Archive for category Robotics

[Abstract+References] Robot assisted rehabilitation of the arm after stroke: prototype design and clinical evaluation


Robot assisted rehabilitation training is a promising tool for post-stroke patients’ recovery, and some new challenges are imposed on robot design, control, and clinical evaluation. This paper presents a novel upper limb rehabilitation robot that can provide safe and compliant force feedbacks to the patient for the benefits of its stiff and low-inertia parallel structure, highly backdrivable capstan-cable transmission, and impedance control method in the workspace. The “assist-as-needed” (AAN) clinical training principle is implemented through the “virtual tunnel” force field design, the “assistance threshold” strategy, as well as the virtual environment training games, and preliminary clinical results show its effectiveness for motor relearning for both acute and chronic stroke patients, especially for coordinated movements of shoulder and elbow.

Supplementary material

11432_2017_9076_MOESM1_ESM.pdf (1.7 mb)

Robot assisted rehabilitation of the arm after stroke: prototype design and clinical evaluation
11432_2017_9076_MOESM2_ESM.mp4 (96.2 mb)

Supplementary material, approximately 96.2 MB.
11432_2017_9076_MOESM3_ESM.mp4 (43.6 mb)

Supplementary material, approximately 43.6 MB.

Source: Robot assisted rehabilitation of the arm after stroke: prototype design and clinical evaluation | SpringerLink

, , , , , , , , ,

Leave a comment

[Abstract+References] A Low-Cost and Lightweight Alternative to Rehabilitation Robots: Omnidirectional Interactive Mobile Robot for Arm Rehabilitation 


Robotic rehabilitation is a growing field. Robots facilitate repetitive therapies, which have positive effects on the rehabilitation of patients who lack arm control because of central nervous system lesions. However, the use of such rehabilitation robots is rare due to high costs and low acceptance among patients. Therefore, this study is focused on the development and control of a novel low-cost omnidirectional interactive mobile robotic platform with force feedback to assist and guide a patient’s hand during therapy. The primary goals for such a mobile robot are to minimize its weight and dimensions, which are significant factors in patient acceptance. Position-based stiffness control was employed with a proportional derivative controller to control the position of the robot and to assist the patient during motion. A user interface with given tasks was built to manage tasks, obtain test results and set control variables. Test results showed that the developed experimental mobile robot successfully assisted and guided the user during the test period.


