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Every movement requires the nervous system to solve a complex biomechanical control problem, but this process is mostly veiled from one's conscious awareness. Simultaneously, we also have conscious experience of controlling our movements - our sense of agency (SoA). Whether SoA corresponds to those neural representations that implement actual neuromuscular control is an open question with ethical, medical, and legal implications. If SoA is the conscious experience of control, this predicts that SoA can be decoded from the same brain structures that implement the so-called inverse kinematic computations for planning movement. We correlated human fMRI measurements during hand movements with the internal representations of a deep neural network (DNN) performing the same hand control task in a biomechanical simulation - revealing detailed cortical encodings of sensorimotor states, idiosyncratic to each subject. We then manipulated SoA by usurping control of participants' muscles via electrical stimulation, and found that the same voxels which were best explained by modeled inverse kinematic representations - which, strikingly, were located in canonically visual areas - also predicted SoA. Importantly, model-brain correspondences and robust SoA decoding could both be achieved within single subjects, enabling relationships between motor representations and awareness to be studied at the level of the individual. 

Designing plant-driven actuators presents an opportunity to create new types of devices that grow, age, and decay, such as robots that embody these qualities in their physical structure. Plant-robot hybrids that grow and decay incorporate unpredictable and gradual transformations inherent across living organisms and suggest an alternative to the design principles of immediacy, responsiveness, control, accuracy, and durability commonly found in robotic design. To explore this, we present a design space of primitives for plant-driven robotic actuators. Proof-of-concept prototypes illustrate how concepts like slow change, slow movement, decay, and destruction can be incorporated into robotic forms. We describe the design considerations required for building plant-driven actuators for robots, including experimental findings regarding the mechanical properties of plant forces. Finally, we speculate on the potential benefits of plant-robot hybrids to interactive domains such as robotics. 

Our muscles are the primary means through which we affect the external world, and the sense of agency (SoA) over the action through those muscles is fundamental to our self-awareness. However, SoA research to date has focused almost exclusively on agency over action outcomes rather than over the musculature itself, as it was believed that SoA over the musculature could not be manipulated directly. Drawing on methods from human–computer interaction and adaptive experimentation, we use human-in-the-loop Bayesian optimization to tune the timing of electrical muscle stimulation so as to robustly elicit a SoA over electrically actuated muscle movements in male and female human subjects. We use time-resolved decoding of subjects' EEG to estimate the time course of neural activity which predicts reported agency on a trial-by-trial basis. Like paradigms which assess SoA over action consequences, we found that the late (post-conscious) neural activity predicts SoA. Unlike typical paradigms, however, we also find patterns of early (sensorimotor) activity with distinct temporal dynamics predicts agency over muscle movements, suggesting that the “neural correlates of agency” may depend on the level of abstraction (i.e., direct sensorimotor feedback versus downstream consequences) most relevant to a given agency judgment. Moreover, fractal analysis of the EEG suggests that SoA-contingent dynamics of neural activity may modulate the sensitivity of the motor system to external input. SIGNIFICANCE STATEMENTThe sense of agency, the feeling of “I did that,” when directing one's own musculature is a core feature of human experience. We show that we can robustly manipulate the sense of agency over electrically actuated muscle movements, and we investigate the time course of neural activity that predicts the sense of agency over these actuated movements. We find evidence of two distinct neural processes: a transient sequence of patterns that begins in the early sensorineural response to muscle stimulation and a later, sustained signature of agency. These results shed light on the neural mechanisms by which we experience our movements as volitional. 

Force-feedback enhances digital touch by enabling users to share non-verbal aspects such as rhythm, poses, and so on. To achieve this, interfaces actuate the user’s to touch involuntarily (using exoskeletons or electrical-muscle-stimulation); we refer to this as computer-driven touch. Unfortunately, forcing users to touch causes a loss of their sense of agency. While researchers found that delaying the timing of computer-driven touch preserves agency, they only considered the naïve case when user-driven touch is aligned with computer-driven touch. We argue this is unlikely as it assumes we can perfectly predict user-touches. But, what about all the remainder situations: when the haptics forces the user into an outcome they did not intend or assists the user in an outcome they would not achieve alone? We unveil, via an experiment, what happens in these novel situations. From our findings, we synthesize a framework that enables researchers of digital-touch systems to trade-off between haptic-assistance vs. sense-of-agency. 

We propose a haptic device that alters the perceived softness of real rigid objects without requiring to instrument the objects. Instead, our haptic device works by restricting the user's fingerpad lateral deformation via a hollow frame that squeezes the sides of the fingerpad. This causes the fingerpad to become bulgier than it originally was—when users touch an object's surface with their now-restricted fingerpad, they feel the object to be softer than it is. To illustrate the extent of softness illusion induced by our device, touching the tip of a wooden chopstick will feel as soft as a rubber eraser. Our haptic device operates by pulling the hollow frame using a motor. Unlike most wearable haptic devices, which cover up the user's fingerpad to create force sensations, our device creates softness while leaving the center of the fingerpad free, which allows the users to feel most of the object they are interacting with. This makes our device a unique contribution to altering the softness of everyday objects, creating “buttons” by softening protrusions of existing appliances or tangibles, or even, altering the softness of handheld props for VR. Finally, we validated our device through two studies: (1) a psychophysics study showed that the device brings down the perceived softness of any object between 50A-90A to around 40A (on Shore A hardness scale); and (2) a user study demonstrated that participants preferred our device for interactive applications that leverage haptic props, such as making a VR prop feel softer or making a rigid 3D printed remote control feel softer on its button. 

