A Comparison Between Conventional and Terrain-Specific Adaptive Pushrim-Activated Power-Assisted Wheelchairs.

Pushrim-activated power-assisted wheels (PAPAWs) are assistive technologies that provide on-demand propulsion assistance to wheelchair users. In this study, we aimed to develop an adaptive PAPAW controller that responds effectively to changes in environmental conditions (e.g., type of surface or terrain). Experiments were conducted to collect kinematics of wheelchair motion using a frame-mounted inertial measurement unit (IMU) while performing a variety of wheelchair activities on different indoor/outdoor terrains. Statistical characteristics of velocity and acceleration measurements were extracted and used to develop a terrain classification framework to identify certain indoor and outdoor terrains. The terrain classification framework, based on random forest classification algorithms and kinematic features, was implemented and tested in our laboratory-developed PAPAW. This computationally efficient terrain classification framework was successfully implemented and tested in real-time. The power-assist ratio of each wheel was adjusted based on the type of terrain (e.g., more assistance was provided on outdoor terrains). Our findings revealed that propulsion effort (e.g., peak input torque) on asphalt was significantly reduced when using adaptive controllers compared to conventional PAPAW controllers. In addition, subjective views of participants regarding the workload of wheelchair propulsion (e.g., physical/cognitive effort) supported the positive effects of adaptive PAPAW controllers. We believe that the adoption of terrain-specific adaptive controllers has the potential to improve the accessibility of outdoor terrains and to prevent or delay upper extremity joint degeneration or pain.

A Comparison Between Conventional and User-Intention-Based Adaptive Pushrim-Activated Power-Assisted Wheelchairs.

Pushrim-activated power-assisted wheel (PAPAW) users ideally require different levels of assistance depending on activity and preference. Therefore, it is important to design and develop adaptive PAPAW controllers to account for these differences. The main objective of this work was to integrate a user intention estimation framework into a PAPAW and develop personalized adaptive controllers. We performed experiments to gather kinetics of wheelchair propulsion for a variety of daily life wheelchair activities. The propulsion characteristics (i.e., pushrim forces) were used to train intention estimation models and characterize implicit user intentions when performing daily life wheelchair maneuvers. These intentions included moving straight forward, performing a right/left turn, and braking. The intention estimation framework, based on random forest classification algorithms and kinetic features, was implemented and tested in our laboratory-developed PAPAW. This computationally efficient framework was successfully implemented and tested for each participant in real-time. Our results revealed that the real-time user intention predictions were similar to the offline models. The power-assist ratio of each wheel was adjusted based on which user intention was identified. Data collected from four participants provided evidence regarding the effectiveness of using adaptive intention-based controllers. For instance, the propulsion effort was significantly reduced when using an adaptive PAPAW controller. Subjective views of participants regarding the workload of wheelchair propulsion (e.g., physical/cognitive effort) were also gathered. Our findings suggest that rankings of different controllers varied among different participants and across different wheelchair maneuvers, indicating the need for customized adaptive controllers to fit different users' activities and preferences.

Training strategies for the user interface of vocational assistive robots.

Two different user training strategies were tested on the ProVAR (professional vocational assistant robot) system. Test subjects were either trained on the full system or first separately on the graphical user interface (UI) alone, away from the robotic arm followed by training on the full system with both the UI and robotic arm. Beginning training separately from the robot allows an introduction to the system to be initiated earlier and at the location most convenient for the user. However this extra training time is not offset by a shortening of the total training time needed to master the system. The choice to do UI only training should be selected based on other motivations such as the desire to engage a potential user during mandatory bed rest, an often otherwise underutilized time.

Mutability of bifunctional thigh muscle activity in pedaling due to contralateral leg force generation.

Locomotion requires uninterrupted transitions between limb extension and flexion. The role of contralateral sensorimotor signals in executing smooth transitions is little understood even though their participation is crucial to bipedal walking. However, elucidating neural interlimb coordinating mechanisms in human walking is difficult because changes to contralateral sensorimotor activity also affect the ipsilateral mechanics. Pedaling, conversely, is ideal for studying bilateral coordination because ipsilateral mechanics can be independently controlled. In pedaling, the anterior and posterior bifunctional thigh muscles develop needed anterior and posterior crank forces, respectively, to dominate the flexion-to-extension and extension-to-flexion transitions. We hypothesized that contralateral sensorimotor activity substantially contributes to the appropriate activation of these bifunctional muscles during the limb transitions. Bilateral pedal forces and surface electromyograms (EMGs) from four thigh muscles were collected from 15 subjects who pedaled with their right leg against a right-crank servomotor, which emulated the mechanical load experienced in conventional two-legged coupled-crank pedaling. In one pedaling session, the contralateral (left) leg pseudo-pedaled (i.e., EMG activity and pedal forces were pedaling-like, but pedal force was not allowed to affect crank rotation). In other sessions, the mechanically decoupled contralateral leg was first relaxed and then produced rhythmic isometric force trajectories during either leg flexion or one of the two limb transitions of the pedaling leg. With contralateral force production in the extension-to-flexion transition (predominantly by the hamstrings), rectus femoris activity and work output increased in the pedaling leg during its flexion-to-extension transition, which occurs simultaneously with contralateral extension-to-flexion in conventional pedaling. Similarly, with contralateral force production in the other transition (i.e., flexion-to-extension; predominantly by rectus femoris), hamstrings activity and work output increased in the pedaling leg during its extension-to-flexion transition. Therefore rhythmic isometric force generation in the contralateral leg supported the ongoing bifunctional muscle activity and resulting work output in the pedaling leg. The results suggest that neural interlimb coordinating mechanisms fine-tune bifunctional muscle activity in rhythmic lower-limb tasks to ensure limb flexion/extension transitions are executed successfully.