Cheng-Shiu Chung

Personal Mobility and Manipulation Appliance—Design, Development, and Initial Testing

The ability to perform activities of daily living and mobility-related activities of daily living are substantial indicators of ones ability to live at home and to participate in ones community. Technologies to assist with mobility and manipulation are among the most important tools that clinicians can provide to people with disabilities to promote independence and community participation. For people with severe disabilities involving both the upper and lower extremities, there are few systems that provide practical and coordinated assistance with mobility and manipulation tasks. The personal mobility and manipulation appliance (PerMMA) was created in response to goals set forth by a team of clinicians and people with disabilities.

Functional assessment and performance evaluation for assistive robotic manipulators: Literature review

Abstract Context The user interface development of assistive robotic manipulators can be traced back to the 1960s. Studies include kinematic designs, cost-efficiency, user experience involvements, and performance evaluation. This paper is to review studies conducted with clinical trials using activities of daily living (ADLs) tasks to evaluate performance categorized using the International Classification of Functioning, Disability, and Health (ICF) frameworks, in order to give the scope of current research and provide suggestions for future studies. Methods We conducted a literature search of assistive robotic manipulators from 1970 to 2012 in PubMed, Google Scholar, and University of Pittsburgh Library System – PITTCat. Results Twenty relevant studies were identified. Conclusion Studies were separated into two broad categories: user task preferences and user-interface performance measurements of commercialized and developing assistive robotic manipulators. The outcome measures and ICF codes associated with the performance evaluations are reported. Suggestions for the future studies include (1) standardized ADL tasks for the quantitative and qualitative evaluation of task efficiency and performance to build comparable measures between research groups, (2) studies relevant to the tasks from user priority lists and ICF codes, and (3) appropriate clinical functional assessment tests with consideration of constraints in assistive robotic manipulator user interfaces. In addition, these outcome measures will help physicians and therapists build standardized tools while prescribing and assessing assistive robotic manipulators.

Stability analysis of electrical powered wheelchair-mounted robotic-assisted transfer device.

The ability of people with disabilities to live in their homes and communities with maximal independence often hinges, at least in part, on their ability to transfer or be transferred by an assistant. Because of limited resources and the expense of personal care, robotic transfer assistance devices will likely be in great demand. An easy-to-use system for assisting with transfers, attachable to electrical powered wheelchairs (EPWs) and readily transportable, could have a significant positive effect on the quality of life of people with disabilities. We investigated the stability of our newly developed Strong Arm, which is attached and integrated with an EPW to assist with transfers. The stability of the system was analyzed and verified by experiments applying different loads and using different system configurations. The model predicted the distributions of the systems center of mass very well compared with the experimental results. When real transfers were conducted with 50 and 75 kg loads and an 83.25 kg dummy, the current Strong Arm could transfer all weights safely without tip-over. Our modeling accurately predicts the stability of the system and is suitable for developing better control algorithms to enhance the safety of the device.

Development of an advanced mobile base for personal mobility and manipulation appliance generation II robotic wheelchair.

Abstract Background This paper describes the development of a mobile base for the Personal Mobility and Manipulation Appliance Generation II (PerMMA Gen II robotic wheelchair), an obstacle-climbing wheelchair able to move in structured and unstructured environments, and to climb over curbs as high as 8 inches. The mechanical, electrical, and software systems of the mobile base are presented in detail, and similar devices such as the iBOT mobility system, TopChair, and 6X6 Explorer are described. Findings The mobile base of PerMMA Gen II has two operating modes: “advanced driving mode” on flat and uneven terrain, and “automatic climbing mode” during stair climbing. The different operating modes are triggered either by local and dynamic conditions or by external commands from users. A step-climbing sequence, up to 0.2 m, is under development and to be evaluated via simulation. The mathematical model of the mobile base is introduced. A feedback and a feed-forward controller have been developed to maintain the posture of the passenger when driving over uneven surfaces or slopes. The effectiveness of the controller has been evaluated by simulation using the open dynamics engine tool. Conclusion Future work for PerMMA Gen II mobile base is implementation of the simulation and control on a real system and evaluation of the system via further experimental tests.

Autonomous function of wheelchair-mounted robotic manipulators to perform daily activities

Autonomous functions for wheelchair-mounted robotic manipulators (WMRMs) allow a user to focus more on the outcome from the task - for example, eating or drinking, instead of moving robot joints through user interfaces. In this paper, we introduce a novel personal assistive robotic system based on a position-based visual servoing (PBVS) approach. The system was evaluated with a complete drinking task, which included recognizing the location of the drink, picking up the drink from a start location, conveying the drink to the proximity of the users mouth without spilling, and placing the drink back on the table. For a drink located in front of the wheelchair, the success rate was nearly 100%. Overall, the total time of completing drinking task is within 40 seconds.

Task-Oriented Performance Evaluation for Assistive Robotic Manipulators: A Pilot Study.

