Controlling a robotic arm for functional tasks using a wireless head-joystick: A case study of a child with congenital absence of upper and lower limbs

Children with movement impairments needing assistive devices for activities of daily living often require novel methods for controlling these devices. Body-machine interfaces, which rely on body movements, are particularly well-suited for children as they are non-invasive and have high signal-to-noise ratios. Here, we examined the use of a head-joystick to enable a child with congenital absence of all four limbs to control a seven degree-of-freedom robotic arm. Head movements were measured with a wireless inertial measurement unit and used to control a robotic arm to perform two functional tasks—a drinking task and a block stacking task. The child practiced these tasks over multiple sessions; a control participant performed the same tasks with a manual joystick. Our results showed that the child was able to successfully perform both tasks, with movement times decreasing by ~40–50% over 6–8 sessions of training. The child’s performance with the head-joystick was also comparable to the control participant using a manual joystick. These results demonstrate the potential of using head movements for the control of high degree-of-freedom tasks in children with limited movement repertoire.


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According to the 2010 American Census, there were approximately 300,000 children with disabilities requiring some form of assistance with activities of daily living [1]. In this context, 48 assistive devices such as wheelchairs and robotic arms are vital for activities requiring mobility 49 and manipulation. Importantly, these devices are not only critical from a sensorimotor perspective, 50 but they also support psychosocial development by providing children with greater independence 51 [2]. . For children in particular, interfaces based on brain signals, invasive or non-invasive, 58 are less than ideal for long-term use because of issues related to risks of surgery, signal quality, 59 signal drift and longevity [10], [11]. These limitations highlight the need for developing body-60 machine interfaces that are non-invasive and robust, and, importantly, also have form factors that 61 make them inconspicuous during interaction with peers [12]. is limited [18], especially in children. In this study, we investigated the use of an IMU-based head joystick for controlling a robotic arm 78 to perform high-DOF functional tasks. In a child with congenital absence of all four limbs, we 79 examined the child's ability to perform two tasks related to activities of daily living -(i) picking 80 up a cup and drinking using a straw, and (ii) manipulating objects placed on a table. We show that 81 the child can use the head-joystick to successfully perform these complex tasks and improve over 82 time to a level that is comparable to that of an unimpaired individual using a manual joystick.  He controlled the robot with its accompanying manual joystick. He had no prior experience 96 interacting with the system or observing its use.

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All participants provided informed consent or assent (including parental consent in case of child) 98 and experimental protocols were approved by the IRB at Michigan State University. 1, is anthropomorphic with 2 DOFs at the shoulder, 1 DOF at the elbow, 3 DOFs at the wrist, and 104 a 1 DOF gripper; specifications of the robot can be found at www.kinovarobotics.com.         We used two tasks that mimicked activities of daily living to assess the participants' ability to 211 control all 7 DOFs of the robotic arm: a drinking task and a stacking task.  The second task involved stacking five cube-shaped blocks of decreasing size (see Table 1 and subsequent placement strategy. Indeed, this task was more difficult than the drinking task.     Task completion. Task completion was measured by the number of successful trials at the task.

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For the stacking task, trials were considered incomplete if the participant was not able to finish 292 stacking all five blocks. However, we still report the characteristics of these incomplete trials in 293 the data analysis as they potentially reflect exploration and learning strategies. The goal of this study was to examine the use of an IMU-based head-joystick for controlling a 351 robotic arm to perform high-DOF functional tasks. We showed that a child with congenital limb 352 absence was able to successfully use the head-joystick to perform two complex functional tasks.

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Moreover, the child was able to improve his performance over time to a level comparable to that 354 of an unimpaired individual using a manual joystick.  Our work also extends prior work on using head gestures to control a robot [18]. In that study, 403 adult participants (able-bodied adults and tetraplegics) used a similar head-mounted IMU to 404 control a 7 DOF robotic arm to accomplish pick and place tasks, but focused only on a single 405 session of practice. Although conducted as a case study, our results add to these prior findings by 406 demonstrating that (i) these interfaces are well-suited for children, and (ii) the improvement in 407 performance over multiple practice sessions is substantial (up to 40-50% reduction in movement 408 times) and comparable to manual joystick performance.

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In terms of further improvements to our design, we wish to highlight two issues. In conclusion, we showed that for a child with congenital limb absence, a head-joystick is a viable 422 means for controlling a robot arm to perform complex tasks of daily living. Developing efficient, 423 non-invasive techniques with intuitive control of high DOFs, and quantifying their performance in 424 a larger sample is a key challenge that needs to be addressed in future studies.