Muscle synergy analysis provides a method for quantifying differences in muscle use between expert and novice athletes. However, the practical applications of muscle synergy analysis with feedback remain underexplored. In this paper, we present a golf putting training system that utilizes electrical muscle stimulation (EMS) feedback guided by muscle synergy analysis. Considering the individual differences, we use optimal transport to compute the muscle synergy similarity between users and experts. This approach allows users to model their muscle usage after the expert whose synergy is closest. Based on the muscle synergy differences between the expert and the user, EMS is applied to the muscles that need activation. As a result, users can practice putting with increased awareness of the muscles targeted by EMS, resulting in changes in muscle synergy and improved performance. User studies with 44 novices demonstrated that the proposed system significantly improved putting accuracy.
The Pelvic Chair is a shape-changing chair that touches the pelvic area. Through rhythmic and gentle movements on different parts of the pelvic area, the touch interactions from the Pelvic Chair invite attention to the anatomy, muscles, and connectedness. We present a user study with 14 participants focusing on their experience of being touched by the Pelvic Chair. Through our qualitative analysis of participants' experiences, we show that meaningful touch can offer an active approach to sensing the pelvic floor that contributes to increasing somatic literacy - becoming familiar with the pelvic floor, being able to feel and distinguish between tension and relaxation, and establishing new connections between the pelvic floor and the body. Using the Pelvic Chair as a design case we show the potential for technology-initiated touch in providing an intimate and safe way of touching and connecting with the body.
This paper introduces TelePulse, a system integrating biomechanical simulation with electrical muscle stimulation (EMS) to provide precise haptic feedback for robot teleoperation tasks in virtual reality (VR). TelePulse has two components: a physical simulation part that calculates joint torques based on real-time force data from remote manipulators, and an electrical stimulation part that converts these torques into muscle stimulation. Two experiments were conducted to evaluate the system. The first experiment assessed the accuracy of EMS generated through biomechanical simulations by comparing it with electromyography (EMG) data during force-directed tasks, while the second experiment evaluated the impact of TelePulse on teleoperation performance during sanding and drilling tasks. The results suggest that TelePulse provided more accurate stimulation across all arm muscles, thereby enhancing task performance and user experience in the teleoperation environment. In this paper, we discuss the effect of TelePulse on teleoperation, its limitations, and areas for future improvement.
Electrical Muscle Stimulation (EMS) induces muscle movement through external currents, offering a novel approach to motor learning. Researchers investigated using EMS as an alternative to conventional non-movement-inducing feedback techniques, such as vibrotactile and electrotactile feedback. While EMS shows promise in areas such as dance, sports, and motor skill acquisition, neurophysiological models of motor learning conflict about the impact of externally induced movements on sensorimotor representations. This study evaluated EMS against electrotactile feedback and a control condition in a two-session experiment assessing fast learning, consolidation, and learning transfer. Our results suggest an overall positive impact of EMS in motor learning. Although traditional electrotactile feedback had a higher learning rate, EMS increased the learning plateau, as measured by a three-factor exponential decay model. This study provides empirical evidence supporting EMS as a plausible method for motor augmentation and skill transfer, contributing to understanding its role in motor learning.
Electrical muscle stimulation (EMS) has been leveraged to assist in learning motor skills by actuating the user’s muscles. However, existing systems provide static demonstration—actuating the correct movements, regardless of the user’s learning progress. Instead, we contrast two versions of a piano-tutoring system: a conventional EMS setup that moves the participant’s fingers to play the sequence of movements correctly, and a novel adaptive-EMS system that changes its guidance strategy based on the participant’s performance. The adaptive-EMS dynamically adjusts its guidance: (1) demonstrate by playing the entire sequence when errors are frequent; (2) correct by lifting incorrect fingers and actuating the correct one when errors are moderate; and (3) warn by lifting incorrect fingers when errors are low. We found that adaptive-EMS improved learning outcomes (recall) and was preferred by participants. We believe this approach could inspire new types of physical tutoring systems that promote adaptive over static guidance.
Understanding neuromusculoskeletal mechanisms significantly impacts skill specialization and proficiency. While existing methods can infer large muscle activities during gross motor movements, the estimation of dexterous motor control involving miniature muscles remains underexplored. Targeting the coordinated hand muscles in advanced piano performance, we learn spatiotemporal discrete representations of electromyography (EMG) data and hand postures utilizing a multimodal dataset. Subsequently, we train a precise and cost-effective neural network model. Based on this model, PiaMuscle is introduced to investigate if visualizing muscle activities during piano training enhances piano performance. Quantitative and qualitative results of a user study with highly skilled professional pianists demonstrate that PiaMuscle provides reliable muscle activation data to support and optimize force control. Our research underscores the potential of a naturalistic workflow to estimate small muscles' activities from readily accessible human-centric information and more accurately when combined with tool-centric data, thereby enhancing skill acquisition.
When several individuals collaborate on a shared task, their brain activities often synchronize. This phenomenon, known as Inter-brain Synchronization (IBS), is notable for inducing prosocial outcomes such as enhanced interpersonal feelings, including closeness, trust, empathy, and more. Further strengthening the IBS with the aid of external feedback would be beneficial for scenarios where those prosocial feelings play a vital role in interpersonal communication, such as rehabilitation between a therapist and a patient, motor skill learning between a teacher and a student, and group performance art. This paper investigates whether visual, auditory, and haptic feedback of the IBS level can further enhance its intensity, offering design recommendations for feedback systems in IBS. We report findings when three different types of feedback were provided: IBS level feedback by means of on-body projection mapping, sonification using chords, and vibration bands attached to the wrist.