  1. 1.
    Riener, R.; Nef, T.; Colombo, G.: Robot-aided neurorehabilitation of the upper extremities. Med. Biol. Eng. Comput. 43(1), 2–10 (2015)CrossRefGoogle Scholar
  2. 2.
    Sunderland, A.; Tinson, D.J.; Bradley, E.L.; Fletcher, D.; Hewer, R.L.; Wade, D.T.: Enhanced physical therapy improves recovery of arm function after stroke. A randomised controlled trial. J. Neurol. Neurosurg. Psychiatry 55(7), 530–535 (1992)CrossRefGoogle Scholar
  3. 3.
    Kwakkel, G.; Kollen, B.J.; Wagenaar, R.C.: Long term effects of intensity of upper and lower limb training after stroke: a randomised trial. J. Neurol. Neurosurg. Psychiatry 72(4), 473–479 (2002)Google Scholar
  4. 4.
    Reinkensmeyer, D.J.; Dewald, J.; Rymer, W.Z.: Guidance-based quantification of arm impairment following brain injury: a pilot study. IEEE Trans. Rehabil. Eng. 7(1), 1–11 (1999)Google Scholar
  5. 5.
    Reinkensmeyer, D.J.; Schmit, B.D.; Rymer, W.Z.: Mechatronic assessment of arm impairment after chronic brain injury. Technol. Health Care 7(6), 431–435 (1998)Google Scholar
  6. 6.
    Lum, P.S.; Reinkensmeyer, D.J.; Lehman, S.L.: Robotic assist devices for bimanual physical therapy: preliminary experiments. IEEE Trans. Rehabil. Eng. 1(3), 185–191 (1993)CrossRefGoogle Scholar
  7. 7.
    Lum, P.S.; Lehman, S.L.; Reinkensmeyer, D.J.: The bimanual lifting rehabilitator: an adaptive machine for therapy of stroke patients. IEEE Trans. Rehabil. Eng. 3(2), 166–174 (1995)CrossRefGoogle Scholar
  8. 8.
    Hesse, S.; Schulte-Tigges, G.; Konrad, M.; Bardeleben, A.; Werner, C.: Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects. Arch. Phys. Med. Rehabil. 84(6), 915–920 (2003)CrossRefGoogle Scholar
  9. 9.
    Cozens, J.A.: Robotic assistance of an active upper limb exercise in neurologically impaired patients. IEEE Trans. Rehabil. Eng. 7(2), 254–256 (1999)CrossRefGoogle Scholar
  10. 10.
    Hogan, N.; Krebs, H.I.; Charnnarong, J.; Srikrishna, P.; Sharon, A.: MIT-MANUS: a workstation for manual therapy and training. I. In: Robot and Human Communication Proceedings, pp. 161–165 (1992)Google Scholar
  11. 11.
    Hogan, N.; Krebs, H.I.; Charnnarong, J.; Srikrishna, P.; Sharon, A.: MIT-MANUS: a workstation for manual therapy and training II. In: Applications in Optical Science and Engineering, pp. 28–34 (1993)Google Scholar
  12. 12.
    Van der Linde R.Q.; Lammertse, P.; Frederiksen, E.; Ruiter, B.: The HapticMaster a new high-performance haptic interface. In: Proceedings of Eurohaptics, pp. 1–5 (2002)Google Scholar
  13. 13.
    Nef, T.; Riener, R.: ARMin-design of a novel arm rehabilitation robot. In: Rehabilitation Robotics, pp. 57–60 (2005)Google Scholar
  14. 14.
    Werry I.; Dautenhahn K.: Applying mobile robot technology to the rehabilitation of autistic children. In: Proceedings of SIRS99-7th Symposium on Intelligent Robotic Systems (1999)Google Scholar
  15. 15.
    Eriksson, J.; Mataric, M.J.; Winstein, C.: Hands-off assistive robotics for post-stroke arm rehabilitation. In: Proceedings of IEEE International Conference on Rehabilitation Robotics, pp. 21–24 (2005)Google Scholar
  16. 16.
    Tapus, A.; Tăpus, C.; Matarić, M.J.: User–robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy. Intell. Serv. Robot. 1(2), 169–183 (2008)CrossRefGoogle Scholar
  17. 17.
    Pin, F.G.; Killough, S.M.: A new family of omnidirectional and holonomic wheeled platforms for mobile robots. IEEE Trans. Robot. Autom. 10(4), 480–489 (1994)CrossRefGoogle Scholar
  18. 18.
    Huang, L.; Lim, Y.S.; Lee, D.; Teoh, C.E.: Design and analysis of a four-wheel omnidirectional mobile robot. In: 2nd International Conference of Autonomous Robots and Agents, pp. 425–428 (2004)Google Scholar
  19. 19.
    Zeng, G.; Hemami, A.: An overview of robot force control. Robotica 15(05), 473–482 (1997)CrossRefGoogle Scholar
  20. 20.
    Evans, F.; Evans, F.G.; Abdelnour, T.: Anatomical data for analyzing human motion. Res. Q. Exerc. Sport 54(2), 169–178 (1983)CrossRefGoogle Scholar
  21. 21.
    D’Ausilio, A.: Arduino: a low-cost multipurpose lab equipment. Behav. Res. Methods 44(2), 305–313 (2012)CrossRefGoogle Scholar
  22. 22.
    Teikari, P.; Najjar, R.P.; Malkki, H.; Knoblauch, K.; Dumortier, D.; Gronfier, C.; Cooper, H.M.: An inexpensive Arduino-based LED stimulator system for vision research. J. Neurosci. Methods 211(2), 227–236 (2012)CrossRefGoogle Scholar
  23. 23.

