A Semi-passive Planar Manipulandum for Upper-Extremity Rehabilitation

Functional resistance training methods for targeting patient-specific gait deficits: A review of devices and their effects on muscle activation, neural control, and gait mechanics

BACKGROUND

Injuries to the neuromusculoskeletal system often result in weakness and gait impairments. Functional resistance training during walking-where patients walk while a device increases loading on the leg-is an emerging approach to combat these symptoms. However, there are many methods that can be used to resist the patient, which may alter the biomechanics of the training. Thus, all methods may not address patient-specific deficits.

METHODS

We performed a comprehensive electronic database search to identify articles that acutely (i.e., after a single training session) examined how functional resistance training during walking alters muscle activation, gait biomechanics, and neural plasticity. Only articles that examined these effects during training or following the removal of resistance (i.e., aftereffects) were included.

FINDINGS

We found 41 studies that matched these criteria. Most studies (24) used passive devices (e.g., weighted cuffs or resistance bands) while the remainder used robotic devices. Devices varied on if they were wearable (14) or externally tethered, and the type of resistance they applied (i.e., inertial [14], elastic [8], viscous [7], or customized [12]). Notably, these methods provided device-specific changes in muscle activation, biomechanics, and spatiotemporal and kinematic aftereffects. Some evidence suggests this training results in task-specific increases in neural excitability.

INTERPRETATION

These findings suggest that careful selection of resistive strategies could help target patient-specific strength deficits and gait impairments. Also, many approaches are low-cost and feasible for clinical or in-home use. The results provide new insights for clinicians on selecting an appropriate functional resistance training strategy to target patient-specific needs.

Manipulating abnormal synergistic coupling of joint torques through force applications at the Hand: A Simulation-Based study

Loss of independent joint control due to abnormal coupling of shoulder and elbow torques (i.e., abnormal synergies) is a common impairment after stroke and has been linked to poor upper-extremity function in stroke survivors. Previous research has shown that the flexor synergy (i.e., shoulder abduction coupled with elbow flexion) can be treated by progressively increasing shoulder abduction loading during elbow extension exercises. However, this finding has not been implemented in planar reaching exercises, as this requires a clear understanding of the relationship between external forces on the hand and elicited joint torques when reaching for different targets on a table. The objective of this study was to model this relationship and determine reach/force combinations that could be used to counteract either the flexor or extensor synergies. We used a musculoskeletal model to compute shoulder and elbow joint torques when reaching for targets on a table against different force directions and magnitudes. We found that force direction modulated the coupling of shoulder and elbow torques and force magnitude scaled each torque uniformly such that the extent of coupling remained the same. Additionally, we found that forces on the hand could be used to gradually increase the magnitude of simultaneous shoulder and elbow torques that counteract either the flexor or extensor synergy. These results provide the foundation to develop therapeutic interventions that address abnormal joint couplings following stroke using forces on the hand during planar reaching. Future studies should examine the therapeutic benefits of these findings in patient populations such as stroke.

Motor Modules are Impacted by the Number of Reaching Directions Included in the Analysis

Muscle synergy analysis is commonly used to study how the nervous system coordinates the activation of a large number of muscles during human reaching. In synergy analysis, muscle activation data collected from various reaching directions are subjected to dimensionality reduction techniques to extract muscle synergies. Typically, muscle activation data are obtained only from a limited set of reaches with an inherent assumption that the performed reaches adequately represent all possible reaches. In this study, we investigated how the number of reaching directions included in the synergy analysis influences the validity of the extracted synergies. We used a musculoskeletal model to compute muscle activations required to perform 36 evenly spaced planar reaches. Nonnegative matrix factorization (NMF) and principal component analysis (PCA) were then used to extract reference synergies. We then selected several subsets of reaches and compared the ability of the extracted synergies from each subset to represent the muscle activation from all 36 reaches. We found that 6 reaches were required to extract valid synergies, and a further reduction in the number of reaches changed the composition of the resulting synergies. Further, we found that the choice of reaching directions included in the analysis for a given number of reaches also affected the validity of the extracted synergies. These findings indicate that both the number and the choice of reaching directions included in the analysis impacted the validity of the extracted synergies.

Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study

BACKGROUND

Robotic rehabilitation is a highly promising approach to recover lost functions after stroke or other neurological disorders. Unfortunately, robotic rehabilitation currently suffers from "motor slacking", a phenomenon in which the human motor system reduces muscle activation levels and movement excursions, ostensibly to minimize metabolic- and movement-related costs. Consequently, the patient remains passive and is not fully engaged during therapy. To overcome this limitation, we envision a new class of body-powered robots and hypothesize that motor slacking could be reduced if individuals must provide the power to move their impaired limbs via their own body (i.e., through the motion of a healthy limb).

OBJECTIVE

To test whether a body-powered exoskeleton (i.e. robot) could reduce motor slacking during robotic training.

METHODS

We developed a body-powered robot that mechanically coupled the motions of the user's elbow joints. We tested this passive robot in two groups of subjects (stroke and able-bodied) during four exercise conditions in which we controlled whether the robotic device was powered by the subject or by the experimenter, and whether the subject's driven arm was engaged or at rest. Motor slacking was quantified by computing the muscle activation changes of the elbow flexor and extensor muscles using surface electromyography.

RESULTS

Subjects had higher levels of muscle activation in their driven arm during self-powered conditions compared to externally-powered conditions. Most notably, subjects unintentionally activated their driven arm even when explicitly told to relax when the device was self-powered. This behavior was persistent throughout the trial and did not wane after the initiation of the trial.

CONCLUSIONS

Our findings provide novel evidence indicating that motor slacking can be reduced by self-powered robots; thus demonstrating promise for rehabilitation of impaired subjects using this new class of wearable system. The results also serve as a foundation to develop more sophisticated body-powered robots (e.g., with controllable transmissions) for rehabilitation purposes.

Development, Dynamic Modeling, and Multi-Modal Control of a Therapeutic Exoskeleton for Upper Limb Rehabilitation Training

Robot-assisted training is a promising technology in clinical rehabilitation providing effective treatment to the patients with motor disability. In this paper, a multi-modal control strategy for a therapeutic upper limb exoskeleton is proposed to assist the disabled persons perform patient-passive training and patient-cooperative training. A comprehensive overview of the exoskeleton with seven actuated degrees of freedom is introduced. The dynamic modeling and parameters identification strategies of the human-robot interaction system are analyzed. Moreover, an adaptive sliding mode controller with disturbance observer (ASMCDO) is developed to ensure the position control accuracy in patient-passive training. A cascade-proportional-integral-derivative (CPID)-based impedance controller with graphical game-like interface is designed to improve interaction compliance and motivate the active participation of patients in patient-cooperative training. Three typical experiments are conducted to verify the feasibility of the proposed control strategy, including the trajectory tracking experiments, the trajectory tracking experiments with impedance adjustment, and the intention-based training experiments. The experimental results suggest that the tracking error of ASMCDO controller is smaller than that of terminal sliding mode controller. By optimally changing the impedance parameters of CPID-based impedance controller, the training intensity can be adjusted to meet the requirement of different patients.

A Portable Passive Rehabilitation Robot for Upper-Extremity Functional Resistance Training

OBJECTIVE

Loss of arm function is common in individuals with neurological damage, such as stroke or cerebral palsy. Robotic devices that address muscle strength deficits in a task-specific manner can assist in the recovery of arm function; however, current devices are typically large, bulky, and expensive to be routinely used in the clinic or at home. This study sought to address this issue by developing a portable planar passive rehabilitation robot, PaRRo.

METHODS

We designed PaRRo with a mechanical layout that incorporated kinematic redundancies to generate forces that directly oppose the user's movement. Cost-efficient eddy current brakes were used to provide scalable resistances. The lengths of the robot's linkages were optimized to have a reasonably large workspace for human planar reaching. We then performed theoretical analysis of the robot's resistive force generating capacity and steerable workspace using MATLAB simulations. We also validated the device by having a subject move the end-effector along different paths at a set velocity using a metronome while simultaneously collecting surface electromyography (EMG) and end-effector forces felt by the user.

RESULTS

Results from simulation experiments indicated that the robot was capable of producing sufficient end-effector forces for functional resistance training. We also found the endpoint forces from the user were similar to the theoretical forces expected at any direction of motion. EMG results indicated that the device was capable of providing adjustable resistances based on subjects' ability levels, as the muscle activation levels scaled with increasing magnet exposures.

CONCLUSION

These results indicate that PaRRo is a feasible approach to provide functional resistance training to the muscles along the upper extremity.

SIGNIFICANCE

The proposed robotic device could provide a technological breakthrough that will make rehabilitation robots accessible for small outpatient rehabilitation centers and in-home therapy.