Electrical muscle stimulation (EMS) is an emergent technique that miniaturizes force feedback, especially popular for untethered haptic devices, such as mobile gaming, VR, or AR. However, the actuation displayed by interactive systems based on EMS is coarse and imprecise. EMS systems mostly focus on inducing movements in large muscle groups such as legs, arms, and wrists; whereas individual finger poses, which would be required, for example, to actuate a user's fingers to fingerspell even the simplest letters in sign language, are not possible. The lack of dexterity in EMS stems from two fundamental limitations: (1) lack of independence: when a particular finger is actuated by EMS, the current runs through nearby muscles, causing unwanted actuation of adjacent fingers; and, (2) unwanted oscillations: while it is relatively easy for EMS to start moving a finger, it is very hard for EMS to stop and hold that finger at a precise angle; because, to stop a finger, virtually all EMS systems contract the opposing muscle, typically achieved via controllers (e.g., PID)—unfortunately, even with the best controller tuning, this often results in unwanted oscillations. To tackle these limitations, we propose dextrEMS, an EMS-based haptic device featuring mechanical brakes attached to each finger joint. The key idea behind dextrEMS is that while the EMS actuates the fingers, it is our mechanical brake that stops the finger in a precise position. Moreover, it is also the brakes that allow dextrEMS to select which fingers are moved by EMS, eliminating unwanted movements by preventing adjacent fingers from moving. We implemented dextrEMS as an untethered haptic device, weighing only 68g, that actuates eight finger joints independently (metacarpophalangeal and proximal interphalangeal joints for four fingers), which we demonstrate in a wide range of haptic applications, such as assisted fingerspelling, a piano tutorial, guitar tutorial, and a VR game. Finally, in our technical evaluation, we found that dextrEMS outperformed EMS alone by doubling its independence and reducing unwanted oscillations. 

We propose a technique that allows an unprecedented level of dexterity in electrical muscle stimulation (EMS), i.e., it allows interactive EMS-based devices to flex the user's fingers independently of each other. EMS is a promising technique for force feedback because of its small form factor when compared to mechanical actuators. However, the current EMS approach to flexing the user's fingers (i.e., attaching electrodes to the base of the forearm, where finger muscles anchor) is limited by its inability to flex a target finger's metacarpophalangeal (MCP) joint independently of the other fingers. In other words, current EMS devices cannot flex one finger alone, they always induce unwanted actuation to adjacent fingers. To tackle the lack of dexterity, we propose and validate a new electrode layout that places the electrodes on the back of the hand, where they stimulate the interossei/lumbricals muscles in the palm, which have never received attention with regards to EMS. In our user study, we found that our technique offers four key benefits when compared to existing EMS electrode layouts: our technique (1) flexes all four fingers around the MCP joint more independently; (2) has less unwanted flexion of other joints (such as the proximal interphalangeal joint); (3) is more robust to wrist rotations; and (4) reduces calibration time. Therefore, our EMS technique enables applications for interactive EMS systems that require a level of flexion dexterity not available until now. We demonstrate the improved dexterity with four example applications: three musical instrumental tutorials (piano, drum, and guitar) and a VR application that renders force feedback in individual fingers while manipulating a yo-yo. 

We propose a new class of haptic devices that provide haptic sensations by delivering liquid-stimulants to the user's skin; we call this chemical haptics. Upon absorbing these stimulants, which contain safe and small doses of key active ingredients, receptors in the user's skin are chemically triggered, rendering distinct haptic sensations. We identified five chemicals that can render lasting haptic sensations: tingling (sanshool), numbing (lidocaine), stinging (cinnamaldehyde), warming (capsaicin), and cooling (menthol). To enable the application of our novel approach in a variety of settings (such as VR), we engineered a self-contained wearable that can be worn anywhere on the user's skin (e.g., face, arms, legs). Implemented as a soft silicone patch, our device uses micropumps to push the liquid stimulants through channels that are open to the user's skin, enabling topical stimulants to be absorbed by the skin as they pass through. Our approach presents two unique benefits. First, it enables sensations, such as numbing, not possible with existing haptic devices. Second, our approach offers a new pathway, via the skin's chemical receptors, for achieving multiple haptic sensations using a single actuator, which would otherwise require combining multiple actuators (e.g., Peltier, vibration motors, electro-tactile stimulation). We evaluated our approach by means of two studies. In our first study, we characterized the temporal profiles of sensations elicited by each chemical. Using these insights, we designed five interactive VR experiences utilizing chemical haptics, and in our second user study, participants rated these VR experiences with chemical haptics as more immersive than without. Finally, as the first work exploring the use of chemical haptics on the skin, we offer recommendations to designers for how they may employ our approach for their interactive experiences. 

A stretchable pressure sensor is a necessary tool for perceiving physical interactions that take place on soft/deformable skins present in human bodies, prosthetic limbs, or soft robots. However, all existing types of stretchable pressure sensors have an inherent limitation, which is the interference of stretching with pressure sensing accuracy. Here, we present a design for a highly stretchable and highly sensitive pressure sensor that can provide unaltered sensing performance under stretching, which is realized through the synergistic creations of an ionic capacitive sensing mechanism and a mechanically hierarchical microstructure. Via this optimized structure, our sensor exhibits 98% strain insensitivity up to 50% strain and a low pressure detection limit of 0.2 Pa. With the capability to provide all the desired characteristics for quantitative pressure sensing on a deformable surface, this sensor has been used to realize the accurate sensation of physical interactions on human or soft robotic skin.