Objective The objectives of this study were to evaluate the performance of commercially available assistive robotic manipulators (ARMs) user interfaces and to investigate the concurrent validity and sensitivity to change with task-oriented performance evaluation tools (TO-PETs) for ARMs. Design This was a nonblinded randomized controlled study with power-wheelchair users with upper-extremity impairments (N = 10). Participants were trained to use 2 ARMs with their respective original user interfaces (keypad and joystick) and evaluated the performance using TO-PET and the adapted Wolf Motor Function Test (WMFT-ARM). Task completion time, ISO 9241-9 throughput, trajectory parameters, NASA-TLX, and questionnaires were the main outcome measurements. Concurrent validity and sensitivity were evaluated. Results Statistical differences were found in ISO 9241-9 throughput between the 2 user interfaces for the single motion tasks and WMFT-ARM. However, there was no statistical difference found on the self-reported perceived workload and ease of use. Moderate to high correlation was found between the TO-PET and WMFT-ARM (P < 0.001). The TO-PET demonstrated higher Cohen d (0.910–1.085) than the WMFT-ARM. Conclusions The findings of this study provide a preliminary comparison between 2 commercial ARMs with their different user interfaces among novice ARM users. Recommendations for training and evaluation were revealed.

Spectral Machine Learning for Predicting Power Wheelchair Exercise Compliance

Pressure ulcers are a common and devastating condition faced by users of power wheelchairs. However, proper use of power wheelchair tilt and recline functions can alleviate pressure and reduce the risk of ulcer occurrence. In this work, we show that when using data from a sensor instrumented power wheelchair, we are able to predict with an average accuracy of 92% whether a subject will successfully complete a repositioning exercise when prompted. We present two models of compliance prediction. The first, a spectral Hidden Markov Model, uses fast, optimal optimization techniques to train a sequential classifier. The second, a decision tree using information gain, is computationally efficient and produces an output that is easy for clinicians and wheelchair users to understand. These prediction algorithms will be a key component in an intelligent reminding system that will prompt users to complete a repositioning exercise only in contexts in which the user is most likely to comply.

Performance evaluation of 3D vision-based semi-autonomous control method for assistive robotic manipulator

Abstract We developed a 3D vision-based semi-autonomous control interface for assistive robotic manipulators. It was implemented based on one of the most popular commercially available assistive robotic manipulator combined with a low-cost depth-sensing camera mounted on the robot base. To perform a manipulation task with the 3D vision-based semi-autonomous control interface, a user starts operating with a manual control method available to him/her. When detecting objects within a set range, the control interface automatically stops the robot, and provides the user with possible manipulation options through audible text output, based on the detected object characteristics. Then, the system waits until the user states a voice command. Once the user command is given, the control interface drives the robot autonomously until the given command is completed. In the empirical evaluations conducted with human subjects from two different groups, it was shown that the semi-autonomous control can be used as an alternative control method to enable individuals with impaired motor control to more efficiently operate the robot arms by facilitating their fine motion control. The advantage of semi-autonomous control was not so obvious for the simple tasks. But, for the relatively complex real-life tasks, the 3D vision-based semi-autonomous control showed significantly faster performance. Implications for Rehabilitation A 3D vision-based semi-autonomous control interface will improve clinical practice by providing an alternative control method that is less demanding physically as well cognitively. A 3D vision-based semi-autonomous control provides the user with task specific intelligent semiautonomous manipulation assistances. A 3D vision-based semi-autonomous control gives the user the feeling that he or she is still in control at any moment. A 3D vision-based semi-autonomous control is compatible with different types of new and existing manual control methods for ARMs.

Performance Evaluation of a Mobile Touchscreen Interface for Assistive Robotic Manipulators: A Pilot Study

Background: Assistive robotic manipulators (ARMs) have been developed to provide enhanced assistance and independence in performance of daily activities among people with spinal cord injury when a caregiver is not on site. However, the current commercial ARM user interfaces (UIs) may be difficult to learn and control. A touchscreen mobile UI was developed to overcome these challenges. Objective: The object of this study was to evaluate the performance between 2 ARM UIs, touchscreen and the original joystick, using an ARM evaluation tool (ARMET). Methods: This is a pilot study of people with upper extremity impairments (N = 8). Participants were trained on 2 UIs, and then they chose one to use when performing 3 tasks on the ARMET: flipping a toggle switch, pushing down a door handle, and turning a knob. Task completion time, mean velocity, and open interviews were the main outcome measurements. Results: Among 8 novice participants, 7 chose the touchscreen UI and 1 chose the joystick UI. All participants could complete the ARMET tasks independently. Use of the touchscreen UI resulted in enhanced ARMET performance (higher mean moving speed and faster task completion). Conclusions: Mobile ARM UIs demonstrated easier learning experience, less physical effort, and better ARMET performance. The improved performance, the accessibility, and lower physical effort suggested that the touchscreen UI might be an efficient tool for the ARM users.

Daily Task-Oriented Performance Evaluation for Commercially Available Assistive Robotic Manipulators

This preliminary study investigates the performance and cognitive loading of the two commercial wheelchairmounted assistive robotic manipulators (ARMs) with their original user interfaces (UIs). This study of 20 able-bodied individuals evaluated the performance of two user interfaces, keypad and joystick, using six tasks on an activities of daily living (ADL) task board with environment-independent measures, self-reported cognitive loading and questionnaires. Participants performed tasks with two commercial arms with their original UIs in a randomized order of arm and the six tasks on the adl task board. Performance was evaluated using completion time, throughput, and trajectory parameters. Self-reported measures of workload and questionnaires were also administered. Statistical performance differences were found in the translational tasks (p<0.05) in task completion time, throughput, and difficulty. The keypad showed faster performance on the knob turning task. Similar responses were reported in the perceived workload with both UI. Participants rated the UI’s low on frustration and physical workload, but higher on mental effort. The findings of this study provide a preliminary comparison between two commercial ARMs with their original UIs. Barriers and recommendations for training and evaluation for first time users were discovered. The results provide information to help develop ARM UI and recommendations for clinicians and health service providers to develop better training and evaluation for arm users.