Source: A Low-Cost and Lightweight Alternative to Rehabilitation Robots: Omnidirectional Interactive Mobile Robot for Arm Rehabilitation | SpringerLink

, , , , , ,

Leave a comment

Smart walk assist improves rehabilitation – YouTube

Using smart algorithms to help the brain develop a new way of walking after a stroke. Incredible advances in rehab technologies!

, , , , ,

Leave a comment

[Abstract] Use of Lower-Limb Robotics to Enhance Practice and Participation in Individuals With Neurological Conditions

Purpose: To review lower-limb technology currently available for people with neurological disorders, such as spinal cord injury, stroke, or other conditions. We focus on 3 emerging technologies: treadmill-based training devices, exoskeletons, and other wearable robots.

Summary of Key Points: Efficacy for these devices remains unclear, although preliminary data indicate that specific patient populations may benefit from robotic training used with more traditional physical therapy. Potential benefits include improved lower-limb function and a more typical gait trajectory.

Statement of Conclusions: Use of these devices is limited by insufficient data, cost, and in some cases size of the machine. However, robotic technology is likely to become more prevalent as these machines are enhanced and able to produce targeted physical rehabilitation.

Recommendations for Clinical Practice: Therapists should be aware of these technologies as they continue to advance but understand the limitations and challenges posed with therapeutic/mobility robots.

Source: Use of Lower-Limb Robotics to Enhance Practice and Participa… : Pediatric Physical Therapy

, , , , , , ,

Leave a comment

[WEB SITE] New algorithm helps neurological disorder patients to walk naturally

Soon, wheelchairs may no longer be needed; new research enables patients with neurological disorders to walk again.

Millions of people cannot move their limbs as a result of a neurological disorder or having experienced an injury. But a newly developed algorithm, when coupled with robot-assisted rehabilitation, can help patients who had a stroke or a spinal cord injury to walk naturally.

In the United States, there are approximately 17,000 new cases of spinal cord injury (SCI) every year. Of these, 20 percent result in complete paraplegia (paralysis of the legs and lower half of body) and over 13 percent result in tetraplegia (paralysis of all four limbs).

But SCI is not the only reason that people experience this type of disability. Stroke, multiple sclerosis, cerebral palsy, and a range of other neurological disorders can all lead to paralysis. In fact, a recent survey estimated that in the U.S., almost 5.4 million people live with paralysis, with stroke being the leading cause of this disability.

Now, researchers from the National Centre of Competence in Research Robotics at École Polytechnique Fédérale de Lausanne (EPFL), and at the Lausanne University Hospital in Switzerland, have come up with a groundbreaking technology that may help these patients to regain their locomotor skills.

The scientists came up with an algorithm that helps a robotic harness to facilitate the movements of the patients, thus enabling them to move naturally.

The new research has been published in the journal Science Translational Medicine, and the first author of the study is Jean-Baptiste Mignardot.

Helping people to walk again

Current rehabilitation technologies for people with motor disabilities as a result of SCI or stroke involve walking on a treadmill, with the upper torso being supported by an apparatus. But existing technologies are either too rigid or do not allow the patients to move naturally in all directions.

As the authors of the new study explain, the challenge of locomotor rehabilitation resides in helping the nervous system to “relearn” the right movements. This is difficult due to the loss of muscle mass in the patients, as well as to the neurological wiring that has “forgotten” correct posture.

In order to overcome these obstacles and promote natural walking, Mignardot and colleagues designed an algorithm that coordinates with a robotic rehabilitation harness. The team tested the algorithm in more than 30 patients. The “smart walk assist” markedly and immediately improved the patients’ locomotor abilities.

