Assessing Wrist Movement with Robotic Devices
ABSTRACT
Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor function after neurological injury. Complementing this application, exoskeletons can augment traditional clinical assessments through precise, repeatable measurements of joint angles and movement quality. These measures assume that exoskeletons are making accurate joint measurements with a negligible effect on movement. For the coupled and coordinated joints of the wrist and hand, the validity of these two assumptions cannot be established by characterizing the device in isolation. To examine these assumptions, we conducted three user-in-the-loop experiments with able-bodied participants. First, we compared robotic measurements to an accepted modality to determine the validity of joint- and trajectorylevel measurements. Then, we compared those movements to movements without the device to investigate the effects of device dynamic properties on wrist movement characteristics. Lastly, we investigated the effect of the device on coordination with a redundant, coordinated pointing task with the wrist and hand. For all experiments, smoothness characteristics were preserved in the robotic kinematic measurement and only marginally impacted by robot dynamics, validating the exoskeletons for use as assessment devices. Stemming from these results, we propose design guidelines for exoskeletal assessment devices.
EXISTING SYSTEM :
It has been recognized that a robotic device’s inherent dynamics can affect human movements, and researchers have proposed metrics to quantify their effect and closed loop force control methods to mitigate these effects . However, the impact of robot dynamics on measures of movement smoothness and coordination of the wrist have not been fully reported. Wrist pointing movements have been observed to be less smooth and more variable than pointing movements of elbow and shoulder. Still, kinematic characterization of movement is an appealing method of assessment for rehabilitation applications since such movements can be measured non-invasively with the very robotic devices used to deliver treatment
PROPOSED SYSTEM :
Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor function after neurological injury. To meet rising needs and leverage new assessment modalities, robots are being utilized in rehabilitation as therapeutic and assessment tools. Their measurement of joint and task space movement hinges on two assumptions. First, it is typically assumed that the human and robot joints are aligned, and second, wearing the exoskeleton does not significantly impact movement. For multi-articular joints such as the wrist, validating these assumptions are not trivial. To investigate the validity of these assumptions, we conducted three experiments. First, we evaluated the accuracy of kinematic joint measurement compared to anatomic joint measurements. For the tested pointing task, the kinematic measures were comparable to accepted goniometry despite limitations caused by movement relative to the device and the variable (between subjects) and changing (within subjects) anatomic joint axes orientation. Kinematic measurements also preserved movement smoothness characteristics key to many robotic assessments. To investigated the second assumption, we conducted two experiments comparing movement with to movement without the robot. The second experiment identified effects of device inertia on wrist movement smoothness, and recommended the use of inertially isotropic wrist devices, with assessment not along robot joints, but rather of coordinated movements of both the human and robot joints. The last experiment examined the interaction between exoskeletons and hand-wrist motor coordination, and showed that familiar coordinations were perturbed for healthy individuals, but unfamiliar movements were not significantly impacted by the presence of a robotic assessment device.
CONCLUSION :
To meet rising needs and leverage new assessment modalities, robots are being utilized in rehabilitation as therapeutic and assessment tools. Their measurement of joint and task space movement hinges on two assumptions. First, it is typically assumed that the human and robot joints are aligned, and second, wearing the exoskeleton does not significantly impact movement. For multi-articular joints such as the wrist, validating these assumptions are not trivial. To investigate the validity of these assumptions, we conducted three experiments. First, we evaluated the accuracy of kinematic joint measurement compared to anatomic joint measurements. For the tested pointing task, the kinematic measures were comparable to accepted goniometry despite limitations caused by movement relative to the device and the variable (between subjects) and changing (within subjects) anatomic joint axes orientation. Kinematic measurements also preserved movement smoothness characteristics key to many robotic assessments. To investigated the second assumption, we conducted two experiments comparing movement with to movement without the robot. The second experiment identified effects of device inertia on wrist movement smoothness, and recommended the use of inertially isotropic wrist devices, with assessment not along robot joints, but rather of coordinated movements of both the human and robot joints. The last experiment examined the interaction between exoskeletons and hand-wrist motor coordination, and showed that familiar coordinations were perturbed for healthy individuals, but unfamiliar movements were not significantly impacted by the presence of a robotic assessment device. We hypothesize that these unfamiliar tasks constitute the bulk of movements made by individuals with neuromuscular motor impairment. Therefore, we conclude that the kinematic data from robotic wrist exoskeletons reliably represent human movement and preserves smoothness characteristics. Stemming from these results, we propose design guidelines for exoskeletons as measurement devices.