Brian A. Cohn

Lauren Baron, Brian Cohn, Roghayeh Barmaki

There have been a resurge lately on virtual therapy and other virtual- and tele-medicine services due to the new normal of practicing 'shelter at home'. In this paper, we propose a creative drawing game for virtual therapy and investigate user's comfort and movement freedom in a pilot study. In a mixed-design study, healthy participants (N=16, 8 females) completed one of the easy or hard trajectories of the virtual therapy game in standing and seated arrangements using a virtual-reality headset. The results from participants' movement accuracy, task completion time, and usability questionnaires indicate that participants had significant performance differences on two levels of the game based on its difficulty (between-subjects factor), but no difference in seated and standing configurations (within-subjects factor). Also, the hard mode was more favorable among participants. This work offers implications on virtual reality and 3D-interactive systems, with specific contributions to virtual therapy, and serious games for healthcare applications.

Ali Marjaninejad, Darío Urbina-Meléndez, Brian A. Cohn et al.

Robots will become ubiquitously useful only when they can use few attempts to teach themselves to perform different tasks, even with complex bodies and in dynamical environments. Vertebrates, in fact, successfully use trial-and-error to learn multiple tasks in spite of their intricate tendon-driven anatomies. Roboticists find such tendon-driven systems particularly hard to control because they are simultaneously nonlinear, under-determined (many tendon tensions combine to produce few net joint torques), and over-determined (few joint rotations define how many tendons need to be reeled-in/payed-out). We demonstrate---for the first time in simulation and in hardware---how a model-free approach allows few-shot autonomous learning to produce effective locomotion in a 3-tendon/2-joint tendon-driven leg. Initially, an artificial neural network fed by sparsely sampled data collected using motor babbling creates an inverse map from limb kinematics to motor activations, which is analogous to juvenile vertebrates playing during development. Thereafter, iterative reward-driven exploration of candidate motor activations simultaneously refines the inverse map and finds a functional locomotor limit-cycle autonomously. This biologically-inspired algorithm, which we call G2P (General to Particular), enables versatile adaptation of robots to changes in the target task, mechanics of their bodies, and environment. Moreover, this work empowers future studies of few-shot autonomous learning in biological systems, which is the foundation of their enviable functional versatility.

Brian A. Cohn, Dilan D. Shah, Ali Marjaninejad et al.

We present a virtual reality (VR) experience that creates a research-grade benchmark in assessing patients with active upper-limb tremor, while simultaneously offering the opportunity for patients to engage with VR experiences without their pathologic tremor. Accurate and precise use of handheld motion controllers in VR gaming applications may be limited for patients with upper limb tremor. In parallel, objective tools measuring tremor are not in widespread, routine clinical use. We used a commercially available VR system and designed a challenging virtual-balloon-popping test mimicking a common nose-to-target pointing task used by medical practitioners to subjectively evaluate tremor in the exam room. Within our VR experience, we offer a software mode which uses a low-pass filter to adjust hand position and pointing orientation over a series of past data points. This digital filter creates a smoothing function for hand movement which effectively removes the patient's tremor in the VR representation. While the patient completes trials of the reaching task, quantitative data on the pathologic tremor is digitally recorded. With speed, accuracy, and the tremor components computed across three axes of movement, patients can be evaluated for their tremor amplitudes in a quantitative, replicable, and enjoyable manner. Removal of tremor in digital space may allow patients having significant upper limb tremor to have both an objective clinical measurement of symptoms while providing patients positive feedback and interaction.