This mobile harness, which is attached to the ceiling, enables patients to walk. This video shows how it works:

Additionally, after only 1 hour of training with the harness and algorithm, the “unsupported walking ability” of five of the patients improved considerably. By contrast, 1 hour on a conventional treadmill did not improve gait.

The researchers developed the so-called gravity-assist algorithm after carefully monitoring the movements of the patients and considering parameters such as “leg movement, length of stride, and muscle activity.”

As the authors explain, based on these measurements, the algorithm identifies the forces that must be applied to the upper half of the body in order to allow for natural walking.

The smart walk assist is an innovative body-weight support system because it manages to resist the force of gravity and push the patient back and forth, to the left and to the right, or in more of these directions at once, which recreates a natural gait and movement that the patients need in their day to day lives.

Grégoire Courtine, a neuroscientist at EPFL and the Lausanne University Hospital, comments on the significance of the findings, saying, “I expect that this platform will play a critical role in the rehabilitation of walking for people with neurological disorders.”

This is a smart, discreet, and efficient assistance that will aid rehabilitation of many persons with neurological disorders.”

Prof. Jocelyne Bloch, Department of Neurosurgery, Lausanne University Hospital

Source: New algorithm helps neurological disorder patients to walk naturally

, , , , , , ,

Leave a comment

[WEB SITE] Integration of FES Into G-EO System Gait Trainer Receives FDA Nod

Reha Technology USA Inc announces it now offers FDA-approved integrated Functional Electronic Stimulation (FES) for its G-EO System Evolution robotic gait trainer.

“The FES in conjunction with the G-EO System will allow clinicians to generate contractions in paralyzed or weakened muscles in lower extremities at the appropriate time in the walking cycle to maximize patient outcomes,” says Matthew Brooks, clinical director of Reha Technology USA Inc, in a media release.

The G-EO System robotic gait trainer provides passive and active, assistive and resistive training and the simulation of stairs walking up and down.

“We look forward to add this integrated FES feature to all of our current and future customers and we are confident that this extended offering will create added value for their therapy environment,” adds executive VP Paul Abrams, in the release.

[Source(s): Reha Technology USA Inc, PR Newswire]

Source: Integration of FES Into G-EO System Gait Trainer Receives FDA Nod – Rehab Managment

, , , ,

Leave a comment

[VIDEO] Pablo Product Film – YouTube

Δημοσιεύτηκε στις 18 Ιουλ 2017

The PABLO is the latest in a long row of clinically tried and tested robotic- and computer-assisted therapy devices for arms and hands. The new design and the specially developed tyroS software make the PABLO more flexible and offer an expanded spectrum of therapy options.

, , , , , , , , , ,

Leave a comment

[Abstract] Preliminary study on the design and control of a pneumatically-actuated hand rehabilitation device


In recent years, the robotic devices have been used in hand rehabilitation training practice. The majority of existing robotic devices for rehabilitation belong to the rigid exoskeleton. However, rigid exoskeletons may have some limitations such as heavy weight, un-safety and inconvenience. This paper presents a device designed to help post-stroke patients to stretch their spastic hands. This hand rehabilitation device actuator is fabricated by soft material, powered with fluid pressure, and embedded in one glove surface. The distinguished features of this device are: safety, low cost, light weight, convenience and pneumatic actuation. In clinical practice, rehabilitation therapists should help the post-stroke patients to stretch fingers to a desired joint position. Therefore, the control objective of the proposed hand rehabilitation device is to drive the patient’s finger bending angle to a predesigned position. To this end, curvature sensors embedded in the glove are used to measure the finger’s bending angle. A commercial data glove is used to collect the actual finger’s bending angle for calibrating the curvature sensors based on a three-layer back-propagation (BP) neural network. Then the error between the designed joint position and the actual joint position can be calculated. An error proportional control strategy is adopted for the positioning control objective (the controller’s input is the pump speed). Finally, experiments are conducted to validate the effectiveness of control method and the capacity of the proposed hand rehabilitation device.

