: Bio-Logging Application

Control system design of a 3-DOF upper limbs rehabilitation robot

A system approach for control development of lower-limbs training machines

Posture and body acceleration tracking by inertial and magnetic sensing: Application in behavioral analysis of free-ranging animals