Training Modalities in Rehabilitation Robotics
As we saw in the previous two lessons, rehabilitation robots can generally be categorized as upper-limb rehabilitation robots and lower-limb rehabilitation robots. No matter which part of the body they are targeting to rehabilitate, they can provide four different types of physical therapy that should be chosen based on the patient’s needs. They are passive rehabilitation, active-assisted rehabilitation, active-resisted rehabilitation, and bilateral manipulation.
Passive Rehabilitation can be used at the early stages of the impairment, where the affected limb has no movement. In this type of therapy, the robot moves the affected limb of the patient through a predefined injury-free trajectory a couple of times during each session, and the patient does no effort to help the robot perform the task. This type of therapy is possible with all rehabilitation robots. For instance, the image below shows passive rehabilitation provided by an end-effector-based robot:
And the photo below shows the passive training mode for an ankle rehabilitation robot:
Ren et al. conducted a clinical study where three subjects were involved in a 40-minute passive rehabilitation session. They concluded that passive therapy has the ability to reduce the spasms and stiffness of the affected limb.
In this training mode, the patient initiates the movement and is partially assisted by the rehabilitation robot if she/he is unable to complete the movement. In this type, the robot looks for a signal from the patient (such as an electromyogram or EMG) to perform the movement. For instance, Gloreha Sinfonia is an upper limb rehabilitation robot that detects the movements of the patient and hand and assists the patient if necessary:
This type of therapy is for patients who have a level of control over the movement of their limbs and can initiate the movement by themselves.
A clinical study described in the review article by Proietti et al. on eight subjects for eighteen one-hour sessions over the course of six weeks showed that the movement of the impaired limb has significantly improved after this type of therapy.
In this training mode, the patient initiates the movement and is resisted by the robotic device to challenge the patient’s movement. MIT-Manus (with the commercial name InMotion), which is an end-effector-based upper rehabilitation robot, applied all of the passive, active-assisted, and active-resisted training modes to enhance the training outcomes:
Fasoli et al. conducted active-resistive training on eight subjects for eighteen one-hour session treatments and their goal was to improve the long-term strength of the arm.
This type of training is inspired by mirror therapy, where a mirror is put beside the unaffected limb that blocks the patient’s view of the affected limb that, creates the illusion that both limbs are working properly. This creates visual stimulation and is proven to affect the outcome of the training. In robot-assisted mirror training, the impaired limb “mirrors” or copies the movement of the functional limb. The movement of the functional limb is monitored by sensors in real-time and then copied to the affected limb.
Research showed that this type of training can significantly improve the impaired hemisphere of the brain and motor functions.
One or a combination of these training modalities can be used to treat patients at different stages of disabilities or impairments.
- Babaiasl, M., Mahdioun, S.H., Jaryani, P. and Yazdani, M., 2016. A review of technological and clinical aspects of robot-aided rehabilitation of upper-extremity after stroke. Disability and Rehabilitation: Assistive Technology, 11(4), pp.263-280.
- Ren, Y., Kang, S.H., Park, H.S., Wu, Y.N. and Zhang, L.Q., 2012. Developing a multi-joint upper limb exoskeleton robot for diagnosis, therapy, and outcome evaluation in neurorehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 21(3), pp.490-499.
- Proietti, T., Crocher, V., Roby-Brami, A. and Jarrasse, N., 2016. Upper-limb robotic exoskeletons for neurorehabilitation: a review on control strategies. IEEE reviews in biomedical engineering, 9, pp.4-14.
- Fasoli, S.E., Krebs, H.I., Stein, J., Frontera, W.R., Hughes, R. and Hogan, N., 2004. Robotic therapy for chronic motor impairments after stroke: Follow-up results. Archives of physical medicine and rehabilitation, 85(7), pp.1106-1111.