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.
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DextrEMS: Increasing Dexterity in Electrical Muscle Stimulation by Combining it with Brakes
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.
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- Award ID(s):
- 2047189
- NSF-PAR ID:
- 10317682
- Date Published:
- Journal Name:
- ACM Symposium on User Interface Software and Technology
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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We present PixeLite, a novel haptic device that produces distributed lateral forces on the fingerpad. PixeLite is 0.15 mm thick, weighs 1.00 g, and consists of a 4×4 array of electroadhesive brakes (“pucks”) that are each 1.5 mm in diameter and spaced 2.5 mm apart. The array is worn on the fingertip and slid across an electrically grounded countersurface. It can produce perceivable excitation up to 500 Hz. When a puck is activated at 150 V at 5 Hz, friction variation against the countersurface causes displacements of 627 ± 59 μ m. The displacement amplitude decreases as frequency increases, and at 150 Hz is 47 ± 6 μ m. The stiffness of the finger, however, causes a substantial amount of mechanical puck-to-puck coupling, which limits the ability of the array to create spatially localized and distributed effects. A first psychophysical experiment showed that PixeLite's sensations can be localized to an area of about 30% of the total array area. A second experiment, however, showed that exciting neighboring pucks out of phase with one another in a checkerboard pattern did not generate perceived relative motion. Instead, mechanical coupling dominates the motion, resulting in a single frequency felt by the bulk of the finger.more » « less
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Current VR/AR systems are unable to reproduce the physical sensation of fluid vessels, due to the shifting nature of fluid motion. To this end, we introduce SWISH, an ungrounded mixed-reality interface, capable of affording the users a realistic haptic sensation of fluid behaviors in vessels. The chief mechanism behind SWISH is in the use of virtual reality tracking and motor actuation to actively relocate the center of gravity of a handheld vessel, emulating the moving center of gravity of a handheld vessel that contains fluid. In addition to solving challenges related to reliable and efficient motor actuation, our SWISH designs place an emphasis on reproducibility, scalability, and availability to the maker culture. Our virtual-to-physical coupling uses Nvidia Flex's Unity integration for virtual fluid dynamics with a 3D printed augmented vessel containing a motorized mechanical actuation system. To evaluate the effectiveness and perceptual efficacy of SWISH, we conduct a user study with 24 participants, 7 vessel actions, and 2 virtual fluid viscosities in a virtual reality environment. In all cases, the users on average reported that the SWISH bucket generates accurate tactile sensations for the fluid behavior. This opens the potential for multi-modal interactions with programmable fluids in virtual environments for chemistry education, worker training, and immersive entertainment.more » « less
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Introduction Individuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system.
Methods In this paper, we present a hybrid controller using a model predictive control (MPC) formulation that combines the actuation of both an exoskeleton and an FES system. The MPC cost function is designed to distribute actuation on a single degree of freedom to favor FES control effort, reducing exoskeleton power consumption, while ensuring smooth movements along different trajectories. Our controller was tested with nine able-bodied participants using FES surface stimulation paired with an upper limb powered exoskeleton. The hybrid controller was compared to an exoskeleton alone controller, and we measured trajectory error and torque while moving the participant through two elbow flexion/extension trajectories, and separately through two wrist flexion/extension trajectories.
Results The MPC-based hybrid controller showed a reduction in sum of squared torques by an average of 48.7 and 57.9% on the elbow flexion/extension and wrist flexion/extension joints respectively, with only small differences in tracking accuracy compared to the exoskeleton alone.
Discussion To realize practical implementation of hybrid FES-exoskeleton systems, the control strategy requires translation to multi-DOF movements, achieving more consistent improvement across participants, and balancing control to more fully leverage the muscles' capabilities.
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Stable precision grips using the fingertips are a cornerstone of human hand dexterity. However, our fingers become unstable sometimes and snap into a hyperextended posture. This is because multilink mechanisms like our fingers can buckle under tip forces. Suppressing this instability is crucial for hand dexterity, but how the neuromuscular system does so is unknown. Here we show that people rely on the stiffness from muscle contraction for finger stability. We measured buckling time constants of 50 ms or less during maximal force application with the index finger—quicker than feedback latencies—which suggests that muscle-induced stiffness may underlie stability. However, a biomechanical model of the finger predicts that muscle-induced stiffness cannot stabilize at maximal force unless we add springs to stiffen the joints or people reduce their force to enable cocontraction. We tested this prediction in 38 volunteers. Upon adding stiffness, maximal force increased by 34 ± 3%, and muscle electromyography readings were 21 ± 3% higher for the finger flexors (mean ± SE). Muscle recordings and mathematical modeling show that adding stiffness offloads the demand for muscle cocontraction, thus freeing up muscle capacity for fingertip force. Hence, people refrain from applying truly maximal force unless an external stabilizing stiffness allows their muscles to apply higher force without losing stability. But more stiffness is not always better. Stiff fingers would affect the ability to adapt passively to complex object geometries and precisely regulate force. Thus, our results show how hand function arises from neurally tuned muscle stiffness that balances finger stability with compliance.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3472749.3474759