Related Articles

Source: Preliminary study on the design and control of a pneumatically-actuated hand rehabilitation device – IEEE Xplore Document

, , , , , , , , , , , ,

Leave a comment

[ARTICLE] A Finger Exoskeleton Robot for Finger Movement Rehabilitation – Full Text HTML


In this study, a finger exoskeleton robot has been designed and presented. The prototype device was designed to be worn on the dorsal side of the hand to assist in the movement and rehabilitation of the fingers. The finger exoskeleton is 3D-printed to be low-cost and has a transmission mechanism consisting of rigid serial links which is actuated by a stepper motor. The actuation of the robotic finger is by a sliding motion and mimics the movement of the human finger. To make it possible for the patient to use the rehabilitation device anywhere and anytime, an Arduino™ control board and a speech recognition board were used to allow voice control. As the robotic finger follows the patients voice commands the actual motion is analyzed by Tracker image analysis software. The finger exoskeleton is designed to flex and extend the fingers, and has a rotation range of motion (ROM) of 44.2°.

1. Introduction

Statistically, one in six people in the world will have a stroke [1] at some time, or develop some debilitating bone condition. Most strokes are caused by an interruption of the blood supply to part of the brain. It is very important for stroke patients to move the parts of the body that have been affected to restore and retrain movement. This rehabilitation is very important for the patient and is particularly so for the achievement of full movement. This not only helps to maintain muscle tension and strength, and increase durability, but also promotes blood circulation [2].
Rehabilitation systems have been extensively studied for effective restoration and training of muscle activity in the arm or hand [3,4]. The degree of upper limb rehabilitation is also used in clinical tests [5]. However, a finger exoskeleton is more difficult to design than one for the arm because it requires many more degrees of freedom (DOF) of motion and this involves small moving parts [6]. The design of a typical finger mechanism is complicated, has involved control requirements, and is usually very expensive. To reduce the cost and simplify the fabrication and operation, many people working on the problem began to use underactuated mechanisms in the design of a robot finger [7,8].
An underactuated mechanism has fewer driving sources than the number of DOF. Such an underactuated finger mechanism can be simple in structure, and is easily made even simpler by linking the motion of individual joints, or linking the motion of one finger to another finger [9]. Tendon-actuated and linkage mechanisms are the most common underactuated mechanisms in current use. However, the development and progress of robotic engineering has allowed the underactuated robot to include more DOF and has also lowered the complexity in many different applications.
A tendon-driven mechanism [10] can simply use a nylon line to stretch and bend the fingers. It has the advantage of simplicity and also absorbs shock; however, the line itself is under tension, which puts more load on the finger joints that increases friction forces, and is itself subject to elastic deformation. This kind of mechanism can only be used under a small load. Linkage-type mechanisms driven by auxiliary links to control the fingers have advantages. They are easy to analyze and mechanically rigid, but the many links lead to a loose structure and a humanoid robot finger comparable in size to that of a real finger is not easy to achieve [11].
Various hand exoskeleton technologies for rehabilitation and assistive robotics have recently been developed [12]. To design a proper hand or finger exoskeleton, the biomechanics of the hand/finger, robotic mechanisms, and control methods must be considered. Hand exoskeletons can be driven by different actuators, including electric actuators, pneumatic actuators, and smart material actuators [12]. Allota [13] used external servo motors to drive the exoskeleton fingers, whereas the radio control (RC) servomotors pulled the cables to actuate the fingers in the opening or closure phase. Polygerinos [14] used a soft pneumatic glove to produce bending motions to follow the motion of human fingers.
In this paper, a rehabilitative robotic finger is presented that can be used to maintain muscle strength through repetitive action, which also has the effect of functional recovery by rebuilding the sensorimotor links through the reorganization process in the damaged brain. To avoid the limitations of the heavy and bulky exoskeleton, the design of the finger used an underactuated mechanism, and a 3D printer was used to fabricate a prototype. Thus, the exoskeleton is affordable and competes with conventional therapy costs. In continuous passive motion therapy, a patient usually cannot control the movement through conscious effort; therefore, we used auto speech recognition to help patients control rehabilitation efforts themselves. A specific key word was used to start the robot and a carefully chosen stepper motor was used to power the mechanism. The actual motion was analyzed using the Open Source Physics tool, Tracker.

