Eric Wolbrecht and David Reinkensmeyer discuss their stroke rehab robot, FINGER

Posted by Biome on 13th February 2014 - 0 Comments


After suffering a stroke, many patients will be left with functional impairment requiring rehabilitation. Over the past few decades, it has been increasingly recognised that robotic devices may have a role to play in this rehabilitation. These robots not only play an important role in assisting in patients with physical therapy, but also have the potential to collect valuable information on the efficacy of rehabilitation techniques. In new research published in the Journal of NeuroEngineering and Rehabilitation, Eric Wolbrecht from the University of Idaho, USA, David Reinkensmeyer from the University of California, Irvine, USA, and colleagues describe the development and preliminary testing of a new robot called ‘FINGER’, which can assist with finger rehabilitation (see it in action in the video below). Wolbrecht and Reinkensmeyer tell us more about how FINGER performed and the use of robotic devices in stroke rehabilitation.

 

FINGER robot. Image source: David Reinkensmeyer, University of California, Irvine, USA.

What role do robotic devices play in rehabilitation after stroke?

Robotic devices have several important roles for post-stroke therapy and rehabilitation. After over 20 years of research, robotic devices for stroke therapy are gaining acceptance and being utilized in medical facilities around the world. By automating the repetitive and strenuous aspects of therapy, these ‘rehab-robots’ can augment traditional physical therapy. Furthermore, many of these devices allow the type and difficulty of the robot-assisted therapy to be prescribed by the physical or occupational therapist. As the technology matures and costs decrease, robotic devices may facilitate a reduction in the cost of rehabilitation therapy, and hopefully, an increase in the quantity of rehabilitation therapy received by those in need.

Of equal importance is the scientific role robotic devices play in improving post-stroke therapy. These devices allow the direct comparison of control strategies (i.e. how the robot physically interacts with a patient) and the collection of quantitative data not previously possible. As such, ‘rehab-robots’ are highly valuable experimental instruments for determining what therapy strategies are most effective, which types of patients benefit from which types of therapy, how motivation promotes effort and adherence, and many other scientific questions about therapy and recovery after stroke.

 

You have created a rehabilitation robot called FINGER. Can you tell us more about it?

FINGER (Finger Individuating Grasp Exercise Robot) is a device for assisting in finger rehabilitation after neurologic injury. FINGER was developed to assist stroke patients in moving their fingers individually in a naturalistic curling motion while playing a game similar to Guitar Hero. FINGER consists of a pair of stacked single degree-of-freedom 8-bar mechanisms, one for the index and one for the middle finger. Each 8-bar mechanism connects to the subject’s proximal and middle phalanges, and is designed to accommodate multiple finger sizes and finger-to-finger widths.

The goal was to make FINGER capable of assisting with motions where precise timing is important. Precision design, low friction bearings, and separate high speed linear actuators allowed FINGER to individually actuate the fingers with a high bandwidth of control (-3 dB at approximately 8 Hz). This combination makes FINGER a novel device for post-stroke therapy and allows for unique therapy measurements and experimental protocols. [See FINGER in action below]

 

How did you test FINGER and what did you find?

For initial evaluation, we asked 16 individuals with a stroke and four without impairment to play a game similar to Guitar Hero while connected to FINGER. During the tests, we were able to modulate the subject’s success rate at the game by automatically adjusting the controller gains of FINGER. We also used FINGER to measure subjects’ effort and finger individuation while playing the game. These results demonstrated the ability of FINGER to motivate subjects with an engaging game environment that challenges individuated control of the fingers, automatically controls assistance levels, and quantifies finger individuation after stroke.

 

Using FINGER, you were able to adjust how challenging the computer game was for participants. Why is maintaining the right level of challenge important in rehabilitation?

Evidence suggests that without sufficient challenge, the perception that the therapy is too easy may promote neurological disengagement that is detrimental to functional recovery. This may occur regardless of the best intentions of the subject. At the other end, where the challenge is too extreme, patients may not be able to complete the prescribed motion or may become frustrated

 

How could using a robotic device, such as FINGER, help patients in their daily lives?

We expect that improvements in hand movement ability gained from intensive training with FINGER in the clinic will transfer to everyday use. Also, we would like to use FINGER or devices like it for home-based therapy, which may be the most important advance the field can make, since this would greatly increase access to therapy. Improvements in robotic technology are allowing less obtrusive and less expensive devices to be developed. Combining these home therapy devices with engaging therapy games, such as the game similar to Guitar Hero used by FINGER, may greatly increase the amount of therapy available to post-stroke survivors.

 

Where do you see the future of robots in rehabilitation, say in the next 10 years?

One of the most promising avenues for robots in rehabilitation is to support and enhance regeneration research, such as stem-cell therapies. As stem-cell technology improves, robotic devices may be able to help patients ‘train’ their new brain cells.

 

What’s next for your research?

We have begun clinical experiments with FINGER.  These experiments include other devices, notably the MusicGlove and the Manumeter to administer therapy and assess patient adherence and progress. Additional evaluation metrics include brain imaging, sensory testing, and clinical outcomes, which we hope will help us predict who can benefit most from the various types of therapy that are possible with FINGER. We are also designing a thumb mechanism add-on for FINGER, since retraining opposable thumb movement is critical for a return to normal function.

 

Questions from Stephanie Harriman, Deputy Medical Editor for BioMed Central. 

 

More about the author(s)

Eric Wolbrecht, Assistant Professor, University of Idaho, USA.

Eric Wolbrecht is an Assistant Professor in the Department of Mechanical Engineering at the University of Idaho, USA. He obtained his Masters degree in mechanical engineering from Oregon State University, USA and his PhD in mechanical and aerospace engineering from the University of California, Irvine, USA. During his career Wolbrecht has worked as an engineer for John Deere and Yamaha. His current research interests include robotics, nonlinear and adaptive control, motor learning, control of pneumatic actuators and neurorehabilitation.

David Reinkensmeyer, Professor, University of California, Irvine, USA.

 

 

David Reinkensmeyer is a Professor received the in the Department of Mechanical and Aerospace Engineering at the University of California, Irvine, USA. He received his Masters and PhD degrees in electrical engineering from the University of California, Berkeley, USA, where he investigated human control of hand movements and robotic devices for movement therapy after stroke. Reinkensmeyer went on to pursue his postdoctoral research in the Sensory Motor Performance Program of the Rehabilitation Institute of Chicago and in the Department of Physical Medicine and Rehabilitation at Northwestern University Medical School, USA, where he became an Assistant Professor. His research now focuses on neuromuscular control, motor learning, robotics, and rehabilitation.

Research

Design and preliminary evaluation of the FINGER rehabilitation robot: controlling challenge and quantifying finger individuation during musical computer game play

Taheri H, Rowe JB, Gardner D, Chan V, Gray K, Bower C, Reinkensmeyer DJ and Wolbrecht ET
Journal of NeuroEngineering and Rehabilitation 2014, 11:10

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