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We performed functional MRI using a novel MRI-compatible hand-induced robotic device to evaluate its utility for monitoring hand motor function in individuals recovering from neurological deficits.
Functional magnetic resonance imaging (fMRI) is a non-invasive magnetic resonance imaging technique that images brain activation in vivo, using endogenous deoxyhemoglobin as an endogenous contrast agent to detect changes in blood-level-dependent oxygenation (BOLD effect). We combined fMRI with a novel robotic device (MR-compatible hand-induced robotic device [MR_CHIROD]) so that a person in the scanner can execute a controlled motor task, hand-squeezing, which is a very important hand movement to study in neurological motor disease. We employed parallel imaging (generalized auto-calibrating partially parallel acquisitions [GRAPPA]), which allowed higher spatial resolution resulting in increased sensitivity to BOLD. The combination of fMRI with the hand-induced robotic device allowed precise control and monitoring of the task that was executed while a participant was in the scanner; this may prove to be of utility in rehabilitation of hand motor function in patients recovering from neurological deficits (e.g., stroke). Here we outline the protocol for using the current prototype of the MR_CHIROD during an fMRI scan.
Appropriate imaging metrics may monitor and predict the likelihood of therapy success in individuals better than clinical assessments and provide information to improve and individualize therapy planning. We have developed experience with patients recovering from chronic stroke1,2,3,4,5,6,7,8. Developing optimal individualized strategies that focus on how motor training can influence incremental improvement either in reorganization of neural activity and/or motor function is still challenging. Insights into the underlying structural remodeling and re-organization processes for functional recovery in the brain after neurological disease can allow us to evaluate the relationship between distributed topographic patterns of neural activity and functional recovery via functional neuroimaging methods and brain mapping. Success will facilitate developing personalized treatment strategies optimized to yield improvements in grip strength in broad population with neurological conditions based on magnetic resonance imaging (MRI) metrics9.
Here we present a protocol that employs a newly re-designed robotic hand device that provides a controllable resistance force against which a subject grips and releases a handle in synchrony with an oscillating visual stimulus. The MR_CHIROD v3 (MR-compatible Hand-Induced RObotic Device) is a system for presentation of adjustable forces against which gripping and releasing motions are performed, while measuring and recording applied force, grip displacement and timestamps for each data point (Figure 1). The device was engineered to provide reliable assessments of brain activation images during fMRI (functional Magnetic Resonance Imaging), which can be used to evaluate blood-oxygen-level dependent (BOLD) changes in brain responses of patients recovering from neurological disorders. MR-compatibility is achieved through the use of entirely non-ferrous/non-magnetic components for the structure and pneumatic actuator elements and shielded sensor/electronic components that are positioned on the scanner’s bed. Figure 2 shows the device attached to an MR scanner bed, and with a subject in the magnet bore grasping the handle of the MR_CHIROD v3 (Figure 3). Interface and control components are positioned outside the MR scanner room (Figure 4).
The device is used simultaneously with brain imaging methods to assess relevant brain activations. The primary use of the system is to provide a motor task that generates activations of the brain's motor areas, which are detected using fMRI. Brain activation while using the MR_CHIROD during imaging can assess neuroplasticity in neurological disease. By tracking changes in activations in the course of and after motor training using the MR_CHIROD, progress of motor rehabilitation following any neurological disease that leads to motor deficits (e.g., stroke) may be observed.
The MR_CHIROD v3 can also be table-mounted, for use in intra-scan training exercises, in which the subject grips and releases in response to suitable visual stimuli for periods of 45 min, three times per week during the study. Our experience with robotically delivered training, monitored with imaging, suggests that the recovery window for stroke patients for instance may never close1.
Our rationale for building and using an MR-compatible hand-grip robot is that robotic recovery has the potential to produce a great impact on impairment due to its easy deployment, applicability across various motor impairments, high measurement reliability, and capacity to deliver high intensity training protocols10. Our MR-compatible robot can: (a) be set for subject-specific ranges of motion and be programmatically adjusted to apply subject-specific force levels; (b) control, measure and record force and displacement parameters through a host computer; (c) remotely adjust control parameters without requiring interruption of scanning for access to the MR scanner room or repositioning of the subject; and (d) provide therapy via training exercises precisely and consistently for extended periods.
We are aware of no commercially available recovery robotic device that can be used with an MR scanner to measure the subject’s hand grip force and displacement while applying computer-controlled time-varying force. Tsekos et al.11 have reviewed a variety of primarily research-based, MR-compatible robotic and rehabilitation devices, including earlier iterations of the MR_CHIROD series of devices. Other devices were designed for studying wrist motion, finger motion, isometric grip strength, and multi-joint movements. For devices that actively provide resistive or other forces, a variety of MR-compatible technologies have been employed including hydraulics, pneumatics, mechanical linkages and electrorheological fluid dampers. Some devices include multiple degrees of freedom, including another extension of the earlier MR_CHIROD versions added a rotational degree of freedom and hydraulic force application, however it was not adapted for MR-compatibility12.
Our hand-grip-specific device has the advantages of portability (it is regularly transported between the MR facility and office-based training sites), and capability of producing large, computer-controlled, time-varying resistive forces. Current use of pneumatic technology in the MR_CHIROD avoids the need for high voltage sources necessary for electro-rheological fluid-based systems, the potential for leakage of hydraulic fluid, and complex cable/linkages linking the interface mechanism with external power and control components.
The MR_CHIROD was the first device that was demonstrated to function in conjunction with fMRI for brain mapping in stroke patients1. Importantly, the MR_CHIROD v3 is particularly useful for home- or office-based training, as the system and its software were designed for use without expert clinical support and with motivational elements (“gamification”). Relative to physical therapist-facilitated training in a hospital, office- or home-based training is less expensive and more convenient, making it easier for patients to adhere to daily therapy. The device, already relatively inexpensive relative to some of the other research-based devices, can be reengineered to improve the cost-to-benefit ratio. Virtual reality and gamification of training, both of which are compatible with the MR_CHIROD v3, can engage patients, increase their attention during the task, and improve motivation, thus increasing the effectiveness of recovery13.
All experiments were approved by the Institutional Review Board at Massachusetts General Hospital and performed as approved at the Athinoula A. Martinos Center for Biomedical Imaging.
1. Subject Preparation
NOTE: Inclusion criteria are: (i) right hand dominance, (ii) ability to give written informed consent. Exclusion was implemented on the basis of screening for contra-indicators in the magnetic resonance environment such as the following: (a) Routine MRI exclusion criteria, such as the presence of a pacemaker or cerebral aneurysm clip and metal implants or metal content in body; (b) history of seizures (c) claustrophobia; (d) pregnancy.
2. Setup
3. Enter Volunteer Data and Calibrate the MR Scanner
4. Run fMRI Session
5. Complete the MRI Session
6. Take-down
The methodology outlined in the protocol allows the collection of fMRI images while the volunteer is performing the task in real-time in the magnet. Experiments were performed in the Bay 1 facility of the Massachusetts General Hospital Athinoula A. Martinos Center for Biomedical Imaging, using a 3T full-body magnetic resonance scanner. Figure 2 and Figure 3 show the placement of the MR_CHIROD on the table and the patient in place operating it. In
We present fMRI of a motor task using the latest version of a novel robotic device, the MR_CHIROD1,2,8. The MR_CHIROD has been designed to execute a hand-squeezing grip task which has can be performed by chronic stroke patients and has been studied previously1,2,3,4,5...
None of the authors have conflict to disclose.
This work was supported by a grant from the National Institute of Neurological Disorders and Stroke (Grant number 1R01NS105875-01A1) of the National Institutes of Health to A. Aria Tzika. This work was performed at the Athinoula A. Martinos Center for Biomedical Imaging. We wish to thank Director Dr. Bruce R. Rosen, M.D., Ph.D. and members of the Martinos Center staff for their support. We further wish to thank Mr. Christian Pusatere and Mr. Michael Armanini for their assistance in running experiments. Lastly, we thank Dr. Michael A. Moskowitz and Dr. Rosen for their guidance in the conception and development of the MR_CHIROD series of devices and the associated stroke studies.
Name | Company | Catalog Number | Comments |
Ball bearings, plastic with glass balls (8) | McMaster-Carr | 6455K97 | |
Bi-directional logic level converter | Adafruit | 395 | |
Dual LS7366R Quadrature Encoder Buffer | SuperDroid Robots | TE-183-002 | |
Feather M0 WiFi w/ATWINC1500 | Adafruit | Adafruit 3010 | |
Flanged nuts, fiberglass, 3/8”-16 (8) | McMaster-Carr | 98945A041 | |
Garolite rod, ¾” dia, 4’ long | McMaster-Carr | 8467K84 | |
Laptop | Various | Any laptop with USB2.0 port(s) and MATLAB | |
Load Cell (20kg) | Robotshop | RB-PHI-119 | |
Load Cell Amplifier- HX711 | Mouser | 474-SEN-13879 | |
MATLAB | MathWorks | 2008 version or later with Psychophysics Toolbox | |
Magnetic resonance imaging scanner | Siemens | Skyra 3T | 3T full body scanner with BOLD and GRAPPA capabilities |
MR_CHIRODv3 | fabricated in-house | Bespoke plastic & 3D printed structure | |
Op amp development board | Schmartboard | 710-0011-01 | |
Panel Mount Power Supply | Delta | PMT-D2V100W1AA | |
Plastic tubing & tube fittings | McMaster-Carr | various | |
Pyrex/graphite piston/cylinder module | Airpot | 2KS240-3 | |
Screws, ¼”-20, nylon | McMaster-Carr | various | |
Shaft Collars for ¾” dia shaft, nylon (2) | McMaster-Carr | 9410T6 | Stock metal clamping screws replaced with plastic screws |
Shielded cables (2) | US Digital | CA-C5-SH-C5-25 | |
Threaded rod, fiberglass, 3/8”-16 | McMaster-Carr | 91315A010 | |
Transmissive optical encoder code strip | US Digital | LIN-2000-3.5-0.5 | |
Transmissive Optical Encoder Module | US Digital | EM2-0-2000-I | |
PTFE sleeve bearings | McMaster-Carr | 2639T32 |
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