2. Design and Simulation

The design of the exoskeleton robot was undertaken with a number of important considerations in mind, the most pertinent of which were shape, size, cost, and weight. The weight and cost of the exoskeleton are critical to the users. In our design, the cost (around 30 US dollars) is affordable and competes with conventional therapy costs, while the weight is less than 45 grams. The device needed to fit on a finger and its movement had to follow the finger of the disabled patient. Before embarking on the project, we first studied finger bending motion as well as the general structure of finger muscles and bones. The input torque is set to 30 N-mm according to the motor selected. In the experiment, this torque can move the finger slowly, which is suitable for slight stroke patients. For moderate stroke patients, a higher torque motor with a similar size can be selected with a slight increase of cost and weight. We used Solidworks™ and Autodesk Inventor™ to both design and analyze the system.

2.1. Design

The slider-type robotic finger we designed can be divided into two main parts: the slider itself and the N-shaped linkage, as shown in Figure 1. The design concept of the slider mechanism was to locate the centers of the two arc-shaped sliders on the proximal and distal finger joints separately and to ensure the robotic finger followed human finger motion. In addition, the N-shaped linkage mechanism was designed to connect the proximal and distal arc-shaped sliders and to make them bend together. The N-shaped linkage used is simple and reduced the size of the finger.
Inventions 02 00012 g001

Figure 1. Design of the finger exoskeleton robot that allows the finger to curl from (a) extended to (d) flexed.

The prototype robotic finger has three sliders, five links, ten bolts, and one motor. As the motor rotates, the blue crank moves the gray coupler forwards or backwards. The gray coupler pushes and pulls the yellow slider arm, making it move along the slot. When the yellow slider moves, this causes the green link, or N-shaped linkage, to rotate, which in turn causes the yellow and outer red sliders to move together. The N-shaped linkage continues to push and pull the outer red slider, causing it to move along the slot. The outer red slider connects to the human finger and causes it to bend.[…]

Continue —>  Inventions | Free Full-Text | A Finger Exoskeleton Robot for Finger Movement Rehabilitation | HTML

, , ,

Leave a comment

[ARTICLE] Robotic-assisted serious game for motor and cognitive post-stroke rehabilitation – Full Text PDF



Stroke is a major cause of long-term disability that can cause motor and cognitive impairments. New technologies such as robotic devices and serious games are increasingly being developed to improve post-stroke rehabilitation. The aim of the present project was to develop a ROBiGAME serious game to simultaneously improve motor and cognitive deficits (in particular hemiparesis and hemineglect). In this context, the difficulty level of the game was adapted to each patient’s performance, and this individualized adaptation was addressed as the main challenge of the game development. The game was implemented on the REAplan end-effector rehabilitation robot, which was used in continuous interaction with the game. A preliminary feasibility study of a target pointing game was run in order to validate the game features and parameters. Results showed that the game was perceived as enjoyable, and that patients reported a desire to play the game again. Most of the targets included in the game design were realistic, and they were well perceived by the patients. Results also suggested that the cognitive help strategy could include one visual prompting cue, possibly combined with an auditory cue. It was observed that the motor assistance provided by the robot was well adapted for each patient’s impairments, but the study results led to a suggestion that the triggering conditions should be reviewed. Patients and therapists reported the desire to receive more feedback on the patient’s performances. Nevertheless, more patients and therapists are needed to play the game in order to give further and more comprehensive feedback that will allow for improvements of the serious game. Future steps also include the validation of the motivation assessment module that is currently under development.

Full Text PDF


, , , , , , , , , , ,

Leave a comment

%d bloggers like this: